Miracle-dz/UniFAR-FTUs huggingface dataset:
Traveling threads: a new multithreaded execution model

Computer architecture is plagued by the von Neumann bottleneck. This work introduces and evaluates the traveling thread execution model in which threads migrate to the memory resources close to the data they require rather than perform remote memory accesses. This helps address the von Neumann problem by exposing additional concurrency within programs to tolerate long memory latencies, reduces two-way request/response network transactions typical of caching architectures to one way thread migration transactions, and reduces or eliminates cache coherency traffic.
The Relationship between Movement and Pain Related Fear, Function, and Depression in Chronic Pain Patients

Chronic pain affects multiple facets of a person’s life. Interdisciplinary programs are effective in treating chronic pain, but approaches used to improve function are different between programs. It is unclear which aspect of rehabilitation is responsible for improving function. In these programs, patients’ allocation to groups and post program assessments are based on subjective and self-report evaluations from the patients. The purpose of this study was to objectively evaluate chronic pain patients’ day and night movement to see the relationship between movement to baseline and final outcomes in pain related fear, function, depression, and pain. Twenty-four patients were diagnosed with chronic pain and wait listed for a chronic pain rehabilitation program (age=48.1±11.8years, weight=76.2±21.2kg, height=164.6±7.3cm). There were two groups at this rehabilitation center, specialized (S) and super-specialized (SP), 12 patients in each group. Patients’ pain related fear, function, depression, and pain was assessed prior to the starting the program and at the completion of the 9-week program. Day movement and night movement were monitored for 7 days prior to starting the program using actigraphy. All pain related fear, function, depression, and pain variables significantly improved upon completion of the program. Movement during the day was significantly related to self-reported function, but not to the 6-minute walk test. Moreover, movement during the day was correlated with depression and pain. In conclusion, day and night movement cannot be used to predict successful completion of the program. Clinicians should use self-reported and objective function measurements to accurately reflect patient ability.
Time and Semantic Similarity - What is the Best Alternative to Capture Implicit Links in CSCL Conversations?

The goal of our research is to compare novel semantic techniques for identifying implicit links between utterances in multi-participant CSCL chat conversations. Cohesion, reflected by the strength of the semantic relations behind the automatically identified links, is assessed using WordNet-based semantic distances, as well as unsupervised semantic models, i.e. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA). The analysis is built on top of the ReaderBench framework and multiple identification heuristics were compared, including: semantic cohesion metrics, normalized cohesion measures and Mihalcea’s formula. A corpus of 55 conversations in which participants used explicit links between utterances where they considered necessary for clarity was used for validation. Our study represents an in-depth analysis of multiple methods used to identify implicit links and reveals the accuracy of each technique in terms of capturing the explicit references made by users. Statistical similarity measures ensured the best overall identification accuracy when using Mihalcea’s formula, while WordNet-based techniques provided best results for un-normalized similarity scores applied on a window of 5 utterances and a time frame of 1 minute.
What demographic attributes do our digital footprints reveal? A systematic review

To what extent does our online activity reveal who we are? Recent research has demonstrated that the digital traces left by individuals as they browse and interact with others online may reveal who they are and what their interests may be. In the present paper we report a systematic review that synthesises current evidence on predicting demographic attributes from online digital traces. Studies were included if they met the following criteria: (i) they reported findings where at least one demographic attribute was predicted/inferred from at least one form of digital footprint, (ii) the method of prediction was automated, and (iii) the traces were either visible (e.g. tweets) or non-visible (e.g. clickstreams). We identified 327 studies published up until October 2018. Across these articles, 14 demographic attributes were successfully inferred from digital traces; the most studied included gender, age, location, and political orientation. For each of the demographic attributes identified, we provide a database containing the platforms and digital traces examined, sample sizes, accuracy measures and the classification methods applied. Finally, we discuss the main research trends/findings, methodological approaches and recommend directions for future research.
Disrupted‐in‐schizophrenia‐1 protects synaptic plasticity in a transgenic mouse model of Alzheimer’s disease as a mitophagy receptor

Mitochondrial dysfunction is an early feature of Alzheimer's disease (AD). Accumulated damaged mitochondria, which are associated with impaired mitophagy, contribute to neurodegeneration in AD. We show levels of Disrupted‐in‐schizophrenia‐1 (DISC1), which is genetically associated with psychiatric disorders and AD, decrease in the brains of AD patients and transgenic model mice and in Aβ‐treated cultured cells. Disrupted‐in‐schizophrenia‐1 contains a canonical LC3‐interacting region (LIR) motif (210FSFI213), through which DISC1 directly binds to LC3‐I/II. Overexpression of DISC1 enhances mitophagy through its binding to LC3, whereas knocking‐down of DISC1 blocks Aβ‐induced mitophagy. We further observe overexpression of DISC1, but not its mutant (muFSFI) which abolishes the interaction of DISC1 with LC3, rescues Aβ‐induced mitochondrial dysfunction, loss of spines, suppressed long‐term potentiation (LTP). Overexpression of DISC1 via adeno‐associated virus (serotype 8, AAV8) in the hippocampus of 8‐month‐old APP/PS1 transgenic mice for 4 months rescues cognitive deficits, synaptic loss, and Aβ plaque accumulation, in a way dependent on the interaction of DISC1 with LC3. These results indicate that DISC1 is a novel mitophagy receptor, which protects synaptic plasticity from Aβ accumulation‐induced toxicity through promoting mitophagy.
TRAFFIC-FLOW THEORY

Traffic-flow theories seek to describe in a precise mathematical way the interactions among vehicles, drivers, and the infrastructure. This article outlines the revised "Monograph on Traffic Flow Theory," which can be viewed on the Turner-Fairbank Highway Research Center Web site (www.tfhrc.gov/its/tft/tft.htm/). This report is an updated and expanded version of two previous works that were sponsored by the Transportation Research Board and its predecessor, the Highway Research Board. The revised monograph includes new developments in traffic-flow theory since 1975. Chapter 3 (Human Factors) and chapter 5 (Continuum Flow Models) are two completely new chapters in this report. All chapters deal with issues on a much broader basis than the previous reports. More importantly, issues of, and application to, intelligent transportation systems are discussed in the chapters to the extent possible. The Traffic Simulation chapter is expanded from the microscopic simulation model to the mesoscopic and macroscopic simulation models, and the simulation-based traffic assignment is expanded to address time-dependent traffic assignment issues.
Do You Speak Math? Visualizing Patterns of Student Technical Language in a Mathematics MOOC

: The recent advent of massive open online courses (MOOCs) has created an incredibly vast, rich, and largely unexplored body of data. We have analyzed one MOOC by visualizing the language used by students in their online forums, connecting vocabulary to traditional performance assessments throughout the course, prototyping a tool for future use across courses and platforms.
Purposive and qualitative active vision

The traditional view of the problem of computer vision as a recovery problem is questioned, and the paradigm of purposive-qualitative vision is offered as an alternative. This paradigm considers vision as a general recognition problem (recognition of objects, patterns or situations). To demonstrate the usefulness of the framework, the design of the Medusa of CVL is described. It is noted that this machine can perform complex visual tasks without reconstructing the world. If it is provided with intentions, knowledge of the environment, and planning capabilities, it can perform highly sophisticated navigational tasks. It is explained why the traditional structure from motion problem cannot be solved in some cases and why there is reason to be pessimistic about the optimal performance of a structure from motion module. New directions for future research on this problem in the recovery paradigm, e.g., research on stability or robustness, are suggested. <<ETX>>
Congestion control in TCP/IP networks: a combined ECN and BECN approach

In this paper a novel algorithm is proposed which combines the merits of explicit congestion notification (ECN) and backward explicit congestion notification (BECN) mechanisms for congestion control in TCP/IP networks. A comparative performance evaluation of the combined ECN and BECN mechanism is carried out using both long-lived FTP flows and short-lived Web traffic. The simulation results show that the combined ECN+BECN mechanism benefits from BECN's early notification under heavy congestion and ECN's reliable delivery of congestion notification. It is observed that the ECN+BECN mechanism significantly reduces queue fluctuations due to early congestion indication compared to ECN. The loss of BECN Internet control message protocol (ICMP) source quenches on the reverse path does not adversely impact performance due to this combined approach. It is also shown that the ECN+BECN scheme can significantly reduce the ICMP source quench reverse traffic in a network compared to a BECN only network. Experiments with Web traffic workloads show measurable improvement in both average object transfer delay and fairness over ECN.
Real-Time Character Animation Techniques

This report reviews the literature in the field of computer animation and robotics to illustrate the numerous approaches to simulating, controlling and displaying the realistic, real-time animation of virtual characters. Critical analyses of the various high-level approaches are conducted, with a view to identifying key areas of interest for future research in the area of “Real-Time Character Animation Techniques”
Experts Learn More (than Newcomers): An Exploratory Study of Argumentation in an Online Help Forum

: Online help forums have emerged as a powerful form of knowledge sharing with significant implications for CSCL. To understand knowledge construction and learning within online help forums, this study examined the interactional dynamics amongst help-givers (experts) and help-seekers (newcomers) in an open, voluntary help forum for Java computer programming language. A purposive sample of active threads was analyzed using a coding scheme adapted from the argumentative knowledge construction (AKC) framework. The study found that while help-givers actively engaged in advanced argumentative and social moves, help-seekers seldom did. Furthermore, the number of advanced epistemic messages was lower than expected and both help-givers and help-seekers often veered off-topic towards socialization and conflict-oriented interactions. The study questions the feasibility of online help forums for facilitating acquisition of domain-specific knowledge by help-seekers but demonstrates the viability of the platform as a mechanism for experts to expand their knowledge. Our findings suggest that those who know more are able to learn more given their ability to engage in argumentation.
The Wrist and Its Disorders

Part I: Basic Science. The Development of Wrist Surgery: An Historical Review. Anatomy of the Wrist. Vascularity of the Carpus. The Physiologic Bases for Wrist Function. Pathogenesis and Pathokinetics of Perilumate Wrist Instability. Part II: Evaluation and Special Procedures. Physical Examination of the Wrist. Post-Traumatic Wrist Pain and Instability: A Radiographic Approach to Diagnosis. Soft Tissue Radiography of the Wrist. Advanced Imaging of the Carpus. Wrist Arthroscopy. Clinical Applications of Wrist Arthroscopy. Part III: Carpal Bones. Introduction to Carpal Instabilities. Carpal Fractures and Dislocations. Scaphoid Non-Union. Scapholunate Injuries. Triquetrolunate Instability. Midcarpal and Proximal Carpal Instabilities. Kienbock's Disease and Idiopathic Necrosis of Carpal Bones. Part IV: The Distal Radius and Ulna. Fractures of the Distal Radius. Distal Radius Malunion. Disorders of the Distal Radioulnar Joint and Triangular Fibrocartilage Complex: An Overview. Treatment of Acute Injuries of the Triangular Fibrocartilage Complex. Treatment of Acute Injuries of the Distal Radioulnar Joint. Treatment of Chronic Disorders of the Distal Radioulnar Joint. Part V: Carpometacarpal Joints. Carpometacarpal Joint of the Thumb. The Medial Four Carpometacarpal Joints. Part VI: Nerve, Sports, And Occupational Disorders. Nerve Injuries Associated with Wrist Trauma. Occupational and Sports Injuries of the Wrist. Part VII: Developmental and Degenerative Disorders. Congenital and Developmental Wrist Disorders in Children. Traumatic and Acquired Wrist Disorders in Children. Tumours of the Wrist. Degenerative Disorders of the Carpus. Inflammatory and Rheumatoid Arthritis. Part VIII: Surgical Options for Common Wrist Disorders. Soft Tissue Arthroplasty About the Wrist. Implant Arthroplasty in the Carpal and Radiocarpal Joints. Total Wrist Arthroplasty. Partial Wrist Fusions: Intercarpal and Radiocarpal Joints. Total Wrist Arthroplasty. Partial Wrist Fusions: Intercarpal and Radiocarpal. Arthrodesis of the Wrist: Indications and Surgical Technique. Amputations About the Wrist. Part IX: Wrist Therapy and Rehabilitation. Assessment. Conservative Rehabilitation. Postoperative Rehabilitation.
Identification of Online Abuse and It’s Inhibition

Online abuse is an act of attacking an individual repeatedly with an intent to harm. This has a very disturbing effect on many individual irrespective of the age group. In this paper, we propose a new representation learning method to solve this problem. Our method named Naïve Bayes classifier is a simple probabilistic classifier based on Bayes’ theorem with naïve independence assumptions between the features. Naive Bayes is an highly scalable with different number of parameters linear in number of predictors in a learning problem. The proposed method is able to exploit the hidden feature structure of abusive information and learn a robust and discriminative representation of text. We have implemented our algorithm using five lakhs of tweets and around one thousands of users.
Improved multidirectional associative memories for training sets including common terms

Improved multidirectional associative memories (IMAMs) are proposed and simulated. The IMAM fundamental component is a multilayer neural network. IMAMs can memorize and recall multiple associations even when training sets include common terms, such as the training sets composed of (A,a,1), (A,b,2), (C,b,3). The structure of the proposed IMAMs is represented by mutual connections of multilayer neural networks. The proposed IMAMs require less parameters compared with other associative memories and are capable of automatic recall. Recall performance can be greatly improved by using a priority coefficient. <<ETX>>
Faithful and unfaithful students in time series learning

A model neuron with delay line feedback connections can learn a time series generated by another neuron. In the case that both neurons have identical transfer functions, a model neuron (student) is capable of reproducing the instruction sequence generated by another neuron (teacher), but the parameters are not uniquely determined by learning a quasi-periodic time series. A student that has completed the learning can be either faithful or unfaithful, depending on whether it continues mimicking the teacher's time series over a long interval after the learning or whether it departs from the teacher and eventually generates a time series that bears no resemblance to the teacher's. In the case that both neurons have different transfer functions, a student is generally incapable of reproducing the instruction sequence. Each student readjusts its parameters so as to minimize the mean-squared deviation between the instruction signal and its own output, but this parameter set is not uniquely determined. In this unrealizable learning, the degeneracy among faithful students is lifted and there is no more distinction between faithful and unfaithful students.
Citation Analysis in Research Evaluation (Information Science & Knowledge Management)

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An exploration of the factors involved in lifestyle decisions in young people with cystic fibrosis using decision making vignettes, and the role of perceived risk in infection

This study explored the factors involved in lifestyle decision making in young people with Cystic Fibrosis, specifically the role of infection risk. Certain pathogens present a high risk of infection to people with Cystic Fibrosis, and can significantly affect their health. It is therefore important that people with the disease attempt to minimise the risk of contracting these infections. There was limited literature relating specifically to infection risk and decision making in this population. However, this study drew on decision making literature from other areas, with regard to engaging in risktaking behaviours. The study employed a vignette methodology, presenting a series of lifestyle situations to eight participants and asking them to think aloud whilst deciding whether to engage in the activity. This was followed by a brief interview. An interview was also conducted with a Consultant Microbiologist, offering a detailed understanding of the level of risk presented in each vignette. Thematic Analysis was used to interpret the results, highlighting a number of important themes. Participants frequently chose to engage in activities that would present an increased risk of infection. It was often important to find a balance between maintaining their health and engaging in a fulfilling life. However, at times, participants lacked an adequate understanding of the level of risk or the nature of the infections to make an informed decision. Implications for future research and clinical practice are discussed.
Designing the User Interface: Strategies for Effective Human-Computer Interaction

For courses in Human-Computer Interaction. The Sixth Edition of Designing the User Interface provides a comprehensive, authoritative, and up-to-date introduction to the dynamic field of human-computer interaction (HCI) and user experience (UX) design. This classic book has defined and charted the astonishing evolution of user interfaces for three decades. Students and professionals learn practical principles and guidelines needed to develop high quality interface designs that users can understand, predict, and control. The book covers theoretical foundations and design processes such as expert reviews and usability testing. By presenting current research andinnovations in human-computer interaction, the authors strive toinspire students, guide designers, and provoke researchers to seek solutions that improve the experiences of novice and expert users, while achieving universal usability. The authors also provide balanced presentations on controversial topics such as augmented and virtual reality, voice and natural language interfaces, and information visualization. Updates include current HCI design methods, new design examples, and totally revamped coverage of social media, search and voice interaction. Major revisions were made toEVERY chapter, changing almost every figure (170 new color figures) and substantially updating the references.
Effect of Momordica charantia Aqueous Leaf Extract on the Isolated Mammalian Heart

Background: Momordica charantia is one of the most commonly used medicinal plants for both ritual and ethnomedical practices. Its use includes as an abortifacient, laxative and in the treatment of pneumonia. Despite the widespread use of its aqueous leaf extract, its pharmacological effects on the heart are not sufficiently investigated. Objectives: The main objective was to determine the effect of Momordica charantia aqueous leaf extract on the isolated mammalian heart. A secondary objective was to investigate possible effects on β adrenergic receptors of the heart. Methodology: Six healthy rabbits were included in the study. Each rabbit was sacrificed and the heart mounted on the Langerndorff apparatus. Baseline rate and force of contraction were taken, after which the aqueous leaf extract administered in increasing doses and changes in rate and force of contraction noted. The effects of the extract on the heart were similarly investigated in the presence of propranolol (a non-selective β adrenergic receptor antagonist) were also noted. Unpaired T-test and repeated measures ANOVA were used to test for statistical significance. P-values greater than < 0.05 indicated statistical significance. Results: There was significant, dose dependent, increase in the force and rate of contraction after administering the extract (P < 0.0001). However, in the presence of propranolol, the increase noted was not statistically significant. Discussion: The study shows that Momordica charantia aqueous leaf extract has dose dependent effect on both force and rate of cardiac muscle contraction. Keywords : Momordica charantia, aqueous extract, rate and force of contraction, heart.
Dynamical Processes on Complex Networks

The availability of large data sets have allowed researchers to uncover complex properties such as large scale fluctuations and heterogeneities in many networks which have lead to the breakdown of standard theoretical frameworks and models. Until recently these systems were considered as haphazard sets of points and connections. Recent advances have generated a vigorous research effort in understanding the effect of complex connectivity patterns on dynamical phenomena. For example, a vast number of everyday systems, from the brain to ecosystems, power grids and the Internet, can be represented as large complex networks. This new and recent account presents a comprehensive explanation of these effects.