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The Sociology of Sport Journal (SSJ) is celebrating its 40th anniversary with a special issue that focuses on liberation, futurity, intersectionality, and interdisciplinarity. The guest editors discuss the significance of these themes in studying sport, physical culture, and the physically active body. They emphasize the importance of critical scholarship that highlights the experiences of marginalized groups and challenges systems of oppression. The editors hope that SSJ and the North American Society for the Sociology of Sport (NASSS) can provide spaces for emerging scholars and contribute to the future of the field. [Extracted from the article]

Background: Growing evidence indicated that to develop of atherosclerosis observed more often by people with Alzheimer's disease (AD), but the underlying mechanism is not fully clarified. Considering that amyloid-β (Aβ) deposition in the brain is the key pathophysiology of AD and plasma Aβ is closely relate to Aβ deposition in the brain, in the present study, we investigated the relationships between atherosclerosis and plasma Aβ levels. Methods: This was a population based cross-sectional study. Patients with high risk of atherosclerosis from Qubao Village, Xi'an were underwent carotid ultrasound for assessment of atherosclerosis. Venous blood was collected on empty stomach in the morning and plasma Aβ1−40 and Aβ1−42 levels were measured using ELISA. Multivariate logistic regression analysis was performed to investigate the relationships between carotid atherosclerosis (CAS) and plasma Aβ levels. Results: Among 344 patients with high risk of atherosclerosis, 251(73.0%) had CAS. In the univariate analysis, the plasma Aβ levels had no significant differences between CAS group and non-CAS group (Aβ1−40: 53.07 ± 9.24 pg/ml vs. 51.67 ± 9.11pg/ml, p = 0.211; Aβ1−42: 40.10 ± 5.57 pg/ml vs. 40.70 pg/ml ± 6.37pg/ml, p = 0.285). Multivariate logistic analysis showed that plasma Aβ levels were not associated with CAS (Aβ1−40: OR = 1.019, 95%CI: 0.985–1.054, p = 0.270;Aβ1−42: OR = 1.028, 95%CI: 0.980–1.079, p = 0.256) in the total study population. After stratified by hypertension, CAS was associated with plasma Aβ1−40 positively (OR = 1.063, 95%CI: 1.007–1.122, p = 0.028) in the non-hypertension group, but not in hypertensive group. When the plasma Aβ concentrations were classified into four groups according to its quartile, the highest level of plasma Aβ1−40 group was associated with CAS significantly (OR = 4.465, 95%CI: 1.024–19.474, p = 0.046). Conclusion: Among patients with high risk of atherosclerosis, CAS was associated with higher plasma Aβ1−40 level in non-hypertension group, but not in hypertension group. These indicated that atherosclerosis is associated with plasma Aβ level, but the relationship may be confounded by hypertension. [ABSTRACT FROM AUTHOR]

We report an unprecedented Ni‐catalyzed direct monofluoromethylthiolation of acyl chlorides, in situ generated from carboxylic acids, with elemental sulfur (S8) as the S source and fluoroiodomethane (ICH2F) as the CH2F radical source to produce a series of monofluoromethylthioesters in moderate to good yields. This approach features excellent functional group tolerance and broad substrate scope. Additionally, the late‐stage monofluoromethylthiolation of complex bioactive molecules can also be accomplished using this method. [ABSTRACT FROM AUTHOR]

The motive of the study is to examine real effective exchange rates (REER) for Dutch disease effect (DDE) and evaluate the favourite exchange rate regime (ERR) for oil exporters, besides considering the time effect and development stages. This study included yearly data from 2001 to 2010 for 51 oil‐exporting nations. For empirical estimation, this study employed the dynamic panel threshold model. The study deduced that a nonlinear relationship in net oil‐exporting countries. The findings revealed that oil‐exporting countries experiencing a reduction in non‐oil exports if the real exchange rate (RER) exceeds than 3% (from the previous year), validating the Dutch disease phenomenon in oil‐exporting countries. Moreover, exposure to this threat increases with a fixed ERR, developing countries and early periods of exporting oil. Specifically, the results of the study contribute to empirical knowledge in economic sciences and provide useful insights into political implications and strategic planning for policymakers in oil‐exporting countries. [ABSTRACT FROM AUTHOR]

This study reports the copper‐catalyzed α‐indolmethylation of 2‐pyridylacetates with 3‐indoleacetic acids. This reaction offers an approach to generating alkylideneindolenine electrophiles via the oxidative decarboxylation of 3‐indoleacetic acids. The developed reaction system demonstrates good versatility, extending beyond the indolmethylation of 2‐pyridylacetates to include activated esters and nitroalkanes. Moreover, a biological evaluation revealed that several products exhibited antiproliferative activity against different cancer cell lines. [ABSTRACT FROM AUTHOR]

Hyperspectral scanning capacitance microscopy (SCM) measures d C / d V − V spectra at every XY location of a semiconductor sample surface area. We report its application to GaN-based high electron mobility transistor (HEMT) structures to map threshold voltage (Vth) at the nanoscale. The consistency between the conventional SCM data and the hyperspectral SCM data set of the same area on the HEMT surface provides evidence for the reliability of hyperspectral SCM. We developed a method to extract a map of Vth distribution across the surface of the HEMT structure at the nanoscale from the hyperspectral SCM data set. The map reveals that most of the fissures (i.e., enlarged pits formed at threading dislocation surface endings) on the nitride sample surface reduce local Vth. Other variations in Vth in regions free of the fissures could be a result of thickness and/or composition inhomogeneities in the Al x Ga 1 − x N barrier layer. Conventional SCM and other techniques cannot provide these detailed insights obtained through hyperspectral SCM. [ABSTRACT FROM AUTHOR]

Pose estimation of metal parts plays a vital role in industrial grasping areas. It is challenging to obtain complete point clouds of metal parts because of their reflective properties. This study introduces an approach for recovering the 6D pose of CAD-known metal parts from images captured by a single RGB camera. The proposed strategy only requires RGB images without depth information. The core idea of the proposed method is to use multiple views to estimate the metal parts' pose. First, the pose of metal parts is estimated in the first view. Second, ray casting is employed to simulate additional views with the corresponding status of the metal parts, enabling the calculation of the camera's next best viewpoint. The camera, mounted on a robotic arm, is then moved to this calculated position. Third, this study integrates the known camera transformations with the poses estimated from different viewpoints to refine the final scene. The results of this work demonstrate that the proposed method effectively estimates the pose of shiny metal parts. [ABSTRACT FROM AUTHOR]

In order to cope with the grid fluctuation caused by large‐scale wind power connected to the grid, the wind thermal power generation system has been proposed and extensively studied. The wind thermal power generation system uses a wind turbine to drive a heat generation device to heat the heat storage medium, which is further exchanged to drive a turbine to generate electricity. A superconducting magnetic eddy current heater (SMH) is proposed for the characteristics of wind thermal power generation system, which uses non‐resistive, large current‐carrying superconducting coils for excitation, and has high output efficiency and power density. The working principle of magnetic eddy current heating is analysed, and the structure of SMH with no ferromagnetic material and two heating screens inside and outside is proposed according to the characteristics of SMH. An analytical model of the SMH is established, and the influence of the structure and materials of the SMH on the magnetic field distribution is analysed. Based on this, a 22‐pole SMH was designed and analysed for output power at 10–20 rpm. A three‐dimensional magnetism‐stress combined analysis model of SMH is established, and the strain and stress characteristics of SMH are simulated under the condition of maximum output power, which verifies the feasibility of the mechanical properties of existing superconducting materials for application in SMH. [ABSTRACT FROM AUTHOR]

Dataset biases are notoriously detrimental to model robustness and generalization. The identify-emphasize paradigm appears to be effective in dealing with unknown biases. However, we discover that it is still plagued by two challenges: A, the quality of the identified bias-conflicting samples is far from satisfactory; B, the emphasizing strategies only produce suboptimal performance. In this paper, for challenge A, we propose an effective bias-conflicting scoring method (ECS) to boost the identification accuracy, along with two practical strategies — peer-picking and epoch-ensemble. For challenge B, we point out that the gradient contribution statistics can be a reliable indicator to inspect whether the optimization is dominated by bias-aligned samples. Then, we propose gradient alignment (GA), which employs gradient statistics to balance the contributions of the mined bias-aligned and bias-conflicting samples dynamically throughout the learning process, forcing models to leverage intrinsic features to make fair decisions. Furthermore, we incorporate self-supervised (SS) pretext tasks into training, which enable models to exploit richer features rather than the simple shortcuts, resulting in more robust models. Experiments are conducted on multiple datasets in various settings, demonstrating that the proposed solution can mitigate the impact of unknown biases and achieve state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Prestressed anchor cables are commonly utilized to reinforce slopes in earthquake-prone zones. The existing upper bound limit analyses of seismic slopes reinforced with prestressed anchor cables have the following limitations: (1) neglecting variable seismic excitations; (2) ignoring the three-dimensional spatial layout of cables because of using the plane-strain analysis. In this study, the time-space effects of seismic waves are analytically described by sin-cos functions incorporating wave amplification or soil damping. Based on the upper bound of plastic theory and a three-dimensional discretized failure mechanism, internal energy dissipation rate and work rates contributed by gravitational forces, variable seismic excitations, and prestressed anchor cables are computed. An energy-based function of dynamic factors of safety (DFS) is established, followed by a global optimization to identify the critical harmonic pattern of DFS. The accuracy is checked by numerical simulations where the seismic stability of an engineering slope adjacent to Yu-Huai railway is evaluated. Comparisons also show that the conventional simplified method not only cannot reflect the spatial layout of cables but also overestimate the mechanical contribution of cables. Finally, the dominant effects of the layout of cables, soil properties as well as physical parameters of seismic waves on the DFS and the critical failure mechanism are discussed. A method to evaluate the stability of seismic cable-reinforced slopes A kinematical admissible 3D failure mechanism of cable-reinforced slopes is generated Critical harmonic pattern of safety factors is explicitly obtained. Effect of cable layout, dynamic parameters and soil properties are discussed. [ABSTRACT FROM AUTHOR]

Daily activities often occur in familiar environments, affording us an opportunity to learn. Laboratory studies have shown that people readily acquire an implicit spatial preference for locations that frequently contained a search target in the past. These studies, however, have focused on group characteristics, downplaying the significance of individual differences. In a pre-registered study, we examined the stability of individual differences in two variants of an implicit location probability learning (LPL) task. We tested the possibility that individual differences were stable in variants that shared the same search process, but not in variants involving different search processes. In Experiment 1, participants performed alternating blocks of T-among-Ls and 5-among-2s search tasks. Unbeknownst to them, the search target appeared disproportionately often in one region of space; the high-probability regions differed between the two tasks. LPL transferred between the two tasks. In addition, individuals who showed greater LPL in the T-task also did so in the 5-task and vice versa. In Experiment 2, participants searched for either a camouflaged-T against background noise or a well-segmented T among well-segmented Ls. These two tasks produced task-specific learning that did not transfer between tasks. Moreover, individual differences in learning did not correlate between tasks. Thus, LPL is associated with stable individual differences across variants, but only when the variants share common search processes. [ABSTRACT FROM AUTHOR]

Aims: To identify health literacy profiles in individuals receiving haemodialysis and to explore how these profiles interact with individuals' self‐efficacy, engagement with traditional dietary habits, self‐reported fluid restriction and relative‐interdialytic weight gain. Design: A cross‐sectional study engaging nephrology departments from four hospitals in Guangdong Province, China. Methods: A sample of 433 individuals receiving haemodialysis participated between December 2018 and July 2019. We assessed health literacy, self‐efficacy and self‐reported fluid restriction using the Health Literacy Questionnaire, the Fluid Self‐efficacy Scale and the Fluid Adherence Subscale, respectively. Traditional dietary habits, including daily tea drinking, soup drinking and preserved food consumption, were measured using three yes/no questions. Relative‐interdialytic weight gain was calculated by dividing the mean interdialytic weight gain (from three recent intervals) by dry weight. Latent profile analysis and structural equation modelling were performed. Results: Three health literacy profiles were identified: low, moderate and high. Compared to those in the low health literacy profile, individuals in high and moderate health literacy profiles demonstrated an indirect association with reduced relative‐interdialytic weight gain. This reduction can be attributed to their higher self‐efficacy levels, decreased reliance on dietary habits and higher self‐reported fluid restrictions. Conclusions: Most participants exhibited either low or moderate levels of health literacy. Improving health literacy has the potential to promote self‐efficacy and foster effective fluid restriction, ultimately leading to a reduction in relative‐interdialytic weight gain in individuals receiving haemodialysis. Impact: This study reveals heterogeneity in health literacy levels among individuals receiving haemodialysis and illuminates the connections between an individual's entire spectrum of health literacy and fluid management. These findings provide valuable insights for developing person‐centred fluid management interventions, especially for individuals with diverse cultural dietary backgrounds within the haemodialysis population. Reporting Method: We adhered to the STROBE guideline. Patient or Public Contribution: Patients were included only for collecting their data. [ABSTRACT FROM AUTHOR]

The significant population of Chinese rural-to-urban migrant children has sparked considerable domestic and international concern regarding their disadvantaged family circumstances and their escalating prevalence of internalizing and externalizing problems. Derived from the resource substitution hypothesis, non-cognitive factors such as personality traits may act as "substitution" resources for educational outcomes of children from less privileged families. Yet, the compensatory role of personality traits as substitution resources in children's mental health has received limited attention, including that of migrant children. This study examined the interplay of trait-like grit and family SES on emotional and conduct problems among Chinese migrant and urban children. The current sample consisted of 770 migrant children (Mage = 10.45 and SDage = 0.68 years; 38.4% girls) and their 222 urban counterparts (Mage = 10.34 and SDage = 0.46 years; 45.5% girls). Moderated polynomial regressions with response surface analysis on a two-wave data with an interval of over six months showed that grit served as a "substitution" resource for the less socioeconomically advantaged children. The compensatory effect of perseverance of effort on urban children's emotional problems and that of consistency of interest on migrant children's conduct problems were visualized. Moreover, the two compensatory effects were found to be robust and unique, even after children's effortful control, a grit-related construct, was taken into account. These findings not only support the resource substitution hypothesis, but also underscore the protective role that grit plays in children under less privileged environments. [ABSTRACT FROM AUTHOR]

A high-speed backlight system was adopted to investigate the evolution process of the inside-out-gas (IOG) effervescent atomizer and subsequent influence on spray morphology. The results show that bubble flow and annular flow are the most obvious flow patterns when the liquid flow rate is 20 g/s. During the transition from bubble to annular flow, slug flow occurred at gas–liquid mass ratio (GLR) of 3.2%. The annular flow was observed when the GLR further increased to 6.4%. In particular, when the mixing chamber is in a large bubble flow, an annular flow can still be formed at the orifice for the small exit diameter. For the annular flow, a relatively stable spray cone angle was observed. On the contrary, the slug flow has a greater oscillation for the spray cone angle. It was found that bubble flow in the orifice has little effect on atomization effect. For the spray cone angle, the oscillation in the slug flow is larger. Furthermore, the effects of GLR and liquid injection pressure drop are carefully considered in the empirical formula fitting compared to the widely used empirical formula. The empirical formula of the discharge coefficient of the effervescent atomizer is fitted, which provides fast data support for engineering applications. [ABSTRACT FROM AUTHOR]

Introduction: Stroke is one of the common diseases that pose a severe threat to human health, with immune cells playing a crucial role in its onset and recovery. However, the specific mechanisms and causal relationships of different immune cell groups in various clinical stroke subtypes are unclear. This study explored the causal relationship between immune cells and stroke and its subtypes using Mendelian randomization (MR) analysis. Methods: Data from genome-wide association studies were analyzed using inverse-variance weighted (IVW), MR-Egger, and weighted median methods for MR analysis, along with heterogeneity tests, sensitivity analysis, and pleiotropy analysis. Results: CD45RA+CD28−CD8+ T cell %T cell (OR 1.002, 95% CI 1.001–1.003; PFDR = 0.02), CD27 on CD24+CD27+ B cell (OR 1.127, 95% CI 1.061–1.198; PFDR = 0.04), CD27 on IgD−CD38dim B cell (OR 1.138, 95% CI 1.076–1.203; PFDR = 0.005), and CD27 on switched memory B cell (OR 1.144, 95% CI 1.076–1.216; PFDR = 0.01) were found to increase the risk of large artery stroke. Switched memory B cell %lymphocyte (OR 1.206, 95% CI 1.103–1.318; PFDR = 0.02) increased the risk of small vessel stroke. Reverse MR analysis did not reveal any reverse causal associations. Furthermore, by substituting the outcome data, a secondary MR analysis was conducted to validate the primary findings. Conclusion: Our study reveals several causal links between immune phenotypes and stroke and its different subtypes, highlighting the complex interactions between the immune system and stroke. These findings provide new directions for further uncovering the biological basis of stroke and assist in advancing research on early interventions and treatment strategies. [ABSTRACT FROM AUTHOR]

Introduction: Recruitment is complete in the fourth INTEnsive ambulance-delivered blood pressure Reduction in hyper-ACute stroke Trial (INTERACT4), a multicenter, prospective, randomized, open-label, blinded endpoint assessed trial of prehospital blood pressure (BP) lowering initiated in the ambulance for patients with a suspected acute stroke and elevated BP in China. According to the registered and published trial protocol and developed by the blinded trial Steering Committee and Operations team, this manuscript outlines a detailed statistical analysis plan for the trial prior to database lock. Methods: Patients were randomized (1:1) to intensive (target systolic BP 130–140 mm Hg within 30 min) or guideline-recommended BP management (BP lowering only considered if systolic BP >220 mm Hg) group. Primary outcome is an ordinal analysis of the full range of scores on the modified Rankin scale at 90 days. A modified sample size of 2,320 was estimated to provide 90% power to detect a 22% reduction in the odds (common odds ratio of 0.78) of a worse functional outcome using ordinal logistic regression, on the assumption of 5% patients with missing outcome and 6% patients with a stroke mimic. Conclusion: The statistical analysis plan for the trial has been developed to ensure transparent, verifiable, and prespecified analysis and to avoid potential bias in the evaluation of the trial intervention. [ABSTRACT FROM AUTHOR]

Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities. [ABSTRACT FROM AUTHOR]

Material science has historically evolved in tandem with advancements in technologies for characterization, synthesis, and computation. Another type of technology to add to this mix is machine learning (ML) and artificial intelligence (AI). Now increasingly sophisticated AI‐models are seen that can solve progressively harder problems across a variety of fields. From a material science perspective, it is indisputable that machine learning and artificial intelligence offer a potent toolkit with the potential to substantially accelerate research efforts in areas such as the development and discovery of new functional materials. Less clear is how to best harness this development, what new skill sets will be required, and how it may affect established research practices. In this paper, those question are explored with respect to increasingly more sophisticated ML/AI‐approaches. To structure the discussion, a conceptual framework of an AI‐ladder is introduced. This AI‐ladder ranges from basic data‐fitting techniques to more advanced functionalities such as semi‐autonomous experimentation, experimental design, knowledge generation, hypothesis formulation, and the orchestration of specialized AI modules as stepping‐stones toward general artificial intelligence. This ladder metaphor provides a hierarchical framework for contemplating the opportunities, challenges, and evolving skill sets required to stay competitive in the age of artificial intelligence. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation This study was undertaken to delineate 21‐year sex‐specific trends in recurrence and postrecurrence mortality.Between 2000 and 2020, first‐ever ischemic stroke (IS) patients, ascertained from the population‐based BASIC (Brain Attack Surveillance in Corpus Christi) project in South Texas, were followed for recurrent stroke and all‐cause mortality until December 31, 2020. Multivariable regression models with an interaction between calendar year and sex were used to estimate sex‐specific trends and sex differences in recurrence and postrecurrence mortality.Of the 6,057 IS patients (median age = 69 years, 49.8% women), 654 (10.8%) had a recurrence and 399 (47.7%) had postrecurrence mortality during 5 years of follow‐up. In 2000, women had 2.5% higher albeit non‐statistically significant 5‐year risk of recurrence than men in absolute scale. With the trend declining in women by 7.6% (95% confidence interval [CI] = −10.8 to −4.5%) and in men by 3.6% (95% CI = −6.5% to −0.7%), the risk at the end of the study period was 1.5% (95% CI = −0.3% to 3.6%) lower among women than men. For postrecurrence mortality, the risk was 10.2% lower among women in 2000, but the sex difference was 3.3% by the end of the period, which was due to a larger overall increase in the risk among women than men over the entire time period.The declines in recurrent stroke suggest successful secondary stroke prevention, especially in women. However, the continued high postrecurrence mortality among both sexes at the end of study period emphasizes the need for ongoing interventions to improve prognosis in those who have had recurrent cerebrovascular events. ANN NEUROL 2024 [ABSTRACT FROM AUTHOR]

Reversion from mild cognitive impairment (MCI) to normal cognition (NC) is not uncommon and indicates a better cognitive trajectory. This study aims to identify predictors of MCI reversion and develop a predicting model. A total of 391 MCI subjects (mean age = 74.3 years, female = 61 %) who had baseline data of magnetic resonance imaging, clinical, and neuropsychological measurements were followed for two years. Multivariate logistic analyses were used to identify the predictors of MCI reversion after adjusting for age and sex. A stepwise backward logistic regression model was used to construct a predictive nomogram for MCI reversion. The nomogram was validated by internal bootstrapping and in an independent cohort. In the training cohort, the 2-year reversion rate was 19.95 %. Predictors associated with reversion to NC were higher education level (p = 0.004), absence of APOE 4 allele (p = 0.001), larger brain volume (p < 0.005), better neuropsychological measurements performance (p < 0.001), higher glomerular filtration rate (p = 0.035), and lower mean arterial pressure (p = 0.060). The nomogram incorporating five predictors (education, hippocampus volume, the Alzheimer's Disease Assessment Scale-Cognitive score, the Rey Auditory Verbal Learning Test-immediate score, and mean arterial pressure) achieved good C-indexes of 0.892 (95 % confidence interval [CI], 0.859–0.926) and 0.806 (95 % CI, 0.709–0.902) for the training and validation cohort. Observational duration is relatively short; The predicting model warrant further validation in larger samples. This prediction model could facilitate risk stratification and early management for the MCI population. • The 2-year reversion rate from MCI to NC was 19.95%. • Predictors of reversion included education, APOE4 allele, brain volume, neuropsychological tests performance, eGFR, and MAP. • The predicting model achieved good performance for the training and validation cohort. [ABSTRACT FROM AUTHOR]

Metallic lithium (Li) is recognized as a promising candidate for anode material of Li‐ion batteries owing to high theoretical specific capacity and low redox potential. However, uncontrollable dendrite growth and huge volume expansion during Li plating/stripping processes hinder its practical application. Herein, N‐doped carbon nanofibers@MoP nanoflakes (NCNF@MoP) is developed as a potential host to address the above challenges. During the formation of solid electrolyte interphase, MoP nanoflakes can be changed into metallic Mo with high lithiophilicity and Li3P with high ionic conductivity. The whole composite host is transformed into a mixed ion/electron conducting network to reduce nucleation overpotential and accelerate diffusion kinetics at the electrode/electrolyte interface. As a proof of concept, the symmetric cell using NCNF@MoP host presents a long‐term cycling up to 2500 h with a low nucleation overpotential of 10 mV at 1 mA cm−2. Additionally, the Li‐NCNF@MoP||LiFePO4 full cell demonstrates a good capacity retention of 92.6% over 2200 cycles at a high current density of 5C (1 C = 169 mA g−1). [ABSTRACT FROM AUTHOR]

Projecting a vector onto a simplex is a well-studied problem that arises in a wide range of optimization problems. Numerous algorithms have been proposed for determining the projection; however, the primary focus of the literature is on serial algorithms. We present a parallel method that decomposes the input vector and distributes it across multiple processors for local projection. Our method is especially effective when the resulting projection is highly sparse, which is the case, for instance, in large-scale problems with independent and identically distributed (i.i.d.) entries. Moreover, the method can be adapted to parallelize a broad range of serial algorithms from the literature. We fill in theoretical gaps in serial algorithm analysis and develop similar results for our parallel analogues. Numerical experiments conducted on a wide range of large-scale instances, both real world and simulated, demonstrate the practical effectiveness of the method. History: Accepted by Antonio Frangioni, Area Editor for Design & Analysis of Algorithms—Continuous. Funding: This work was supported by the Office of Naval Research [Grant N00014-23-1-2632]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0328) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0328). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]

Hydroxychloroquine (HCQ), 2‐([4‐([7‐Chloro‐4‐quinolyl]amino)pentyl]ethylamino)ethanol, exhibited significant biological activity, while its side effects cannot be overlooked. The RP‐HPLC enantio‐separation was investigated for cost‐effective and convenient optical purity analysis of HCQ. The thermodynamic resolution of Rac‐HCQ, driven by enthalpy and entropy, was achieved on the C18 column using Carboxymethyl‐β‐cyclodextrin (CM‐β‐CD) as the chiral mobile phase agent (CMPA). The effects of CCM‐β‐CD, pH, and triethylamine (TEA) V% on the enantio‐separation process were explored. Under the optimum conditions at 24°C, the retention times for the two enantiomers were tR1=29.39min$$ {t}_{R1}=29.39\ \min $$ and tR2=32.42min$$ {t}_{R2}=32.42\ \min $$, resulting in Rs=1.87$$ {R}_s=1.87 $$. The resolution via diastereomeric salt formation of Rac‐HCQ was developed to obtain the active pharmaceutical ingredient of single enantiomer S‐HCQ. Di‐p‐Anisoyl‐L‐Tartaric Acid (L‐DATA) was proved effective as the resolution agent for Rac‐HCQ. Surprisingly, it was found that refluxing time was a key fact affecting the resolution efficiency, which meant the kinetic dominate during the process of the resolution. Four factors—solvent volume, refluxing time, filtration temperature, and molar ratio—were optimized using the single‐factor method and the response surface method. Two cubic models were established, and the reliability was subsequently verified. Under the optimal conditions, the less soluble salt of 2L‐DATA:S‐HCQ was obtained with a yield of 96.9% and optical purity of 63.0%. The optical purity of this less soluble salt increases to 99.0% with a yield of 74.2% after three rounds recrystallization. [ABSTRACT FROM AUTHOR]

With the rapid development of molecular sequencing and imaging technology, the multi-omics of medicinal plants enters the single-cell era. We discuss spatial multi-omics applied in medicinal plants, evaluate the special products' biosynthesis pathways, and highlight the applications, perspectives, and challenges of biomanufacturing natural products (NPs). [ABSTRACT FROM AUTHOR]

Training deep learning models for vision-based monitoring of construction sites usually requires a large amount of labeled data. Semisupervised learning methods can efficiently obtain unlabeled data with substantial cost savings. Thus, this paper proposes a semisupervised object detection method for construction site monitoring. Weather as well as strong and weak data augmentation are integrated to cope with the complex construction site conditions (weather changes, camera view shifts, and so on) by integrating semisupervised learning to leverage the valid information in unlabeled construction site images. To validate its effectiveness, the proposed method was tested on the Alberta Construction Image Data Set (ACID), a public data set for the construction research community. The experimental results revealed that the proposed method achieves an average accuracy [mean average precision (mAP)] of 81.1% when trained on only 3% of the labeled images. This study helps to significantly reduce the development cost of vision-based object detection models for construction sites. [ABSTRACT FROM AUTHOR]

This paper reports the successful fabrication of a new nanofibrous membrane, F-PI/PAN, through electrospinning of polyacrylonitrile (PAN) and fluorinated polyimide (F-PI). The nanofibrous membrane exhibits comprehensive properties for high-temperature filtration and robust PM2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 microns or less) removal. The introduction of F enhances the hydrophobicity of the PI. The relationship between the hydrophobic performance and the filtration performance of particles is investigated. The chemical group of the composite membrane was demonstrated using FITR, while the surface morphology was investigated using field emission scanning electron microscopy. The TGA results indicated good thermal stability at 300 °C. Various ratios of F-PI membranes were prepared to characterize the change in properties, with the optimal mass ratio of F-PI being 20 wt%. As the proportion of F-PI increases, its mechanical and filtration efficiency properties and hydrophobicity become stronger. The contact angle reaches its maximum of 128 ± 5.2° when PAN:F-PI = 6:4. Meanwhile, when PAN:F-PI = 8:2, the filtration efficiency reaches 99.4 ± 0.3%, and the elongation at break can reach 76%. The fracture strength can also reach 7.1 MPa, 1.63 times that of the pure PAN membrane. [ABSTRACT FROM AUTHOR]

A novel framework for adaptive energy management, rooted in deep learning principles, is proposed to minimize fuel consumption in extended‐range electric vehicles amidst intricate driving scenarios. This innovative approach integrates a long short‐term memory (LSTM) network for pattern recognition across three driving patterns and an adaptive fuzzy controller. To mitigate the impact of poor hyperparameter selection on recognition accuracy, Gray Wolf Optimization is employed to optimize the hidden layer nodes, training times, and learning rate of the LSTM. Simultaneously, a genetic algorithm is utilized to optimize the vertex coordinates of the fuzzy control membership function, enabling the adaptive adjustment of parameters in the fuzzy energy management strategy. The condition recognition model accurately identifies the vehicle's driving status and seamlessly transitions to an energy management strategy tailored to the present conditions. This ensures optimal operation, enhancing overall fuel efficiency and performance. The simulation results robustly validate the efficacy of this approach: the GWO‐LSTM network achieves an impressive 97.7% accuracy in recognizing working conditions, surpassing the 88.9% accuracy of the traditional LSTM network. Furthermore, the fuel consumption reduction achieved by the adaptive fuzzy energy management strategy amounts to 11.9% compared with the conventional fuzzy energy management approach. This outcome underscores the tangible enhancement in vehicle fuel economy resulting from the seamless integration of deep learning techniques. [ABSTRACT FROM AUTHOR]

Lactate dehydrogenase A (LDHA) primarily catalyzes the conversion between lactic acid and pyruvate, serving as a key enzyme in the aerobic glycolysis pathway of sugar in tumor cells. LDHA plays a crucial role in the occurrence, development, progression, invasion, metastasis, angiogenesis, and immune escape of tumors. Consequently, LDHA not only serves as a biomarker for tumor diagnosis and prognosis but also represents an ideal target for tumor therapy. Although LDHA inhibitors show great therapeutic potential, their development has proven to be challenging. In the development of LDHA inhibitors, the key active sites of LDHA are emphasized. Nevertheless, there is a relative lack of research on the amino acid residues around the active center of LDHA. Therefore, in this study, we investigated the amino acid residues around the active center of LDHA. Through structure comparison analysis, five key amino acid residues (Ala30, Met41, Lys131, Gln233, and Ala259) were identified. Subsequently, the effects of these five residues on the enzymatic properties of LDHA were investigated using site-directed mutagenesis. The results revealed that the catalytic activities of the five mutants varied to different degrees in both the reaction from lactic acid to pyruvate and pyruvate to lactic acid. Notably, the catalytic activities of LDHAM41G and LDHAK131I were improved, particularly in the case of LDHAK131I. The results of the molecular dynamics analysis of LDHAK131I explained the reasons for this phenomenon. Additionally, the optimum temperature of LDHAM41G and LDHAQ233M increased from 35 °C to 40 °C, whereas in the reverse reaction, the optimum temperature of LDHAM41G and LDHAK131I decreased from 70 °C to 60 °C. These findings indicate that Ala30, Met41, Lys131, Gln233, and Ala259 exert diverse effects on the catalytic activity and optimum temperature of LHDA. Therefore, these amino acid residues, in addition to the key catalytic site of the active center, play a crucial role. Considering these residues in the design and screening of LDHA inhibitors may lead to the development of more effective inhibitors. [ABSTRACT FROM AUTHOR]

The widespread antimicrobial resistance (AMR) calls for the development of new antimicrobial strategies. Antibiotic adjuvant rescues antibiotic activity and increases the life span of the antibiotics, representing a more productive, timely, and cost-effective strategy in fighting drug-resistant pathogens. Antimicrobial peptides (AMPs) from synthetic and natural sources are considered new-generation antibacterial agents. Besides their direct antimicrobial activity, growing evidence shows that some AMPs effectively enhance the activity of conventional antibiotics. The combinations of AMPs and antibiotics display an improved therapeutic effect on antibiotic-resistant bacterial infections and minimize the emergence of resistance. In this review, we discuss the value of AMPs in the age of resistance, including modes of action, limiting evolutionary resistance, and their designing strategies. We summarise the recent advances in combining AMPs and antibiotics against antibiotic-resistant pathogens, as well as their synergistic mechanisms. Lastly, we highlight the challenges and opportunities associated with the use of AMPs as potential antibiotic adjuvants. This will shed new light on the deployment of synergistic combinations to address the AMR crisis. [ABSTRACT FROM AUTHOR]

Redox is a unique, programmable modality capable of bridging communication between biology and electronics. Previous studies have shown that the E. coli redox-responsive OxyRS regulon can be re-wired to accept electrochemically generated hydrogen peroxide (H2O2) as an inducer of gene expression. Here we report that the redox-active phenolic plant signaling molecule acetosyringone (AS) can also induce gene expression from the OxyRS regulon. AS must be oxidized, however, as the reduced state present under normal conditions cannot induce gene expression. Thus, AS serves as a "pro-signaling molecule" that can be activated by its oxidation—in our case by application of oxidizing potential to an electrode. We show that the OxyRS regulon is not induced electrochemically if the imposed electrode potential is in the mid-physiological range. Electronically sliding the applied potential to either oxidative or reductive extremes induces this regulon but through different mechanisms: reduction of O2 to form H2O2 or oxidation of AS. Fundamentally, this work reinforces the emerging concept that redox signaling depends more on molecular activities than molecular structure. From an applications perspective, the creation of an electronically programmed "pro-signal" dramatically expands the toolbox for electronic control of biological responses in microbes, including in complex environments, cell-based materials, and biomanufacturing. [ABSTRACT FROM AUTHOR]

Background: To develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis. Methods: A total of 2211 ultrasound images of 980 pathologically confirmed PTs (Training set: n = 721; Validation set: n = 82; Internal-test set: n = 89; External-test set: n = 88) from 907 patients were retrospectively included in this study. The optimal model was selected and the diagnostic performance evaluation is conducted by utilizing the area under curve (AUC) of the receiver-operating characteristic(ROC) based on five different DL networks constructed at varying depths. Furthermore, a comparison of different seniority radiologists was made in the presence of the optimal auxiliary diagnosis model. Additionally, the diagnostic confusion matrix of the optimal model was calculated, and an analysis and summary of misjudged cases' characteristics were conducted. Results: The Resnet18 demonstrated superior diagnostic performance, with an AUC value of 0.947, accuracy of 88.5%, sensitivity of 78.2%, and specificity of 92.7% in internal-test set, and with an AUC value of 0.925, accuracy of 89.8%, sensitivity of 83.3%, and specificity of 90.6% in external-test set. The PTs were subjectively assessed twice by six radiologists, both with and without the assisted of the model. With the assisted of the model, both junior and senior radiologists demonstrated enhanced diagnostic performance. In the internal-test set, there was an increase in AUC values by 0.062 and 0.082 for junior radiologists respectively, while senior radiologists experienced an improvement of 0.066 and 0.106 in their respective AUC values. Conclusions: The DL model based on ultrasound images demonstrates exceptional capability in distinguishing between benign and malignant PTs, thereby assisting radiologists of varying expertise levels to achieve heightened diagnostic performance, and serve as a noninvasive imaging adjunct diagnostic method for clinical purposes. [ABSTRACT FROM AUTHOR]

PURPOSE: Preoperative prediction of postoperative complications (PCs) in inpatients with cancer is challenging. We developed an explainable machine learning (ML) model to predict PCs in a heterogenous population of inpatients with cancer undergoing same-hospitalization major operations. METHODS: Consecutive inpatients who underwent same-hospitalization operations from December 2017 to June 2021 at a single institution were retrospectively reviewed. The ML model was developed and tested using electronic health record (EHR) data to predict 30-day PCs for patients with Clavien-Dindo grade 3 or higher (CD 3+) per the CD classification system. Model performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), and calibration plots. Model explanation was performed using the Shapley additive explanations (SHAP) method at cohort and individual operation levels. RESULTS: A total of 988 operations in 827 inpatients were included. The ML model was trained using 788 operations and tested using a holdout set of 200 operations. The CD 3+ complication rates were 28.6% and 27.5% in the training and holdout test sets, respectively. Training and holdout test sets' model performance in predicting CD 3+ complications yielded an AUROC of 0.77 and 0.73 and an AUPRC of 0.56 and 0.52, respectively. Calibration plots demonstrated good reliability. The SHAP method identified features and the contributions of the features to the risk of PCs. CONCLUSION: We trained and tested an explainable ML model to predict the risk of developing PCs in patients with cancer. Using patient-specific EHR data, the ML model accurately discriminated the risk of developing CD 3+ complications and displayed top features at the individual operation and cohort level. This article shows that machine learning algorithms can estimate preoperative risk in patients with cancer. [ABSTRACT FROM AUTHOR]

The environmental impact from the waste disposal has been widely concerned around the world. The conversion of wastes to useful resources is important for the sustainable society. As a typical family of wastes, biomass materials basically composed of collagen, protein and lignin are considered as useful resources for recycle and reuse. In recent years, the development of carbon material derived from biomasses, such as plants, crops, animals and their application in electrochemical energy storage have attracted extensive attention. Through the selection of the appropriate biomass, the optimization of the activation method and the control of the pyrolysis temperatures, carbon materials with desired features, such as high‐specific surface area, variable porous framework, and controllable heteroatom‐doping have been fabricated. Herein, this review summarized the preparation methods, morphologies, heteroatoms doping in the plant/animal‐derived carbonaceous materials, and their application as electrode materials for secondary batteries and supercapacitors, and as electrode support for lithium‐sulfur batteries. The challenges and prospects for the controllable synthesis and large‐scale application of biomass‐derived carbonaceous materials have also been outlooked. [ABSTRACT FROM AUTHOR]

The development and integration of high-performance electronic devices are critical in advancing energy storage with dielectric capacitors. Poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) (PVTC), as an energy storage polymer, exhibits high-intensity polarization in low electric strength fields. However, a hysteresis effect can result in significant residual polarization, leading to a severe energy loss, which impacts the resultant energy storage density and charge/discharge efficiency. In order to modify the polarization properties of the polymer, a biaxially oriented polypropylene (BOPP) film with linear characteristics has been selected as an insulating layer and combined with the PVTC ferroelectric polarization layer to construct PVTC/BOPP bilayer films. The hetero-structure and polarization characteristics of the bilayer film have been systematically studied. Adjusting the BOPP volume content to 67% resulted in a discharge energy density of 10.1 J/cm3 and an energy storage efficiency of 80.9%. The results of this study have established the mechanism for a composite structure regulation of macroscopic energy storage performance. These findings can provide a basis for the effective application of ferroelectric polymer-based composites in dielectric energy storage. [ABSTRACT FROM AUTHOR]

A widely used organophosphate flame retardant (OPFR), triphenyl phosphate (TPP), is frequently detected in various environmental media and humans. However, there is little known on the human corneal epithelium of health risk when exposed to TPP. In this study, human normal corneal epithelial cells (HCECs) were used to investigate the cell viability, morphology, apoptosis, and mitochondrial membrane potential after they were exposed to TPP, as well as their underlying molecular mechanisms. We found that TPP decreased cell viability in a concentration-dependent manner, with a half maximal inhibitory concentration (IC50) of 220 μM. Furthermore, TPP significantly induced HCEC apoptosis, decreased mitochondrial membrane potential in a dose-dependent manner, and changed the mRNA levels of the apoptosis biomarker genes (Cyt c, Caspase-9, Caspase-3, Bcl-2, and Bax). The results showed that TPP induced cytotoxicity in HCECs, eventually leading to apoptosis and changes in mitochondrial membrane potential. In addition, the caspase-dependent mitochondrial pathways may be involved in TPP-induced HCEC apoptosis. This study provides a reference for the human corneal toxicity of TPP, indicating that the risks of OPFR to human health cannot be ignored. [ABSTRACT FROM AUTHOR]

The terahertz spectral region, which bridges between electronics and optics, is poised to play an important role in the development of transformative wireless communication and imaging systems with unprecedented functionality. Currently, a major challenge in terahertz technology is to develop high‐performance terahertz beam‐forming devices that can dynamically shape the terahertz radiation in a flexible manner. Existing terahertz beam‐forming devices have limited coding bits, field‐of‐view, and beam gain. Here, a reconfigurable liquid crystal‐integrated terahertz metasurface is experimentally demonstrated, with each metasurface unit cell being independently addressable. The metasurface has a 260° continuous phase tuning range with a liquid crystal layer thickness of only 1% of the free‐space wavelength. The terahertz wave diffracted from the metasurface can be steered toward a wide range of directions is shown, covering a record‐large 110° field‐of‐view with a peak gain of 25 dBi. The metasurface also features a low power consumption and sub‐second switching time. Furthermore, the formation of multiple terahertz beams is demonstrated, with the direction of each beam and the power ratio between beams adjustable on demand. The proposed liquid crystal metasurface possesses compelling prospects for future terahertz communication and imaging applications. [ABSTRACT FROM AUTHOR]

AbstractIntersectionality has facilitated an understanding of the complexities of the adversities and challenges faced by individuals with multiple disadvantaged identities, including gay and bisexual men living with HIV. This study used deficiency- and empowerment-based perspectives together with an intersectionality lens to examine the intersections between sexuality minority and HIV-related stigma and resilience, as well as their compound effects on Chinese gay and bisexual men living with HIV. We conducted in-depth interviews with 21 gay and bisexual men living with HIV in Shenzhen, identifying two overarching themes and six subthemes in the provided accounts via thematic analysis. The theme of ‘Interplay between Minority Identities’ comprised aggravating effects and alleviating effects at the intrapersonal, interpersonal, community and structural levels. The theme of ‘Compound Impact of Intersecting Identities’ was contributed to by the subthemes ‘the pressure to continue family lineage’, ‘persistent health concerns’, ‘financial concerns’, and ‘heightened psychological distress and resilience’. Integrating deficiency and empowerment perspectives, our findings highlight the importance of addressing intersectional stigma and identifying resilience resources to empower Chinese gay and bisexual men living with HIV to thrive amidst compounded adversities. Findings have implications for future intersectional research and intervention practice, especially in fostering resilience within the context of intersectional stigma. [ABSTRACT FROM AUTHOR]

Objective: To compare the potential efficacy and safety of dual therapy and quadruple therapy with vonoprazan (VPZ) as well as the standard quadruple therapy of proton pump inhibitor (PPI) for the eradication of Helicobacter pylori (Hp) infection in Hainan province. Methods: A single-centre, non-blinded, non-inferiority randomized controlled trial was conducted at the outpatient department of gastroenterology at the Second Affiliated Hospital of Hainan Medical University from June 2022 to February 2023. 135 patients aged 18–75 years with Hp infection were enrolled and randomized into three different groups (group V1: VPZ 20 mg twice a day and amoxicillin 1.0 g three times a day for 14 days V2: vonoprazan 20 mg, amoxicillin capsules 1.0 g, furazolidone 0.1 g and bismuth potassiulm citrate 240 mg, twice daily for 14 days;; group V3: ilaprazole 5 mg, Amoxicillin 1.0 g, Furazolidone 100 mg, bismuth potassiulm citrate 240 mg, twice a day for 14 days). Four weeks after the end of treatment, Hp eradication was confirmed by rechecking 13C-urea breath test (UBT). Results: The eradication efficacy of V1 and V3 was non-inferior to that of V2, which is consistent with the results obtained from the Kruskal-Wallis H test. The eradication rate by intentional analysis was 84.4% (38/45, 95%CI 73.4%–95.5%, P>0.05) for all the three groups. If analyzed by per-protocol, the eradication rates were 88.4% (38/43, 95%CI 78.4%–98.4%), 92.7% (38/41, 95%CI 84.4%–101.0%),88.4% (38/43，95%CI 78.4%–98.4%) in groups V1, V2 and V3, respectively, which did not show a significant difference (P > 0.05). The incidence of adverse effects was significantly lower in VPZ dual therapy compared to the other two treatment regimens (P < 0.05). VPZ dual therapy or quadruple therapy was also relatively less costly than standard quadruple therapy. Conclusion: VPZ dual therapy and quadruple therapy shows promise of not being worse than the standard quadruple therapy by a clinically relevant margin. More studies might be needed to definitively determine if the new therapy is equally effective or even superior. [ABSTRACT FROM AUTHOR]

Highlights Carbon fiber reinforced plastics (CFRP) has strong sensitivity to temperature, as the stacking sequence is titanium alloy (Ti) to CFRP, the damage of CFRP is more severe due to the accumulation of cutting heat. In this study, a stress‐strain constitutive model of CFRP with the effect of thermal stress is proposed. On the basis, a simulation model of drilling Ti/CFRP stacks is established to explore the heat effect on the drilling damage. Based on the results, it can be concluded that the burr of Ti at hole exit is generally low due to the support of CFRP, and the burr height increases by 56.61% as the temperature rises from 182.02 to 355.69 °C. Besides, the intralaminar damage of CFRP is mainly caused by the fiber tensile failure and matrix tensile failure, and the matrix tensile failure is more affected by temperature. Moreover, delamination of CFRP decreases slightly with the reduce of drilling temperature. In addition, serious damage of CFRP on the hole wall usually occurs within the cutting angle of 90° to 135°, and pit defects can be reduced in a lower drilling temperature. A thermal effect stress‐strain constitutive model of CFRP is proposed. Ti/CFRP drilling model is developed based on the proposed constitutive model. Fiber and matrix tensile failure are main form of intralaminar damage of CFRP. Matrix tensile failure is more sensitive to temperature. [ABSTRACT FROM AUTHOR]

Background: Danggui Sini decoction (DSD), a traditional Chinese medicine formula, has the function of nourishing blood, warming meridians, and unblocking collaterals. Our clinical and animal studies had shown that DSD can effectively protect against oxaliplatin (OXA)-induced peripheral neuropathy (OIPN), but the detailed mechanisms remain uncertain. Multiple studies have confirmed that gut microbiota plays a crucial role in the development of OIPN. In this study, the potential mechanism of protective effect of DSD against OIPN by regulating gut microbiota was investigated. Methods: The neuroprotective effects of DSD against OIPN were examined on a rat model of OIPN by determining mechanical allodynia, biological features of dorsal root ganglia (DRG) as well as proinflammatory indicators. Gut microbiota dysbiosis was characterized using 16S rDNA gene sequencing and metabolism disorders were evaluated using untargeted and targeted metabolomics. Moreover the gut microbiota mediated mechanisms were validated by antibiotic intervention and fecal microbiota transplantation. Results: DSD treatment significantly alleviated OIPN symptoms by relieving mechanical allodynia, preserving DRG integrity and reducing proinflammatory indicators lipopolysaccharide (LPS), IL-6 and TNF-α. Besides, DSD restored OXA induced intestinal barrier disruption, gut microbiota dysbiosis as well as systemic metabolic disorders. Correlation analysis revealed that DSD increased bacterial genera such as Faecalibaculum, Allobaculum, Dubosiella and Rhodospirillales_unclassified were closely associated with neuroinflammation related metabolites, including positively with short-chain fatty acids (SCFAs) and sphingomyelin (d18:1/16:0), and negatively with pi-methylimidazoleacetic acid, l-glutamine and homovanillic acid. Meanwhile, antibiotic intervention apparently relieved OIPN symptoms. Furthermore, fecal microbiota transplantation further confirmed the mediated effects of gut microbiota. Conclusion: DSD alleviates OIPN by regulating gut microbiota and potentially relieving neuroinflammation related metabolic disorder. [ABSTRACT FROM AUTHOR]

This project presents a quantitative detection method to identify raccoon‐derived ingredient adulteration in sausage products. The specific copy gene of the raccoon was selected as the target gene. According to the specificity of its primer and probe, the quantitative detection method of raccoon microdrops by droplet digital PCR was established. In addition, the accuracy of the proposed method was verified by artificially mixed samples, and the applicability of this method was tested based on the commercially available products. The experimental results indicate that the raccoon mass (M) and raccoon‐extracted DNA concentration have a good linear relationship when the sample content is 5–100 mg, and there is also a significant linear relationship between DNA content and DNA copy number (C) with R2 =.9982. Therefore, using DNA concentration as the median signal, the conversion equation between raw raccoon mass (M) and DNA copy number (C) could be obtained as follows: M = (C + 177.403)/16.954. The detection of artificially mixed samples and commercial samples shows that the method is accurate and suitable for quantitative adulteration detection of various sausage products in the market. [ABSTRACT FROM AUTHOR]

The accelerated calcium dissolution tests of concrete with different replacement rates of manufactured sand (ρms) and different contents of stone powder (ρsp) were carried out using the ammonium chloride solution. The results show that the dissolution resistance of manufactured sand concrete (MSC) is higher than that of ordinary concrete, although the ρms and ρsp influence its physical and mechanical properties. When the ρms is low, the mass loss ratio and dissolution depth of MSC after dissolution both increase with the increasing ρsp. They also increase with the increasing of ρms, but the ρsp no longer influences them when the ρms is high. The ρsp corresponding to the maximum ultrasonic velocity of MSC is different for the various ρms. The addition of manufactured sand inhibits the reduction of the compressive strength after dissolution, while stone powder has no significant impact on this. Finally, the fitting model of dissolution depth and prediction model of compressive strength of MSC after dissolution are established. [ABSTRACT FROM AUTHOR]

Although many researchers have examined the synchronization characteristics of numerous dynamic models, equipment that utilizes synchronization phenomena with high yield, optimal isolation effect, and robust stability performance has not yet been completely into reality. In this paper, a novel model scheme with three bodies driven by four vibrators is presented, and the aim is to clarify the mechanism of synchronization and stability and find the self-balancing behavior of the system where the dynamic load transmitted to the foundation is zero. The motion differential equations of the system and the theoretical criteria for achieving stable synchronization behavior are provided. The kinetic and coupling dynamic characteristics of the system are discussed in detail through numerical analyses, including the stable states of four vibrators, phase relationships among three bodies, synchronization and stability ability coefficients, and a maximum of the coupling torque, etc. It shows that the self-balancing behavior of the system is occurring in Region 2, where the reverse relative motion of two rigid bodies exhibits stronger harmonic vibration, and the isolation body embodies no vibration, which probably leads to the minimum of transmitting the dynamic loads to the foundation. Additionally, it found the diversity of the nonlinear system, which is in all the other Regions except for Region 2. The characteristics analysis and simulation results verify the validity and feasibility of the theoretical investigation. [ABSTRACT FROM AUTHOR]

The existing constitutive models of shape memory alloy (SMA) cannot accurately describe the mechanical behavior in martensitic strengthening segment since their loading and unloading paths in strengthening segment completely overlap. This study proposes a multi-segment linear mathematical model for SMA, which realizes the separation of loading path and unloading path in strengthening segment. A four-story steel frame structure and corresponding braced structures with various SMA constitutive models are designed, and seismic control effects of SMA braces with these models are analyzed and compared through time history analysis. The results show that the sub-cycle unloading mode of SMA constitutive model affects the seismic mitigation capacity of SMA brace in a certain extent. The position of the inflection point of unloading path has very little influence on the structural control ability of SMA braces. The SMA brace using the SMA constitutive model with a single linear sub-cyclic unloading path has the minimal seismic response and the highest seismic reduction ratio. For most evaluation indexes, the seismic mitigation ability calculated by the proposed path separation constitutive model is in the middle of the results calculated by the existing models. SMA models without considering the mechanical behavior of strengthening segment may lead to an erroneous estimation of the energy consumption of SMA brace and the structural damage. The difference of simulation results among various SMA constitutive models is almost independent with ground motion. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to propose a deep learning (DL)–based framework for identifying the composition of thyroid nodules and assessing their malignancy risk. Methods: We conducted a retrospective multicenter study using ultrasound images from four hospitals. Convolutional neural network (CNN) models were constructed to classify ultrasound images of thyroid nodules into solid and non-solid, as well as benign and malignant. A total of 11,201 images of 6784 nodules were used for training, validation, and testing. The area under the receiver-operating characteristic curve (AUC) was employed as the primary evaluation index. Results: The models had AUCs higher than 0.91 in the benign and malignant grading of solid thyroid nodules, with the Inception-ResNet AUC being the highest at 0.94. In the test set, the best algorithm for identifying benign and malignant thyroid nodules had a sensitivity of 0.88, and a specificity of 0.86. In the human vs. DL test set, the best algorithm had a sensitivity of 0.93, and a specificity of 0.86. The Inception-ResNet model performed better than the senior physicians (p < 0.001). The sensitivity and specificity of the optimal model based on the external test set were 0.90 and 0.75, respectively. Conclusions: This research demonstrates that CNNs can assist thyroid nodule diagnosis and reduce the rate of unnecessary fine-needle aspiration (FNA). Clinical relevance statement: High-resolution ultrasound has led to increased detection of thyroid nodules. This results in unnecessary fine-needle aspiration and anxiety for patients whose nodules are benign. Deep learning can solve these problems to some extent. Key Points: • Thyroid solid nodules have a high probability of malignancy. • Our models can improve the differentiation between benign and malignant solid thyroid nodules. • The differential performance of one model was superior to that of senior radiologists. Applying this could reduce the rate of unnecessary fine-needle aspiration of solid thyroid nodules. [ABSTRACT FROM AUTHOR]

Bicycles and other forms of micromobility have been anecdotally used in past disasters to help save lives and improve community recovery. However, research and practice are scarce on this resilient transportation strategy, which limits its usefulness and possible benefits. To fill this gap, our paper investigates the potential role bicycles and micromobility in facilitating (or limiting) disaster response and recovery. Given the lack of exploration on the topic, we convened an online workshop where we conducted brainstorming and focus group discussions with disaster experts from various government agencies, not-for-profit organizations, academia, and policy groups. We present a synthesis of that discussion, along with a review of the existing literature. We conclude there is strong potential for bicycles and micromobility for different disaster phases, hazard types, and groups of people. However, multiple barriers exist related to implementation and safety, suggesting a need for future research and policy in the transportation and emergency management fields and practices. • Feasibility of micromobility to aid evacuation is determined by disaster type, disaster phase, vehicle type, and geography. • Micromobility has the potential to aid both the short-term response and longer-term recovery from natural disasters. • Micromobility is flexible and cheap for resource movement and can navigate roads that are impassable for cars and trucks. • Availability of bikes and micro-modes is both a barrier and a facilitator for use during disaster response. • Many political and coordination barriers remain to make micromobility a part of disaster planning. [ABSTRACT FROM AUTHOR]

• Explore the relationship between industrial solid waste and socioeconomic. • Analyze the flow relationships among different sectors of industrial solid waste. • Determine the industrial solid waste discharge responsibility for each sector. • Identify the key sectors for industrial solid waste discharge. • Simulate industrial solid waste reduction measures. Rapid economic development inevitably leads to the discharge of a large amount of common industrial solid waste (CISW), which not only pollutes the environment but also restricts economic development in turn. In this study, a dynamic common industrial solid waste (DCISW) model is developed to analyze the retrospectively CISW development in Shanghai from 2000 to 2017 and simulate prospectively multi-perspective emission reduction measures. Specifically, the dynamic linkages between CISW and socio-economics are established at both the systematic and sectoral levels through input–output analysis, ecological network analysis, and related socio-economic indicators. Abatement measure simulations are conducted using RAS and other methods. The findings reveal that the growth of CISW in Shanghai is closely related to its fast-growing economy. The Others sector (OS) receives the most CISW from other sectors, while the Mining industry (MI) sends the most CISW to others. From production-based, consumption-based, and income-based perspectives, Chemical Products (CP) consistently remain the largest contributors. For the proposed waste generation intensity (WGI) indicator, the Mining industry (MI) is regarded as the main sector in all three perspectives. Moreover, the MI consistently emerges as the key sector of the system. CISW simulations indicate that improving the MI emission technology and increasing the MI output value will be top priorities for CISW emission reduction in Shanghai. This study is expected to provide scientific support to address the CISW problem in Shanghai and other similar fast-growing metropolises. [ABSTRACT FROM AUTHOR]

The urbanization of suburbs has a significant impact on ocular health, however, the effect of this phenomenon on the epidemiology of eye diseases in the sub-urbanization region of China remains unclear. In this context, the population-based Beichen Eye Study (BCES) was conducted in the Beichen District of Tianjin, China. This article aims to summarize the background, design scheme and operation process of the study. The Chinese Clinical Trial Registry number was ChiCTR2000032280. In total, 8218 participants were randomly selected by a multi-stage sampling method. After their qualification was confirmed, participants were mainly invited to a centralized clinic via telephone interviews after promotion of the study in the community. Examinations included a standardized interview, anthropometric assessment, autorefraction, ocular biometry, visual acuity, anterior and posterior segment examinations, dry eye disease (DED), intra-ocular pressure, visual field testing, gonioscopy, and imaging of anterior segment, posterior segment, fundus, and optic disc. A peripheral venous blood sample was also collected for biochemical testing. For observational purposes, a community-based type II diabetes mellitus management mode was created and assessed for its effect in preventing the progression of diabetic retinopathy (DR). Of the 8,218 residents, 7,271 were eligible for inclusion, and 5,840 (80.32%) subjects were enrolled in the BCES. Most of the participants were female (64.38%) with a median age of 63 years, and 98.23% representing Han Chinese descent. Conclusions: This study provides insights into the epidemiological characteristics of major ocular diseases and their moderators in a suburbanized region of China. [ABSTRACT FROM AUTHOR]

Scale-resolving solutions for computational fluid dynamics problems have usually been challenging due to their request for computing resources. A two-scale framework was proposed for more efficient solutions to couple a local fine-mesh solution with a global coarse-mesh solution. The methodology was successfully implemented and demonstrated for a canonical turbulent channel flow and for a tripped turbulent boundary layer. The solution mapping from the local fine-mesh to the global coarse-mesh region is realized by modifying the flow-governing equations in the under-resolved coarse-mesh region through adding extra forcing source terms generated from the space-time-averaged fine-mesh solutions. However, the high-gradient transitional region presents additional challenges when applying the Chebyshev spectral method for mapping the source terms; thus the high-gradient frontal region has not been fully resolved in the streamwise direction. In the present work, the propagation of the source terms is facilitated by machine learning tools (multilayer perceptron-based neural network) so as to implement the method in flowfields with high gradients or drastic changes in the mean velocity. The neural-network-based propagation model is shown to be capable of accurately estimating the source terms in the near-wall coarse-mesh region. The mean flow there thus can be nicely reproduced by the source-term propagation. The machine-learning tools thus provide potential as the more advanced source-term propagation method for the two-scale framework to be implemented in more complicated flowfields. [ABSTRACT FROM AUTHOR]

Pumpkin (Cucurbita maxima) is an important vegetable crop of the Cucurbitaceae plant family. The fruits of pumpkin are often used as directly edible food or raw material for a number of processed foods. In nature, mature pumpkin fruits differ in size, shape, and color. The Atlantic Giant (AG) cultivar has the world's largest fruits and is described as the giant pumpkin. AG is well-known for its large and bright-colored fruits with high ornamental and economic value. At present, there are insufficient studies that have focused on the formation factors of the AG cultivar. To address these knowledge gaps, we performed comparative transcriptome, proteome, and metabolome analysis of fruits from the AG cultivar and a pumpkin with relatively small fruit (Hubbard). The results indicate that up-regulation of gene-encoded expansins contributed to fruit cell expansion, and the increased presence of photoassimilates (stachyose and D-glucose) and jasmonic acid (JA) accumulation worked together in terms of the formation of large fruit in the AG cultivar. Notably, perhaps due to the rapid transport of photoassimilates, abundant stachyose that was not converted into glucose in time was detected in giant pumpkin fruits, implying that a unique mode of assimilate unloading is in existence in the AG cultivar. The potential molecular regulatory network of photoassimilate metabolism closely related to pumpkin fruit expansion was also investigated, finding that three MYB transcription factors, namely CmaCh02G015900, CmaCh01G018100, and CmaCh06G011110, may be involved in metabolic regulation. In addition, neoxanthin (a type of carotenoid) exhibited decreased accumulation that was attributed to the down-regulation of carotenoid biosynthesis genes in AG fruits, which may lead to pigmentation differences between the two pumpkin cultivars. Our current work will provide new insights into the potential formation factors of giant pumpkins for further systematic elucidation. [ABSTRACT FROM AUTHOR]