Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong Stationarity Conditions for Optimal Control of Hybrid Systems

We present necessary and sufficient optimality conditions for finite-time optimal control problems for a class of hybrid systems described by linear complementarity models. Although these optimal control problems are difficult in general due to the presence of complementarity constraints, we provide a set of structural assumptions ensuring that the tangent cone of the constraints possesses geometric regularity properties. These imply that the classical Karush–Kuhn–Tucker conditions of nonlinear programming theory are both necessary and sufficient for local optimality, which is not the case for general mathematical programs with complementarity constraints. We also present sufficient conditions for global optimality. We proceed to show that the dynamics of every continuous piecewise affine (PWA) system can be written as the optimizer of a mathematical program, which results in a linear complementarity model satisfying our structural assumptions. Hence, our stationarity results apply to a large class of hybrid systems with PWA dynamics. We present simulation results showing the substantial benefits possible from using a nonlinear programming approach to the optimal control problem with complementarity constraints instead of a more traditional mixed-integer formulation.
Prevalence of trichomoniasis amongst women in Nnewi, Anambra State, Nigeria

A survey of trichomoniasis amongst women in Nnewi, Anambra State, was carried out. Mid-stream early morning urine and vaginal swabs were collected in screw-capped sterile bottles and Evepon swab sticks respectively from 1,440 women aged 14 to 50 years from 4 communities, Otolo, Umudim, Uruagu and Nnewichi. The samples were transported to the Medical Parasitology Laboratory, Nnamdi Azikiwe University Teaching Hospital, Nnewi, for parasitological examination. Laboratory findings showed that 310 (21.53%) respondents were infected with trichomoniasis. Age-related prevalence of infection showed that respondents aged 21-30 years had the highest prevalence of infection (23.53%) while those aged 41-50 years had the least prevalence (12.07%). Occupational-related prevalence of infection revealed that traders aged 31-40 years had the highest prevalence (39.98%) of infection while civil servants aged 14-20 years had the least prevalence (5.20%) of infection. Relating prevalence of infection to marital status, 33.47% of single women and 15.25% of married women were infected. The highest prevalence of infection (24.48%) was observed amongst single women aged 21-30 years, while the least prevalence of infection (9.86%) was observed amongst single women aged 41-50 years. Analysis of the data showed a significant difference (p Keywords : age-related prevalence, occupational groups, trichomoniasis, Nnewi, Nigeria. Nigerian Journal of Parasitology Vol. 28 (1) 2007: pp. 6-10
Acalculous cholecystitis presenting in an out-patient with no risk factors

Acute acalculous cholecystitis (AAC) is recognised to occur in patients with serious co-morbid illnesses such as after major surgery, severe trauma, burns, multi-organ failure, systemic sepsis and prolonged intravenous hyperalimentation. The development of AAC in outpatients with none of the traditional risk factors appears to be increasing. The incidence of this form of AAC in South Africa has not yet been established. Prompt recognition of this condition and appropriate surgical management is necessary to minimise morbidity and mortality. This report describes a 52-year-old man who developed AAC in the absence of the usual risk factors.
The mastery of antidotes

Aim: To describe various types of Chinese hospitals’ emergency department (ED) physicians’ knowledge of antidotes and the comparative availability of toxicological treatments at these hospitals. Methods: We emailed a written survey to the ED doctors of 900 hospitals in China. The hospitals’ names and addresses were obtained and randomly selected from the 6214 hospitals registered by the Chinese Medical Association. The survey included 23 questions on antidotes to commonly seen poisonings as well as questions on the availability of antidotes and decontamination techniques at each hospital. Results: Six hundred and fifty three hospital emergency directors responded to the survey 72.6% response rate). Overall knowledge of antidotes is not high and varied depending on antidote. Physicians in Eastern China, those working in tertiary-level hospitals and those working in hospitals with higher numbers of beds performed significantly better. On average, only 35.6% of the 23 antidotes were available in all reporting hospitals; 54.1% can get these antidotes from nearby hospitals and 42.0% can get them from a local CDC poison control center. However, only 57.3% can get a requested antidote within two hours. Gastric lavage is the most widely used decontamination procedure, and the availability of extracorporeal decontamination techniques is between 67.2% and 79.6% (depending on type). Conclusion: Knowledge of specific antidotes correlated significantly with size, type, and region of hospital in China rather than with individual physician characteristics. Significant antidotes remain unavailable or unavailable within 2 h in about half of all hospitals surveyed, although all major acute decontamination treatments and techniques seem quite prevalent.
The role and function of child contact centres

Abstract Every week 2,000 children attend a contact centre in England, Wales or Scotland to meet and play with either their mother or father or maybe both or other family members in a controlled environment. Why has there been a phenomenal growth in such centres in the past ten years? Why is funding for the centres piecemeal and generally not from Government sources? Do they help or hinder the post-separation period of adjustment?
Graph-Structured Representations for Visual Question Answering

This paper proposes to improve visual question answering (VQA) with structured representations of both scene contents and questions. A key challenge in VQA is to require joint reasoning over the visual and text domains. The predominant CNN/LSTM-based approach to VQA is limited by monolithic vector representations that largely ignore structure in the scene and in the question. CNN feature vectors cannot effectively capture situations as simple as multiple object instances, and LSTMs process questions as series of words, which do not reflect the true complexity of language structure. We instead propose to build graphs over the scene objects and over the question words, and we describe a deep neural network that exploits the structure in these representations. We show that this approach achieves significant improvements over the state-of-the-art, increasing accuracy from 71.2% to 74.4% in accuracy on the abstract scenes multiple-choice benchmark, and from 34.7% to 39.1% in accuracy over pairs of balanced scenes, i.e. images with fine-grained differences and opposite yes/no answers to a same question.
Effect of tauroursodeoxycholic acid on PUFA levels and inflammation in an animal and cell model of hepatic endoplasmic reticulum stress

The aim of this study was to evaluate hepatic polyunsaturated fatty acids (PUFAs) and inflammatory response in an animal and cell model of endoplasmic reticulum (ER) stress. Rats were divided into control, tunicamycin (TM)-treated, and TM + tauroursodeoxycholic acid (TUDCA)-treated groups. Hepatic ER stress was induced by TM and the ER stress inhibitor TUDCA was injected 30 min before induction of ER stress. Liver THLE-3 cells were treated with TM and TUDCA was administered in advance to decrease cytotoxic effects. Necroinflammation was evaluated in liver sections, while cell viability was determined using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay kit. ER stress was confirmed by immunofluorescence and Western blot analysis of C/EBP-homologous protein and 78-kDa glucose-regulated protein. Arachidonic acid (C20:4n-6), dihomo-γ-linolenic acid (C20:3n-6), eicosapentaenoic acid (C20:5n-3), and docosahexaenoic acid (C22:6n-3) in liver tissue and THLE-3 cells were determined by liquid chromatography tandem mass spectrometry (LC-MS/MS). Phospholipase A2 (PLA2), cyclooxygenase (COX), and prostaglandin E2 (PGE2) were measured in tissue and cell samples. Hepatic ER stress was accomplished by TM and was alleviated by TUDCA. TM treatment significantly decreased PUFAs in both liver and THLE-3 cells compared to controls. PLA2, COX, and PGE2 levels were significantly increased in TM-treated rats and THLE-3 cells compared to controls. TUDCA leads to a partial restoration of liver PUFA levels and decreased PLA2, COX, and PGE2. This study reports decreased PUFA levels in ER stress and supports the use of omega-3 fatty acids in liver diseases demonstrating ER stress.
Deep Cross-Modal Hashing

Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been widely used for similarity search in multimedia retrieval applications. However, most existing CMH methods are based on hand-crafted features which might not be optimally compatible with the hash-code learning procedure. As a result, existing CMH methods with hand-crafted features may not achieve satisfactory performance. In this paper, we propose a novel CMH method, called deep cross-modal hashing (DCMH), by integrating feature learning and hash-code learning intothe same framework. DCMH is an end-to-end learning framework with deep neural networks, one for each modality, to perform feature learning from scratch. Experiments on three real datasets with image-text modalities show that DCMH can outperform other baselines to achieve the state-of-the-art performance in cross-modal retrieval applications.
Effects of Mutual Coupling on the Accuracy of Adcock Direction Finding Systems

The design of direction finding (DF) systems intended to operate over large frequency ranges involves various compromises. Typical implementations involve the use of multiple antenna arrays, each of which is scaled to cover a portion of the frequency range of interest. To minimize the size of the resulting multiband antenna assembly, two or more arrays can be combined in a coplanar antenna configuration. However, this introduces the issue of mutual coupling between the elements of the different arrays. A comprehensive study of the effects of mutual coupling on the estimation error for this type of antenna array configuration for two commonly used DF techniques is provided. Several important results clarify key design issues and trade-offs. It is shown that proper design choices are required to avoid uncorrectable ambiguities and the resulting large estimation errors.
Integrated Bayesian Clutter Estimation with JIPDA/MHT Trackers

Based on Poisson point processes, multitarget multi-Bernoulli processes, and set calculus, a Bayesian method is presented to estimate the nonhomogeneous clutter background while simultaneously tracking multiple targets. A major feature of the proposed approach is the seamless integration of clutter estimation with standard multitarget tracking algorithms like the multiple hypothesis tracker (MHT) and the joint integrated probabilistic data association (JIPDA) tracker by exploiting the association events and their probabilities constructed and calculated in standard multitarget tracking algorithms.
Microbiology. Gut bacteria lend a molecular hand to viruses.

On page [245][1] of this week's issue of Science , researchers describe a virus that covers itself with molecules from natural gut bacteria, and those molecules interact with TLR4, a mouse immune system receptor, to make viral infection possible. Nor is this pathogen, the mouse mammary tumor virus, the only virus that co-opts components of the microflora. At least two others, including poliovirus, rely on those same molecules from gut bacteria to invade their host, another team reports in a study, on page [249][2], that echoes the first finding. [1]: http://www.sciencemag. org/content/334/6053/245.abstract [2]: http://www.sciencemag. org/content/334/6053/249.abstract
Prevalence of Supernumerary Teeth in Orthodontic Patients from Southwestern Brazil

El objetivo de este estudio fue investigar la prevalencia de dientes supernumerarios en una poblacion pediatrica de Brasil. Un examinador evaluo la presencia de dientes supernumerarios en radiografias panoramicas de 1719 sujetos (762 hombres y 957 mujeres), con edades comprendidas entre 4 y 14,5 anos (media 8,4 anos de edad), del archivo del Curso de Ortodoncia Preventiva del Hospital de Rehabilitacion de Bauru, Sao Paulo. Los dientes supernumerarios se presentaron en treinta sujetos (1,7%, 16 hombres y 14 mujeres). La diferencia entre sexos no fue estadisticamente significativa. Veintinueve dientes supernumerarios (96,7%) se ubicaron en el maxilar, y solo 1 (3,3%) se ubico en la mandibula. Diecisiete dientes supernumerarios (56,7%) ubicados en el maxilar eran mesiodens. El diagnostico precoz de los dientes supernumerarios es esencial para prevenir la maloclusion y malposicion de los dientes permanentes, lo que demuestra la importancia de la radiografia panoramica en su deteccion.
Martial arts research: weak evidence.

The Review “Interventions shown to aid executive function development in children 4 to 12 years old” by A. Diamond and K. Lee (special section on Investing Early in Education, 19 August, p. [959][1]) cited work that close examination shows to be weak. Some of the studies ([ 1 ][2], [ 2 ][3]) were randomized, but they failed to meet other criteria such as blinding of teachers and parents to pupils' treatment groups. Studies involving martial arts and physical exercise were particularly weak on isolation of variables. One study on martial arts training for children ([ 1 ][2]) compared a treatment group who wore special uniforms, meditated, bowed to their instructor, and were reminded of self-awareness and self-control, to a control group who continued with their ordinary physical education activities; these authors concluded that when some improvement on some scales occurred for the treatment group, the change was caused by the self-awareness and self-control messages, rather than by other ways the two groups differed. Another study ([ 2 ][3]) compared children who did “sport stacking,” a bimanual physical task, with a control group that did not experience any exciting new activity, and concluded that improvement on one of two reading measures was caused by the stacking task. [Figure][4] CREDIT: STUART MONK/ISTOCKPHOTO.COM A relevant volume dealing with treatments for developmental disabilities ([ 3 ][5]) stressed the weakness of evidence for special education interventions and described some such conditions as “fad magnets. ” Unfortunately, early educational interventions seem to be similarly weak in evidence. The stakes are high and the resources scarce in both cases. 1. [↵][6] 1. K. D. Lakes, 2. W. T. Hoyt , Appl. Dev. Psychol. 25, 283 (2004). [OpenUrl][7][CrossRef][8] 2. [↵][9] 1. T. A. Uhrich, 2. R. L. Swalm , Percept. Mot. Skills 104, 1935 (2007). [OpenUrl][10] 3. [↵][11] 1. J. W. Jacobson, 2. R. M. Foxx, 3. J. A. Mulick , Controversial Therapies for Developmental Disabilities (Erlbaum, Mahwah, NJ, 2005). [1]: /lookup/doi/10.1126/science.1204529 [2]: #ref-1 [3]: #ref-2 [4]: pending:yes [5]: #ref-3 [6]: #xref-ref-1-1 "View reference 1 in text" [7]: {openurl}? query=rft.jtitle%253DAppl. %2BDev. %2BPsychol. %26rft.volume%253D25%26rft.spage%253D283%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.appdev. 2004.04. 002%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [8]: /lookup/external-ref? access_num=10.1016/j.appdev. 2004.04. 002&link_type=DOI [9]: #xref-ref-2-1 "View reference 2 in text" [10]: {openurl}? query=rft.jtitle%253DPercept. %2BMot. %2BSkills%26rft.volume%253D104%26rft.spage%253D1935%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [11]: #xref-ref-3-1 "View reference 3 in text"
Recovery Profiles of Cognitive-Sensory Modalities in Patients in the Minimally Conscious State Following Traumatic Brain Injury

Abstract Over the past two decades there has been an increasing number of patients surviving severe traumatic brain injury and entering rehabilitation facilities at an earlier phase in their recovery. These patients often present in a minimally conscious state and are difficult to objectively assess. As a result, a number of batteries have been developed targeting this population. The Western Neuro Sensory Stimulation Profile (WNSSP) was used in the present study to identify patterns in recovery of cognitive-sensory modalities. The WNSSP records of 25 patients in a minimally conscious state were examined and profiles of recovery over four test occasions of a subset of 12 patients were examined in detail. Results demonstrated that within this highly heterogeneous group, Object Manipulation was an early emerging skill, and trends to significance were also observed in Auditory Response, Visual Tracking and Olfactory Response. A case study is presented to illustrate how the WNSSP results can be utilised to direct individualised treatment planning.
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks. This paper re-evaluates state-of-the-art architectures in light of the new Kinetics Human Action Video dataset. Kinetics has two orders of magnitude more data, with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. We provide an analysis on how current architectures fare on the task of action classification on this dataset and how much performance improves on the smaller benchmark datasets after pre-training on Kinetics. We also introduce a new Two-Stream Inflated 3D ConvNet (I3D) that is based on 2D ConvNet inflation: filters and pooling kernels of very deep image classification ConvNets are expanded into 3D, making it possible to learn seamless spatio-temporal feature extractors from video while leveraging successful ImageNet architecture designs and even their parameters. We show that, after pre-training on Kinetics, I3D models considerably improve upon the state-of-the-art in action classification, reaching 80.2% on HMDB-51 and 97.9% on UCF-101.
Health information: does quality count for the consumer?

An aspect of the information literacy of health information consumers is explored, in particular whether and how they evaluate the quality of health information on the Internet and in printed formats. A total of 32 members of patient support groups in North-East Scotland were recruited to take part in information review groups (a variation of focus group methodology) where discussion focused on a set of health information materials. Data analysis revealed 15 ways in which the participants evaluated quality. The two most important indicators of quality were organizational authority and the use of plain language. They did not find many of the indicators of evidence-based information. Participants demonstrated lack of confidence about their ability to select quality health information and relied on preselection by authoritative sources (libraries, support groups, health professionals) and distrusted the Internet.
iCaRL: Incremental Classifier and Representation Learning

A major open problem on the road to artificial intelligence is the development of incrementally learning systems that learn about more and more concepts over time from a stream of data. In this work, we introduce a new training strategy, iCaRL, that allows learning in such a class-incremental way: only the training data for a small number of classes has to be present at the same time and new classes can be added progressively. iCaRL learns strong classifiers and a data representation simultaneously. This distinguishes it from earlier works that were fundamentally limited to fixed data representations and therefore incompatible with deep learning architectures. We show by experiments on CIFAR-100 and ImageNet ILSVRC 2012 data that iCaRL can learn many classes incrementally over a long period of time where other strategies quickly fail.
Race disparity in grants: check the citations.

[Figure][1] CREDIT: DON BAYLEY/ISTOCKPHOTO.COM The Report “Race, ethnicity, and NIH research awards” (D. K. Ginther et al. , 19 August, p. [1015][2]), documenting a lower grant funding rate for black than for white applicants, has generated widespread alarm that there may be a hidden racial bias in the grant review process. However, the study is flawed. Ginther et al. looked at two groups—those with fewer and greater than 84 citations—and found that blacks in both groups were substantially unsuccessful with grant funding. This range does not seem relevant to competitive scientists. A meaningful cutoff for a typical assistant professor, approaching tenure and the renewal of his first grant, would be closer to 1000 citations, not 84. The study also overlooks the fact that citations accumulate over time. Ginther et al. should have used an algorithm that normalizes citations to age. I believe they would have found that scientists who are highly successful, as defined by age-normalized citations or h index, would be equally successful in grant funding, with no disparity for race and ethnicity. [1]: pending:yes [2]: /lookup/doi/10.1126/science.1196783
Healthcare personnel's use of e-information sources in Riyadh governmental hospitals

ICT has enabled a wide dissemination of information and a sharp increase in the magnitude of electronic information sources. The use of e-information sources by healthcare personnel within Saudi Arabia has received little research attention. This paper discusses the use of e-information sources by healthcare personnel in the kingdom. A questionnaire with open-ended questions was designed to collect data from 11 governmental hospitals and health centres in Riyadh. It identified a range of problems and obstacles that impact on the use of electronic information sources. The identification of these difficulties opens the way for development and improvement of the current situation.
L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space

The research focus of designing local patch descriptors has gradually shifted from handcrafted ones (e.g., SIFT) to learned ones. In this paper, we propose to learn high performance descriptor in Euclidean space via the Convolutional Neural Network (CNN). Our method is distinctive in four aspects: (i) We propose a progressive sampling strategy which enables the network to access billions of training samples in a few epochs. (ii) Derived from the basic concept of local patch matching problem, we empha-size the relative distance between descriptors. (iii) Extra supervision is imposed on the intermediate feature maps. (iv) Compactness of the descriptor is taken into account. The proposed network is named as L2-Net since the output descriptor can be matched in Euclidean space by L2 distance. L2-Net achieves state-of-the-art performance on the Brown datasets [16], Oxford dataset [18] and the newly proposed Hpatches dataset [11]. The good generalization ability shown by experiments indicates that L2-Net can serve as a direct substitution of the existing handcrafted descriptors. The pre-trained L2-Net is publicly available.