Miracle-dz/UniFAR-FTUs huggingface dataset:
Biosignal laboratory: a software tool for biomedical signal processing and analysis

Biosignal processing and analysis is a field of great importance in current medical practice. In recent years, biomedical engineers have developed many algorithms and processing techniques in order to help doctors in the examination of many different biosignals, and to find new information embedded in them and not easily observable in the raw data. Since the number and variety of these techniques grows every day, it is becoming more and more difficult to be up to date in biosignal processing. Other aspects such as signals format, algorithms implementation and comparison, artifacts, etc, make the learning process in this field longer and longer, and in many occasions a lot of different software tools are needed to visualize or process biosignals. In this paper we present a program that consists of many of the current typical biosignal processing algorithms: filtering, domain transforms, basic operators, wave detection, and unlike other similar applications, it includes a pattern recognition block. The program can also be used just to exchange signals formats. The objective of this program is to become a usual tool both for medical practice and for biomedical educational purposes.
Detecting Restriction Class Correspondences in Linked Data: The Bayes-ReCCE Bayesian Model Approach

Linked Data consists of many structured data knowledge bases that have been interlinked, often using equivalence statements. These equivalences usually take the form of owl:sameAs statements linking individuals, links between classes are far less common Often, the lack of class links is because their relationships cannot be described as one to one equivalences. Instead, complex correspondences referencing logical combinations of multiple entities are often needed to describe how the classes in an ontology are related to classes in a second ontology. This chapter introduces a novel Bayesian Restriction Class Correspondence Estimation (Bayes-ReCCE) algorithm, an extensional approach to detecting complex correspondences between classes. Bayes-ReCCE operates by analysing features of matched individuals in the knowledge bases, and uses Bayesian inference to search for complex correspondences between the classes these individuals belong to. Bayes-ReCCE is designed to be capable of providing meaningful results even when only small numbers of matched instances are available.
Applying Hierarchical Contextual Parsing with Visual Density and Geometric Features to Typeset Formula Recognition

Applying Hierarchical Contextual Parsing with Visual Density and Geometric Features to Typeset Formula Recognition Michael Patrick Erickson Condon, M.S. Rochester Institute of Technology, 2017 Supervisor: Dr. Richard Zanibbi We demonstrate that recognition of scanned typeset mathematical expression images can be done by extracting maximum spanning trees from line of sight graphs weighted using geometric and visual density features. The approach used is hierarchical contextual parsing (HCP): Hierarchical in terms of starting with connected components and building to the symbol level using visual, spatial, and contextual features of connected components. Once connected components have been segmented into symbols, a new set of spatial, visual, and contextual features are extracted. One set of visual features is used for symbol classification, and another for parsing. The features are used in parsing to assign classifications and confidences to edges in a line of sight symbol graph. Layout trees describe expression structure in terms of spatial relations between symbols, such as horizontal, subscript, and superscript. From the weighted graph Edmonds’ algorithm is used to extract a maximum
Parameterized skeletons in Maude

Algorithmic skeletons are a well-known approach for implementing distributed applications. Declarative versions typically use higher-order functions in functional languages. We show here a different approach based on parameterized modules in Maude, that receive the operations needed to solve a concrete problem as a parameter. Architectures are conceived separately from the skeletons that are executed on top of them. The object-oriented methodology followed facilitates nesting of skeletons and the combination of architectures. Maude analysis tools allow to check properties of the applications built by instantiating a skeleton at different abstraction levels.
CYTOGENETIC DEMONSTRATION OF PERMANENT TOLERANCE IN ADULT OUTBRED DOGS

Two male dogs were given supralethal whole-body irradiation followed by an infusion of bone marrow obtained from unrelated female donors. Three and 4 years later, chromosomal analyses of cells obtained from bone marrow, peripheral blood, and lymph nodes from these males showed in all analyzable cells the presence of the typical female karyotype. It is concluded that in these clinically well, adult animals a true chimeric state and mutual tolerance between graft and host has been achieved on a long-term basis.
Optimization of pinhole SPECT calibration

Previously, we developed a method to determine the acquisition geometry of a pinhole camera. This information is needed for the correct reconstruction of pinhole SPECT images. The method uses a calibration phantom consisting of three point sources. Their positions in the field of view influence the accuracy of the geometry estimate. This study proposes a specific configuration of point sources with a specific position in the field of view for optimal image reconstruction accuracy. For the proposed calibration setup, inaccuracies of the geometry estimate due to noise in the calibration data, only cause subresolution inaccuracies in reconstructed images. Further, the calibration method uses a model of the point source configuration, which is only known with limited accuracy. The study demonstrates however, that, with the proposed calibration setup, the error in reconstructed images is comparable to the error in the phantom model.
Inflationary Hedging Capacity of House Price Returns in Emerging Economy of Nigeria

Oz: Enflasyon riskine karsi koruyucu bir arac olarak konut sahipligi Nijerya’ni basenti Abuja icn arasiimisi. Arasimada besyerlesm bogesindeki konutlar secldi. Daha oceki clisalar kia doemde konut sahiplignin enflasyon riskini en kucu kareler yoteminin kullanarak ve kia doem icn arasimisardi Bu clisa kia ve uzun doemde konut getirilerinin ensflasyondan korunma kapasitesini arasimaktadi. Clisa kia doem enflasy onist etkiyi olcmek icin en kucuk kareler yontemini, ADF duraganlik testini ve uzun donem etkisini olcmek icin de Engel Granger koentegrasyon testini kullanmistir. Sonuclar kisa donemde konut piyasasinin enflasyondan korunma saglamadigini ortaya koymustur . Koentegrasyon regresyon sonucuna gore, uzun doenmde konut piyasasinda tam bir korunma saglandigi ve etkinin de 72,1 % - 88,2 % araliginda oldugu hesaplanmistir. Anahtar Kelimeler: Konut fiyat getirileri, gercek enflasyon, beklenen enflasyon, beklenmeyen enflasyon
Impulsivity and Decision-Making among Men Engaging in Mild Intimate Partner Violence

Research has been conducted supporting a Social Information Processing (McFall, 1982) conceptualization of intimate partner violence perpetration (Holtzworth-Munroe & Hutchinson, 1993; Nedegaard & Sbrocco, 2014). However, it has also been suggested that several transitory factors can influence the individual steps of this model (Crick & Dodge, 1994; McFall, 1989; Lemerise & Aresenio, 2000). One possible transitory factor is impulsivity. This study was designed to evaluate the effect of impulsivity on the perceived ability and utility of abusive behaviors among abusive men. Thirty-two abusive men, thirty-two maritally distressed, nonabusive men, and thirty-two maritally satisfied, nonabusive men were asked to complete a decision-making questionnaire where the subjective expected utilities (SEUs) and perceived ability ratings for specific behaviors were calculated using Multi-Attribute Utility Theory (MAUT). One-way ANOVAs revealed low impulsive abusers rated the SEUs of abusive behaviors significantly higher than any other group. Interestingly, non-impulsive abusers also rated their perceived ability to carry out healthy behaviors lower than all other groups. These findings suggest that there may continue to be value in conceptualizing abusive behavior within an impulsive/reactive and proactive/instrumental context. These findings suggest that abusive men who are low impulsive may be at greater risk of choosing abusive behaviors in marital conflict
Voltage Ripple Minimization in Modular Multilevel Converters using Modified Rotative PWM Scheme

Carrier-based pulse width modulation (PWM) schemes are usually employed in MMC fed variable speed drive (VSD) applications due to ease of implementation. Though this is the case, the phase-disposition PWM (PD-PWM) technique is a better choice as it is able to generate high-quality waveforms with a greater possibility of optimal switching. This technique suffers as it may provide uneven energy distribution among the submodules (SMs) and also non-uniform switch utilization. The use of carrier rotative PWM techniques as applied to MMC‘s will alleviate the problem of uneven energy distribution among the SMs, but the issue of non-uniform switch utilization still remains. A modified rotative PD-PWM (MRPD-PWM) technique is proposed in this paper, which retains the uniform energy distribution among the SMs while evenly distributing voltage distribution across SM capacitors. Moreover, this technique minimizes SM capacitor voltage ripple which can reduce the capacitance requirement in MMC-fed VSD applications. The performance of the proposed PWM scheme is compared with aforementioned PWM techniques for half-bridge submodule (HB-SM) based three-phase MMC in PLECS platform and verified experimentally under the same converter switching frequency.
Development of a Home Care Falls Prevention and Intervention Program

• Objective: To describe a falls prevention program implemented within a home health care agency. • Program: A falls committee made up of nurses and physical therapists was formed. The committee developed a program consisting of the following components: a risk assessment tool based on the medical and nursing literature, a teaching tool to educate patients and caregivers in the home about risk factors and how to reduce them, a referral algorithm for use by staff, and a staff inservice. • Results: There has been decrease in number of falls and staff knowledge and interest has increased. • Conclusion: It is possible to reduce falls in communitydwelling elderly patients.
Entwicklung einer dynamischen und prozessorientierten Augmented Reality Anwendung am Beispiel der AristaFlowBPM Suite und Android.

Diese Masterarbeit beschaftigt sich mit dem sehr aktuellen Themengebiet Augmented Reality (AR) verknupft mit prozessorientierten mobilen Anwendungen. Anhand eines ausgewahlten Szenarios wird gezeigt, dass diese Kombination neue innovative Methoden zum Anzeigen und Bearbeiten von Prozessinformationen ermoglicht. Aktivitaten, welche mit Positionsdaten verbunden sind (z.B. eine Adresse oder Koordinaten), werden direkt in die reale Welt projiziert und sind fur den Nutzer uber eine Smartphone-Kamera oder ein Head-up-Display visuell zuganglich. Auf Grundlage dieser Idee wird eine Android-Anwendung konzipiert, welche wesentliche Funktionen implementiert, um den Nutzer bei der Prozessbearbeitung gezielt zu unterstutzen. Diese werden aus technischer und konzeptioneller Sicht im Detail erlautert. Als Szenario fur diese Anwendung wurde ein Kurierdienst ausgewahlt. Samtliche damit verbundenen Ablaufe, wie das Erfassen einer Kundenunterschrift, die Auswahl eines Abholdatums oder die Authentifizierung des Kuriers, werden durch die Anwendung unterstutzt. Da die Anwendungsfalle, wie z.B. ein Abhol- und Lieferauftrag, sehr prozesslastig sind, eignet sich die AristaFlow BPM Suite optimal als Grundgerust. Zur Navigation bei einer Paketlieferung, kann der Kurier die AR-Sicht benutzen, welche die wichtigsten Prozessinformationen und zusatzlich den Zielort in der realen Welt anzeigt. Navigation und Prozessbearbeitung sind damit fliesend vereint. Darzustellende und zu erfassende Inhalte werden durch die AristaFlow Process-Engine gesteuert. Die Ablaufe sind hier in Form eines Prozesstemplates hinterlegt und konnen bei Bedarf geandert bzw. erweitert werden. Des Weiteren profitiert man von den umfangreichen Organisations- und Prozessmodellierungsmoglichkeiten. Uber den AristaFlow Webservice erhalt die mobile Anwendung Prozessdaten und generiert fur deren Anzeige und Bearbeitung dynamisch GUI-Elemente.
Computer-Assisted Screening and Intervention for Alcohol Problems in Primary Care

ABSTRACT The effectiveness of a bilingual (English/Spanish) computer-assisted alcohol screening/intervention for hazardous and harmful alcohol use, the Health Habits Survey (HHS) was tested in primary care settings. Assessment-only patients were compared with patients exposed to the HHS. Of the 2053 recruited, 151 (7.4%) screened positive on the Alcohol Use Disorders Identification Test (AUDIT) and were re-contacted six months later for follow-up. Significant alcohol reduction was observed in both conditions. No between-group differences were observed. Computer-assisted screening and intervention are feasible in primary care settings and may be a realistic provider-extender when traditional screening is absent or inconsistently implemented.
Statistical methods for comparing brain connectomes at different scales

Physiological Brain connectivity and spontaneous interaction between regions of interest of the brain can be represented by a matrix (full or sparse) or equivalently by a complex network called connectome. This representation of brain connectivity is adopted when comparing different patterns of structural and functional connectivity to null models or between groups of individuals. Two levels of comparison could be considered when analyzing brain connectivity: the global level and the local level. In the global level, the whole brain information is summarized by one summary statistic, whereas in the local analysis, each region of interest of the brain is summarized by a specific statistic. We show that these levels are mutually informatively integrative in some extent. We present different methods of analysis at both levels, the most relevant global and local network measures. We discuss as well the assumptions to be satisfied for each method; the error rates controlled by each method, and the challenges to overcome, especially, in the local case. We also highlight the possible factors that could influence the statistical results and the questions that have to be addressed in such analyses.
Accuracy Analysis of Narrow Band Imaging (NBI) Bronchoscopy Compared To White Light Bronchoscopy in the Diagnostics of Lung Tumours.

Background: Bronchoscopy plays an important role in the diagnostics of lung tumours. One of the technologies looking for their way in the diagnostics of pulmonary diseases is narrow band imaging. The aim of this study was to compare accuracy of examinations in the NBI and the white light (WL) modes in relation to biopsy results for the diagnoses of malignant tumour or severe dysplasia. Methods and results: A group of 500 patients have undergone a bronchoscopic examination in the NBI mode and afterwards in the white light. Biopsies were taken from all areas with pathological findings in both the modes for histological examination. Pathological bronchoscopic images were detected in a total of 382 patients. Positive findings in both the NBI mode and the WL mode were detected in 331 patients (66.2%). Discordant NBI-/WL+ findings were detected in 29 cases (5.8%) and discordant NBI+/WL- findings were detected in 22 cases (4.4%). The relative sensitivity of NBI compared to WL is 1.06 (p < 0.01; NBI sensitivity is significantly higher). The relative rate of false positive results in NBI compared to WL is 0.91 (p = 0.01; the rate of false positive results is significantly lower in NBI). Conclusions: The performed statistical evaluation shows a statistically significant increase in examination accuracy in NBI compared to WL. An NBI examination is able to differentiate between the necrotic avascular region of the tumour and the viable tissue very well even if an examination in the WL mode is not so explicit in this respect.
Stents, Timing and Shades of Electiveness

Volume 4 • Issue 4 • 1000e113 J Anesth Clin Res ISSN:2155-6148 JACR an open access journal In 2007, Grines et al. published a science advisory from the American Heart Association (AHA), American College of Cardiology (ACC), Society for Cardiovascular Angiography and Interventions, American College of Surgeons, and American Dental Association, with representation from the American College of Physicians that stresses the importance of 12 months of dual antiplatelet therapy after placement of a drug-eluting stent and educating patients and health care providers about hazards of premature discontinuation. It also recommends postponing elective surgery for one year, and if surgery cannot be deferred, considering the continuation of aspirin during the perioperative period in high-risk patients with drug-eluting stents [1].
Unsupervised relation extraction from scientific texts using self-organizing maps

Scientific texts represent a rich source of unstructured knowledge. Extracting this knowledge in a supervised manner can become highly expensive in time and human resources. Moreover supervised models are domain- and language-dependent which make them hard to maintain and extend. Hence unsupervised methods have received a lot of attention from researchers in the fields of information extraction and data mining. In this paper, we present our experiments with self-organizing maps (SOMs) for the task of open relation extraction. We combine contextual features of different level (lemmas and parts-of-speech) to help the algorithm to automatically discover lexical and morphological patterns in the corpus. The evaluation results show that our model yields a better performance than the widely used K-means clustering algorithm with the same feature set.
EFSA Panel on Biological Hazards (BIOHAZ); Scientific Opinion on an estimation of the public health impact of setting a new target for the reduction of Salmonella in turkeys

The quantitative contribution of turkeys and other major animal-food sources to the burden of human salmonellosis in the European Union was estimated. A „Turkey Target Salmonella Attribution Model‟ (TTSAM) based on the microbial-subtyping approach was used. TT-SAM includes data from 25 EU Member States, four animal-food sources of Salmonella and 23 Salmonella serovars. The model employs 2010 EU statutory monitoring data on Salmonella in animal populations (EU baseline survey data for pigs), data on reported cases of human salmonellosis and food availability data. It estimates that 2.6 %, 10.6 %, 17.0 % and 56.8 % of the human salmonellosis cases are attributable to turkeys, broilers, laying hens (eggs) and pigs, respectively. The top-6 serovars of fattening turkeys that contribute most to human cases are S. Enteritidis, S. Kentucky, S. Typhimurium, S. Newport, S. Virchow and S. Saintpaul. Comparing the prevalence of Salmonella in turkey flocks reported in 2010 with a theoretical combined prevalence for S. Enteritidis and S. Typhimurium of 1 % (i.e. the transitional target), a reduction of 0.4 % in the percentage of turkey-associated human salmonellosis cases would be achieved. However, when adjusting the combined prevalence of all serovars to 1 %, an 83.2 % reduction in the percentage of turkey-associated human salmonellosis cases, equivalent to 2.2 % of all human salmonellosis cases, is expected. Uncertainty and data limitations are discussed, including recommendations on how these could be overcome. Vertical transmission of Salmonella as well as hatchery acquired Salmonella contamination originating from breeding stock are very important sources for Salmonella infection in turkeys, and therefore controlling Salmonella in breeding flocks as well as in rearing and fattening flocks is necessary to minimise Salmonella in turkeys at slaughter. © European Food Safety Authority, 2012.
News on demand

This paper describes a solution for an interactive video service in the World Wide Web. It looks at creating an information retrieval system based on television and German video text. The service aims at presentation in the World Wide Web. The paper handles all components of this service beginning with content collection and ending with the presentation at the enduser. It starts with a look at the service as it appears to the client. It next deals with obtaining traditional media and processing them into a format for later usage in a teleservice. Then follow reflections on possible client concepts, especially methods to integrate real time video into Webpages. Video transmission also provides the main issues for the server and communication between client and server. After an explanation of our implementation the paper ends with some conclusions about experiences and future work.
Subset selection of training data for machine learning: a situational awareness system case study

Recent advances in machine learning with big data sets has allowed for significant advances in the optimisation of classification and recognition systems. However, for applications such as situational awareness systems, the entirety of the available data dwarfs the amount permissible for a training set with tractable machine learning optimization times. Furthermore, the performance of any optimized system is highly dependent of the training set correctly and completely representing the entire data space of scenarios. In this paper we present a technique to characterize the entire data space to ascertain the key factors for representation and subsequently select a subset that statistically represents the correct mix of scenarios. We demonstrate the effectiveness of these characterization and subset selection techniques by using a genetic algorithm to optimize the performance of a gunfire recognition system.