Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute disorders of mesenteric circulations: the etiology, risk factors and incidence of lesions.

: Acute disorder of mesenteric circulation (ADMC) is an emergency pathology of the abdominal organs. It occurs in 0.2% of general surgery patients. A total of 346 patients with verified (before, during operation and/or on autopsy) diagnosis of ADMC were analyzed retrospectively. There were 217 (62.7%) women and 129 (37.3%) men. The mean age of the patients was 68.4+/-3.6 years. In 50.7% of patients, ADMC was induced by thrombosis of the unpaired visceral branches of the abdominal aorta, in 29.1% -- by embolism of the superior mesenteric artery (SMA), in 7.8% -- by thrombosis of the portomesenteric bed, in 7.5% -- by non-occlusion mesenteric ischemia (NOMI), and in 4.9% by diseases of the parietal vessels of the bowel. The most prevalent risk factors of ADMC were: atherosclerosis of the aorta and its branches, previous reconstructions for occlusion-stenotic arterial lesions, episodes of arterial embolism in the anamnesis, congenital and acquired hemostatic disorders, oral contraception, thromboses of the deep veins and/or pulmonary embolism in the anamnesis, operations on the abdominal organs, different types of acute end chronic heart failure. In SMA thrombosis, occlusion most frequently affects the orifice (93.5%) and initial segment of the great vessel, In embolism it occurs before or at the level of the middle colic artery (in 57.9%). Disseminated bowel necroses are more frequently encountered in occlusions of the arterial bed (87.7% in thromboses and 83.3% emdolism) than in the venous system (8.3%).
Introducing electricity load level detail into a CGE model - Part I - The calibration methodology

The growing importance of the electricity sector in many economies, and of energy and environmental policies, requires a detailed consideration of these sectors and policies in computable general equilibrium (CGE) models, including both technological and temporal aspects. This paper presents the first attempt to our knowledge at building temporal disaggregation into a CGE model, while keeping technological detail. This contribution is coupled with some methodological improvements over existing technology-rich CGE models. The model is able to account for the indirect effects characteristic of CGE models while also mimicking the detailed behavior of the electricity operation and investment present before only in bottom-up detailed models. The present paper is the first of two parts and focuses on the bottom-up topdown calibration methodology needed to build such a model. Part II will present the CGE model applied to the evaluation of an energy policy with temporal consequences.
THE NEW SOUTH WALES DRUG COURT EVALUATION: A PROCESS EVALUATION

PREFACE Over the past three years drug courts have been adopted in several Australian jurisdictions to deal with drug-dependent offenders. The first specialist drug court to be piloted in Australia commenced in 1999 after the New South Wales parliament passed legislation governing the NSW Drug Court Trial. The NSW Drug Court was broadly modelled on the drug courts which had been operating in the United States of America since the late 1980's. The present report is part of a series of studies conducted by the NSW Bureau of Crime Statistics and Research evaluating the NSW Drug Court Trial. Other reports in this series monitor key aspects of the Drug Court's operation, examine its cost-effectiveness in reducing re-offending compared with conventional criminal justice sanctions and investigate changes in the health and well-being of Drug Court participants. This report presents the results of a process evaluation of the Drug Court Trial designed to describe the operation of the Court, identify any problems it encountered and describe how these problems were resolved. Process evaluations are, by definition, not directly concerned with outcomes. They are, nonetheless, generally invaluable in understanding the results of outcome studies. This is no less true in the present case. The study provides a wealth of useful information on the operation of the Drug Court obtained from interviews with members of the Drug Court Team, offenders participating on the Program, and professionals associated with various aspects of the Program. While it was not possible to canvas the views of all persons associated with the Program, most of the key players were interviewed. The results of these interviews should be of general interest to policy makers, the legal fraternity and health workers within the alcohol and other drugs field. ACKNOWLEDGMENTS Valuable time and the information on which this report is based was contributed by the interviewees. Their contributions are greatly appreciated. Ms Lily Trimboli significantly contributed to the early development and design of the project. Ms Trimboli also documented a large proportion of the background information and details of the Drug Court's policies and procedures. Thanks are also due to Jonathan Nichol for desktop publishing the report.
Strategies and applications for creating more memorable passwords

As we continue to learn and grow in an ever evolving technological age, we deepen our understanding of the importance of authentication. There are many different types of authentication, each exhibiting their own strengths and weaknesses. Each authentication mechanism serves the same purpose: to verify a user’s identity. In this thesis, we explore two authentication mechanisms aimed at helping users remember stronger authentication tokens: one aimed at creating a secure, memorable token, and the other aimed at strengthening a previous token (known as a password strengthening technique). The first is GeoPassNotes, a geographic location-based authentication scheme. GeoPassNotes requires users to select a location on a digital map and then annotate it in order to authenticate. The combination of the location and the annotation is the authentication token. GeoPassNotes allows users to select a location that is tied to a significant event / memory, which is very memorable to that person. The other system we design and explore is PassMod, a system designed to help users create more secure versions of their password. This system separates itself from other password strengthening techniques because it interprets and attempts to preserve the original meaning behind the user’s password. We demonstrate that it is possible to create a more secure password without compromising the memorability of the original password. Both GeoPassNotes and PassMod help users produce a more secure, yet memorable authentication token.
Automatic Audio Classification by Using Hidden Markov Model

As one of the key methods to extract content semantics and structure from audio, automatic audio classification, especially for a speech and a music, is valuable for content-based audio retrieval, video summary and retrieval, and spoken document retrieval, etc. Because hidden Markov model (HMM) can well model audio signal抯 time statistical properties, a left-right discrete HMM is proposed to classify a speech, a music and their mixed audio. The experimental results show that HMM is excellent for audio classification, and the optimal classification accuracy is up to 90.28%.
A BP based VSIMM-2-D track-to-measurement association approach

A BP based Variable Structure IMM-2D track- to-measurement association approach is proposed to simultaneously resolve the two most important uncertainties i.e. measurement origin uncertainty and the target motion uncertainy, which exist in the data association problem. Afer handling the measurement to track correlation via global 2-0 assignment, the novel method apply a discrete wavelet transform to map the measurement sequences to meta-mode sequences, then identifies the target's probable model set through BP neural network based on the meta-modes, finally filters and estimates via a variable structure IMM estimator. Simulation results show that the proposed technique can solve track-to-measurement association especially maneuvering target association problem properly.
Cybersickness and anxiety in virtual environments

The question whether feelings of anxiety are confounded with cybersickness in studies on virtual reality exposure therapy (VRET) was raised since the questionnaires used to measure them contain overlapping items. In the experiment, 88 participants were asked to talk in front of a virtual audience. Previous research has shown that this task may induce feelings of anxiety (Slater, Pertaub, & Steed, 1999). A significant correlation between levels of experienced anxiety and the nausea subscale of the Simulator Sickness Questionnaire was found for people who reported no cybersickness in a virtual neutral world. Therefore it must be concluded that when cybersickness is measured in VRET experiments, the results may partly be explained by feel-ings of anxiety rather than cybersickness per se.
Local Administration of Nimodipine and Improvement of Functional Recovery of the Transected Sciatic Nerve after Bridging with Inside-out Artery Graft

Nimodipine is a US Food and Drug Administration approved drug that has been shown to act as a possible pharmacologic treatment for facial nerve injury. The objective was to assess the effect of locally administered nimodipine on transected peripheral nerve regeneration and functional recovery. Sixty male healthy white Wistar rats were divided into four experimental groups (n = 15), randomly: In transected group (TC), left sciatic nerve was transected and stumps were fixed in the adjacent muscle. In treatment group defect was bridged using an inside-out artery graft (IOAG/Nimodipine) filled with 10 μL nimodipine (100 ng/mL). In artery graft group (IOAG), the graft was filled with phosphate-buffered saline alone. In sham-operated group (SHAM), sciatic nerve was exposed and manipulated. Each group was subdivided into three subgroups of five animals each and regenerated nerve fibers were studied 4, 8 and 12 weeks after surgery. Behavioral testing, biomechanical studies, sciatic nerve functional study, gastrocnemius muscle mass and morphometric indices confirmed faster recovery of regenerated axons in IOAG/Nimodipine than IOAG group (p < 0.05). In immunohistochemistry, location of reactions to S- 100 in IOAG/Nimodipine was clearly more positive than that in IOAG group.When loaded in an artery graft nimodipine accelerated and improved functional recovery and morphometric indices of sciatic nerve. This may have clinical implications for the surgical management of patients after facial nerve transection.
Теория и методика профессионального образования THE ACCESS TO HIGHER EDUCATION PROGRAMME IN THE UNITED KINGDOM

This article provides an introduction to the Access to Higher Education programme in the United Kingdom, and selectively reviews the research literature about its effectiveness. The programme gives mainly mature students from non-traditional backgrounds the opportunity to enter higher education. The review first describes the origins and nature of the programme, then examines the raw data of the official statistics, before going on to consider both quantitative and qualitative research studies in turn. The more quantitative studies into the programme’s effectiveness paint an inconclusive picture, with mixed evidence about achievement which is often not generalizable. The more qualitative studies which focus on learners’ experiences generate useful insights but are not designed to judge the programme’s overall effectiveness. The review concludes that while the programme has indeed benefited large numbers of students, further research is needed to assess whether any limitations in student achievement are attributable to the design of the programme itself or due to external factors. In a rapidly changing higher education landscape, the future of the programme is unclear.
Principles of social media monitoring and analysis software

Semenov, Alexander Principles of Social Media Monitoring and Analysis Software Jyvaskyla: University of Jyvaskyla, 2013, 92 p. (+ included articles) (Jyvaskyla Studies in Computing ISSN 1456-5390; 168) ISBN 978-951-39-5224-2 (nid.) ISBN 978-951-39-5225-9 (PDF) This thesis studies how automatic tools can be used in the monitoring and analysis of the digitally-encoded information that exists on the Internet and, more specifically, on social media sites. Social media sites already have over a billion users. In our view, the content existing within social media sites is modelling parts of the social reality, with certain limitations. For instance, not all people have access to the Internet or are represented in social media. The perception of relationships on social media sites differs from the perception of those in the immediate social reality. Also, fake virtual identities are an important aspect. Yet, there are many interesting phenomena in social reality, information about which can be gathered from social media much faster than in real life. The main objective of this thesis is to find out how automatic tools can be used to collect and analyse the data from social media sites and what their limits are. Conceptual-analytical and constructive research approaches are used to solve these problems. This thesis proposes a general three-layer modelling framework for modelling a social media environment. The first level is the social reality, as modelled by social media sites. It is captured by site ontologies. The second level is a multirelational graph structure that can be used to model any social network and its development over time at any known social media site. The third level is the persistent repository for the instances of this graph structure. The thesis presents the requirements and architecture for the social media monitoring software system that implements this framework. The software gathers data from social media sites relying on the site ontologies. These heterogeneous 1st level models are stored at the monitoring site and transformed to the 2nd level homogeneous multirelational graph structure. The 2nd level is implemented as a repository, the schema of which depends on the technology in use; but the interface is homogeneous, relying on the above graph. The thesis also establishes fundamental limits for the remote monitoring and analysis activities that are novel in the context of social media monitoring. The developed software has been used to collect real data from school-shooter networks, the entire contents of the LiveJournal.com site, and from sites in the Finnish segment of the Tor network. The software system can benefit a number of users, such as cyber police or business intelligence companies.
Use of In-Game Rewards to Motivate Daily Self-Report Compliance: Randomized Controlled Trial

Background Encouraging individuals to report daily information such as unpleasant disease symptoms, daily activities and behaviors, or aspects of their physical and emotional state is difficult but necessary for many studies and clinical trials that rely on patient-reported data as primary outcomes. Use of paper diaries is the traditional method of completing daily diaries, but digital surveys are becoming the new standard because of their increased compliance; however, they still fall short of desired compliance levels. Objective Mobile games using in-game rewards offer the opportunity to increase compliance above the rates of digital diaries and paper diaries. We conducted a 5-week randomized control trial to compare the completion rates of a daily diary across 3 conditions: a paper-based participant-reported outcome diary (Paper PRO), an electronic-based participant-reported outcome diary (ePRO), and a novel ePRO diary with in-game rewards (Game-Motivated ePRO). Methods We developed a novel mobile game that is a combination of the idle and pet collection genres to reward individuals who complete a daily diary with an in-game reward. Overall, 197 individuals aged 6 to 24 years (male: 100 and female: 97) were enrolled in a 5-week study after being randomized into 1 of the 3 methods of daily diary completion. Moreover, 157 participants (male: 84 and female: 69) completed at least one diary and were subsequently included in analysis of compliance rates. Results We observed a significant difference (F2,124=6.341; P=.002) in compliance to filling out daily diaries, with the Game-Motivated ePRO group having the highest compliance (mean completion 86.4%, SD 19.6%), followed by the ePRO group (mean completion 77.7%, SD 24.1%), and finally, the Paper PRO group (mean completion 70.6%, SD 23.4%). The Game-Motivated ePRO (P=.002) significantly improved compliance rates above the Paper PRO. In addition, the Game-Motivated ePRO resulted in higher compliance rates than the rates of ePRO alone (P=.09). Equally important, even though we observed significant differences in completion of daily diaries between groups, we did not observe any statistically significant differences in association between the responses to a daily mood question and study group, the average diary completion time (P=.52), or the System Usability Scale score (P=.88). Conclusions The Game-Motivated ePRO system encouraged individuals to complete the daily diaries above the compliance rates of the Paper PRO and ePRO without altering the participants’ responses. Trial Registration ClinicalTrials.gov NCT03738254; http://clinicaltrials.gov/ct2/show/NCT03738254 (Archived by WebCite at http://www.webcitation.org/74T1p8u52)
Autonomy Oriented Computing: From Problem Solving to Complex Systems Modeling (Multiagent Systems, Artificial Societies, and Simulated Organizations)

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc. Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development. Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.
“It is alive!” Evidence for animacy effects in semantic categorization and lexical decision

Abstract Animacy is one of the basic semantic features of word meaning and influences perceptual and episodic memory processes. However, evidence that this variable also influences lexicosemantic processing is mixed. As animacy is a semantic variable thought to have evolutionary roots, we first examined its influence in a semantic categorization task that did not make the animacy dimension salient, namely, concrete-abstract categorization. Animates were categorized faster (and more accurately) than inanimates. We then assessed the influence of animacy in two lexical decision experiments. In Experiment 2, we mostly used legal nonwords, whereas in Experiment 3, we varied the context of the nonwords across participants in such a way that the discriminability between words and nonwords was either high or low. Animates yielded faster decision times than inanimates when legal nonwords were used (Experiment 2) and when the discriminability between words and nonwords was low (i.e., “difficult nonwords” in Experiment 3), but the difference between the two types of words was not reliable when discriminability was high (e.g., illegal strings of letters, i.e., “easy nonwords” in Experiment 3). The findings suggest that animacy is a core meaning-related dimension that influences a large number of processes involved in perception, episodic memory, and semantic memory.
Crowdsourcing Social Media For Robot Learning: A Review

: Methods designed to render capability of robots to learn on their own is a heavily studied area. If robots are to become a constitutional part of our society, they must own the power to learn without direct guidance from a devoted user. Robot possessor never enjoyed the obligation of teaching their robot everything they know. The ability of a robot to use various resources in its environment will help its learning capabilities to be self-guided as well as independent. We investigate the use of social media crowdsourcing to allow a bot to access the huge information volume in gathering resources that are available on Twitter page. In distinction from others, the robot will gather or record the basic human actions that are performed physically and are then upload that video on the Twitter account. It will now ask for the descriptions of those performed actions. Parameters of those recorded actions are used as input into a MC-SVM (Multi-class Support Vector Machine) classification algorithm which will enable the capability of robot to recognize the similar action in future.
Realization of cooperative strategies and swarm behavior in distributed autonomous robotic systems using artificial immune system

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on the immune system in a distributed autonomous robotic system (DARS). The immune system is a living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in a dynamically changing environment. To apply the immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition changes, a robot selects an appropriate behavior strategy, and its behavior strategy is stimulated and suppressed by other robots using communication. Finally, the most stimulated strategy is adopted as the swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. It is used for decision making of the optimal swarm strategy. By T-cell modeling, the adaptation ability of the robot is enhanced in dynamic environments.
Age-stratified sex differences in polysomnographic findings and pharyngeal morphology among children with obstructive sleep apnea.

Background Childhood obstructive sleep apnea (OSA) has important implications for growth, learning, behavior, cognition and cardiovascular health as well as snoring and OSA in adulthood. In this study, we elucidated the sex differences in polysomnographic (PSG) findings and pharyngeal radiographic data in pediatric OSA patients. Methods Sixty three children (age between 3 and 15 years old) with OSA [defined as apnea-hypopnea index (AHI) ≥1/h by polysomnography] were enrolled. Lateral neck radiographs were obtained from the patients. All subjects were separated by age: pre-adolescent group (3-8 years old) and adolescent group (9-15 years old). Results Overall, 45 patients in the pre-adolescent group (33 boys and 12 girls) and 18 patients in the adolescent group (10 boys and 8 girls) were enrolled, and sex differences were compared in each group. We found sex differences in craniofacial features and severity of OSA in the adolescent group, in which girls with OSA had more upper airway space, in addition to lower AHI, lower 3% oxygen desaturation index (ODI), higher minimum SO2 and better sleep efficiency than the boys. Conclusions The present study found revealed sex differences in pediatric OSA patients in the adolescent group. Girls in the adolescent group had more upper airway space in addition to lower AHI, lower 3% ODI, higher minimum SO2 and better sleep efficiency than boys.