Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable Structural Networks at the Active Site of the SARS-CoV and SARS-CoV2 Main Proteases

The novel coronavirus SARS-CoV2 (CoV2) emerged in December 2019. This virus has 88% genomic similarity with SARS-CoV (CoV), and both viruses largely depend on their main protease (Mpro) to regulate infection. Mpro thus represents an attractive target for anti-SARS drug design. The CoV and CoV2 Mpro are 97% identical at the sequence level, with 12 variable residues, and their X-ray structures appear similar. We thus structurally analysed how these variable residues affect the intra-molecular interactions between key residues in the CoV2 Mpro active-site. Compared to CoV Mpro, the 12 divergent residues in CoV2 Mpro exhibit modified intra-molecular interaction networks that ultimately restructure the molecular micro-environment. These altered networks also indirectly affect the networks of other active-site residues at the entrance (T26, M49 and Q192) and near the catalytic region (F140, H163, H164, M165 and H172) of the Mpro. This suggest CoV2 indirectly (via neighbours) reshape key molecular networks around the Mpro active-site. It seems that the CoV2 Mpro deceives us with its apparent structurally identical to the CoV Mpro while this viral system accumulates mass mutations (12 variable residues) at key positions. Some of these identified CoV2 Mpro networks at the active-site might guide design of efficient CoV2 Mpro inhibitors.
Is dynamic contrast enhancement still necessary in multiparametric magnetic resonance for diagnosis of prostate cancer: a systematic review and meta-analysis

Background The purpose of this study is to systematically review the literatures assessing the value of dynamic contrast enhancement (DCE) in the multiparametric magnetic resonance imaging (mpMRI) for the diagnosis of prostate cancer (PCa). Methods We searched Embase, PubMed and Web of science until January 2019 to extract articles exploring the possibilities whether the pre-biopsy biparametric magnetic resonance imaging (bpMRI) can replace the position of mpMRI in the diagnosis of PCa. The sensitivity and specificity of bpMRI were all included. The study quality was assessed by QUADAS-2. Bivariate random effects meta-analyses and a hierarchical summary receiver operating characteristic plot were performed for further study through Revman 5 and Stata12. Results After searching, we acquired 752 articles among which 45 studies with 5,217 participants were eligible for inclusion. The positive likelihood ratio for the detection of PCa was 2.40 (95% CI: 1.50–3.80) and the negative likelihood ratio was 0.31 (95% CI: 0.18–0.53). The sensitivity and specificity were 0.77 (95% CI: 0.73–0.81) and 0.81 (95% CI: 0.76–0.85) respectively. Based on our result, pooled specificity demonstrated little difference between bpMRI and mpMRI [bpMRI, 0.81 (95% CI, 0.76–0.85); mpMRI, 0.82 (95% CI, 0.72–0.88); P=0.169]. The sensitivity, however, indicated a significant difference between these two groups [bpMRI, 0.77 (95% CI, 0.73–0.81); mpMRI, 0.84 (95% CI, 0.78–0.89); P=0.001]. Conclusions bpMRI with high b-value is a sensitive tool for diagnosing PCa. Consistent results were found in multiple subgroup analysis.
Current Status of ‘Sanghuang’ as a Group of Medicinal Mushrooms and Their Perspective in Industry Development

ABSTRACT ‘Sanghuang’ is one of the most important groups of medicinal macrofungi and has been used in traditional Chinese medicine for the past two centuries. However, knowledge about ‘Sanghuang’ is distributed in journals of different disciplines, which has meant it is not well known. To facilitate the benefit of ‘Sanghuang’ to human health, here we summarize its current status as a group of medicinal macrofungi. ‘Sanghuang’ consists of all members of the genus Sanghuangporus, which now accommodates 14 described species distributed around the world. The powders or chips of basidiocarps as supplements are the main method of consumption. In the case that wild basidiocarps of ‘Sanghuang’ are not sufficient, cultivation is supposed to provide a solution to promote the long-term utilization of ‘Sanghuang’ basidiocarps. ‘Sanghuang’ mainly possesses antitumor, antioxidant, anti-inflammatory, immunomodulatory, antidiabetic, hepatoprotective, and other medicinal properties. Polysaccharides, polyphenols, pyrones, and terpenes are the main metabolites responsible for these medicinal functions. Finally, four directions are proposed to improve the sustainable utilization of ‘Sanghuang’ resources, viz. accurate identification and standard deposition, documentation of species diversity, multi-omics analyses, and a cover-all database. Hopefully, this review will draw more attention to the utilization of ‘Sanghuang’ as medicinal mushrooms in a large scale of industry.
The Isolated Choice Effect and Its Implications for Gender Diversity in Organizations

We highlight a feature of personnel selection decisions that can influence the gender diversity of groups and teams. Specifically, we show that people are less likely to choose candidates whose gender would increase group diversity when making personnel selections in isolation (i.e., when they are responsible for selecting a single group member) than when making collections of choices (i.e., when they are responsible for selecting multiple group members). We call this the isolated choice effect. Across six preregistered experiments (n = 3,509), we demonstrate that the isolated choice effect has important consequences for group diversity. When making sets of hiring and selection decisions (as opposed to making a single hire), people construct more gender-diverse groups. Mediation and moderation studies suggest that people do not attend as much to diversity when making isolated selection choices, which drives this effect. This paper was accepted by Yuval Rottenstreich, decision analysis.
Inductive Power Transmission for Wearable Textile Heater using Series-None Topology

In this paper, an inductive-power-transmission (IPT) system for a wearable textile heater is proposed to comfortably provide heating to a user’s body. The conductive thread, which has high electrical resistance, was sewn into a receiver (Rx) coil on clothing to generate high temperature with a low current. The proposed wearable heaters are completely washable thanks to their nonmetallic materials, other than conductive threads in the clothing. We introduced series-none (SN) topology to eliminate a resonant capacitor in the wearable textile heater. A single resonant capacitor in a transmitter (Tx) in SN mode was implemented to resonate both Tx and Rx, resulting in increased power delivered to the load (PDL) while maintaining high-power transfer efficiency (PTE), comparable with conventional series-series (SS) topology. When the supply voltage of the power amplifier was 7 V, while the PTE of the SS and SN modes was 85.2% and 75.8%, respectively, the PDL of the SS and SN modes was 2.74 and 4.6 W, respectively.
Modeling and Experiment Verification of Transmissivity of Low-THz Radar Signal Through Vehicle Infrastructure

This paper is concerned with modelling of the transmissivity of Low-Terahertz waves through automotive bumper and headlight cover material. This work is part of wider comprehensive studies on the potential for the use higher frequency bands for future automotive sensors. Theoretical models for transmissivity prediction are described, the methodology of experimentation is discussed and experimental results are presented. The theoretical models of reflection and transmission of different base materials which are covered by different layers of paint are based on Fresnel theory, and the phenomena caused by the half wavelength thickness of the medium is analyzed mathematically. The experimental verification of the models in this paper have been undertaken at 300 GHz and 670 GHz, using 77 GHz as a reference frequency.
Correlates of Condom use Among Community College Women: The Role of Victimization, Substance Use, and Mental Health Symptoms

ABSTRACT Research is needed to understand intersecting health risks among community college students. Applying a syndemic framework, the present research explored childhood sexual victimization, adolescent sexual victimization, intimate partner violence (IPV), marijuana use, alcohol consumption, and symptoms of depression and post-traumatic stress disorder as additive as well as interactive correlates of women's condom use. Questionnaires were administered to a sample of 212 women between the ages of 18 to 24 attending a community college. A series of logistic regression analyses documented that an increased number of psychosocial risk factors was associated with not using a condom during sexual intercourse. Experiencing both adolescent sexual victimization and lifetime IPV, compared to experiencing one form of victimization, increased the odds of not using a condom. Endorsing both lifetime IPV and past year marijuana use, compared to endorsing only one of these factors, also increased the odds of not using a condom. These findings highlight the importance of targeting intersections between adolescent sexual victimization, IPV, marijuana use, and sexual risk behavior when developing educational programs for community college women.
Steerable High-Gain Dual-Reflector Antenna at X-Band for Solar Orbiter

This article presents the design, optimization, analysis, and test of a dual-axis steerable X-band dual-reflector antenna for Solar Orbiter. The system is a part of the onboard antenna subsystem of the Solar Orbiter probe, a science mission from the European Space Agency (ESA) whose goal is to study the Sun and its heliosphere. From the engineering point of view, it is remarkably the extremely harsh orbit environmental conditions. The presented high-gain antenna must operate within a thermal range from −200 °C to 580 °C. To withstand such constraints, the design of the dual-reflector system is optimized considering the thermal distortions imposed by the environment, yielding the final design whose radio frequency (RF) performances are marginally impacted during the different orbit conditions and phases of the mission. An exhaustive verification campaign is also performed to test the antenna under nearly orbit environment.
Risk-averse flexible policy on ambulance allocation in humanitarian operations under uncertainty

Proactive ambulance management is constructive to improve the response efficiency for emergency medical service (EMS) systems under uncertainty. In this paper, we present a dynamic optimisation model concerning the ambulance dispatching and relocation. We develop a flexible operation policy driven by the interval rolling to match vehicles with calls in batch. We formulate the problem in Markov Decision Process and incorporate queues to minimise the average response and delay time. Considering the curse-of-dimensionality, we provide a simulation-based empirical dynamic programming with the state aggregation and post-decision state to solve the model. To further accelerate the computational efficiency, a greedy heuristic method is introduced to improve the quality of sampling operations. Then, a risk-averse model is developed based on the stochastic dominance strategy to improve operational reliability. We develop an equivalent linear programming to evaluate concave dominating functions. We test the performance by a numerical case and extract managerial insights for practitioners. Our results show that the proposed flexible and risk-averse solution outperforms the classic model on reducing the delay under uncertain calls. And the improvement is more active during peak hours, when real-time needs exceed available ambulances.
Computational simulation of sacral-alar-iliac (S2AI) screw fixation of pelvis and implications for fluoroscopic procedure: A cadaver study

Purpose: To determine an easy and convenient method of sacral-alar-iliac (S2AI) screw fixation and introduce the surgical landmarks for fluoroscopic procedure by analyzing 3-D models of pelvis and virtual implantation in a 3-D model. Materials and Methods: Eighty-two cadavers underwent computed tomography scans and the images imported into Mimics® software to make the 3-D pelvis model. The pedicle screw (Ø 8.5 mm/length 115 mm) was processed into a 3-D model using a 3-D-sensor (Comet5®) at the actual size and virtually placed as the S2AI screw. The ideal screw position was defined as the maximal intraosseous length without cortical perforation along the entire path. The ideal entry point and screw trajectory were verified and assessed to introduce the surgical landmark for fluoroscopic procedure. Results: There was no cortical violation around nerve root canal and greater sciatic notch through the entry point between first and second dorsal sacral foramen. There was no impossible model of S2AI screws. The average screw length was 99.8 mm (range, 59.8–115 mm; standard deviation, 16.1) and just one model had shorter than 65 mm S2AI screw. The factors limiting the intra-iliac screw length were sex (p = 0.000) and the iliac groove around the sacroiliac joint (p = 0.000). A free 360° rotation with magnification revealed that the screw trajectory was consistently directed toward the anteroinferior iliac spine (AIIS) in any plane. Conclusion: The ideal entry point of S2AI screw showed a wide range of tolerance between the first and second dorsal sacral foramen; and thus, there was no need for deep dissection to identify the first dorsal sacral foramen. Considering the tendency to shift the pilot hole laterally and the ideal screw trajectory was consistently directed toward AIIS, the entry point is better to be located with a medial shift.
Offline Model Guard: Secure and Private ML on Mobile Devices

Performing machine learning tasks in mobile applications yields a challenging conflict of interest: highly sensitive client information (e.g., speech data) should remain private while also the intellectual property of service providers (e.g., model parameters) must be protected. Cryptographic techniques offer secure solutions for this, but have an unacceptable overhead and moreover require frequent network interaction.In this work, we design a practically efficient hardware-based solution. Specifically, we build OFFLINE MODEL GUARD (OMG) to enable privacy-preserving machine learning on the predominant mobile computing platform ARM—even in offline scenarios. By leveraging a trusted execution environment for strict hardware-enforced isolation from other system components, OMG guarantees privacy of client data, secrecy of provided models, and integrity of processing algorithms. Our prototype implementation on an ARM HiKey 960 development board performs privacy-preserving keyword recognition using TensorFlow Lite for Microcontrollers in real time.
Pivoted Subgraph Isomorphism: The Optimist, the Pessimist and the Realist

Given query graph Q with pivot node v , Pivoted Subgraph Isomorphism (PSI ) finds all distinct nodes in an input graph G that correspond to v in all matches of Q in G. PSI is a core operation in many applications such as frequent subgraph mining, protein functionality prediction and in-network node similarity. Existing applications implement PSI as an instance of the general subgraph isomorphism algorithm, which is expensive and under-optimized. As a result, these applications perform poorly and do not scale to large graphs. In this paper, we propose SmartPSI; a system to efficiently evaluate PSI queries. We develop two algorithms, called optimistic and pessimistic, each tailored for different instances of the problem. Based on machine learning, SmartPSI builds on-the-fly a classifier to decide which of the two algorithms is appropriate for evaluating each graph node. SmartPSI also implements a machine learning-based optimizer to generate low-cost execution plans. Our experimental evaluation with large-scale real graphs shows that SmartPSI outperforms existing approaches by up to two orders of magnitude and is able to process significantly larger graphs. Moreover, SmartPSI is shown to achieve up to 6 times performance improvement when it replaces standard subgraph isomorphism in the state-of-the-art distributed frequent subgraph mining system.
Seedling assemblages and the alternative successional pathways experienced by Atlantic forest fragments

Background: Habitat loss and fragmentation have been argued to drastically alter the composition of tree assemblages inhabiting small forest fragments but the successional trajectory experienced by such edge-affected habitats remains controversial. Aims: Here we examine whether small fragments (3.4–91.2 ha) support seedling assemblages more similar to those in 10–70-year-old secondary forests than to those in mature forests, in order to infer to what extent fragments move toward early successional systems. Methods: Using 59 0.1-ha plots distributed in a fragmented landscape of Brazilian Atlantic forest, we evaluated species richness and functional and taxonomic composition of seedling assemblages in 20 small forest fragments, 19 stands of secondary forest and 20 stands of mature forests in the interior of an exceptionally large fragment (ca. 3500 ha). Results: Small fragments presented the least species-rich seedling assemblages (17.2 ± 5.7 species), followed by secondary (22.5 ± 5.3), and mature forest (28.4 ± 5.3). Small fragments had seedling assemblages with functional and taxonomic composition more similar to those in secondary than in mature forest. Small fragments had a greater relative richness and abundance of pioneer trees (ca. 40% more), vertebrate-dispersed (6–25%), and those bearing medium-sized seeds (30–70%), while large-seeded species and individuals were reduced (>50% decrement) in comparison to seedling assemblages in mature forest. Conclusions: By comparing seedlings across a wide range of successional habitats we offer evidence that small forest fragments are experiencing an alternative successional pathway towards an early-successional system with reduced plant diversity.
The Influence of Model Structure on Conclusions about the Viability and Harvesting of Serengeti Wildebeest

We investigate how the viability and harvestability predicted by population models are affected by details of model construction. Based on this analysis we discuss some of the pitfalls associated with the use of classical statistical techniques for resolving the uncertainties associated with modeling population dynamics. The management of the Serengeti wildebeest (Connochaetes taurinus) is used as a case study. We fitted a collection of age‐structured and unstructured models to a common set of available data and compared model predictions in terms of wildebeest viability and harvest. Models that depicted demographic processes in strikingly different ways fitted the data equally well. However, upon further analysis it became clear that models that fit the data equally well could nonetheless have very different management implications. In general, model structure had a much larger effect on viability analysis (e.g., time to collapse) than on optimal harvest analysis (e.g., harvest rate that maximizes harvest). Some modeling decisions, such as including age‐dependent fertility rates, did not affect management predictions, but others had a strong effect (e.g., choice of model structure). Because several suitable models of comparable complexity fitted the data equally well, traditional model selection methods based on the parsimony principle were not practical for judging the value of alternative models. Our results stress the need to implement analytical frameworks for population management that explicitly consider the uncertainty about the behavior of natural systems.
Going Local: Do Consent Decrees and Other Forms of Federal Intervention in Municipal Police Departments Reduce Police Killings?

Abstract Despite calls for police reform to address lethal use of force, there has been little empirical evaluation of consent decrees—settlement agreements that address police departments’ use of force policies and practice. This study considers the effect of Department of Justice intervention on law enforcement agencies’ levels of use of force. Data on the number of people killed by police between the years 2000 and 2016 were drawn from Fatal Encounters, a crowd-sourced dataset. These data were combined with information on the date of consent decree implementation to create a department-by-year panel dataset. The findings suggested that while there is little evidence that consent decrees targeting use of force decrease police killings, there was some evidence that other forms of intervention did affect levels of lethal use of force.
GroupTravel: Customizing Travel Packages for Groups

We present GroupTravel, a framework that generates cus-tomized travel packages (TPs) for a group of individuals. GroupTravel implements different consensus functions proposed in group recommendation to reach agreement among members. Given a group whose members provide a travel query, GroupTravel returns k Composite Items (CIs) of Points Of Interest (POIs) that are valid, representative, cohesive and personalized. Validity is achieved by satisfying the query expressed by the group. Representativity ensures good coverage of a city. Cohesiveness reflects geographic proximity of POIs forming a CI. Personalization is achieved by choosing POIs that best match the travel preferences of group members. Additionally, group members can interact with generated TPs to customize them. With extensive synthetic experiments and user studies, we examine the benefit of personalization and the impact of different group consensus on user satisfaction. We also show that providing the ability to interact with TPs and reflecting that in the consensus yields better TPs.
Repairing of Record Linkage: Turning Errors into Insight

Linking records from different data sources, referred to as record linkage, is a longstanding but not yet satisfactorily resolved question in many fields of science. For practitioners, it is difficult to ensure the quality of linkage at the time of applying linkage techniques in real world applications. Instead, linkage errors are often detected later on, mostly by users of the applications. This not only requires us to repair errors, but also provides us with opportunities to observe the linkage quality and uncover why such errors occur. In viewing that record linkage is a complex and evolving process, we study how to acquire insights from linkage errors for achieving high-quality linkage. We propose a generic repairing framework which allows us to start with imperfect linkage models, and dynamically repair linkage models and errors for improved linkage quality. We have evaluated our repairing framework over three real-world datasets and the experimental results show that the performance of the proposed tree-structured classifier SVM-tree outperforms the baseline methods.
Excessive Momentum and False Alarms in Late‐Spring ENSO Forecasts

The unanticipated stalled El Niño‐Southern Oscillation (ENSO) evolution of 2014 raises questions about the reliability of the coupled models that were used for forecast guidance. Here we have analyzed the skill and reliability of forecasts of the Niño 3.4 tendency (3‐month change) in the North American multimodel ensemble (1982–2018). We found that forecasts initialized April–June (AMJ) have “excessive momentum” in the sense that the forecast Niño 3.4 tendency is more likely to be a continuation of the prior observed conditions than it should be. Models tend to predict warming when initialized after observed warming conditions and cooling when initialized after observed cooling conditions. Excessive momentum appears in AMJ forecast busts and false alarms including the 2014 one. In some models, excessive momentum appears to be related to model formulation rather than initialization. A concerning trend is that four of the nine years with AMJ forecast busts occurred in the last decade.