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Background: One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician’s ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.
Objectives: The aim of the study is to enhance an existing, interoperable, and rulebased CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.
Methods: We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians’ diagnoses as reference
Sustainable tourism is a niche market that has been growing in recent years. At the same time, companies in the mass tourism market have increasingly marketed themselves with a “green” image, although this market is not sustainable. In order to successfully market sustainability, targeted marketing tactics are needed.
The aim of this research is to establish appropriate marketing tactics for sustainable tourism in the niche market and in the mass market. The purpose is to uncover current marketing tactics for both the mass tourism market and the sustainable tourism niche market. It also intends to explore how consumers who are more interested in sustainability differ from consumers with less interest in sustainability in terms of their perception of sustainability in tourism. Furthermore, this research paper will assess the trustworthiness of sustainable travel offers and the trustworthiness of quality seals in sustainable tourism. For this purpose, an online survey was conducted, which was addressed at German-speaking consumers. The survey showed, that consumers with more general interest in sustainability also consider sustainability to be more relevant in tourism. Offers for sustainable travel and quality seals were perceived as not very trustworthy. Moreover, no link could be found between the interest in sustainability and the perception of trustworthiness.
On the basis of the above, it is advisable to directly advertise sustainability in the niche market and to mention sustainability in the mass market only as an accompaniment or not at all. Further research could be undertaken to identify which factors influence the trustworthiness of offers, and trustworthiness of quality seals in sustainable tourism.
The present research study investigated the susceptibility of common mastitis pathogens—obtained from clinical mastitis cases on 58 Northern German dairy farms—to routinely used antimicrobials. The broth microdilution method was used for detecting the Minimal Inhibitory Concentration (MIC) of Streptococcus agalactiae (n = 51), Streptococcus dysgalactiae (n = 54), Streptococcus uberis (n = 50), Staphylococcus aureus (n = 85), non-aureus staphylococci (n = 88), Escherichia coli (n = 54) and Klebsiella species (n = 52). Streptococci and staphylococci were tested against cefquinome, cefoperazone, cephapirin, penicillin, oxacillin, cloxacillin, amoxicillin/clavulanic acid and cefalexin/kanamycin. Besides cefquinome and amoxicillin/clavulanic acid, Gram-negative pathogens were examined for their susceptibility to marbofloxacin and sulfamethoxazole/trimethoprim. The examined S. dysgalactiae isolates exhibited the comparatively lowest MICs. S. uberis and S. agalactiae were inhibited at higher amoxicillin/clavulanic acid and cephapirin concentration levels, whereas S. uberis isolates additionally exhibited elevated cefquinome MICs. Most Gram-positive mastitis pathogens were inhibited at higher cloxacillin than oxacillin concentrations. The MICs of Gram-negative pathogens were higher than previously reported, whereby 7.4%, 5.6% and 11.1% of E. coli isolates had MICs above the highest concentrations tested for cefquinome, marbofloxacin and sulfamethoxazole/trimethoprim, respectively. Individual isolates showed MICs at comparatively higher concentrations, leading to the hypothesis that a certain amount of mastitis pathogens on German dairy farms might be resistant to frequently used antimicrobials.
Catalogs of competency-based learning objectives (CLO) were introduced and promoted as a prerequisite for high-quality, systematic curriculum development. While this is common in medicine, the consistent use of CLO is not yet well established in epidemiology, biometry, medical informatics, biomedical informatics, and nursing informatics especially in Germany. This paper aims to identify underlying obstacles and give recommendations in order to promote the dissemination of CLO for curricular development in health data and information sciences. To determine these obstacles and recommendations a public online expert workshop was organized. This paper summarizes the findings.
Compounds that exhibit the spin crossover effect are known to show a change of spin states through external stimuli. This reversible switching of spin states is accompanied by a change of the properties of the compound. Complexes, like iron (II)-triazole complexes, that exhibit this behavior at ambient temperature are often discussed for potential applications. In previous studies we synthesized iron (II)-triazole complexes and implemented them into electrospun nanofibers. We used Mössbauer spectroscopy in first studies to prove a successful implementation with maintaining spin crossover properties. Further studies from us showed that it is possible to use different electrospinning methods to either do a implementation or a deposition of the synthesized solid SCO material into or onto the polymer nanofibers. We now used a solvent in which both, the used iron (II)-triazole complex [Fe(atrz)3](2 ns)2 and three different polymers (Polyacrylonitrile, Polymethylmethacrylate and Polyvinylpyrrolidone), are soluble. This shall lead to a higher homogeneous distribution of the complex along the nanofibers. Mössbauer spectroscopy and other measurements are therefore in use to show a successful implementation without any significant changes to the complex.
The objective of this study was to investigate the occurrence of bacteremia in dairy cows with severe mastitis. Milk samples were collected from affected udder quarters, and corresponding blood samples were collected from dairy cows with severe mastitis at the time of diagnosis before any therapeutic measures were undertaken. The cultural detection of pathogens in blood classified a bacteremia. Further diagnostic tests were performed to provide evidence of bacteremia. This was realized by PCR with regard to S. aureus, E. coli and S. uberis and the Limulus test. Detection of culturable pathogens in the blood of cows with severe clinical mastitis was rare and occurred in only one of 70 (1.4%) cases. Overall, bacterial growth was detected in 53 of 70 (75.7%) milk samples. S. uberis (22/70), E. coli (12/70) and S. aureus (4/70) were the most frequently isolated pathogens from milk of cows with severe mastitis. PCR was performed in 38 of 70 (54.3%) blood samples. PCR was positive in eight of 38 cases. S. uberis was found most frequently in six blood samples (8.6%). E. coli was found on PCR in one blood sample (1.4%). S. aureus was identified in one blood sample (1.4%). When Coliforms were detected in the quarter milk sample, a Limulus test was performed in the corresponding blood sample. In three of 15 cases, the Limulus test was positive (4.3% of samples). Further studies are needed to investigate the occurrence of bacteremia in cows with severe mastitis in a higher population size.
Complex Event Processing (CEP) is a modern software technology for the dynamic analysis of continuous data streams. CEP is able of searching extremely large data streams in real time for the presence of event patterns. So far, specifying event patterns of CEP rules is still a manual task based on the expertise of domain experts. This paper presents a novel batinspired swarm algorithm for automatically mining CEP rule patterns that express the relevant causal and temporal relations hidden in data streams. The basic suitability and performance of the approach is proven by extensive evaluation with both synthetically generated data and real data from the traffic domain.
M2M (machine-to-machine) systems use various communication technologies for automatically monitoring and controlling machines. In M2M systems, each machine emits a continuous stream of data records, which must be analyzed in real-time. Intelligent M2M systems should be able to diagnose their actual states and to trigger appropriate actions as soon as critical situations occur. In this paper, we show how complex event processing (CEP) can be used as the key technology for intelligent M2M systems. We provide an event-driven architecture that is adapted to the M2M domain. In particular, we define different models for the M2M domain, M2M machine states and M2M events. Furthermore, we present a general reference architecture defining the main stages of processing machine data. To prove the usefulness of our approach, we consider two real-world examples ‘solar power plants’ and ‘printers’, which show how easily the general architecture can be extended to concrete M2M scenarios.
In this article, we present the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in a consultancy situation. Software agents act as clients and advisors, using their knowledge to assist human users. In the presented architecture, the domain knowledge is modeled semantically by means of XML-based ontology languages such as OWL. Using an inference engine, the agents reason, based on their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand, private data, which has to be protected against unauthorized access; and on the other hand, publicly accessible knowledge spread over different Web sites. As in a real consultancy, an agent only reveals sensitive private data, if they are indispensable for finding a solution. In addition, depending on the actual consultancy situation, each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. Due to the standardization of OWL, knowledge models easily can be shared and accessed via the Internet. The usefulness of our approach is proved by the implementation of an advisory system in the Semantic E-learning Agent (SEA) project, whose objective is to develop virtual student advisers that render support to university students in order to successfully organize and perform their studies.
Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who struggle to complete those tasks successfully, resulting in high failure rates and low service quality. A promising solution to ensure higher quality of service is to continuously adapt the assignment and respond to failure-causing events by transferring tasks to better-suited workers who use different routes or vehicles. However, implementing task transfers in mobile crowdsourcing is difficult because workers are autonomous and may reject transfer requests. Moreover, task outcomes are uncertain and need to be predicted. In this paper, we propose different mechanisms to achieve outcome prediction and task coordination in mobile crowdsourcing. First, we analyze different data stream learning approaches for the prediction of task outcomes. Second, based on the suggested prediction model, we propose and evaluate two different approaches for task coordination with different degrees of autonomy: an opportunistic approach for crowdshipping with collaborative, but non-autonomous workers, and a market-based model with autonomous workers for crowdsensing.
To optimise udder health at the herd level, identifying incurable mastitis cases as well as providing an adequate therapy and culling strategy are necessary. Cows with clinical mastitis should be administered antibiotic medication if it is most likely to improve mammary cure. The somatic cell count (SCC) in milk of the monthly implemented Dairy Herd Improvement (DHI) test represents the most important tool to decide whether a cow has a promising mammary cure rate. Differential cell count (DCC) facilitates the specification of the immunological ability of defence, for example by characterising leukocyte subpopulations or cell viability. The aim of this study was to assess the DCC and cell viability in DHI milk samples regarding the cytological (CC) and bacteriological cure (BC) of the udder within a longitudinal study, thereby gaining a predictive evaluation of whether a clinical mastitis benefits from an antibiotic treatment or not. The cows enrolled in this study had an SCC above 200,000 cells/mL in the previous DHI test. Study 1 assessed the CC by reference to the SCC of two consecutive DHI tests and included 1010 milk samples: 28.4% of the mammary glands were classified as cytologically cured and 71.6% as uncured. The final mixed logistic regression model identified the total number of non-vital cells as a significant factor associated with CC. An increasing amount of non-vital cells was related to a lower individual ability for CC. Cows which were in the first or second lactation possessed a higher probability of CC than cows having a lactation number above two. If animals developed a clinical mastitis after flow cytometric investigation, the BC was examined in study 2 by analysing quarter foremilk samples microbiologically. Taking 48 milk samples, 81.3% of the mammary glands were classified as bacteriologically cured and 18.7% as uncured. The percentage of total non-vital cells tended to be lower for cows which were cured, but no significance could be observed. This study revealed that the investigation of the proportion of non-vital cells in DHI milk samples can enhance the prognosis of whether an antibiotic treatment of clinical mastitis might be promising or not. Prospectively, this tool may be integrated in the DHI tests to facilitate the decision between therapy or culling.
We present a methodology based on mixed-integer nonlinear model predictive control for a real-time building energy management system in application to a single-family house with a combined heat and power (CHP) unit. The developed strategy successfully deals with the switching behavior of the system components as well as minimum admissible operating time constraints by use of a special switch-cost-aware rounding procedure. The quality of the presented solution is evaluated in comparison to the globally optimal dynamic programming method and conventional rule-based control strategy. Based on a real-world scenario, we show that our approach is more than real-time capable while maintaining high correspondence with the globally optimal solution. We achieve an average optimality gap of 2.5% compared to 20% for a conventional control approach, and are faster and more scalable than a dynamic programming approach.
This paper presents the fundamental investigation on crack propagation rate (CPR) and Stress Intensity Factor (SIF) for a typical fatigue and welded specimens which are Compact Tension (CT) and Single Edge Notch Tension (SENT) as well as Butt and longitudinal T-joint. The material data of austenitic stainless steel SS316L was used to observe crack propagation rate with different initial crack length and different tensile load was used for the fracture mechanics investigation. The geometry of the specimens was modelled by using open source software CASCA while Franc 2D was used for post processing based on Paris Erdogan Law with different crack increment steps. The analysis of crack propagation using fracture mechanics technique requires an accurate calculation of the stress intensity factor SIF and comparison of the critical strength of the material (KIC) was used to determine the critical crack length of the specimens. it can be concluded that open source finite element method software can be used for predicting of fatigue life on simplified geometry.
Microservices build a deeply distributed system. Although this offers significant flexibility for development teams and helps to find solutions for scalability or security questions, it also intensifies the drawbacks of a distributed system. This article offers a decision framework, which helps to increase the resiliency of microservices. A metamodel is used to represent services, resiliency patterns, and quality attributes. Furthermore, the general idea for a suggestion procedure is outlined.
There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.
Clinical scores and motion-capturing gait analysis are today’s gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients’ actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee.
Worldwide, seagrass meadows are under threat. Consequently, there is a strong need for seagrass restoration to guarantee the provision of related ecosystem services such as nutrient cycling, carbon sequestration and habitat provision. Seagrass often grows in vast meadows in which the presence of seagrass itself leads to a reduction of hydrodynamic energy. By modifying the environment, seagrass thus serves as foundation species and ecosystem engineer improving habitat quality for itself and other species as well as positively affecting its own fitness. On the downside, this positive feedback mechanism can render natural recovery of vanished and destroyed seagrass meadows impossible. An innovative approach to promote positive feedback mechanisms in seagrass restoration is to create an artificial seagrass (ASG) that mimics the facilitation function of natural seagrass. ASG could provide a window of opportunity with respect to suitable hydrodynamic and light conditions as well as sediment stabilization to allow natural seagrass to re-establish. Here, we give an overview of challenges and open questions for the application of ASG to promote seagrass restoration based on experimental studies and restoration trials and we propose a general approach for the design of an ASG produced from biodegradable materials. Considering positive feedback mechanisms is crucial to support restoration attempts. ASG provides promising benefits when habitat conditions are too harsh for seagrass meadows to re-establish themselves.
NOA is a search engine for scientific images from open access publications based on full text indexing of all text referring to the images and filtering for disciplines and image type. Images will be annotated with Wikipedia categories for better discoverability and for uploading to WikiCommons. Currently we have indexed approximately 2,7 Million images from over 710 000 scientific papers from all fields of science.
Scientific papers from all disciplines contain many abbreviations and acronyms. In many cases these acronyms are ambiguous. We present a method to choose the contextual correct definition of an acronym that does not require training for each acronym and thus can be applied to a large number of different acronyms with only few instances. We constructed a set of 19,954 examples of 4,365 ambiguous acronyms from image captions in scientific papers along with their contextually correct definition from different domains. We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of the acronym. We show that this method clearly outperforms (classical) cosine similarity. Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.
Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.
Concreteness of words has been measured and used in psycholinguistics already for decades. Recently, it is also used in retrieval and NLP tasks. For English a number of well known datasets has been established with average values for perceived concreteness.
We give an overview of available datasets for German, their correlation and evaluate prediction algorithms for concreteness of German words. We show that these algorithms achieve similar results as for English datasets. Moreover, we show for all datasets there are no significant differences between a prediction model based on a regression model using word embeddings as features and a prediction algorithm based on word similarity according to the same embeddings.
Image captions in scientific papers usually are complementary to the images. Consequently, the captions contain many terms that do not refer to concepts visible in the image. We conjecture that it is possible to distinguish between these two types of terms in an image caption by analysing the text only. To examine this, we evaluated different features. The dataset we used to compute tf.idf values, word embeddings and concreteness values contains over 700 000 scientific papers with over 4,6 million images. The evaluation was done with a manually annotated subset of 329 images. Additionally, we trained a support vector machine to predict whether a term is a likely visible or not. We show that concreteness of terms is a very important feature to identify terms in captions and context that refer to concepts visible in images.
Malnutrition, nutritional deficiency, or undernutrition is an imbalanced nutritional status resulting from insufficient intake of nutrients to meet normal physiologic requirements. Malnutrition in childhood has both short-term consequences and long-term consequences on mental and physical health as well as the overall health development of children. Of all regions in the world, the Asia and the Pacific region has achieved the fastest rate of economic growth. There is no evidence that this rapid economic growth translates into a decline in malnutrition of children in Asian countries such as India.
Surface atomic relaxation and magnetism on hydrogen-adsorbed Fe(110) surfaces from first principles
(2016)
We have computed adsorption energies, vibrational frequencies, surface relaxation and buckling for hydrogen adsorbed on a body-centred-cubic Fe(110) surface as a function of the degree of H coverage. This adsorption system is important in a variety of technological processes such as the hydrogen embrittlement in ferritic steels, which motivated this work, and the Haber–Bosch process. We employed spin-polarised density functional theory to optimise geometries of a six-layer Fe slab, followed by frozen mode finite displacement phonon calculations to compute Fe–H vibrational frequencies. We have found that the quasi-threefold (3f) site is the most stable adsorption site, with adsorption energies of ∼3.0 eV/H for all coverages studied. The long-bridge (lb) site, which is close in energy to the 3f site, is actually a transition state leading to the stable 3f site. The calculated harmonic vibrational frequencies collectively span from 730 to 1220 cm−1, for a range of coverages. The increased first-to-second layer spacing in the presence of adsorbed hydrogen, and the pronounced buckling observed in the Fe surface layer, may facilitate the diffusion of hydrogen atoms into the bulk, and therefore impact the early stages of hydrogen embrittlement in steels.
The effect of magnetism on hydrogen adsorption and subsurface diffusion through face-centred cubic (fcc) γ-Fe(0 0 1) was investigated using spin-polarised density functional theory (s-DFT). The non-magnetic (NM), ferromagnetic (FM), and antiferromagnetic single (AFM1) and double layer (AFMD) structures were considered. For each magnetic state, the hydrogen preferentially adsorbs at the fourfold site, with adsorption energies of 4.07, 4.12, 4.03 and 4.05 eV/H atom for the NM, FM, AFM1 and AFMD structures. A total barrier of 1.34, 0.90, 1.32 and 1.25 eV and a bulk-like diffusion barrier of 0.6, 0.2, 0.4 and 0.3 eV were calculated for the NM, FM, AFM1 and AFMD magnetic states. The Fe atoms nearest to the H atom exhibited a reduced magnetic moment, whereas the next-nearest neighbour Fe atoms exhibited a non-negligible local perturbation in the magnetic moment. The presence of magnetically ordered structures has a minimal influence on the minimum energy path for H diffusion through the lattice and on the adsorption of H atoms on the Fe(0 0 1) surface, but we computed a significant reduction of the bulk-like diffusion barriers with respect to the non-magnetic state of fcc γ-Fe.
The adsorption of O atoms on the Fe(1 1 0) surface has been investigated by density functional theory for increasing degrees of oxygen coverage from 0.25 to 1 monolayer, to follow the evolution of the Osingle bondFe(1 1 0) system into an FeO(1 1 1)-like monolayer. We found that the quasi-threefold site is the most stable adsorption site for all coverages, with adsorption energies of ∼2.8–4.0 eV per O atom. Oxygen adsorption results in surface geometrical changes such as interlayer relaxation and buckling, the latter of which decreases with coverage. The calculated vibrational frequencies range from 265 to 470 cm−1 for the frustrated translational modes and 480–620 cm−1 for the stretching mode, and hence are in good agreement with the experimental values reported for bulk FeO wüstite. The hybridization of the oxygen 2p and iron 3d orbitals increases with oxygen coverage, and the partial density of states for the Osingle bondFe(1 1 0) system at full coverage resembles the one reported in the literature for bulk FeO. These results at full oxygen coverage point to the incipient formation of an FeO(1 1 1)-like monolayer that would eventually lead to the bulk FeO oxide layer.
This study is concerned with the early stages of hydrogen embrittlement on an atomistic scale. We employed density functional theory to investigate hydrogen diffusion through the (100), (110) and (111) surfaces of γ-Fe. The preferred adsorption sites and respective energies for hydrogen adsorption were established for each plane, as well as a minimum energy pathway for diffusion. The H atoms adsorb on the (100), (110) and (111) surfaces with energies of ∼4.06 eV, ∼3.92 eV and ∼4.05 eV, respectively. The barriers for bulk-like diffusion for the (100), (110) and (111) surfaces are ∼0.6 eV, ∼0.5 eV and ∼0.7 eV, respectively. We compared these calculated barriers with previously obtained experimental data in an Arrhenius plot, which indicates good agreement between experimentally measured and theoretically predicted activation energies. Texturing austenitic steels such that the (111) surfaces of grains are preferentially exposed at the cleavage planes may be a possibility to reduce hydrogen embrittlement.
The present investigation was conducted to investigate the in-vitro activity of ethanolic extract of roots of Centaurea behens by using DPPH radical scavenging activity, nitric oxide radical scavenging activity, hydrogen peroxide radical scavenging activity, hydroxyl radical. Result suggests that the extract possess significant antioxidant activity as compared to the standard ascorbic acid and thus further in vivo investigation is required to evaluate the medicinal significance of the extract which can be used for assessing the possible therapeutic importance of the drug.
AlphaGo’s victory against Lee Sedol in the game of Go has been a milestone in artificial intelligence. After this success, the team behind the program further refined the architecture and applied it to many other games such as chess or shogi. In the following thesis, we try to apply the theory behind AlphaGo and its successor AlphaZero to the game of Abalone. Due to limitations in computational resources, we could not replicate the same exceptional performance.
Background: Stereotactic radiosurgery (SRS) is an effective treatment for trigeminal neuralgia (TN). Nevertheless, a proportion of patients will experience recurrence and treatment-related sensory disturbances. In order to evaluate the predictors of efficacy and safety of image-guided non-isocentric radiosurgery, we analyzed the impact of trigeminal nerve volume and the nerve dose/volume relationship, together with relevant clinical characteristics.
Methods: Two-hundred and ninety-six procedures were performed on 262 patients at three centers. In 17 patients the TN was secondary to multiple sclerosis (MS). Trigeminal pain and sensory disturbances were classified according to the Barrow Neurological Institute (BNI) scale. Pain-free-intervals were investigated using Kaplan Meier analyses. Univariate and multivariate Cox regression analyses were performed to identify predictors.
Results: The median follow-up period was 38 months, median maximal dose 72.4 Gy, median target nerve volume 25mm3, and median prescription dose 60 Gy. Pain control rate (BNI I-III) at 6, 12, 24, 36, 48, and 60 months were 96.8, 90.9, 84.2, 81.4, 74.2, and 71.2%, respectively. Overall, 18% of patients developed sensory disturbances. Patients with volume ≥ 30mm3 were more likely to maintain pain relief (p = 0.031), and low integral dose (< 1.4 mJ) tended to be associated with more pain recurrence than intermediate (1.4–2.7 mJ) or high integral dose (> 2.7 mJ; low vs. intermediate: log-rank test, χ2 = 5.02, p = 0.019; low vs. high: log-rank test, χ2 = 6.026, p = 0.014). MS, integral dose, and mean dose were the factors associated with pain recurrence, while re-irradiation and MS were predictors for sensory disturbance in the multivariate analysis.
Conclusions: The dose to nerve volume ratio is predictive of pain recurrence in TN, and re-irradiation has a major impact on the development of sensory disturbances after non-isocentric SRS. Interestingly, the integral dose may differ significantly in treatments using apparently similar dose and volume constraints.
A new type of rotary compressor, called “rotary-chamber compressor”, consists of two interlocking rotors with 4 wings each, that perform non-uniform rotary movements. Both rotors have the same direction of rotation, while one rotor is accelerating, the other rotor is retarding. After surpassing a specific mark, the sequence changes and the leading rotor begins to retard and vice versa. Due to the resulting relative phase difference, the volume between the two wings is changing periodically, which allows pulsating working chambers. The technology was first introduced by its founder Jürgen Schukey in 1987. Since then, no further development on this machine is known to us except our own. In this contribution, a study on the kinematics of the rotary-chamber-compressor is presented. Initial studies have shown that changes in the kinematics of the rotors will have a direct influence on the thermodynamical variables, which, if optimized, can lead to an increased performance of the machine. Therefore, a mathematical model has been developed to obtain the performance parameters from different kinematic concepts by using numerical CFD analysis. Furthermore, additional optimization possibilities will be listed and discussed.
Primary data is an important source ofinformation for Competitive Intelligence. Traditionally, it has been collected from interviews with stakeholders, talks at conferences and other means of direct interpersonal communication. The role of the Internet in the data collection – if it was used at all – was that of a provider of supplementary secondary data. Here, this approach is challenged and, using three examples of Social Media, it is shown that the Internet can and does provide valuable primary information to the Competitive Intelligence professional. Accordingly, a case is made for a shift of focus in the data collection process.
Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.
Purpose: Radiology reports mostly contain free-text, which makes it challenging to obtain structured data. Natural language processing (NLP) techniques transform free-text reports into machine-readable document vectors that are important for creating reliable, scalable methods for data analysis. The aim of this study is to classify unstructured radiograph reports according to fractures of the distal fibula and to find the best text mining method.
Materials & Methods: We established a novel German language report dataset: a designated search engine was used to identify radiographs of the ankle and the reports were manually labeled according to fractures of the distal fibula. This data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (BOW), term frequency-inverse document frequency (TF-IDF), principal component analysis (PCA), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), and document embedding (doc2vec). The extracted document vectors were used to train neural networks (NN), support vector machines (SVM), and logistic regression (LR) to recognize distal fibula fractures. The results were compared via cross-tabulations of the accuracy (acc) and area under the curve (AUC).
Results: In total, 3268 radiograph reports were included, of which 1076 described a fracture of the distal fibula. Comparison of the text representation methods showed that BOW achieved the best results (AUC = 0.98; acc = 0.97), followed by TF-IDF (AUC = 0.97; acc = 0.96), NMF (AUC = 0.93; acc = 0.92), PCA (AUC = 0.92; acc = 0.9), LDA (AUC = 0.91; acc = 0.89) and doc2vec (AUC = 0.9; acc = 0.88). When comparing the different classifiers, NN (AUC = 0,91) proved to be superior to SVM (AUC = 0,87) and LR (AUC = 0,85).
Conclusion: An automated classification of unstructured reports of radiographs of the ankle can reliably detect findings of fractures of the distal fibula. A particularly suitable feature extraction method is the BOW model.
Key Points:
- The aim was to classify unstructured radiograph reports according to distal fibula fractures.
- Our automated classification system can reliably detect fractures of the distal fibula.
- A particularly suitable feature extraction method is the BOW model.
Data and Information Science: Book of Abstracts at BOBCATSSS 2022 Hybrid Conference, 23rd - 25th of May 2022, Debrecen.
This year marks the 30th anniversary of the BOBCATSSS. The BOBCATSSS is an international, annual symposium designed for librarians and information professionals in a rapidly changing environment. Over the past 30 years, the conference has included exciting topics, great venues, interested guests and engaging presenters.
This year we would like to introduce the topics of the many papers presented in the Book of Abstracts for the first time in presence at the University of Debrecen and hybrid. The Book of Abstracts provides an overview of all presentations given at BOBCATSSS. Presentations are listed in alphabetical order by title and include speeches, Pecha Kuchas, posters and workshops.
The theme of BOBCATSSS is Data and Information Science. Data and information are the basis for decisions and processes in business, politics and science. Particularly important in the current era of digital transformation. This is exactly where this year's subthemes come in. They deal with data science, openness as well as institutional roles.
With the increasing significance of information technology, there is an urgent need for adequate measures of information security. Systematic information security management is one of most important initiatives for IT management. At least since reports about privacy and security breaches, fraudulent accounting practices, and attacks on IT systems appeared in public, organizations have recognized their responsibilities to safeguard physical and information assets. Security standards can be used as guideline or framework to develop and maintain an adequate information security management system (ISMS). The standards ISO/IEC 27000, 27001 and 27002 are international standards that are receiving growing recognition and adoption. They are referred to as “common language of organizations around the world” for information security. With ISO/IEC 27001 companies can have their ISMS certified by a third-party organization and thus show their customers evidence of their security measures.
Systematizing IT Risks
(2019)
IT risks — risks associated with the operation or use of information technology — have taken on great importance in business, and IT risk management is accordingly important in the science and practice of information management. Therefore, it is necessary to systematize IT risks in order to plan, manage and control for different risk-specific measures. In order to choose and implement suitable measures for managing IT risks, effect-based and causebased procedures are necessary. These procedures are explained in detail for IT security risks because of their special importance.
Aim/Purpose: We explore impressions and experiences of Information Systems graduates during their first years of employment in the IT field. The results help to understand work satisfaction, career ambition, and motivation of junior employees. This way, the attractiveness of working in the field of IS can be increased and the shortage of junior employees reduced.
Background: Currently IT professions are characterized by terms such as “shortage of professionals” and “shortage of junior employees”. To attract more people to work in IT detailed knowledge about experiences of junior employees is necessary.
Methodology: Data from a large survey of 193 graduates of the degree program “Information Systems” at University of Applied Sciences and Arts Hannover (Germany) show characteristics of their professional life like work satisfaction, motivation, career ambition, satisfaction with opportunities, development and career advancement, satisfaction with work-life balance. It is also asked whether men and women gain the same experiences when entering the job market and have the same perceptions.
Findings: The participants were highly satisfied with their work, but limitations or restrictions due to gender are noteworthy.
Recommendations for Practitioners: The results provide information on how human resource policies can make IT professions more attractive and thus convince graduates to seek jobs in the field. For instance, improving the balance between work and various areas of private life seems promising. Also, restrictions with respect to the work climate and improving communication along several dimensions need to be considered.
Future Research: More detailed research on ambition and achievement is necessary to understand gender differences.
The objective of this student project was for the students to develop, conduct, and supervise a training course for basic work place applications (word processing and business graphics). Students were responsible for the planning, organizing and the teaching of the course. As participants, underprivileged adolescents took part in order to learn the handling of IT applications and therefore, improve their job skills and have a better chance to get into employment. Therefore the adolescents do the role of trainees at the course. Our students worked with a population that is continually overlooked by the field.
As a result, the students trained to design and implement training courses, exercised to manage projects and increased their social responsibility and awareness concerning the way of life and living conditions of other young people. The underprivileged adolescents learned to use important business applications and increased their job skills and job chances. The overall design of our concept required extensive resources to supervise and to steer the students and the adolescents. The lecturers had to teach and to counsel the students and had to be on “stand-by” just in case they were needed to solve critical situations between the two groups of young people.
BYOD Bring Your Own Device
(2013)
Using modern devices like smartphones and tablets offers a wide variety of advantages; this has made them very popular as consumer devices in private life. Using them in the workplace is also popular. However, who wants to carry around and handle two devices; one for personal use, and one for work-related tasks? That is why “dual use”, using one single device for private and business applications, may represent a proper solution. The result is “Bring Your Own Device,” or BYOD, which describes the circumstance in which users make their own personal devices available for company use. For companies, this brings some opportunities and risks. We describe and discuss organizational issues, technical approaches, and solutions.
During the European debt crisis, German and Greek media frequently reported on the political conflict between the two countries. This article examines to what extent the media coverage in one country about the other is considered by German and Greek citizens to be hostile (‘hostile media perception’) and influential (‘influence of presumed influence’). Data from a comparative survey in Germany (n = 492) and Greece (n = 484) show that news coverage by foreign media on the European debt crisis is perceived by respondents as hostile against their own country and as influential. Moreover, both media-related perceptions are linked with intensified perceptions of hostility, such as assumptions that an individual’s country is not respected in the other country or that the other country’s citizens are demanding that the individual’s country be punished. Based on these results, it is discussed whether media-related perceptions can have a conflict-intensifying effect in international crises.
Nowadays, problems related with solid waste management become a challenge for most countries due to the rising generation of waste, related environmental issues, and associated costs of produced wastes. Effective waste management systems at different geographic levels require accurate forecasting of future waste generation. In this work, we investigate how open-access data, such as provided from the Organisation for Economic Co-operation and Development (OECD), can be used for the analysis of waste data. The main idea of this study is finding the links between socioeconomic and demographic variables that determine the amounts of types of solid wastes produced by countries. This would make it possible to accurately predict at the country level the waste production and determine the requirements for the development of effective waste management strategies. In particular, we use several machine learning data regression (Support Vector, Gradient Boosting, and Random Forest) and clustering models (k-means) to respectively predict waste production for OECD countries along years and also to perform clustering among these countries according to similar characteristics. The main contributions of our work are: (1) waste analysis at the OECD country-level to compare and cluster countries according to similar waste features predicted; (2) the detection of most relevant features for prediction models; and (3) the comparison between several regression models with respect to accuracy in predictions. Coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), respectively, are used as indices of the efficiency of the developed models. Our experiments have shown that some data pre-processings on the OECD data are an essential stage required in the analysis; that Random Forest Regressor (RFR) produced the best prediction results over the dataset; and that these results are highly influenced by the quality of available socio-economic data. In particular, the RFR model exhibited the highest accuracy in predictions for most waste types. For example, for “municipal” waste, it produced, respectively, R2 = 1 and MAPE = 4.31 global error values for the test set; and for “household” waste, it, respectively, produced R2 = 1 and MAPE = 3.03. Our results indicate that the considered models (and specially RFR) all are effective in predicting the amount of produced wastes derived from input data for the considered countries.
Decision support systems for traffic management systems have to cope with a high volume of events continuously generated by sensors. Conventional software architectures do not explicitly target the efficient processing of continuous event streams. Recently, event-driven architectures (EDA) have been proposed as a new paradigm for event-based applications. In this paper we propose a reference architecture for event-driven traffic management systems, which enables the analysis and processing of complex event streams in real-time and is therefore well-suited for decision support in sensor-based traffic control sys- tems. We will illustrate our approach in the domain of road traffic management. In particular, we will report on the redesign of an intelligent transportation management system (ITMS) prototype for the high-capacity road network in Bilbao, Spain.
Nowadays, most recommender systems are based on a centralized architecture, which can cause crucial issues in terms of trust, privacy, dependability, and costs. In this paper, we propose a decentralized and distributed MANET-based (Mobile Ad-hoc NETwork) recommender system for open facilities. The system is based on mobile devices that collect sensor data about users locations to derive implicit ratings that are used for collaborative filtering recommendations. The mechanisms of deriving ratings and propagating them in a MANET network are discussed in detail. Finally, extensive experiments demonstrate the suitability of the approach in terms of different performance metrics.
Nowadays, smartphones and sensor devices can provide a variety of information about a user’s current situation. So far, many recommender systems neglect this kind of information and thus cannot provide situationspecific recommendations. Situation-aware recommender systems adapt to changes in the user’s environment and therefore are able to offer recommendations that are more appropriate for the current situation. In this paper, we present a software architecture that enables situation awareness for arbitrary recommendation techniques. The proposed system considers both (semi-)static user profiles and volatile situational knowledge to obtain meaningful recommendations. Furthermore, the implementation of the architecture in a museum of natural history is presented, which uses Complex Event Processing to achieve situation awareness.
In parcel delivery, the “last mile” from the parcel hub to the customer is costly, especially for time-sensitive delivery tasks that have to be completed within hours after arrival. Recently, crowdshipping has attracted increased attention as a new alternative to traditional delivery modes. In crowdshipping, private citizens (“the crowd”) perform short detours in their daily lives to contribute to parcel delivery in exchange for small incentives. However, achieving desirable crowd behavior is challenging as the crowd is highly dynamic and consists of autonomous, self-interested individuals. Leveraging crowdshipping for time-sensitive deliveries remains an open challenge. In this paper, we present an agent-based approach to on-time parcel delivery with crowds. Our system performs data stream processing on the couriers’ smartphone sensor data to predict delivery delays. Whenever a delay is predicted, the system attempts to forge an agreement for transferring the parcel from the current deliverer to a more promising courier nearby. Our experiments show that through accurate delay predictions and purposeful task transfers many delays can be prevented that would occur without our approach.
Background: Maintenance of metal homeostasis is crucial in bacterial pathogenicity as metal starvation is the most important mechanism in the nutritional immunity strategy of host cells. Thus, pathogenic bacteria have evolved sensitive metal scavenging systems to overcome this particular host defence mechanism. The ruminant pathogen Mycobacterium avium ssp. paratuberculosis (MAP) displays a unique gut tropism and causes a chronic progressive intestinal inflammation. MAP possesses eight conserved lineage specific large sequence polymorphisms (LSP), which distinguish MAP from its ancestral M. avium ssp. hominissuis or other M. avium subspecies. LSP14 and LSP15 harbour many genes proposed to be involved in metal homeostasis and have been suggested to substitute for a MAP specific, impaired mycobactin synthesis.
Results: In the present study, we found that a LSP14 located putative IrtAB-like iron transporter encoded by mptABC was induced by zinc but not by iron starvation. Heterologous reporter gene assays with the lacZ gene under control of the mptABC promoter in M. smegmatis (MSMEG) and in a MSMEGΔfurB deletion mutant revealed a zinc dependent, metalloregulator FurB mediated expression of mptABC via a conserved mycobacterial FurB recognition site. Deep sequencing of RNA from MAP cultures treated with the zinc chelator TPEN revealed that 70 genes responded to zinc limitation. Remarkably, 45 of these genes were located on a large genomic island of approximately 90 kb which harboured LSP14 and LSP15. Thirty-five of these genes were predicted to be controlled by FurB, due to the presence of putative binding sites. This clustering of zinc responsive genes was exclusively found in MAP and not in other mycobacteria.
Conclusions: Our data revealed a particular genomic signature for MAP given by a unique zinc specific locus, thereby suggesting an exceptional relevance of zinc for the metabolism of MAP. MAP seems to be well adapted to maintain zinc homeostasis which might contribute to the peculiarity of MAP pathogenicity.
Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories “governance”, “modeling” and “standards”, the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling.
BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.