Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Dimensional Inference over Networks: Linear Convergence and Statistical Guarantees

We study sparse linear regression over a network of agents, modeled as an undirected graph and no server node. The estimation of the s-sparse parameter is formulated as a constrained LASSO problem wherein each agent owns a subset of the N total observations. We analyze the convergence rate and statistical guarantees of a distributed projected gradient tracking-based algorithm under high-dimensional scaling, allowing the ambient dimension d to grow with (and possibly exceed) the sample size N . Our theory shows that, under standard notions of restricted strong convexity and smoothness of the loss functions, suitable conditions on the network connectivity and algorithm tuning, the distributed algorithm converges globally at a linear rate to an estimate that is within the centralized statistical precision of the model, O(s log d/N). When s log d/N = o(1), a condition necessary for statistical consistency, an ε-optimal solution is attained after O(κ log(1/ε)) gradient computations and O(κ/(1−ρ) log(1/ε)) communication rounds, where κ is the restricted condition number of the loss function and ρ measures the network connectivity. The computation cost matches that of the centralized projected gradient algorithm despite having data distributed; whereas the communication rounds reduce as the network connectivity improves. Overall, our study reveals interesting connections between statistical efficiency, network connectivity & topology, and convergence rate in high dimensions. Keywords— High-dimensional inference, distributed convex optimization, linear convergence
Strategic facilities management system in relation with building performance; the significance and relationship

Healthcare design frequently involves complex concepts that are difficult to measure and evaluate because the building require a modern, quality, functional and therapeutic environment. For this specific reason, facilities management has become a very important support system to ensure smoothness in healthcare business. Facilities management in healthcare building is a complicated system involving multiple layers of administrative division and sub-divisions. Building performance such as building impact, function and quality prove to have significant impact on strategic facilities management. This paper will do an extensive review of strategic healthcare business management as a holistic approach and examine how facilities management can effectively manage their division with consideration and understanding of building performance. The correlation between strategic facilities management and building performance will be identified and a framework for strategic FM system with regards to building performance will be developed.
RHONN Modelling-Enabled Nonlinear Predictive Control for Lateral Dynamics Stabilization of an In-Wheel Motor Driven Vehicle

Featuring the fast response and flexibility in control allocation, an electric vehicle with in-wheel motors is a good platform for implementing advanced vehicle dynamics control. Among many active safety functions of an in-wheel motor driven vehicle (IMDV), lateral stability control is a key technology, which can be realized through torque vectoring. To further advance the lateral stabilization performance of the IMDV, in this article a novel data-driven nonlinear model predictive control (NMPC) is proposed based the recurrent high-order neural network (RHONN) modelling method. First, the new RHONN model is developed to represent vehicle’s nonlinear dynamic behaviors. Different from the conventional physics-based modelling method, the RHONN model forms high-order polynomials by neuron states to feature nonlinear dynamics. Based on the RHONN model, the steady-state responses of vehicle’s yaw rate and sideslip angle are iteratively optimized and set as the control objectives for low-level controller, aiming to improve the system robustness. Besides, a nonlinear model predictive controller is designed based on the RHONN, which is expected to improve the prediction accuracy during the receding horizon control. Further, a constrained optimization problem is formulated to derive the required yaw moment for vehicle lateral dynamics stabilization. Finally, the performance of the developed RHONN-based nonlinear MPC is validated on an IMDV in the CarSim/Simulink simulation environment. The validation results show that the developed approach outperforms the conventional method, and further improves the stable margin of the system. It is able to enhance the lateral stabilization performance of the IMDV under various driving scenarios, demonstrating the feasibility and effectiveness of the proposed approach.
Equatorial extreme-mass-ratio inspirals in Kerr black holes with scalar hair spacetimes

In this work we analyze some judiciously chosen solutions of Kerr Black Holes with Scalar Hair (KBHsSH) of special interest for Gravitational Wave (GW) events originated from Extreme Mass Ratio Inspirals (EMRIs). Because of the off-center distribution of energy density, these spacetimes are warped in such a way that not all metric functions behave monotonically on the equatorial plane as in the exterior region of Kerr black holes (KBHs). This has great impact on the orbital parameters, which in turn affects the imprints on signals descendant from EMRIs in a adiabatic evolution. By investigating circular obit parameters, we unveil what qualitative features could be present in the signals that are new and distinct compared to KBHs, and we evolve some inspirals by employing the usual quadrupole formula approximation. We show that the frequencies of the emitted signals behave nonmonotonically, i.e. they can backward chirp, and for some particular cases they can become arbitrarily small, falling below LISA’s sensibility range. Finally, we present two sets of waveforms produced by a noncircular EMRI in which the compact object (CO) follows a type of geodesic motion typically present in spacetimes with a static ring (SR), in which the compact object is periodically momentarily at rest.
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching

We propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D shape represented as a planar curve and a 3D shape represented as a surface; the output is a continuous curve on the surface. We cast the problem as finding the shortest circular path on the product 3-manifold of the surface and the curve. We prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of $O(mn^2\log(n))$, where $m$ and $n$ denote the number of vertices on the template curve and the 3D shape respectively. We also demonstrate that in practice the runtime is essentially linear in $m\! \cdot\! n$ making it an efficient method for shape analysis and shape retrieval. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval.
The reconstruction of invasion histories with genomic data in light of differing levels of anthropogenic transport

Unravelling the history of range shifts is key for understanding past, current and future species distributions. Anthropogenic transport of species alters natural dispersal patterns and directly affects population connectivity. Studies have suggested that high levels of anthropogenic transport homogenize patterns of genetic differentiation and blur colonization pathways. However, empirical evidence of these effects remains elusive. We compared two range-shifting species (Microcosmus squamiger and Ciona robusta) to examine how anthropogenic transport affects our ability to reconstruct colonization pathways using genomic data. We first investigated shipping networks from the 18th century onwards, cross-referencing these with regions where the species have records to infer how each species has potentially been affected by different levels of anthropogenic transport. We then genotyped thousands of single-nucleotide polymorphisms from 280 M. squamiger and 190 C. robusta individuals collected across their extensive species' ranges and reconstructed colonization pathways. Differing levels of anthropogenic transport did not preclude the elucidation of population structure, though specific inferences of colonization pathways were difficult to discern in some of the considered scenario sets. We conclude that genomic data in combination with information of underlying introduction drivers provide key insights into the historic spread of range-shifting species. This article is part of the theme issue ‘Species’ ranges in the face of changing environments (part I)’.
API Management Patterns for Public, Partner, and Group Web API Initiatives with a Focus on Collaboration

API management of public, partner, and group Web APIs (APIs) is an organizational function at the interface between several stakeholders inside and outside of an organization. Most current API management literature is concerned with technical aspects of API management. Therefore, we use a design science approach to identify API management stakeholders, pattern candidates, and patterns focusing on collaboration. We derive these results from 16 expert interviews with API management team members, mainly working at established and SME organizations in Europe. The pattern’s target audience are API provider team members. The purpose of this paper is to describe the design approach, the two exemplary patterns ”Role-based marketing” and ”Frontend venture”, and six overarching observations made during the pattern language design. The first observation is that API provider teams usually control the resources used to collaborate with API consumers. Nevertheless, consumers want personal contact and contractual agreements before integrating an API. Also, most API management concerns are related to the API consumer. Then again, few standardized approaches for collaboration with backend functionality providers, legal or marketing exist. Additionally, an API has its own lifecycle. Finally, the strategic relevance of the API resources and the API consumers’ organizational structure influence a patterns’ suitability.
Molecular Mapping of Quantitative Trait Loci for Fusarium Head Blight Resistance in the Brazilian Spring Wheat Cultivar “Surpresa”

Fusarium head blight (FHB) is a devastating disease in wheat. The use of resistant germplasm from diverse sources can significantly improve resistance to the disease. “Surpresa” is a Brazilian spring wheat cultivar with moderate FHB resistance, different from currently used sources. In this study, we aimed to identify and map the genetic loci for FHB resistance in Surpresa. A mapping population consisting of 187 recombinant inbred lines (RILs) was developed from a cross between Surpresa and a susceptible spring wheat cultivar, “Wheaton. ” The population was evaluated for FHB by the point-inoculation method in three greenhouse experiments and four field trials between 2016 and 2018. Mean disease severity for Surpresa and Wheaton was 41.2 and 84.9% across the 3 years of experiments, ranging from 30.3 to 59.1% and 74.3 to 91.4%, respectively. The mean FHB severity of the NILs was 57%, with an overall range from 7 to 100%, suggesting transgressive segregation in the population. The population was genotyped using a two-enzyme genotyping-by-sequencing approach, and a genetic map was constructed with 5,431 single nucleotide polymorphism (SNP) markers. Four QTL for type II resistance were detected on chromosomes 3A, 5A, 6A, and 7A, explaining 10.4–14.4% of the total phenotypic variation. The largest effect QTL was mapped on chromosome 7A and explained 14.4% of the phenotypic variation; however, it co-localized with a QTL governing the days to anthesis trait. A QTL for mycotoxin accumulation was also detected on chromosome 1B, explaining 18.8% of the total phenotypic variation. The QTL for FHB resistance identified in the study may diversify the FHB resistance gene pool and increase overall resistance to the disease in wheat.
Transcriptome Analysis for Identification of Genes Related to Growth and Development, Digestion and Detoxification, Olfaction in the Litchi Stink Bug Tessaratoma papillosa

Tessaratoma papillosa is a major pest of Litchi chinensis and Dimocarpus longan. Adult and nymph secretions are not only harmful to plants but also to humans. At present, there are not a lot of research on T. papillosa, especially omics research. We used high-throughput sequencing technology to sequence the T. papillosa transcriptome and obtained 67,597 unigenes homologous to Halyomorpha halys (88.03%). Subsequently, RNA-SEQ and comparative analyses were performed on the 14 different developmental stages and tissues. A total of 462 unigenes related to growth and development, 1,851 unigenes related to digestion and detoxification, and 70 unigenes related to olfaction were obtained. Moreover, expression analysis showed that the T. papillosa major life activities genes are uniformly expressed across all developmental states. However, the adult midgut gene expression patterns were utterly different from that of the nymphs. Similarly, female fat body genes exhibited distinct expression patterns compared to that of males and nymphs. Thus, different developmental stages and physiological functions affect gene expression patterns. We also found that most of the differential genes were associated with cellular maintenance. This study will help understand the growth and development of litchi stink bugs, their choice of host plants, food digestion and detoxification, and their reproductive behavior. In addition, this result can provide reference information for some target genes in the process of control of T. papillosa.
Association of Novel Androgen Receptor Axis-Targeted Therapies With Diarrhea in Patients With Prostate Cancer: A Bayesian Network Analysis

Objective To perform a systematic review and network meta-analysis to characterize the effect of novel androgen receptor axis-target (ARAT) agents on diarrhea and constipation. Methods We searched the Pubmed, Web of Science, and ClinicalTrials.gov up to September 2021 for phase 3 randomized controlled trials (RCTs) of patients receiving novel ARAT agents for prostate cancer (CaP). A Cochrane risk-of-bias tool was used to assess trial quality. The primary outcomes were risk ratio (RR) of any-grade diarrhea and constipation for patients receiving ARAT treatment. RRs of competing treatments were evaluated by pairwise and Bayesian network meta-analysis. Results In this study, 13 trials with 15,117 participants comparing 5 treatments (abiraterone, enzalutamide, apalutamide, darolutamide, and placebo) were identified. Use of novel ARAT agents was associated with a significant increased risk of any-grade diarrhea (RR = 1.30, 95% CI [1.16, 1.44]). As for subgroup analysis, abiraterone, enzalutamide, and apalutamide were all associated with significant increased risk of any-grade diarrhea (abiraterone: RR = 1.40, 95% CI [1.09, 1.81]; enzalutamide: RR = 1.17, 95% CI [1.02, 1.35]; apalutamide: RR = 1.35, 95% CI [1.03, 1.76]). Based on Bayesian modeling, abiraterone and enzalutamide showed the highest and lowest probability to rank first in terms of increasing risk of any-grade diarrhea. There were no significant differences of risk in any-grade constipation, grade 3 or greater diarrhea, and constipation between ARAT and control group. Conclusion The present study indicates that the use of novel ARAT agents is associated with a significantly higher risk of diarrhea. Across the four agents, abiraterone may relate to the highest risk of diarrhea among patients with metastatic hormone sensitive prostate cancer (mHSPC) and castration-resistant prostate cancer (CRPC).
Ocean Warming Leads to Increases in Aerobic Demand and Changes to Gene Expression in the Pinfish (Lagodon rhomboides)

Anthropogenic climate change is causing increases in the frequency, intensity, and duration of marine heatwaves (MHWs). These short-term warming events can last for days to weeks and can produce severe disruptions in marine ecosystems, as many aquatic species are poikilotherms that depend on the conditions of the environment for physiological processes. It is crucial to investigate the effects of these thermal fluctuations on species that play a disproportionate ecological role in marine ecosystems, such as the pinfish (Lagodon rhomboides) in the Gulf of Mexico and western Atlantic. In this study, we exposed pinfish to a simulated MHW in aquaria and examined the impacts of acute warming on two life stages (juvenile and adult), measuring oxygen consumption and gene expression in two relevant tissue types (liver and muscle). We saw significant increases in routine metabolic rate with increasing temperature in both juveniles (24.58 mgO2/kg/h increase per 1°C of warming) and adults (10.01 mgO2/kg/h increase per 1°C of warming). These results indicate that exposure to increased temperatures was more metabolically costly for juveniles than for adults, on a mass-specific basis. This was also observed in the molecular analyses, where the largest number of differentially expressed genes were observed in the juvenile pinfish. The analyses of gene expression suggest warming produces changes to immune function, cell proliferation, muscle contraction, nervous system function, and oxygen transport. These results indicate that this ecologically relevant species will be significantly impacted by projected increases in frequency and magnitude of MHWs, particularly in the juvenile stage.
Comparison of Minimally Invasive Versus Abdominal Radical Hysterectomy for Early-Stage Cervical Cancer: An Updated Meta-Analysis

Background Although minimally invasive surgery (MIS) was commonly used to treat patients with early-stage cervical cancer, its efficacy remained controversial. Methods We systematically searched PubMed, Web of Science, and Cochrane Library databases until March 2021 to compare the prognosis of early-stage cervical cancer patients who underwent MIS (laparoscopic or robot-assisted radical hysterectomy) or ARH. The primary outcomes included rates of 3- and 5-year disease-free survival (DFS) and overall survival (OS). The study protocol was registered in PROSPERO: CRD42021258116. Results This meta-analysis included 48 studies involving 23346 patients (11220, MIS group; 12126, ARH group). The MIS group had a poorer medium-term (3-year) DFS (HR=1.08, 95% CI: 1.01-1.16, p=0.031) than the ARH group, without significant difference in medium-term OS as well as long-term (5-year) DFS and OS. Subgroup analysis of 3-year prognosis revealed that although patients in Western countries who underwent MIS had shorter DFS than those who underwent ARH (HR=1.10, p=0.024), no difference was observed in DFS among those in Asian countries. Moreover, MIS was linked to poorer 3-year DFS in patients with stage I cervical cancer (HR=1.07, p=0.020). Notably, subgroup analysis of 5-year prognosis revealed that patients with tumor size ≥2 cm undergoing MIS exhibited a shorter DFS than those who underwent ARH (HR=1.65, p=0.041). Conclusion Patients with early-stage cervical cancer undergoing MIS may have a poorer prognosis than those undergoing ARH. Therefore, applying MIS in early-stage cervical cancer patients should be conducted with caution. Systematic Review Registration The study protocol was registered in PROSPERO: CRD42021258116.
Prevalence of Internet Gaming Disorder in Medical Students: A Meta-Analysis

Introduction In the last decade, the technological advances have led to increased usage of the Internet. Internet-based games are now more readily available, and they are also more attractive and engageable for individuals. Previous studies have established university students as vulnerable population with regards to IGD. Despite the unique stressors and demands of the course, there is little information about the pooled prevalence of IGD in medical students. Objectives The current meta-analysis aims to establish the pooled prevalence of IGD among medical students in different countries, and factors affecting the pooled prevalence. Methods A comprehensive search was conducted from 23 May 2021 to 30 May 2021. The following databases were searched: PubMed, PsychINFO, Cochrane CENTRAL, Google Scholar, Scopus, Web of Science, Embase, Science Direct. The search terminologies included permutations of the keywords for IGD and medical students. All statistical analysis was performed with the Comprehensive Meta-analysis Version 3.0 program based on random-effects model. Results Three hundred ninety-six articles were identified from the search of the databases. The final data set consisted of 6 studies with a pooled cohort size of 2,236 medical students. The pooled prevalence of IGD in each country is as follows: Egypt had the highest prevalence rate of 10.9% (95% CI: 7.3–16.1%), followed by Saudi Arabia (8.8, 95% CI: 5.7–13.2%), Indonesia (6.1, 95% CI: 0.7–37.5%) and India (3.8, 95% CI: 2.7–5.5%) (p < 0.005). Conclusions In conclusion, this meta-analysis reports that the pooled prevalence of IGD among medical students from different countries is 6.2%, which is around twice as high than that of the general population.
Where the Blame Lies: Unpacking Groups Into Their Constituent Subgroups Shifts Judgments of Blame in Intergroup Conflict

Whom do individuals blame for intergroup conflict? Do people attribute responsibility for intergroup conflict to the in-group or the out-group? Theoretically integrating the literatures on intergroup relations, moral psychology, and judgment and decision-making, we propose that unpacking a group by explicitly describing it in terms of its constituent subgroups increases perceived support for the view that the unpacked group shoulders more of the blame for intergroup conflict. Five preregistered experiments (N = 3,335 adults) found support for this novel hypothesis across three distinct intergroup conflicts: the Israeli-Palestinian conflict, current racial tensions between White people and Black people in the United States, and the gender gap in wages in the United States. Our findings (a) highlight the independent roles that entrenched social identities and cognitive, presentation-based processes play in shaping blame judgments, (b) demonstrate that the effect of unpacking groups generalizes across partisans and nonpartisans, and (c) illustrate how constructing packed versus unpacked sets of potential perpetrators can critically shape where the blame lies.
RiskEstim: A Software Package to Quantify COVID-19 Importation Risk

We present an R package developed to quantify coronavirus disease 2019 (COVID-19) importation risk. Quantifying and visualizing the importation risk of COVID-19 from inbound travelers is urgent and imperative to trigger public health responses, especially in the early stages of the COVID-19 pandemic and emergence of new SARS-CoV-2 variants. We provide a general modeling framework to estimate COVID-19 importation risk using estimated pre-symptomatic prevalence of infection and air traffic data from the multi-origin places. We use Hong Kong as a case study to illustrate how our modeling framework can estimate the COVID-19 importation risk into Hong Kong from cities in Mainland China in real time. This R package can be used as a complementary component of the pandemic surveillance system to monitor spread in the next pandemic.