Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormalities of Eye–Hand Coordination in Patients with Writer’s Cramp: Possible Role of the Cerebellum

Background Writer’s cramp (WC) is one of the commonly observed focal dystonias. The pathophysiology of WC has not been fully understood. The role of the cerebellum has been increasingly recognized in the pathogenesis of dystonia. As the cerebellum is crucial for maintaining accurate eye–hand coordination (EHC), its role in the pathogenesis of WC can be investigated by studying the EHC in patients with WC. Methods Fifteen patients with WC (women:men, 3:12) and 15 age- and gender-matched controls performed oculomotor and EHC tasks. A visually guided stimulus (VGS) task was first performed with eye-only condition (EOC) and then with EHC. Results A significant interaction between the groups (controls and patients) and tasks (EOC and EHC) with age as a covariate confirmed that the two groups reacted differently to the tasks in saccadic latency (F(1,27) = 4.8; p = 0.039) and average saccade acceleration (F(1,27) = 10.6; p = 0.003). The curvature index of acceleration of the hand was significantly more in patients compared to controls (patients vs. controls, 2.4±0.4 vs. 1.8±0.2, p = 0.01). While performing the EHC task, there was a significant correlation of the Writer’s Cramp Rating Score with the average saccadic speed (–0.61, p = 0.016), peak saccadic deceleration (0.59, p = 0.019) and average saccadic acceleration (–0.63, p = 0.012). Discussion Saccadic acceleration and latency are abnormal while performing EHC tasks in patients with WC. Our study gives further insights into the possible role of the cerebellum in the pathogenesis of WC.
A General Method for the Chemical Synthesis of Large‐Scale, Seamless Transition Metal Dichalcogenide Electronics

The capability to directly build atomically thin transition metal dichalcogenide (TMD) devices by chemical synthesis offers important opportunities to achieve large‐scale electronics and optoelectronics with seamless interfaces. Here, a general approach for the chemical synthesis of a variety of TMD (e.g., MoS2, WS2, and MoSe2) device arrays over large areas is reported. During chemical vapor deposition, semiconducting TMD channels and metallic TMD/carbon nanotube (CNT) hybrid electrodes are simultaneously formed on CNT‐patterned substrate, and then coalesce into seamless devices. Chemically synthesized TMD devices exhibit attractive electrical and mechanical properties. It is demonstrated that chemically synthesized MoS2–MoS2/CNT devices have Ohmic contacts between MoS2/CNT hybrid electrodes and MoS2 channels. In addition, MoS2–MoS2/CNT devices show greatly enhanced mechanical stability and photoresponsivity compared with conventional gold‐contacted devices, which makes them suitable for flexible optoelectronics. Accordingly, a highly flexible pixel array based on chemically synthesized MoS2–MoS2/CNT photodetectors is applied for image sensing.
Unsupervised Depth Estimation, 3D Face Rotation and Replacement

We present an unsupervised approach for learning to estimate three dimensional (3D) facial structure from a single image while also predicting 3D viewpoint transformations that match a desired pose and facial geometry. We achieve this by inferring the depth of facial keypoints of an input image in an unsupervised manner, without using any form of ground-truth depth information. We show how it is possible to use these depths as intermediate computations within a new backpropable loss to predict the parameters of a 3D affine transformation matrix that maps inferred 3D keypoints of an input face to the corresponding 2D keypoints on a desired target facial geometry or pose. Our resulting approach, called DepthNets, can therefore be used to infer plausible 3D transformations from one face pose to another, allowing faces to be frontalized, transformed into 3D models or even warped to another pose and facial geometry. Lastly, we identify certain shortcomings with our formulation, and explore adversarial image translation techniques as a post-processing step to re-synthesize complete head shots for faces re-targeted to different poses or identities.
GB-PANDAS:: Throughput and heavy-traffic optimality analysis for affinity scheduling

Dynamic affinity scheduling has been an open problem for nearly three decades. The problem is to dynamically schedule multi-type tasks to multi-skilled servers such that the resulting queueing system is both stable in the capacity region (throughput optimality) and the mean delay of tasks is minimized at high loads near the boundary of the capacity region (heavy-traffic optimality). As for applications, dataintensive analytics like MapReduce, Hadoop, and Dryad fit into this setting, where the set of servers is heterogeneous for different task types, so the pair of task type and server determines the processing rate of the task. The load balancing algorithm used in such frameworks is an example of affinity scheduling which is desired to be both robust and delay optimal at high loads when hot-spots occur. Fluid model planning, the MaxWeight algorithm, and the generalized c? -rule are among the first algorithms proposed for affinity scheduling that have theoretical guarantees on being optimal in different senses, which will be discussed in the related work section. All these algorithms are not practical for use in data center applications because of their non-realistic assumptions. The join-the-shortest-queue-MaxWeight (JSQMaxWeight), JSQ-Priority, and weighted-workload algorithms are examples of load balancing policies for systems with two and three levels of data locality with a rack structure. In this work, we propose the Generalized-Balanced-Pandas algorithm (GB-PANDAS) for a system with multiple levels of data locality and prove its throughput optimality. We prove this result under an arbitrary distribution for service times, whereas most previous theoretical work assumes geometric distribution for service times. The extensive simulation results show that the GB-PANDAS algorithm alleviates the mean delay and has a better performance than the JSQMaxWeight algorithm by up to twofold at high loads. We believe that the GB-PANDAS algorithm is heavy-traffic optimal in a larger region than JSQ-MaxWeight, which is an interesting problem for future work.
Piloting an email-based resource package for job seekers with multiple sclerosis

Abstract Purpose: Media-based rehabilitation provides a powerful opportunity to examine vocational behaviors in the disability sector. However, this research is preliminary at best. This paper reports pilot data. Method: Eighteen adults with multiple sclerosis (MS) accessed an email-delivered, resource-based package, Work and MS. Pre- and post-access vocational self-efficacy and identity (Job-Procurement Self Efficacy Scale, My Vocational Situation Scale- primary outcomes), life orientation and depressed mood (Life Orientation Test – revised and Patient Health Questionnaire-9 – secondary outcomes) were assessed. Pre- and post-change scores were examined with Wilcoxon signed ranks tests and Hedges g effect sizes with associated 95% confidence intervals. Reliable change analyses were additionally calculated to determine the clinical significance of individual change scores. Results: Significant and positive effects were reported for vocational self-efficacy, identity, and optimism. Reliable change scores in one or more of these key outcomes were reported by 30% of the sample. Satisfaction with the content and delivery of the email-based intervention was also noted. Conclusions: Preliminary evidence suggests that Work and MS can help to promote vocational goals, interests and strengths among job seekers with a disability by providing a set of tools, information and linkages relating to vocational pursuits and career development. Replication with a randomized control design is indicated. Implications for Rehabilitation Research indicates a high unemployment rate among working-age adults with MS. A combination of disease-specific, psychological, programmatic and societal variables contribute to employment instability in this group. This pilot study demonstrates that an e-mail-based resource package, Work and MS, provides an innovative and feasible option for promoting consumer engagement with vocational services and, potentially, improving vocational outcomes. Work and MS has potential applicability to other disability groups.
ubiMonitor: intelligent fusion of body-worn sensors for real-time human activity recognition

Real-time monitoring of the human daily activities using wearable sensors has attracted lots of attention from researchers due to its crucial role in emerging fields such as pervasive healthcare and ambient assisted living. However, despite being an active field, recent benchmarks show a difficulty in providing robust monitoring of the different various activities under realistic everyday life conditions. In this paper, based on an in-depth understanding of the nature of 3D accelerometers and the physical properties of the different daily activities, we propose ubiMonitor as an accurate real-time activity monitor using low-cost off-the-shelf three body-worn 3D accelerometers. For a robust monitoring, ubiMonitor (1) intelligently fuses the accelerometers and the acceleration in each of the three axes to provide key discriminative features for the different activities, (2) employs a novel hierarchical activity recognition scheme, and (3) applies an effective postprocessing stage to remove falsely detected activities and enhance the overall system accuracy. Experimental results using real traces from different eight subjects show that ubiMonitor can achieve an overall accuracy more than 95% with a median latency less than 3 msec. This is better than state-of-the-art by 23.4% in the recognition accuracy with a reduction of 70% in the sensors used.
Game AI revisited

More than a decade after the early research efforts on the use of artificial intelligence (AI) in computer games and the establishment of a new AI domain the term ``game AI'' needs to be redefined. Traditionally, the tasks associated with game AI revolved around non player character (NPC) behavior at different levels of control, varying from navigation and pathfinding to decision making. Commercial-standard games developed over the last 15 years and current game productions, however, suggest that the traditional challenges of game AI have been well addressed via the use of sophisticated AI approaches, not necessarily following or inspired by advances in academic practices. The marginal penetration of traditional academic game AI methods in industrial productions has been mainly due to the lack of constructive communication between academia and industry in the early days of academic game AI, and the inability of academic game AI to propose methods that would significantly advance existing development processes or provide scalable solutions to real world problems. Recently, however, there has been a shift of research focus as the current plethora of AI uses in games is breaking the non-player character AI tradition. A number of those alternative AI uses have already shown a significant potential for the design of better games. This paper presents four key game AI research areas that are currently reshaping the research roadmap in the game AI field and evidently put the game AI term under a new perspective. These game AI flagship research areas include the computational modeling of player experience, the procedural generation of content, the mining of player data on massive-scale and the alternative AI research foci for enhancing NPC capabilities.
The Role of Empathy and Life Satisfaction in Internet and Smartphone Use Disorder

Recent studies have yielded initial evidence for an association between Internet Use Disorder (IUD), empathy, and life satisfaction. In the present study we sought to replicate these previous findings, and then to extend this research by also examining the relationship between empathy, life satisfaction, and the related phenomenon of Smartphone Use Disorder (SUD). The present study included independent samples from China (N = 612, 162 females) and Germany (N = 304, 207 females), with the same set of questionnaires administered to both samples. IUD was measured with Pawlikowski's s-IAT and SUD was assessed with the short version of Kwon's Smartphone Addiction Scale. The Interpersonal Reactivity Index (IRI) was used to assess individual differences in empathy. Please note that for the German sample data on the empathy quotient (EQ) are also available. Life satisfaction data were collected using items from the SOEP-Questionnaire (Socio-Economic Panel, Germany). In both of our samples we replicated previous findings showing the association between higher IUD, lower empathy, and lower life satisfaction scores. In addition, individuals with higher SUD showed higher scores on the IRI Personal Distress scale in China and Germany, while further associations between IRI dimensions and SUD were only found in the Chinese sample. Personal Distress is known to be highly correlated with the personality trait of Neuroticism, hence higher stress/negative emotionality in tense social situations is related to SUD. In the present study we confirm earlier findings showing the relationship between empathy, life satisfaction, and IUD, and extend some of these findings to SUD. We also emphasize the importance of cross-cultural studies when investigating IUD/SUD in the context of empathy and life satisfaction.
Pronominal Anaphora in Basque : Annotation issues for later computational

This paper describes the process followed in the annotation of pronominal anaphora in the Eus3LB Corpus of Basque. Our aim is to use this annotation as the basis for later computational treatment of Basque language. We present the criteria defined for the tagging, the problems we found with the ambiguity and some relevant linguistic conclusions about the features of the antecedents needed to link them correctly to their anaphoric elements. 1 The Eus3LB corpus is a part of the corpus of the 3LB project (Palomar et al., 2004).
Regression of left atrial diameter after kidney transplantation is associated with prolonged survival: an observational study

Renal transplantation reduces the dramatically elevated risk of cardiovascular death in dialysis patients. We previously showed that left atrial diameter before transplantation predicts cardiovascular and overall mortality. Now, we investigated the association of changes in cardiac morphology after transplantation and mortality. We retrospectively analyzed data from the Austrian transplant repository using multivariable Cox and competing risk models and multivariable logistic regression for the prediction of changes in cardiac morphology. We identified 414 patients with a median follow‐up of 8 years and observed a significant progression of mean diameter of left atrium (LA), right atrium and right ventricle and a significant regression of left ventricle. Complete case analysis of 243 patients with a regression of initially enlarged LA diameter had a significantly lower risk of adjusted overall and cardiovascular mortality; hazard ratio (HR 0.45, 95% CI 0.30–0.69, P < 0.001, 124 deaths), and HR of 0.43 [95% CI 0.21–0.92, P = 0.029, 48 cardiovascular (CV) deaths], respectively. Only age at transplantation was significantly associated with regression of LA (OR 0.75, 95% CI 0.60–0.93, P = 0.007). Patients with regression of LA after kidney transplantation exhibited a lower overall and CV mortality risk. Besides age, peritoneal dialysis and antihypertensive therapy were mediators of LA regression.
Hepatotoxicity with antibody maytansinoid conjugates: A review of preclinical and clinical findings

Maytansinoids, the potent cytotoxic derivatives of the alkaloid maytansine are used as payloads in antibody maytansinoid conjugates. This article reviews clinical and preclinical hepatotoxicity observed with antibody maytansinoid conjugates used to treat cancer. Specific aspects of drug distribution, metabolism and excretion that may impact hepatotoxicity are reviewed vis‐à‐vis the kind of maytansinoid in the conjugate, cleavable or non‐cleavable linkers, linker–payload combinations, drug to antibody ratio, metabolite formation, hepatic enzyme induction in relation to drug–drug interactions and species, age and gender differences. The article also sheds light on factors that may protect the liver from toxic insults.
Impact of a person-centred community rehabilitation service on outcomes for individuals with a neurological condition

Abstract Purpose: To evaluate the impact of a person-centred, community rehabilitation service on outcomes for people with a neurological condition, in the first year of service. Method: A prospective, observational, pre-post study was conducted with 206 people who had a neurological condition and attended the rehabilitation service to restore function (e.g., Stroke); maximize recovery in an ongoing situation (e.g., Spina Bifida); or maximize function and independence while preparing for inevitable decline (e.g., Parkinson’s Disease). Outcomes were measured via self-report questionnaires, prior to, and following three months of rehabilitation. The primary outcome was achievement of self-identified goals, measured by the Patient-Specific Functional scale. Secondary outcomes included the Lawton Instrumental Activities of Daily Living (IADL) scale, EQ-5D-5L European Quality of Life scale, and ICECAP-O – Index of Capability for Older Adults and health and medical resource use. Results: Participants demonstrated significant goal achievement and a significant reduction in health and medical resource use. There were small positive changes in the Lawton IADL, EQ-5D-5L, and ICECAP-O however these changes were not significant. Conclusions: In the first year of operation, the community rehabilitation service made a significant impact on outcomes for individuals with a neurological condition. Further research is required to identify appropriate measures of activities of daily living and quality of life that reflect person-centred rehabilitation outcomes for restoring function, maximizing function, or preparing for functional decline. Implications for Rehabilitation Self-identified goals are an important guide for achievement of meaningful outcomes for individuals with a neurological condition. Person-centred outcome measures are required to evaluate the benefits of a person-centred community rehabilitation service for individuals with a neurological condition.
Forgetting of Foreign-Language Skills: A Corpus-Based Analysis of Online Tutoring Software

We explore the nature of forgetting in a corpus of 125,000 students learning Spanish using the Rosetta Stone® foreign-language instruction software across 48 lessons. Students are tested on a lesson after its initial study and are then retested after a variable time lag. We observe forgetting consistent with power function decay at a rate that varies across lessons but not across students. We find that lessons which are better learned initially are forgotten more slowly, a correlation which likely reflects a latent cause such as the quality or difficulty of the lesson. We obtain improved predictive accuracy of the forgetting model by augmenting it with features that encode characteristics of a student's initial study of the lesson and the activities the student engaged in between the initial and delayed tests. The augmented model can predict 23.9% of the variance in an individual's score on the delayed test. We analyze which features best explain individual performance.
Segmentation-Based Postprocessing in Real-Time Immersive Video Conferencing

We present a novel, real-time disparity analysis frame work developed for immersive teleconferencing. This two-stage method computes a limited number of highly reliable disparities in the first step and then, filling the remaining holes based on segmentation information. The disparity algorithm is a hybrid recursive matching (HRM) approach. Its computational effort is minimised by the efficient selection of a small number of candidate vectors, guaranteeing both spatial and temporal consistency of disparities. In order to improve the disparity fields in the case of occlusions, a segmentation-based postprocessing is applied. The teleconferencing application requires video processing at ITU-Rec. 601 resolution. In the current version, the algorithm generates disparity maps in real time for both directions (Left Right and Right Left) on a Pentium III, 800 MHz processor.
Detection of metabolites of the new synthetic cannabinoid CUMYL-4CN-BINACA in authentic urine samples and human liver microsomes using high-resolution mass spectrometry.

CUMYL-4CN-BINACA(1-(4-cyanobutyl)-N-(2-phenylpropan-2-yl)-1H-indazole-3-carboxamide) is a recently introduced indazole-3-carboxamide-type synthetic cannabinoid (SC) that was detected in herbal incense seized by of the Council of Forensic Medicine, Istanbul Narcotics Department, in May 2016 in Turkey. Recently introduced SCs are not detected in routine toxicological analysis; therefore, analytical methods to measure these compounds are in demand. The present study aims to identify urinary marker metabolites of CUMYL-4CN-BINACA by investigating its metabolism in human liver microsomes and to confirm the results in authentic urine samples (n = 80). In this study, 5 μM CUMYL-4CN-BINACA was incubated with human liver microsomes (HLMs) for up to 3 hours, and metabolites were identified using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Less than 21% of the CUMYL-4CN-BINACA parent compound remained after 3 hours of incubation. We identified 18 metabolites that were formed via monohydroxylation, dealkylation, oxidative decyanation to aldehyde, alcohol, and carboxylic acid formation, glucuronidation or reaction combinations. CUMYL-4CN-BINACA N-butanoic acid (M16) was found to be major metabolite in HLMs. In urine samples CUMYL-4CN-BINACA was not detected; CUMYL-4CN-BINACA N-butanoic acid (M16) was major metabolite after β-glucuronidase hydrolysis. Based on these findings, we recommend using M16 (CUMYL-4CN-BINACA N-butanoic acid), M8 and M11 (hydroxylcumyl CUMYL-4CN-BINACA) as urinary marker metabolites to confirm CUMYL-4CN-BINACA intake.
Marketing active transportation to school to improve children’s health: Utilizing parental perspectives from an inner-city environment

ABSTRACT Thirty years ago, nearly half of the children in the United States walked or rode their bikes to school. Today, less than 15% of children actively commute to school. With the growing obesity epidemic, encouraging children to walk or bike to school has become a national priority. This research examines factors that influence parental decisions allowing their children to walk to school in an urban environment to identify effective marketing and communication strategies to reach those parents. Results indicate differences in parental perspectives across populations; suggestions for effectively marketing the Safe Routes to School program to minority populations are provided.