Miracle-dz/UniFAR-FTUs huggingface dataset:
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic signal control poses its unique challenges for reinforcement learning in terms of adapting to dynamic traffic environment and coordinating thousands of agents including vehicles and pedestrians. A key factor in the success of modern reinforcement learning relies on a good simulator to generate a large number of data samples for learning. The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios. This motivates us to create a new traffic simulator CityFlow with fundamentally optimized data structures and efficient algorithms. CityFlow can support flexible definitions for road network and traffic flow based on synthetic and real-world data. It also provides user-friendly interface for reinforcement learning. Most importantly, CityFlow is more than twenty times faster than SUMO and is capable of supporting city-wide traffic simulation with an interactive render for monitoring. Besides traffic signal control, CityFlow could serve as the base for other transportation studies and can create new possibilities to test machine learning methods in the intelligent transportation domain.
Fully Integrated On-FPGA Molecular Dynamics Simulations

The implementation of Molecular Dynamics (MD) on FPGAs has received substantial attention. Previous work, however, has consisted of either proof-of-concept implementations of components, usually the range-limited force; full systems, but with much of the work shared by the host CPU; or prototype demonstrations, e.g., using OpenCL, that neither implement a whole system nor have competitive performance. In this paper, we present what we believe to be the first full-scale FPGA-based simulation engine, and show that its performance is competitive with a GPU (running Amber in an industrial production environment). The system features on-chip particle data storage and management, short- and long-range force evaluation, as well as bonded forces, motion update, and particle migration. Other contributions of this work include exploring numerous architectural trade-offs and analysis on various mappings schemes among particles/cells and the various on-chip compute units. The potential impact is that this system promises to be the basis for long timescale Molecular Dynamics with a commodity cluster.
Members of the Lactobacillus Genus Complex (LGC) as Opportunistic Pathogens: A Review

Microorganisms belonging to the Lactobacillus genus complex (LGC) are naturally associated or deliberately added to fermented food products and are widely used as probiotic food supplements. Moreover, these bacteria normally colonize the mouth, gastrointestinal (GI) tract, and female genitourinary tract of humans. They exert multiple beneficial effects and are regarded as safe microorganisms. However, infections caused by lactobacilli, mainly endocarditis, bacteremia, and pleuropneumonia, occasionally occur. The relevance of Lactobacillus spp. and other members of the LGC as opportunistic pathogens in humans and related risk factors and predisposing conditions are illustrated in this review article with more emphasis on the species L. rhamnosus that has been more often involved in infection cases. The methods used to identify this species in clinical samples, to distinguish strains and to evaluate traits that can be associated to pathogenicity, as well as future perspectives for improving the identification of potentially pathogenic strains, are outlined.
Male urethral stricture disease in a regional centre: 10 years of experience

Male urethral stricture disease is a challenging condition with a propensity for recurrence following endoscopic management. In recent years, earlier definitive urethral reconstruction has been advocated through international guidelines, prompted by series suggesting the underutilization of urethroplasty at rates of 0.6–0.8%. However, little local data exists to characterize our urethral stricture patients and we aimed to characterize the management of patients with urethral stricture disease presenting over a 10‐year period to a single regional centre.
Cognitive Graph for Multi-Hop Reading Comprehension at Scale

We propose a new CogQA framework for multi-hop reading comprehension question answering in web-scale documents. Founded on the dual process theory in cognitive science, the framework gradually builds a cognitive graph in an iterative process by coordinating an implicit extraction module (System 1) and an explicit reasoning module (System 2). While giving accurate answers, our framework further provides explainable reasoning paths. Specifically, our implementation based on BERT and graph neural network efficiently handles millions of documents for multi-hop reasoning questions in the HotpotQA fullwiki dataset, achieving a winning joint F_1 score of 34.9 on the leaderboard, compared to 23.1 of the best competitor.
Learning Generative Models across Incomparable Spaces

Generative Adversarial Networks have shown remarkable success in learning a distribution that faithfully recovers a reference distribution in its entirety. However, in some cases, we may want to only learn some aspects (e.g., cluster or manifold structure), while modifying others (e.g., style, orientation or dimension). In this work, we propose an approach to learn generative models across such incomparable spaces, and demonstrate how to steer the learned distribution towards target properties. A key component of our model is the Gromov-Wasserstein distance, a notion of discrepancy that compares distributions relationally rather than absolutely. While this framework subsumes current generative models in identically reproducing distributions, its inherent flexibility allows application to tasks in manifold learning, relational learning and cross-domain learning.
Online Computation with Untrusted Advice

The advice model of online computation captures a setting in which the algorithm is given some partial information concerning the request sequence. This paradigm allows to establish tradeoffs between the amount of this additional information and the performance of the online algorithm. However, if the advice is corrupt or, worse, if it comes from a malicious source, the algorithm may perform poorly. In this work, we study online computation in a setting in which the advice is provided by an untrusted source. Our objective is to quantify the impact of untrusted advice so as to design and analyze online algorithms that are robust and perform well even when the advice is generated in a malicious, adversarial manner. To this end, we focus on well-studied online problems such as ski rental, online bidding, bin packing, and list update. For ski-rental and online bidding, we show how to obtain algorithms that are Pareto-optimal with respect to the competitive ratios achieved; this improves upon the framework of Purohit et al. [NeurIPS 2018] in which Pareto-optimality is not necessarily guaranteed. For bin packing and list update, we give online algorithms with worst-case tradeoffs in their competitiveness, depending on whether the advice is trusted or not; this is motivated by work of Lykouris and Vassilvitskii [ICML 2018] on the paging problem, but in which the competitiveness depends on the reliability of the advice. Furthermore, we demonstrate how to prove lower bounds, within this model, on the tradeoff between the number of advice bits and the competitiveness of any online algorithm. Last, we study the effect of randomization: here we show that for ski-rental there is a randomized algorithm that Pareto-dominates any deterministic algorithm with advice of any size. We also show that a single random bit is not always inferior to a single advice bit, as it happens in the standard model.
Prognostic factors of hepatic resection for hepatocellular carcinoma with cirrhosis: Univariate and multivariate analysis

The objective of this investigation was to study the clinicopathological factors influencing long‐term outcome of hepatocellular carcinoma (HCC) with liver cirrhosis in patients undergoing hepatectomy. Liver cirrhosis, especially the macronodular variety, has been found in up to 90% of patients with HCC. In Asia, the incidence of liver cirrhosis in patients with HCC who had undergone hepatic resection varies from 42.5% to 73.8%. However, the optimal surgical approach for HCC patients with cirrhosis is less clearly defined. Resection of the cirrhotic liver is challenging and remains controversial in the treatment of HCC.
Deep Neural Networks for Marine Debris Detection in Sonar Images

Garbage and waste disposal is one of the biggest challenges currently faced by mankind. Proper waste disposal and recycling is a must in any sustainable community, and in many coastal areas there is significant water pollution in the form of floating or submerged garbage. This is called marine debris. Submerged marine debris threatens marine life, and for shallow coastal areas, it can also threaten fishing vessels [Iniguez et al. 2016, Renewable and Sustainable Energy Reviews]. Submerged marine debris typically stays in the environment for a long time (20+ years), and consists of materials that can be recycled, such as metals, plastics, glass, etc. Many of these items should not be disposed in water bodies as this has a negative effect in the environment and human health. This thesis performs a comprehensive evaluation on the use of DNNs for the problem of marine debris detection in FLS images, as well as related problems such as image classification, matching, and detection proposals. We do this in a dataset of 2069 FLS images that we captured with an ARIS Explorer 3000 sensor on marine debris objects lying in the floor of a small water tank. The objects we used to produce this dataset contain typical household marine debris and distractor marine objects (tires, hooks, valves, etc), divided in 10 classes plus a background class. Our results show that for the evaluated tasks, DNNs are a superior technique than the corresponding state of the art. There are large gains particularly for the matching and detection proposal tasks. We also study the effect of sample complexity and object size in many tasks, which is valuable information for practitioners. We expect that our results will advance the objective of using Autonomous Underwater Vehicles to automatically survey, detect and collect marine debris from underwater environments.
Design an adaptive electronically beamsteering reflectarray antenna for RFID systems

The main objective of this paper is to design an electronically scanning reflectarray antenna for the RFID system to precisely identify and locate the tags. The RA consists of a novel cell design utilizing a varactor diode to provide the phase shifts required to steer the beam in a certain direction. The cell used in the design is Split Slotted Dipole (SSD) that provide minimum re-radiation loss and sufficient phase range and phase slope. The achievable phase range is 300° over the frequency range from 4.8 GHz to 5.9 GHz. Finally, we achieved a steerable directive beam with a beamwidth of 16° from -65° to +65° with low Side Lobe Level (SLL) and a considerable high gain from 14 dB to 17 dB over the operating frequency range.
Human Visual Understanding for Cognition and Manipulation - A primer for the roboticist

Robotic research is often built on approaches that are motivated by insights from self-examination of how we interface with the world. However, given current theories about human cognition and sensory processing, it is reasonable to assume that the internal workings of the brain are separate from how we interface with the world and ourselves. To amend some of these misconceptions arising from self-examination this article reviews human visual understanding for cognition and action, specifically manipulation. Our focus is on identifying overarching principles such as the separation into visual processing for action and cognition, hierarchical processing of visual input, and the contextual and anticipatory nature of visual processing for action. We also provide a rudimentary exposition of previous theories about visual understanding that shows how self-examination can lead down the wrong path. Our hope is that the article will provide insights for the robotic researcher that can help them navigate the path of self-examination, give them an overview of current theories about human visual processing, as well as provide a source for further relevant reading.
Limited Resource Optimal Distribution Algorithm Based on Game Iteration Method

The article provides a solution algorithm for the linear programming problem (LPP) with the latter being presented as an antagonistic matrix game so the game's further solution is based on the iterative method. The algorithm is presented as a computer program. Having applied necessary accuracy, the author has researched the solution assessment convergence rate in relation to the actual value. Program implementation demonstrates high rate of the LPP solution receipt, with the acceptable accuracy being fractions or unities. It allows using the algorithm in the integrated systems for the purpose of their optimal control.
Acute Effects of the New Method Sarcoplasma Stimulating Training Versus Traditional Resistance Training on Total Training Volume, Lactate and Muscle Thickness

Background: Trained subjects have difficulty in achieving continued results following years of training, and the manipulation of training variables through advanced resistance training (RT) methods is widely recommended to break through plateaus. Objective: The purpose of the present study was to compare the acute effects of traditional RT (TRT) versus two types of sarcoplasma stimulating training (SST) methods on total training volume (TTV), lactate, and muscle thickness (MT). Methods: Twelve trained males (20.75 ± 2.3 years; 1.76 ± 0.14 meters; body mass = 79.41 ± 4.6 kg; RT experience = 4.1 ± 1.8 years) completed three RT protocols in a randomly sequenced order: TRT, SST contraction type (SST-CT), or SST rest interval variable (SST-RIV) with 7 days between trials in arm curl (elbow flexors) and triceps pulley extension (elbow extensors) performed on the same day. Results: The SST groups displayed greater acute biceps and triceps brachii (TB) MT versus the TRT session, with no difference in lactate levels between them. The SST-CT resulted in greater biceps and TB MT versus the SST-RIV session. The TTV was greater for the TRT session versus the SST sessions, except in the case of the elbow flexors (no difference was observed between TRT and SST-CT), and higher for the SST-CT versus the SST-RIV. Conclusion: Trained subjects may benefit from using the SST method as this method may offer a superior MT stimulus and reduced training time, even with a lower TTV.
CC Chemokine Receptor-2 Is Not Essential for the Development of Antigen-Induced Pulmonary Eosinophilia and Airway Hyperresponsiveness1

Monocyte chemoattractant proteins-1 and -5 have been implicated as important mediators of allergic pulmonary inflammation in murine models of asthma. The only identified receptor for these two chemokines to date is the CCR2. To study the role of CCR2 in a murine model of Ag-induced asthma, we compared the pathologic and physiological responses of CCR2−/− mice with those of wild-type (WT) littermates following immunization and challenge with OVA. OVA-immunized/OVA-challenged (OVA/OVA) WT and CCR2−/− mice developed significant increases in total cells recovered by bronchoalveolar lavage (BAL) compared with their respective OVA-immunized/PBS-challenged (OVA/PBS) control groups. There were no significant differences in BAL cell counts and differentials (i.e., macrophages, PMNs, lymphocytes, and eosinophils) between OVA/OVA WT and CCR2−/− mice. Serologic evaluation revealed no significant difference in total IgE and OVA-specific IgE between OVA/OVA WT mice and CCR2−/− mice. Lung mRNA expression and BAL cytokine protein levels of IL-4, IL-5, and IFN-γ were also similar in WT and CCR2−/− mice. Finally, OVA/OVA CCR2−/− mice developed increased airway hyper-responsiveness to a degree similar to that in WT mice. We conclude that following repeated airway challenges with Ag in sensitized mice, the development of Th2 responses (elevated IgE, pulmonary eosinophilia, and lung cytokine levels of IL-4 and IL5) and the development of airway hyper-responsiveness are not diminished by a deficiency in CCR2.
Learnable Triangulation of Human Pose

We present two novel solutions for multi-view 3D human pose estimation based on new learnable triangulation methods that combine 3D information from multiple 2D views. The first (baseline) solution is a basic differentiable algebraic triangulation with an addition of confidence weights estimated from the input images. The second, more complex, solution is based on volumetric aggregation of 2D feature maps from the 2D backbone followed by refinement via 3D convolutions that produce final 3D joint heatmaps. Crucially, both of the approaches are end-to-end differentiable, which allows us to directly optimize the target metric. We demonstrate transferability of the solutions across datasets and considerably improve the multi-view state of the art on the Human3.6M dataset.
The future of cell-free DNA testing to guide therapeutic decisions in B-cell lymphomas.

PURPOSE OF REVIEW Tissue biopsy is the current gold standard technique for diagnosis and molecular profiling of lymphomas, but it carries several disadvantages in terms of procedural risks (infectious and haemorrhagic complications, anaesthesiologic risks) and analytic aspects (heterogeneity of tumors, low representation of tumor cells in the tissue). Noninvasive genotyping of B-cell lymphomas through circulating tumor DNA (ctDNA) is emerging as a practical tool to monitor the genetics and course of the disease from diagnosis to eventual relapse.This review will explore recent advances in the field of liquid biopsy in lymphomas, highlighting their clinical implications. RECENT FINDINGS ctDNA has been recently proposed an alternative source of tumor DNA for genotyping purposes, especially for those samples having low tumor representation or when longitudinal genetic monitoring is limited by the inaccessibility of relapsed tumor tissues. Also, ctDNA has been recently proposed radiation-free tool for the early identification of chemorefractory lymphoma patients. SUMMARY The detection of ctDNA circulating in the bloodstream of lymphoma patients can inform about the genetics of the disease at diagnosis identifying druggable alterations, detect the onset of mutation of resistance during treatment, anticipate about relapse earlier than standard methods [e.g. PET associated with computed tomography (PET/CT)] during follow-up.
Assessment of head injury risk associated with feet-first free falls in 12-month-old children using an anthropomorphic test device.

BACKGROUND Short distance falls are a common false history provided in cases of child abuse. Falls are also a common occurrence in ambulating young children. The purpose of this study was to determine the risk of head injury in short distance feet-first free falls for a 12-month-old child. METHODS Feet-first free falls were simulated using an anthropomorphic test device. Three fall heights and five surfaces were tested to determine whether changing fall environment characteristics leads to differences in head injury risk outcomes. Linear head accelerations were measured and angular head accelerations in the anterior-posterior direction were determined. Head injury criteria values and impact durations were also determined for each fall. RESULTS The mean peak linear head acceleration across all trials was 52.2g. HIC15 values were all below the injury assessment reference value. The mean peak angular head acceleration across all trials was 4,246 rad/s2. Impact durations ranged from 12.1 milliseconds to 27.8 milliseconds. In general, head accelerations were greater and impact durations were lower for surfaces with lower coefficients of restitution (a measure of resiliency). In falls onto wood and linoleum over concrete, the ground-based fall was associated with greater accelerations than the two higher fall heights. CONCLUSIONS Results show that fall dynamics play an important role in head injury outcome measures. Different fall heights and impact surfaces led to differences in head injury risk, but the risk of severe head injury across all tested scenarios was low for a 12-month-old child in feet-first free falls.
Evaluation of the Effect of Heat Exposure on the Autonomic Nervous System by Heart Rate Variability and Urinary Catecholamines

Evaluation of the Effect of Heat Exposure on the Autonomic Nervous System by Heart Rate Variability and Urinary Catecholamines: Shinji Yamamoto, et al. Department of Hygiene, Yamaguchi University Graduate School of Medicine—The aim of this study was to investigate the usefulness of heart rate variability (HRV) and urinary catecholamines (CA) as objective indices of heat stress effect. We examined physiological responses, subjective symptoms, HRV and urinary CA to evaluate the effect of heat exposure on the autonomic nervous system. Six healthy male students volunteered for this study. They were exposed on different days to either a thermoneutral condition at wet bulb globe temperature (WBGT) 21°C, or a heated condition at WBGT 35°C for 30 min, while seated on a chair. In the thermoneutral condition, differences of all parameters between the values before and after 30 min exposure were not statistically significant. In the heated condition, heart rate, body temperature and scores for subjective symptoms (feverishness, sweating, mood, and face flushing) significantly increased after 30 min exposure (p<0.05). Also, the high frequency component (HF%) of HRV significantly decreased and the low frequency/high frequency (LF/ HF) ratio of HRV significantly increased after 30 min exposure to the heated condition (p<0.05). There were no significant differences between the amounts of urinary CA before and after the 30 min exposures; however, the norepinephrine amount after 30 min exposure to the heated condition was significantly greater than that of the thermoneutral condition (p<0.05). The heat exposure (WBGT 35°C) induced activation of the sympathetic nervous system and a withdrawal of the parasympathetic nervous system. These findings coincide with observed changes of heart rate, body temperature and subjective symptoms. It is suggested that HRV (HF% and LF/HF ratio) and urinary norepinephrine may be useful objective indices of heat stress; HRV seems to be more sensitive to heat stress than urinary CA.