Miracle-dz/UniFAR-FTUs huggingface dataset:
META: Mimicking Embedding via oThers' Aggregation for Generalizable Person Re-identification

Domain generalizable (DG) person re-identiﬁcation (ReID) aims to test across unseen domains without access to the target domain data at training time, which is a realistic but challenging problem. In contrast to methods assuming an identical model for different domains, Mixture of Experts (MoE) exploits multiple domain-speciﬁc networks for leveraging complementary information between domains, obtaining impressive results. However, prior MoE-based DG ReID methods suffer from a large model size with the increase of the number of source domains, and most of them overlook the exploitation of domain-invariant characteristics. To handle the two issues above, this paper presents a new approach called Mimicking Embedding via oThers’ Aggregation (META) for DG ReID. To avoid the large model size, experts in META do not add a branch network for each source domain but share all the parameters except for the batch normalization layers. Besides multiple experts, META leverages Instance Normalization (IN) and introduces it into a global branch to pursue invariant features across domains. Meanwhile, META considers the relevance of an unseen target sample and source domains via normalization statistics and develops an aggregation network to adaptively integrate multiple experts for mimicking unseen target domain. Beneﬁting from a proposed consistency loss and an episodic training algorithm, we can expect META to mimic embedding for a truly unseen target domain. Extensive experiments verify that META surpasses state-of-the-art DG ReID methods by a
MAVE: A Product Dataset for Multi-source Attribute Value Extraction

Attribute value extraction refers to the task of identifying values of an attribute of interest from product information. Product attribute values are essential in many e-commerce scenarios, such as customer service robots, product ranking, retrieval and recommendations. While in the real world, the attribute values of a product are usually incomplete and vary over time, which greatly hinders the practical applications. In this paper, we introduce MAVE, a new dataset to better facilitate research on product attribute value extraction. MAVE is composed of a curated set of 2.2 million products from Amazon pages, with 3 million attribute-value annotations across 1257 unique categories. MAVE has four main and unique advantages: First, MAVE is the largest product attribute value extraction dataset by the number of attribute-value examples. Second, MAVE includes multi-source representations from the product, which captures the full product information with high attribute coverage. Third, MAVE represents a more diverse set of attributes and values relative to what previous datasets cover. Lastly, MAVE provides a very challenging zero-shot test set, as we empirically illustrate in the experiments. We further propose a novel approach that effectively extracts the attribute value from the multi-source product information. We conduct extensive experiments with several baselines and show that MAVE is an effective dataset for attribute value extraction task. It is also a very challenging task on zero-shot attribute extraction. Data is available at \urlhttps://github.com/google-research-datasets/MAVE .
Non-Gaussian Component Analysis via Lattice Basis Reduction

Non-Gaussian Component Analysis (NGCA) is the following distribution learning problem: Given i.i. d. samples from a distribution on $\mathbb{R}^d$ that is non-gaussian in a hidden direction $v$ and an independent standard Gaussian in the orthogonal directions, the goal is to approximate the hidden direction $v$. Prior work \cite{DKS17-sq} provided formal evidence for the existence of an information-computation tradeoff for NGCA under appropriate moment-matching conditions on the univariate non-gaussian distribution $A$. The latter result does not apply when the distribution $A$ is discrete. A natural question is whether information-computation tradeoffs persist in this setting. In this paper, we answer this question in the negative by obtaining a sample and computationally efficient algorithm for NGCA in the regime that $A$ is discrete or nearly discrete, in a well-defined technical sense. The key tool leveraged in our algorithm is the LLL method \cite{LLL82} for lattice basis reduction.
A novel single-phase AC/DC converter for power factor correction

A novel single-phase AC/DC converter with two pulsewidth modulation (PWM) schemes is proposed to draw a sinusoidal line current with nearly unity power factor, achieve balanced neutral point voltage and regulate the do bus voltage. With the aid of neutral point clamped scheme, a three-level voltage pattern will be generated on the AC side of the proposed rectifier. To track the line current command derived from a voltage controller and a phase-locked loop circuit, a hysteresis current control scheme is used in the inner loop control. A capacitor voltage compensator is employed to achieve the balanced neutral point voltage. Simulation results are performed to investigate the effectiveness of the proposed control scheme.
Micromachined thermoelectric IR sensors fabricated by a self-aligned process

In this paper, we report the fabrication and characterization of micromachined thermoelectric IR sensors through a self-aligned technique. Unlike most conventional front-etched thermoelectric IR sensors, etching windows in the self-aligned process are determined by the spacing between polysilicon thermocouple legs. Due to etching windows for structure release being patterned by a self-aligned process rather than as a last photolithography step, the fabrication complication is reduced and narrow etching windows can be patterned. Using the self-aligned process, three types of thermoelectric IR sensors are fabricated and characterized. With SiO2/Si3N4 as absorber layer, the sensor with rectangular structure shows the highest responsivity of 43.5 V W − 1, and the circular-shaped sensor with polysilicon strips patterned in the absorber area shows the fastest response and the highest specific detectivity of . This self-aligned technique is also directly applicable to other MEMS devices with polysilicon as the structure material, and also makes it possible to manufacture ultrasmall gaps.
Numerical comparison of inspiratory airflow patterns in human nasal cavities with distinct age differences

As a primary determinant of nasal physiological functions, the nasal morphology and its effects on the airflow dynamics have been extensively studied in literature. However, gross flow features reported in literature are mostly obtained from subjects at similar ages, while studies focusing on nasal subjects with distinct age differences are significantly less. To advance current understandings of nasal airflow dynamics in the context of age diversity, this study employed three anatomically accurate nasal cavity models with distinct age features (5‐, 24‐ and 77‐year‐old models) and numerically compared the physiological nasal airflow fields within these nasal cavity models. To demonstrate the validity of the present numerical models, in vivo rhinomanometry measurement was conducted on the 24‐year‐old female nasal model, and key anatomical features and pressure‐flow curves of all three models were compared with models with similar age features in literature work. Apart from results comparison based on conventional velocity flow fields and wall shear stress distributions, a method for quantifying flow partitions in confined airway spaces was developed to reveal the proportions of fractional flow that enters the olfactory region. Our results revealed dramatic intersubject discrepancies between considered nasal cavity models, especially for the fractional flow that enters the olfactory region. Specifically, the 5‐year‐old girl nasal model received the highest proportion of fractional flow, which accounts for 13.3% ~ 15% of overall inhalation flow rates under different activity levels. For the 24‐year‐old female model, on the contrary, the olfactory fractional flow was dramatically reduced (with a local to overall percentage around 4.3%–7.7%). Finally, for the elderly subject—77‐year‐old male model, minimum level of olfactory flux was observed with a local to overall percentage ranging between 3.1% and 4.9% for considered wide range of inhalation flow rates. Therefore, the local flow intersubject variation can reach nearly fourfold. The vast local flow difference is mainly due to the inherent anatomical features (e.g., immature nasal turbinate structure in the child model, the partial narrowing superior nasal valve in the elder model). The results may further lead to discrepant health effects associated with inhalation exposure to airborne particles.
A laser-triggered spark gap model

Laser preionization is a method whereby the formative lag time and jitter of spark gaps can be reduced, and breakdown can be initiated at voltages significantly below the self‐breakdown value. In the spark gaps of interest (100‐ns spark duration), the plasma column expands from an initial laser preionized diameter of approximately 50 μm to an arc of diameter in excess of 1 mm, and conducts greater than 12‐kA peak current. Since the time required for the resistive collapse of the plasma is comparable to the spark duration, the spark gap represents a non‐negligible resistive loss in the circuit. The objective of this study is to understand the basic mechanisms by which laser‐triggered spark gaps develop and to provide a basis to optimize their design and minimize their resistive losses. To study the expansion and conduction phases of laser‐triggered spark gaps, a first principles model has been developed. This model includes gas dynamics, electron collision kinetics, radiation transport, and external circui.
High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

Abstract Background MicroRNAs (miRNAs) are good candidates as biomarkers for Lung cancer (LC). The aim of this article is to figure out the diagnostic value of both single and combined miRNAs in LC. Methods Normative meta-analysis was conducted based on PRISMA. We assessed the diagnostic value by calculating the combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) and the area under the curve (AUC) of single and combined miRNAs for LC and specific subgroups. Results A total of 80 qualified studies with a total of 8971 patients and 10758 controls were included. In non-small cell lung carcinoma (NSCLC), we involved 20 single-miRNAs and found their Sen, Spe and AUC ranged from 0.52-0.81, 0.66-0.88, and 0.68-0.90, respectively, specially, miR-19 with the maximum Sen, miR-20 and miR-10 with the highest Spe as well as miR-17 with the maximum AUC. Additionally, we detected miR-21 with the maximum Sen of 0.74 [95%CI: 0.62-0.83], miR-146 with the maximum Spe and AUC of 0.93 [95%CI: 0.79-0.98] and 0.89 [95%CI: 0.86-0.92] for early-stage NSCLC. We also identified the diagnostic power of available panel (miR-210, miR-31 and miR-21) for NSCLC with satisfying Sen, Spe and AUC of 0.82 [95%CI: 0.78-0.84], 0.87 [95%CI: 0.84-0.89] and 0.91 [95%CI: 0.88-0.93], and furtherly constructed 2 models for better diagnosis. Conclusions We identified several single miRNAs and combined groups with high diagnostic power for NSCLC through pooled quantitative analysis, which shows that specific miRNAs are good biomarker candidates for NSCLC and further researches needed.
Transvenous embolization of moderate to large patent ductus arteriosus in dogs using the Amplatzer vascular plug II

Abstract Background Catheter‐based occlusion of patent ductus arteriosus (PDA) can be performed using different devices. Transvenous embolization using the Amplatzer vascular plug II (AVP‐II) has been studied in humans, but it has not been described in dogs. Objective Evaluate the feasibility and success of transvenous embolization of PDA using the AVP‐II in dogs. Animals Nineteen client‐owned dogs with left‐to‐right shunting PDA, with minimal ductal diameter >2.5 mm. Methods Prospective observational study using AVP‐II with transvenous access for PDA closure in dogs. Results Angiography showed a conical ductus with a long (n = 17) or short (n = 2) ampulla. The minimal diameter of the duct was 4.34 ± 1.11 mm, and the maximal diameter of the ampulla was 13.18 ± 3.47 mm. Technical success was achieved in 18 of the 19 (94.7%) patients after the first intervention and in all 19 (100%) patients after the second intervention. Postrelease angiography documented complete occlusion of the PDA in 10 of 19 (52.6%) dogs. Mild flow acceleration or stenosis of the left pulmonary artery was found in 6 and 1 of the 17 analyzed cases, respectively, by Doppler examination. The closure rate 24 hours after intervention was 94.7% (18/19). The remaining dog had a moderate residual shunt, and delayed complete closure after 3 months led to a 100% closure rate. Conclusion and Clinical Importance The AVP‐II is a safe and effective device for transvenous embolization in dogs with moderate to large PDA.
Efficacy and safety of risankizumab for active psoriatic arthritis: 24-week results from the randomised, double-blind, phase 3 KEEPsAKE 1 trial

Objective To evaluate risankizumab, a biological therapy that inhibits interleukin 23, in patients with active psoriatic arthritis (PsA) who have responded inadequately or are intolerant to ≥1 conventional synthetic disease-modifying antirheumatic drug (csDMARD). Methods In the randomised, placebo-controlled, double-blind KEEPsAKE 1 trial, 964 patients with active PsA were randomised (1:1) to receive risankizumab 150 mg or placebo at weeks 0, 4 and 16. The primary endpoint was the proportion of patients achieving ≥20% improvement in American College of Rheumatology criteria (ACR20) at week 24. Here, we report the results from the 24-week double-blind period; the open-label period with all patients receiving risankizumab is ongoing. Results At week 24, a significantly greater proportion of patients receiving risankizumab achieved the primary endpoint of ACR20 (57.3% vs placebo, 33.5%; p<0.001). Significant differences were also observed for risankizumab versus placebo for the first eight ranked secondary endpoints, including skin and nail psoriasis endpoints, minimal disease activity and resolution of enthesitis and dactylitis (p<0.001). Adverse events and serious adverse events were reported at similar rates in the risankizumab and placebo groups. Serious infections were reported for 1.0% and 1.2% of patients receiving risankizumab and placebo, respectively. There was one death in the risankizumab group (urosepsis deemed unrelated to the study drug). Conclusions Risankizumab treatment results in significantly greater improvement of signs and symptoms of PsA compared with placebo and is well tolerated in patients with active PsA who have responded inadequately or are intolerant to ≥1 csDMARD. Trial registration number NCT03675308.
Tenofovir diphosphate levels in dried blood spots are associated with virologic failure and resistance to first‐line therapy in South Africa: a case–control cohort study

Tenofovir diphosphate (TFV‐DP) in dried blood spots (DBS), a measure of cumulative antiretroviral therapy (ART) adherence, is associated with viral suppression and predicts future viremia in persons with HIV (PWH). However, its utility to identify those at risk for virologic failure (VF) and drug resistance is unknown. To address this, we aimed to establish the association between this adherence biomarker and VF with drug resistance in a cohort of PWH initiating first‐line ART in KwaZulu‐Natal, South Africa.
Comparison of Species Sensitivity Distributions for Sediment‐Associated Nonionic Organic Chemicals Through Equilibrium Partitioning Theory and Spiked‐Sediment Toxicity Tests with Invertebrates

Equilibrium partitioning (EqP) theory and spiked‐sediment toxicity tests are useful methods to develop sediment quality benchmarks. However, neither approach has been directly compared based on species sensitivity distributions (SSDs) to date. In the present study, we compared SSDs for 10 nonionic hydrophobic chemicals (e.g., pyrethroid insecticides, other insecticides, and polycyclic aromatic hydrocarbons) based on 10–14‐day spiked‐sediment toxicity test data with those based on EqP theory using acute water‐only tests. Because the exposure periods were different between the two tests, effective concentrations (i.e., median effective/lethal concentration) were corrected to compare SSDs. Accordingly, we found that hazardous concentrations for 50% and 5% of species (HC50 and HC5, respectively) differed by up to a factor of 100 and 129 between the two approaches, respectively. However, when five or more species were used for SSD estimation, their differences were reduced to a factor of 1.7 and 5.1 for HC50 and HC5, respectively, and the 95% confidence intervals of HC50 values overlapped considerably between the two approaches. These results suggest that when the number of test species is adequate, SSDs based on EqP theory and spiked‐sediment tests are comparable in sediment risk assessments. Environ Toxicol Chem 2022;41:462–473. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
The role of social connection on the experience of COVID-19 related post-traumatic growth and stress

Background Historically social connection has been an important way through which humans have coped with large-scale threatening events. In the context of the COVID-19 pandemic, lockdowns have deprived people of major sources of social support and coping, with others representing threats. Hence, a major stressor during the pandemic has been a sense of social disconnection and loneliness. This study explores how people’s experience of compassion and feeling socially safe and connected, in contrast to feeling socially disconnected, lonely and fearful of compassion, effects the impact of perceived threat of COVID-19 on post-traumatic growth and post-traumatic stress. Methods Adult participants from the general population (N = 4057) across 21 countries worldwide, completed self-report measures of social connection (compassion for self, from others, for others; social safeness), social disconnection (fears of compassion for self, from others, for others; loneliness), perceived threat of COVID-19, post-traumatic growth and traumatic stress. Results Perceived threat of COVID-19 predicted increased post-traumatic growth and traumatic stress. Social connection (compassion and social safeness) predicted higher post-traumatic growth and traumatic stress, whereas social disconnection (fears of compassion and loneliness) predicted increased traumatic symptoms only. Social connection heightened the impact of perceived threat of COVID-19 on post-traumatic growth, while social disconnection weakened this impact. Social disconnection magnified the impact of the perceived threat of COVID-19 on traumatic stress. These effects were consistent across all countries. Conclusions Social connection is key to how people adapt and cope with the worldwide COVID-19 crisis and may facilitate post-traumatic growth in the context of the threat experienced during the pandemic. In contrast, social disconnection increases vulnerability to develop post-traumatic stress in this threatening context. Public health and Government organizations could implement interventions to foster compassion and feelings of social safeness and reduce experiences of social disconnection, thus promoting growth, resilience and mental wellbeing during and following the pandemic.
Tumor‐associated macrophages: An important player in breast cancer progression

Breast cancer is the most common form of malignant tumor in females, accounting for the second highest mortality among cancer patients. In the breast tumor microenvironment, tumor‐associated macrophages (TAMs) are the most abundant immune cells, which regulate the progression of breast cancer. During breast cancer tumorigenesis and progression, TAMs support breast tumor growth by promoting angiogenesis and cancer cell metastasis, inducing cancer stemness, regulating energy metabolism, and supporting immune system suppression. TAMs exhibit a high degree of cellular plasticity. Repolarizing tumor‐related macrophages into M1 macrophages can promote tumor regression. This study reviews the role and mechanism of action of TAMs in the development of breast cancer and establishes TAMs as effective targets for breast cancer treatment.
A systematic literature review of remanufacturing scheduling

This article systematically organises and reviews peer-reviewed journals up to July 2011 to access progress in the scheduling of remanufacturing operations. The simple (infinite capacity, no part commonality, and deterministic parameters), single product remanufacturing scheduling problem is solved using reverse material requirements planning. Material requirements planning and performance-based objectives of the 1990s were replaced by cost-based integer programming models that can achieve solutions to size-restricted problems. Product deterioration is identified as an additional complexity and methodologies are discussed that address this important issue. The synthesis of the literature reveals the importance of buffer inventories in addressing remanufacturing uncertainty, the advantages of ‘simpler’ disassembly release mechanisms and due date scheduling rules, and the improved performance of Kanban over ‘push’ scheduling and flexible Kanban over traditional Kanban. The most recent trend is the development and testing of several promising heuristic methodologies that can address larger and more complex, scheduling situations. Further study is still needed to address the formidable combinations of finite capacity, part commonality and stochastic parameters and, as Kim, Lee, and Xirouchakis (2007) note, the need to address backlogging, multiple periods, and the necessity to integrate disassembly process planning with disassembly scheduling.