Miracle-dz/UniFAR-FTUs huggingface dataset:
Fatal Acinetobacter baumanii Necrotizing Fasciitis following Open Reduction Internal Fixation in a Polytrauma Patient

Necrotizing fasciitis is an uncommon and potentially fatal infection that can affect the epidermis, dermis, and more commonly the subcutaneous, fascia, and muscle layers. NF is usually caused by toxin-producing bacteria with a relatively fast progression associated with severe surrounding tissue destruction. Early diagnosis and management are crucial factors for survival. Broad-spectrum antibiotics along with surgical debridement, sometimes multiple, are needed in order to stop or slow down the progression of NF. Despite optimal care, necrotizing fasciitis remains a highly morbid condition with a high mortality rate. We present a case of a 28-year-old male patient with rapidly developing fatal A. baumannii associated with necrotizing fasciitis, after open reduction and internal fixation (ORIF) of multiple fractures after polytrauma.
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits

We derive an algorithm that achieves the optimal (within constants) pseudo-regret in both adversarial and stochastic multi-armed bandits without prior knowledge of the regime and time horizon. The algorithm is based on online mirror descent (OMD) with Tsallis entropy regularization with power $\alpha=1/2$ and reduced-variance loss estimators. More generally, we define an adversarial regime with a self-bounding constraint, which includes stochastic regime, stochastically constrained adversarial regime (Wei and Luo), and stochastic regime with adversarial corruptions (Lykouris et al.) as special cases, and show that the algorithm achieves logarithmic regret guarantee in this regime and all of its special cases simultaneously with the adversarial regret guarantee. } The algorithm also achieves adversarial and stochastic optimality in the utility-based dueling bandit setting. We provide empirical evaluation of the algorithm demonstrating that it significantly outperforms UCB1 and EXP3 in stochastic environments. We also provide examples of adversarial environments, where UCB1 and Thompson Sampling exhibit almost linear regret, whereas our algorithm suffers only logarithmic regret. To the best of our knowledge, this is the first example demonstrating vulnerability of Thompson Sampling in adversarial environments. Last, but not least, we present a general stochastic analysis and a general adversarial analysis of OMD algorithms with Tsallis entropy regularization for $\alpha\in[0,1]$ and explain the reason why $\alpha=1/2$ works best.
Machine Learning Attack and Defense on Voltage Over-scaling-based Lightweight Authentication

It is a challenging task to deploy lightweight security protocols in resource-constrained IoT applications. A hardware-oriented lightweight authentication protocol based on device signature generated during voltage over-scaling (VOS) was recently proposed to address this issue. VOS-based authentication employs the computation unit such as adders to generate the process variation dependent error which is combined with secret keys to create a two-factor authentication protocol. In this paper, machine learning (ML)-based modeling attacks to break such authentication is presented. We also propose a dynamic obfuscation mechanism based on keys (DOMK) for the VOS-based authentication to resist ML attacks. Experimental results show that ANN, RNN and CMA-ES can clone the challenge-response behavior of VOS-based authentication with up to 99.65% predication accuracy, while the predication accuracy is less than 51.2% after deploying our proposed ML resilient technique.
The BBN model: a mouse bladder cancer model featuring basal-subtype gene expression and MLL3/MLL4 genetic disruption

Bladder cancer is one of the most common cancers in the United States, with an incidence of more than 80,000 new cases per year. The major risk factors for bladder cancer include cigarette smoking, as well as gender, since men are 4 times more likely than women to develop urothelial carcinomas [1]. About 30% of new patients are diagnosed with muscle-invasive bladder cancer (MIBC), with an unfavorable prognosis compared to non-muscle invasive tumors, and only few therapeutic options. Currently, a major issue limiting the development of more effective anticancer drugs for MIBC is the small number of animal models that closely recapitulate the human disease. A promising MIBC animal model is the N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) mouse model [2]. BBN is a carcinogen structurally related to the chemicals found in cigarette smoke. When administered to C57/B6 male mice in drinking water for at least 20 weeks, BBN causes invasive bladder tumors. Early studies revealed morphologic similarities between murine BBN tumors and human bladder tumors. Studies by The Cancer Genome Atlas (TCGA) suggested that MIBC can be further classified into distinct molecular subtypes independently of morphology, incorporating information about genomic alterations and gene expression dysregulations [3]. Notably, cancer molecular subtypes are prognostic of survival, predict sensitivity to specific therapies (chemotherapy and immunotherapy), and hence may aid in precision medicine. To better understand whether the BBN mouse bladder cancer model closely mimicked a specific subgroup of human MIBC, we analyzed its molecular alterations by RNA-seq and whole exome sequencing (WES) [2]. Our RNA-seq analyses revealed that gene expression in the BBN tumors aligned to MIBC belonging to the basal molecular subtype, with increased expression of markers such as Cd44, Cdh3, Krt5, and Krt14. In addition, we observed dysregulation of genes associated with T-cell homeostasis (Il7r, Il2ra, Ripk3) and extracellular signaling [2]. These observations were suggestive of an active but ineffective response of the murine immune system to the BBN-induced tumors. While we are still conducting experiments to validate this hypothesis, our observations Editorial
CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios

Navigation is an essential capability for mobile robots. In this paper, we propose a generalized yet effective 3M (i.e., multi-robot, multi-scenario, and multi-stage) training framework. We optimize a mapless navigation policy with a robust policy gradient algorithm. Our method enables different types of mobile platforms to navigate safely in complex and highly dynamic environments, such as pedestrian crowds. To demonstrate the superiority of our method, we test our methods with four kinds of mobile platforms in four scenarios. Videos are available at this https URL.
Ensemble of Deep Learned Features for Melanoma Classification

The aim of this work is to propose an ensemble of descriptors for Melanoma Classification, whose performance has been evaluated on validation and test datasets of the melanoma challenge 2018. The system proposed here achieves a strong discriminative power thanks to the combination of multiple descriptors. The proposed system represents a very simple yet effective way of boosting the performance of trained CNNs by composing multiple CNNs into an ensemble and combining scores by sum rule. Several types of ensembles are considered, with different CNN architectures along with different learning parameter sets. Moreover CNN are used as feature extractors: an input image is processed by a trained CNN and the response of a particular layer (usually the classification layer, but also internal layers can be employed) is treated as a descriptor for the image and used for training a set of Support Vector Machines (SVM).
Les questions en suspens dans le domaine de la promotion des ventes

La promotion des ventes est un sujet encore relativement nouveau dans la littérature et de nombreuses questions sont encore non résolues. Cet article fait la liste de 15 questions importantes sur cinq thèmes fondamentaux de la promotion des ventes avec l'intention d'identifier celles qui ne sont pas bien traitées sur la base de la littérature actuelle, et qui, pourtant, sont de première importance tant pour les praticiens que pour les chercheurs. Des hypothèses spécifiques de recherche à tester sont aussi proposées. Même si, en aucune manière, les points évoqués sur le plan général ou spécifique, ne constituent une liste exhaustive, ils mettent en valeur les directions les plus importantes pour la recherche actuelle et future.
Effect of Nutrition Education Based on Health Belief Model on Nutritional Knowledge and Dietary Practice of Pregnant Women in Dessie Town, Northeast Ethiopia: A Cluster Randomized Control Trial

Background In Ethiopia, poor dietary practice among pregnant women ranges from 39.3 to 66.1%. Limited nutritional knowledge and wrong perception towards dietary behaviours were underlying factors. Hence, this study was aimed to determine the effect of nutrition education based on Health Belief Model on nutritional knowledge and dietary practice of pregnant women in Dissie town, northeast Ethiopia, 2017 GC. Methods Community-based cluster randomized control trial was employed. A total of 138 pregnant women participated. Nutrition education was given using Health Belief Model (HBM) theory and general nutrition education for intervention and control group, respectively. The baseline and endline nutrition knowledge and dietary practice was assessed using knowledge and dietary practice questions. HBM construct was assessed using five-point likert scale. Data were analyzed using SPSS version 20. Student's t-tests and chi-square tests were used. At 95% confidence level, P < 0.05 was considered statistically significant. Result The mean pre- and postintervention nutritional knowledge was 6.9 and 13.4, and good dietary practice was 56.5% and 84.1% in intervention group, respectively. The increase in mean nutritional knowledge was statistically significant (P < 0.001). In control group, the pre- and postintervention mean nutritional knowledge was 7.4 and 9.8, and good dietary practice was 60.9% and 72.5%, respectively. There was significant difference (P < 0.05) in mean nutritional knowledge and proportion of good dietary practices between two groups at endline, but the difference was not significant (P > 0.05) at baseline. There was significant (P < 0.001) improvement in the scores of HBM constructs in intervention group. Conclusion and Recommendations Providing nutrition education based on Health Belief Model improves nutritional knowledge and dietary practices of pregnant women. Hence, governmental, nongovernmental organization, health extension workers, and other health-care provider should include Health Belief Model construct into existing nutrition education programs. Moreover, government should incorporate HBM theory into national nutrition education guidelines.
Genomic signatures of population bottleneck and recovery in Northwest Atlantic pinnipeds

Abstract Population increases over the past several decades provide natural settings in which to study the evolutionary processes that occur during bottleneck, growth, and spatial expansion. We used parallel natural experiments of historical decline and subsequent recovery in two sympatric pinniped species in the Northwest Atlantic, the gray seal (Halichoerus grypus atlantica) and harbor seal (Phoca vitulina vitulina), to study the impact of recent demographic change in genomic diversity. Using restriction site‐associated DNA sequencing, we assessed genomic diversity at over 8,700 polymorphic gray seal loci and 3,700 polymorphic harbor seal loci in samples from multiple cohorts collected throughout recovery over the past half‐century. Despite significant differences in the degree of genetic diversity assessed in the two species, we found signatures of historical bottlenecks in the contemporary genomes of both gray and harbor seals. We evaluated temporal trends in diversity across cohorts, as well as compared samples from sites at both the center and edge of a recent gray seal range expansion, but found no significant change in genomewide diversity following recovery. We did, however, find that the variance and degree of allele frequency change measured over the past several decades were significantly different from neutral expectations of drift under population growth. These two cases of well‐described demographic history provide opportunities for critical evaluation of current approaches to simulating and understanding the genetic effects of historical demographic change in natural populations.
Update on ocular myasthenia gravis in Taiwan

Myasthenia gravis (MG) is an autoimmune disease involving the neuromuscular junction. Autoantibodies to the acetylcholine receptor or, less frequently, to muscle-specific kinase, attack against the postsynaptic junctional proteins, resulting in fluctuating and variable weakness of muscles. Extraocular, levator palpebrae superioris, and orbicularis oculi muscles are particularly susceptible. The majority of patients with MG present with purely ocular symptoms including ptosis and diplopia initially. About half of these patients progress to generalized disease within 2 years. The prevalence of MG in Taiwan is 140 per million with male to female ratio of 0.7. The incidence rate is higher in the elderly. Several immune-related diseases such as lymphoid malignancy, diabetes, and thyroid diseases are associated with MG in the national population-based studies in Taiwan. Ice pack test, rest test, Tensilon/neostigmine test, circulating antibody measurement, and electrophysiological studies are useful diagnostic tools with variable sensitivity and specificity. For the patients with ocular MG, acetylcholinesterase inhibitors are usually the first-line treatment. Corticosteroids and immunosuppressant could provide better disease control and may reduce the risk of conversion to generalized form although there is still some controversy. A thymectomy is also beneficial for ocular MG, especially in refractory cases. The correction of ptosis and strabismus surgery could improve the visual outcome but should be performed only in stable disease.
A pattern in the imaging data: mere artefact of spatio-temporal resolution

{\it ' Seeing is believing '} \cite{north06}- is the fundamental philosophy of optical imaging based on light microscopy \cite{ntziachristos10}. Since the pioneering works of Antonie van Leeuwenhoek and Robert Hooke in the 17th century, optical microscopy has served as one of the most important tools in biological sciences \cite{thorn16}. But interpreting visual observations with preconceived notions can potentially mislead one to erroneous conclusions.Here we report one such case where, at first sight, the interesting pattern extracted from the images of axonal transport may appear to reveal some hitherto unknown features of cargo transport driven by cytoskeletal motors \cite{ross16}. It may even be tempting to theorize about the possible molecular mechanisms that could give rise the observed pattern. But, as we conclusively demonstrate here, these patterns are mere artifacts of the spatial and temporal resolutions of imaging microscopes. These observed patterns, and their interpretations, are rather universal in the sense that in all those experiments where an observer (or machine), having limited spatial and temporal resolution, tracks the movement of classical objects moving on a one-dimensional track, such enticing patterns will invariably emerge. Our analysis here exposes pitfalls lurking in the way one interprets such patterns; unless critically analyzed, believing in whatever one is seeing, one could draw an illusory conclusion.
Hippocampal Mechanisms Underlying Impairment in Spatial Learning Long After Establishment of Noise-Induced Hearing Loss in CBA Mice

Sensorineural hearing loss (SNHL) has been demonstrated in many clinical reports as a risk factor that promotes the development of cognitive impairment. However, the underlying neurological mechanisms are not clear. Noise exposure is one of the most common causes of SNHL. Although noise exposure causes relatively less damage to general health as compared with other methods for creating hearing loss (such as ototoxicity), it does impair cognitive function. Many studies have shown that the noise-induced cognitive impairment occur via the oxidative stress induced by the noise. In those studies, the effects of the noise-induced hearing loss induced (NIHL) were not addressed. Previously, we have demonstrated in the CBA/CaJ mouse model that oxidative stress was transient after a brief noise exposure, but the NIHL was permanent. In addition, NIHL was followed by a declined cognitive function and decreased hippocampal neurogenesis that were developed long after the oxidative stress disappeared. Therefore, NIHL can cause cognitive impairment independent of its stress effect and can serve as a model to investigate the relationship between hearing loss and the development of cognitive impairment. In the present study, we further demonstrated that the oxidative stress produced by the brief noise exposure did not damage the stem cell bank of hippocampus that was evaluated shortly after the noise exposure. In addition to the reduction in the rate of cell proliferation in hippocampus that was found previously, we found that the NIHL significantly reduced the promoting effect of learning activity on various stages of hippocampal neurogenesis, accompanied by the reduction in learning-induced expression of immediate early genes (IEGs) in hippocampus. Since the MWM-tested spatial function does not directly require auditory input, the results provide evidence for the maintenance role of auditory input on the cognitive function; the reduction of IEG expression that is required in memory-formation may be the initial step in blocking the effect of learning activity on neurogenesis in subjects with NIHL.
Effects of supplemental lighting with different light qualities on growth and secondary metabolite content of Anoectochilus roxburghii

Background Anoectochilus roxburghii is a widespread herbaceous plant with high medicinal value. Wild A. roxburghii resources face extinction due to their slow growth rate and over exploitation. The growing market demand has led to advances in the field of artificial planting of A. roxburghii. Methods to increase the economic benefits of cultivation and the production of medicinal ingredients are very useful. Methods A. roxburghii was exposed to red light, blue light (BL), yellow light (YL), green light, or white light as supplemental lighting at night (18:00–02:00) in a greenhouse or were left in darkness (control, CK) to investigate the effects of various light qualities on growth indices, photosynthetic pigments, chlorophyll fluorescence, root vitality, stomatal density, soluble proteins, sugars, and the accumulation of secondary metabolites. Results Supplementation of BL had a positive effect on A. roxburghii growth and secondary metabolite accumulation. Leaf number, stem diameter, fresh weight, dry weight, chlorophyll a content, and secondary metabolite (total flavonoids, total polyphenols) content increased significantly. YL treatment showed significantly higher soluble sugar and polysaccharide contents than the control. Discussion BL treatment was conducive to promoting the growth and accumulation of secondary metabolites (total flavonoids, total polyphenols); YL treatment significantly increased the content of soluble sugar and polysaccharides more than the control. Polysaccharides and total flavonoids are important medicinal ingredients of Anoectochilus, so future research will focus on the combination of blue and YL.
Predictive significance of preoperative CT findings for suboptimal cytoreduction in advanced ovarian cancer: a meta-analysis

Background Computed tomography (CT) has been extensively used in predicting suboptimal cytoreduction (SCR) in advanced ovarian cancer (OC). However, disagreements remain in literatures on the predictive value of CT findings for SCR. This meta-analysis was designed to determine the ability of eight preoperative CT findings to predict SCR in advanced OC. Materials and methods A comprehensive literature search was conducted for eligible studies to identify the association between the eight preoperative CT findings and SCR in advanced OC. The predictive performances of preoperative CT findings were expressed in terms of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) with pooled proportion. Results A total of 10 studies and 1,614 patients were included in this meta-analysis. Large volume ascites had the highest sensitivity (64%, CI 56–71%), with a PLR of 1.3 (CI 1.1–1.5) and an NLR of 0.73 (0.59–0.90), while lymph node involvement had the highest specificity (89%, CI 79–94%). The highest DOR of 3 (CI 2–4) was achieved in peritoneal involvement and large bowel mesentery involvement. The other CT findings had poorer predictive performance. Conclusion Preoperative CT findings have a poor discriminative capacity to predict SCR in advanced OC. Preoperative CT predictors should be used with caution amid clinical decision-making.
The Epidemiology of Ankle Injuries Identified at the National Football League Combine, 2009-2015

Background: American football is a leading cause of sports-related injuries, with the knee, ankle, and shoulder most commonly involved. Purpose/Hypothesis: The purpose of this study was to describe the epidemiology, characteristics, and imaging findings of ankle injuries in football players at the National Football League (NFL) Combine and determine the relationship to player position. We hypothesized that there would be a high relative incidence of ankle injuries in these players compared with other sports and that there would be a direct correlation between the incidence of ankle injuries and player position. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A retrospective chart review of data collected from NFL Combine participants between 2009 and 2015 was performed. Patient demographics, history, physical examination results, and imaging findings were reviewed. Results: Of 2285 players, 1216 (53.2%) had a history of ankle injuries; of these, 987 (81.2%) had unilateral injuries, while 229 (18.8%) had bilateral injuries (total of 1445 ankles injured). This included 1242 ankle sprains (86.0% of ankle injuries): 417 (33.6% of sprains) high and 930 (74.9%) low. The most common soft tissue injuries were to the anterior talofibular ligament (n = 158, 12.7% of sprains) and syndesmosis (n = 137, 11.0%). Of all players at the NFL Combine with radiographs, 131 (10.9%) had evidence of an ankle fracture, all of which had healed. Magnetic resonance imaging (MRI) identified 66 players (28.9% of players at the combine who underwent MRI) with articular cartilage injuries: 62 involving the talus and 16 involving the tibia. Furthermore, 85 players (37.3% of players with MRI) with tendon injuries were identified: 26 Achilles, 55 peroneal, 3 flexor hallucis longus, and 19 posterior tibial. A total of 611 players (50.6% of players with radiographs) had signs of arthrosis on radiography. Running backs (61.9%), offensive linemen (60.3%), and tight ends (59.4%) had the highest rates of ankle injuries by position, while kickers/punters (23.3%) and long snappers (37.5%) had the lowest. Conclusion: Prior ankle injuries were present in more than 50% of elite college football players attending the NFL Combine. The rate of these ankle injuries varied by player position: offensive linemen, running backs, and tight ends had the highest overall rates, while special teams players had the lowest. Additional prospective work is needed to determine the impact of prior injuries on future playing career.