Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposal for a Method of Extracting Road Layers from Remote Sensing Images Using Conditional GANs

With the recent advances in unmanned aerial vehicle (UAV) technology, remote sensing images have become relatively easy to obtain and their accuracy has increased enough to be able to handle land information. Therefore, there is a growing demand to utilize remote sensing images for extracting semantic objects Conventional methods are mainly focused on pixel-based classification and recently people commonly use convolutional neural networks, which post processing is required to linearize roads that are cut off and accurately shape the contours of buildings. We propose the use of a generative model to carry out this post processing in the networks. Using conditional Generative Adversarial Network (GANs), we translate remote sensing images into map-based images from which roads are easily extracted, while retaining the underlying structure. Next, we extract road layers from the generated images. Through this approach, it is possible to achieve the same effect as if complicating post processing were done in the networks during the object extraction process.
Comparison of Techniques for Tracking Body Composition Changes across a Season in College Women Basketball Players

Body composition assessment has become an integral part of athletes’ training schedules. Questions remain concerning the accuracy of various methods to track body composition changes over a competitive year cycle. The purpose of this study was to compare various methods of tracking body composition across a college women’s basketball season. Fourteen Division II women (age = 20.1 ± 1.2 y) were measured prior to the season (T1), after pre-season conditioning (T2), at mid-season (T3), and at the end of the season (T4) using skinfolds (SKF), two bioelectric impedance analysis (BIA) devices, and dual-energy x-ray absorptiometry (DXA). BIA devices were hand-to-hand (H-BIA) and foot-to-foot (F-BIA) single-frequency models. SKF were used to estimate %fat using four prediction equations. A method × trial factorial ANOVA on %fat with repeated measures over the second factor indicated that all methods except the Durnin-Womersley SKF equation were significantly lower than DXA. Across trials, DXA %fat at T1 (25.3 ± 4.7%) was significantly higher than at T2 (24.3 ± 4.6%), T3 (24.6 ± 4.6%), and T4 (24.4 ± 5.1%). Agreement between DXA and the other methods were moderate (r = 0.48 – 0.86). Rank-order correlations of DXA with the other methods to compare team order indicated H-BIA (rho = 0.67 – 0.78) and F-BIA (rho = 0.62 – 0.77) provided comparable agreement, with SKF methods having lower agreement for team order (rho = 0.46 – 0.73). Compared to the DXA standard, a foot-to-foot BIA device may provide adequate but significantly lower relative tracking of %fat across a women’s basketball season.
An Advising Framework for Multiagent Reinforcement Learning Systems

Reinforcement Learning has long been employed to solve sequential decision-making problems with minimal input data. However, the classical approach requires a long time to learn a suitable policy, especially in Multiagent Systems. The teacher-student framework proposes to mitigate this problem by integrating an advising procedure in the learning process, in which an experienced agent (human or not) can advise a student to guide her exploration. However, the teacher is assumed to be an expert in the learning task. We here propose an advising framework where multiple agents advise each other while learning in a shared environment, and the advisor is not expected to necessarily act optimally. Our experiments in a simulated Robot Soccer environment show that the learning process is improved by incorporating this kind of advice.
Shape improvement of traffic pedestrian hypotheses by means of stereo-vision and superpixels

Shape is a powerful descriptor frequently used in pedestrian detection process. This paper presents a novel stereo and superpixel-based approach for extracting high quality shapes of pedestrian hypotheses from urban traffic scenarios. Gray-levels stereo-vision images of traffic scenes are acquired, high quality stereo-reconstruction and optical flow algorithms are used for computing the depth and motion information. Superpixels are extracted using the intensity images and clustered in different obstacles by a novel paradigm that fuses intensity, depth and motion information. Pedestrian hypotheses are defined as a subset of the scene obstacles obtained by imposing human-specific geometric constraints. A contour tracing algorithm is used for extracting a continuous contour that defines the shape of each pedestrian hypothesis. A comparison between the contours quality of pedestrian hypotheses obtained by this stereo and superpixel approach and another approach based only on stereo-reconstructed points grouping shows improvements in both object shape description and area coverage. Improvements in shape description will increase the accuracy of any further pedestrian detection processes that use pattern matching techniques.
Chinese perspectives on primary care for common mental disorders: Barriers and policy implications

Background: The World Health Organization (WHO) has called for integration of mental health into primary care for a decade. In Western countries, around 15% to 25% of patients with common mental disorders including mood and anxiety disorders seek help from primary care physicians (PCPs). The rate is only about 5% in China. Aims: This article reviews the Chinese findings on the barriers to primary care for common mental disorders and how they compared with Western findings. Methods: A narrative literature review was conducted, focusing on literature published from mid-1990s in English or Chinese. Patient, PCP and health system factors were reviewed. Results: Although Chinese and Western findings show similar themes of barriers, the Chinese have stronger barriers in most aspects, including under-recognition of the need for treatment, stigma on mental illness, somatization, worries about taking psychiatric drugs, uncertainties in the role, competency and legitimacy of PCPs in mental health care and short consultation time. Conclusion: Current policies in China emphasize enhancement of mental health facilities and workforce in the community. Our review suggests that patients’ intention to seek help and PCPs’ competency in mental health care are other fundamental factors to be addressed.
DECK: Discovering Event Composition Knowledge from Web Images for Zero-Shot Event Detection and Recounting in Videos

We address the problem of zero-shot event recognition in consumer videos. An event usually consists of multiple human-human and human-object interactions over a relative long period of time. A common approach proceeds by representing videos with banks of object and action concepts, but requires additional user inputs to specify the desired concepts per event. In this paper, we provide a fully automatic algorithm to select representative and reliable concepts for event queries. This is achieved by discovering event composition knowledge (DECK) from web images. To evaluate our proposed method, we use the standard zero-shot event detection protocol (ZeroMED), but also introduce a novel zero-shot event recounting (ZeroMER) problem to select supporting evidence of the events. Our ZeroMER formulation aims to select video snippets that are relevant and diverse. Evaluation on the challenging TRECVID MED dataset show that our proposed method achieves promising results on both tasks.
Versatile organoaluminium catalysts based on heteroscorpionate ligands for the preparation of polyesters.

A series of alkyl aluminium complexes based on heteroscorpionate ligands were designed as catalysts for the ring-opening polymerisation of cyclic esters and ring-opening copolymerisation of epoxides and anhydrides. Treatment of AlX3 (X = Me, Et) with ligands bpzbeH [bpzbe = 1,1-bis(3,5-dimethylpyrazol-1-yl)-3,3-dimethyl-2-butoxide], bpzteH [bpzte = 2,2-bis(3,5-dimethylpyrazol-1-yl)-1-para-tolylethoxide], and (R,R)-bpzmmH [(R,R)-bpzmm = (1R)-1-{(1R)-6,6-dimethyl-bicyclo[3.1. 1]-2-hepten-2-yl}-2,2-bis(3,5-dimethylpyrazol-1-yl)ethoxide] for 2 hours at 0 °C afforded the mononuclear dialkyl aluminium complexes [AlMe2{κ2-bpzbe}] (1), [AlEt2{κ2-bpzbe}] (2), [AlMe2{κ2-(R,R)-bpzmm}] (3) and [AlEt2{κ2-(R,R)-bpzmm}] (4), and the dinuclear dialkyl complexes [AlMe2{κ2-bpzte}]2 (5) and [AlEt2{κ2-bpzte}]2 (6). The molecular structures of the new complexes were determined by spectroscopic methods and confirmed by X-ray crystallography. The alkyl-containing aluminium complexes can act as highly efficient single-component initiators for the ring-opening polymerisation of ε-caprolactone and l-lactide and for the ring-opening copolymerisation of cyclohexene oxide and phthalic anhydride to give a range of biodegradable polyesters.
The effect of lifelong exercise frequency on arterial stiffness

This study examined the effect of different ‘doses’ of lifelong (>25 years) exercise on arterial stiffening (a hallmark of vascular ageing) in older adults. There are clear dose‐dependent effects of lifelong exercise training on human arterial stiffness that vary according to the site and size of the arteries. Similar to what we have observed previously with ventricular stiffening, 4–5 days week−1 of committed exercise over a lifetime are necessary to preserve ‘youthful’ vascular compliance, especially of the large central arteries. Casual exercise training of two to three times per week may be sufficient for middle‐sized arteries like the carotid to minimize arterial stiffening with ageing. However, there is little effect of exercise training on the small‐sized peripheral arteries at any dose.
Reframing Assistive Robots to Promote Successful Aging

We are living in an exciting time, as people are living longer, more active lives. This is reshaping how we think about aging. Rather than viewing aging as a problem to be fixed (i.e., a deficit model of aging), many aging researchers are viewing aging as a developmental stage of life to be celebrated and supported, that is, “successful aging. ” In this article, we embrace this approach and consider it in the context of assistive robot design in an aim to steer the conversation away from deficit models that have limited robot design possibilities. To explore an alternative design approach to the study of aging in human-robot interaction (HRI), we invited five aging researchers (three geriatricians, one gerontologist, and one epidemiologist) and nine older adults to participate in our research. In the study, participants illustrated their interpretations of aging and suggested potential assistive robots. We found that while all participants perceived the importance of potential disabilities due to aging, they considered potential disabilities as only one aspect of the experience of aging. They highlighted other key themes to consider in designing robots to support successful aging, such as older adults’ autonomy and resilience. We discuss these findings for the HRI community and call for “robots for successful aging. ”
Can machine learning identify interesting mathematics? An exploration using empirically observed laws

We explore the possibility of using machine learning to identify interesting mathematical structures by using certain quantities that serve as fingerprints. In particular, we extract features from integer sequences using two empirical laws: Benford's law and Taylor's law and experiment with various classifiers to identify whether a sequence is, for example, nice, important, multiplicative, easy to compute or related to primes or palindromes.
Systematic identification of factors mediating accelerated mRNA degradation in response to changes in environmental nitrogen

Cellular responses to changing environments frequently involve rapid reprogramming of the transcriptome. Regulated changes in mRNA degradation rates can accelerate reprogramming by clearing or stabilizing extant transcripts. Here, we measured mRNA stability using 4-thiouracil labeling in the budding yeast Saccharomyces cerevisiae during a nitrogen upshift and found that 78 mRNAs are subject to destabilization. These transcripts include Nitrogen Catabolite Repression (NCR) and carbon metabolism mRNAs, suggesting that mRNA destabilization is a mechanism for targeted reprogramming of the transcriptome. To explore the molecular basis of destabilization we implemented a SortSeq approach to screen the pooled deletion collection library for trans factors that mediate rapid GAP1 mRNA repression. We combined low-input multiplexed Barcode sequencing with branched-DNA single-molecule mRNA FISH and Fluorescence-activated cell sorting (BFF) to identify the Lsm1-7p/Pat1p complex and general mRNA decay machinery as important for GAP1 mRNA clearance. We also find that the decapping modulators EDC3 and SCD6, translation factor eIF4G2, and the 5’ UTR of GAP1 are factors that mediate rapid repression of GAP1 mRNA, suggesting that translational control may impact the post-transcriptional fate of mRNAs in response to environmental changes.
Correlated time‐variation of bulk microstructure and rheology in asphalt binders

We use near‐infrared dark‐field optical microscopy to probe isothermal time variation of the volume fraction of naturally‐occurring, subsurface microstructures in PG 64‐22 asphalt binders at temperature T=30∘C , following a rapid heating (cooling) increment |ΔT|=20∘C from initial temperature T0=10∘C(50∘C) . We compare these microstructure variations with isothermal time variations of the magnitude |G30∗(t)| of the bulk complex shear modulus measured for identical sample conditions with a Dynamic Shear Rheometer. The main findings are: (1) Microstructure volume fraction (inferred from intensity I(t) of near‐infrared optical scatter) and |G∗(t)| both continue to change appreciably long after measurable changes of binder temperature cease. Moreover, delayed time variations in I(t) and |G∗(t)| (2) correlate closely with each other; (3) evolve on three distinct time scales – several minutes, ∼1 h, >1 day; (4) depend on binder aging; (5) are more pronounced after a cooling step ( ΔT=−20∘C ) than after a heating step ( ΔT=+20∘C ); and (6) account for hysteresis in I(t) and |G∗(t)| curves observed during heating–cooling cycles.
Acute Cardiovascular Responses after a Single Bout of Blood Flow Restriction Training

Different types of exercise might produce reductions in blood pressure (BP). One physiological mechanism that could explain the lowering adaptation effect on BP after an exercise program is an improved in baroreflex control of muscle sympathetic nerve activity. Consequently, exploring the different methods of training and their post-exercise hypotension (PEH) becomes of interest for healthcare providers. Recently, it has been suggested that blood flow restriction training (BFR) can generate PEH. The aim of this study was to determine the acute response on cardiovascular variables after low intensity resistance training with BFR in normotensive subjects. Twenty-four male (24.38±3.88 years) performed four sets of plantar flexion at 30% 1RM (1×30 + 3×15 repetitions) with 30% of maximal occlusion pressure and 60 seconds resting period. The restrictive pressure was released during the intervals between sets. BP, heart rate (HR), blood oxygen saturation (SpO2) and double product (DP) were measured in baseline, after each set of exercise and 15, 30, 45, 60 minutes and 24 hours after exercise. An immediate significant increase across the set was observed for HR values (11.5%) (p<0.05) during application the protocol. SBP and DBP values also increased during exercise although mildly (1.7% and 1%, respectively) without significant differences compared with pre-values. A post-exercise hypotension was obtained 15min post-training (SBP: −6.9%; DBP: −3%). There was no significant change in SpO2 and DP during and post-exercise with BFR. Cardiovascular responses were altered mildly during BFR-training and after the single bout. In conclusion, BFR in young normotensive humans generated post-exercise hypotension.
Jatrorrhizine Hydrochloride Suppresses Proliferation, Migration, and Secretion of Synoviocytes In Vitro and Ameliorates Rat Models of Rheumatoid Arthritis In Vivo

Jatrorrhizine hydrochloride (JH), an active component isolated from the traditional Chinese herb Coptis chinensis, has been reported to have antimicrobial, antitumor, antihypercholesterolemic, and neuroprotective activities. However, its antirheumatoid arthritis (RA) property remains unknown. In this study, a collagen-induced arthritis (CIA) rat model was used to evaluate the therapeutic effects of JH on RA by using arthritis score, radiological evaluation, and histopathological assessment. The in vitro effects of JH on proliferation, migration, and production of inflammatory mediators in RA-derived fibroblast-like synoviocyte MH7A cells were determined by the EdU incorporation assay, wound healing assay, real-time PCR, and ELISA, respectively. The in vivo studies showed that JH treatment significantly prevented the progression and development of RA in CIA rats through anti-inflammation and suppressing bone destruction. The in vitro studies revealed that JH could effectively attenuate the destructive phenotypes of MH7A cells, including inhibiting proliferation, migration, and production of inflammatory mediators. Further mechanistic analysis demonstrated that JH suppressed tumor necrosis factor alpha (TNFα)-stimulated activations of nuclear factor of kappaB (NF-κB) and mitogen-activated protein kinases (MAPKs) (ERK and p38) leading to the downregulation of proinflammatory cytokines, which might be beneficial to the antiproliferative and antimigratory activities of FLS cells. Collectively, our results demonstrated that JH has a great potential to be developed into a novel therapeutic agent for treating RA.
XPG rs17655 G>C polymorphism associated with cancer risk: evidence from 60 studies

Xeroderma pigmentosum group G (XPG), a key component in nucleotide excision repair pathway, functions to cut DNA lesions during DNA repair. Genetic variations that alter DNA repair gene expression or function may decrease DNA repair ability and impair genome integrity, thereby predisposing to cancer. The association between XPG rs17655 G>C polymorphism and cancer risk has been investigated extensively, but the results remain contradictory. To get a more accurate conclusion, we performed a comprehensive meta-analysis of 60 case-control studies, involving 27,098 cancer cases and 30,535 healthy controls. Crude odds ratios (ORs) and 95% confidence interval (CIs) were calculated to determine the association of interest. Pooled analysis indicated that the XPG rs17655 G>C polymorphism increased the risk of overall cancer (CC vs. GG: OR=1.10, 95% CI=1.00-1.20; CG vs. GG: OR=1.06, 95% CI=1.02-1.11; CG+CC vs. GG: OR=1.07, 95% CI=1.02-1.12; C vs. G: OR=1.05, 95% CI=1.01-1.09). Stratification analysis by cancer type further showed that this polymorphism was associated with increased risk of gastric cancer and colorectal cancer. This meta-analysis indicated that the XPG gene rs17655 G>C polymorphism was associated with increased overall cancer risk, especially the risk of gastric cancer and colorectal cancer. Further validation experiments are needed to strength our conclusion.
Unsupervised Learning of Multi-Level Descriptors for Person Re-Identification

In this paper, we propose a novel coding method named weighted linear coding (WLC) to learn multi-level (e.g., pixel-level, patch-level and image-level) descriptors from raw pixel data in an unsupervised manner. It guarantees the property of saliency with a similarity constraint. The resulting multi-level descriptors have a good balance between the robustness and distinctiveness. Based on WLC, all data from the same region can be jointly encoded. Consequently, when we extract the holistic image features, it is able to preserve the spatial consistency. Furthermore, we apply PCA to these features and compact person representations are then achieved. During the stage of matching persons, we exploit the complementary information resided in multi-level descriptors via a score-level fusion strategy. Experiments on the challenging person re-identification datasets - VIPeR and CUHK 01, demonstrate the effectiveness of our method.
Category coding with neural network application

In many applications of neural network, it is common to introduce huge amounts of input categorical features, as well as output labels. However, since the required network size should have rapid growth with respect to the dimensions of input and output space, there exists huge cost in both computation and memory resources. In this paper, we present a novel method called category coding (CC), where the design philosophy follows the principle of minimal collision to reduce the input and output dimension effectively. In addition, we introduce three types of category coding based on different Euclidean domains. Experimental results show that all three proposed methods outperform the existing state-of-the-art coding methods, such as standard cut-off and error-correct output coding (ECOC) methods.
Ion-beam-induced bending of semiconductor nanowires

The miniaturisation of technology increasingly requires the development of both new structures as well as novel techniques for their manufacture and modification. Semiconductor nanowires (NWs) are a prime example of this and as such have been the subject of intense scientific research for applications ranging from microelectronics to nano-electromechanical devices. Ion irradiation has long been a key processing step for semiconductors and the natural extension of this technique to the modification of semiconductor NWs has led to the discovery of ion beam-induced deformation effects. In this work, transmission electron microscopy with in situ ion bombardment has been used to directly observe the evolution of individual silicon and germanium NWs under irradiation. Silicon NWs were irradiated with either 6 keV neon ions or xenon ions at 5, 7 or 9.5 keV with a flux of 3 × 1013 ions cm−2 s−1. Germanium NWs were irradiated with 30 or 70 keV xenon ions with a flux of 1013 ions cm−2 s−1. These new results are combined with those reported in the literature in a systematic analysis using a custom implementation of the transport of ions in matter Monte Carlo computer code to facilitate a direct comparison with experimental results taking into account the wide range of experimental conditions. Across the various studies this has revealed underlying trends and forms the basis of a critical review of the various mechanisms which have been proposed to explain the deformation of semiconductor NWs under ion irradiation.
Molecular Investigation of an Anthrax Epidemic in Guizhou Province, China

To the Editor: Anthrax is a zoonosis to which most mammals, especially herbivores, are considered susceptible. [1] Humans almost invariably contract anthrax from handling infected animals, from carcasses of animals that have died from the disease, or from the meat, skin, hair, bones, etc., of such animals. [1,2] Guizhou Province is a historical epicenter of anthrax in the southwest of China. [3] In June 2013, an epidemic suspected to be anthrax consisting of five human cases occurred in Wengan County. The clinical symptoms included erythema, papules, and vesicles on the skin of the hands and forearm, accompanied by tissue swelling, infiltration, central cutaneous necrosis, and ulcerative scabs, which are consistent with the Diagnostic Criteria for Anthrax (WS 283‐2008). Five strains suspected to be Bacillus anthracis were collected from one of the five patients as well as from soil samples from this epidemic. To provide an etiologic basis for the diagnosis of patients and epidemics and to enhance our understanding of the genetic characteristics of B. anthracis in Guizhou Province, a retrospective molecular epidemiological investigation was carried out on the five isolates collected in this epidemic.