bluuebunny/crossref_metadata_2025 huggingface dataset:
Seeing and understanding epistemic actions
Authors: Croom Sholei , Zhou Hanbei , Firestone Chaz
Published: November 2023

Many actions have instrumental aims, in which we move our bodies to achieve a physical outcome in the environment. However, we also perform actions with epistemic aims, in which we move our bodies to acquire information and learn about the world. A large literature on action recognition investigates how observers represent and understand the former class of actions; but what about the latter class? Can one person tell, just by observing another person’s movements, what they are trying to learn? Here, five experiments exploreepistemic action understanding. We filmed volunteers playing a “physics game” consisting of two rounds: Players shook an opaque box and attempted to determine i) the number of objects hidden inside, or ii) the shape of the objects inside. Then, independent subjects watched these videos and were asked to determine which videos came from which round: Who was shaking for number and who was shaking for shape? Across several variations, observers successfully determined what an actor was trying to learn, based only on their actions (i.e., how they shook the box)—even when the box’s contents were identical across rounds. These results demonstrate that humans can infer epistemic intent from physical behaviors, adding a new dimension to research on action understanding.
Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions
Authors: Espinoza Baltazar , Adiga Aniruddha , Venkatramanan Srinivasan , Warren Andrew Scott , Chen Jiangzhuo , Lewis Bryan Leroy , Vullikanti Anil , Swarup Samarth , Moon Sifat , Barrett Christopher Louis , Athreya Siva , Sundaresan Rajesh , Chandru Vijay , Laxminarayan Ramanan , Schaffer Benjamin , Poor H. Vincent , Levin Simon A. , Marathe Madhav V.
Published: November 2023

Disease surveillance systems provide early warnings of disease outbreaks before they become public health emergencies. However, pandemics containment would be challenging due to the complex immunity landscape created by multiple variants. Genomic surveillance is critical for detecting novel variants with diverse characteristics and importation/emergence times. Yet, a systematic study incorporating genomic monitoring, situation assessment, and intervention strategies is lacking in the literature. We formulate an integrated computational modeling framework to study a realistic course of action based on sequencing, analysis, and response. We study the effects of the second variant’s importation time, its infectiousness advantage and, its cross-infection on the novel variant’s detection time, and the resulting intervention scenarios to contain epidemics driven by two-variants dynamics. Our results illustrate the limitation in the intervention’s effectiveness due to the variants’ competing dynamics and provide the following insights: i) There is a set of importation times that yields the worst detection time for the second variant, which depends on the first variant’s basic reproductive number; ii) When the second variant is imported relatively early with respect to the first variant, the cross-infection level does not impact the detection time of the second variant. We found that depending on the target metric, the best outcomes are attained under different interventions’ regimes. Our results emphasize the importance of sustained enforcement of Non-Pharmaceutical Interventions on preventing epidemic resurgence due to importation/emergence of novel variants. We also discuss how our methods can be used to study when a novel variant emerges within a population.
Estimating the value of democracy relative to other institutional and economic outcomes among citizens in Brazil, France, and the United States
Authors: Adserà Alicia , Arenas Andreu , Boix Carles
Published: November 2023

How much do citizens value democracy? How willing are they to sacrifice their liberties and voting rights for growth, equality, or other social outcomes? We design a conjoint experiment in nationally representative surveys in Brazil, France, and the United States in which respondents choose between different societies that randomly vary in their economic outcomes (country income, income inequality, social mobility), political outcomes (democracy, public health insurance), and the level of personal income for each respondent. Our research allows us to estimate the respondents’ willingness to trade off democracy for individual income (as well as other societal attributes). We find that, on average, individuals are strongly attached to democracy and a robust welfare state. They prefer to live in a country without free democratic elections only if their individual income multiplies by at least three times and in a country without public health insurance only if their individual income more than doubles. After estimating these preferences at the individual level for all respondents, we show that, although there is an authoritarian minority in all three countries, forming a nondemocratic majority (by offering more income and/or other goods to respondents) is very unlikely. Our findings imply that, contrary to a growing discussion about the crisis of democracy, liberal democratic values remain substantially robust in high and middle income democracies.
The cyclophilin A-binding loop of the capsid regulates the human TRIM5α sensitivity of nonpandemic HIV-1
Authors: Twizerimana Augustin P. , Becker Daniel , Zhu Shenglin , Luedde Tom , Gohlke Holger , Münk Carsten
Published: November 2023

The rather few cases of humans infected by HIV-1 N, O, or P raise the question of their incomplete adaptation to humans. We hypothesized that early postentry restrictions may be relevant for the impaired spread of these HIVs. One of the best-characterized species-specific restriction factors is TRIM5α. HIV-1 M can escape human (hu) TRIM5α restriction by binding cyclophilin A (CYPA, also known as PPIA, peptidylprolyl isomerase A) to the so-called CYPA-binding loop of its capsid protein. How non-M HIV-1s interact with huTRIM5α is ill-defined. By testing full-length reporter viruses (Δ
env
) of HIV-1 N, O, P, and SIVgor (simian IV of gorillas), we found that in contrast to HIV-1 M, the nonpandemic HIVs and SIVgor showed restriction by huTRIM5α. Work to identify capsid residues that mediate susceptibility to huTRIM5α revealed that residue 88 in the capsid CYPA-binding loop was important for such differences. There, HIV-1 M uses alanine to resist, while non-M HIV-1s have either valine or methionine, which avail them for huTRIM5α. Capsid residue 88 determines the sensitivity to TRIM5α in an unknown way. Molecular simulations indicated that capsid residue 88 can affect
trans
-to-
cis
isomerization patterns on the capsids of the viruses we tested. These differential CYPA usages by pandemic and nonpandemic HIV-1 suggest that the enzymatic activity of CYPA on the viral core might be important for its protective function against huTRIM5α.
The genome of a bunyavirus cannot be defined at the level of the viral particle but only at the scale of the viral population
Authors: Yvon Michel , German Thomas L. , Ullman Diane E. , Dasgupta Ranjit , Parker Maxwell H. , Ben-Mahmoud Sulley , Verdin Eric , Gognalons Patrick , Ancelin Aurélie , Laï Kee Him Joséphine , Girard Justine , Vernerey Marie-Stéphanie , Fernandez Emmanuel , Filloux Denis , Roumagnac Philippe , Bron Patrick , Michalakis Yannis , Blanc Stéphane
Published: November 2023

Bunyaviruses are enveloped negative or ambisense single-stranded RNA viruses with a genome divided into several segments. The canonical view depicts each viral particle packaging one copy of each genomic segment in one polarity named the viral strand. Several opposing observations revealed nonequal ratios of the segments, uneven number of segments per virion, and even packaging of viral complementary strands. Unfortunately, these observations result from studies often addressing other questions, on distinct viral species, and not using accurate quantitative methods. Hence, what RNA segments and strands are packaged as the genome of any bunyavirus remains largely ambiguous. We addressed this issue by first investigating the virion size distribution and RNA content in populations of the tomato spotted wilt virus (TSWV) using microscopy and tomography. These revealed heterogeneity in viral particle volume and amount of RNA content, with a surprising lack of correlation between the two. Then, the ratios of all genomic segments and strands were established using RNA sequencing and qRT-PCR. Within virions, both plus and minus strands (but no mRNA) are packaged for each of the three L, M, and S segments, in reproducible nonequimolar proportions determined by those in total cell extracts. These results show that virions differ in their genomic content but together build up a highly reproducible genetic composition of the viral population. This resembles the genome formula described for multipartite viruses, with which some species of the order
Bunyavirales
may share some aspects of the way of life, particularly emerging properties at a supravirion scale.
Language contact, identity building and attitudes towards the use of a minoritized language in the public
space
Authors: Arias Álvarez Alba , Bernardo-Hinesley Sheryl
Published: November 2023

Recent sociolinguistic studies have emphasized the role of the Linguistic Landscape in analyzing language
attitudes and identities in relation to minoritized languages. The present study examines language attitudes and perceptions of
Asturian speakers towards the use of Asturian, a minoritized regional language spoken in Asturies, Spain, in the public space.
Data was gathered through a survey questionnaire distributed amongst residents of Mieres, a municipality located in the center of
Asturies. Through qualitative and quantitative analyses, results show that the presence of Asturian linguistic and semiotic
resources reinforces participants’ Asturian identity. Findings reveal positive language attitudes: not only do participants
believe that speaking Asturian is an essential part of being Asturian, but they want Asturians to continue learning and speaking
the language. This study shows how the Linguistic Landscape is a valuable tool in uncovering language attitudes and perceptions,
which are inextricably linked to one’s identity within a community.
Recovering critical parameter for nonlinear Allen–Cahn equation by fully discrete continuous data assimilation algorithms
*
Authors: Wang Wansheng , Jin Chengyu , Huang Yunqing
Published: November 2023

The purpose of this study is to recover the diffuse interface width parameter for nonlinear Allen–Cahn equation by a continuous data assimilation algorithm proposed recently. We obtain the large-time error between the true solution of the Allen–Cahn equation and the data assimilated solution produced by implicit–explicit one-leg fully discrete finite element methods due to discrepancy between an approximate diffuse interface width and the physical interface width. The strongly A-stability of the one-leg methods plays key roles in proving the exponential decay of initial error. Based on the long-time error estimates, we develop several algorithms to recover both the true solution and the true diffuse interface width using only spatially discrete phase field function measurements. Numerical experiments confirm our theoretical results and verify the effectiveness of the proposed methods.
Operation stage division and RUL prediction of bearings based on 1DCNN-ON-LSTM
Authors: Guo Runxia , Li Haonan , Huang Chao
Published: November 2023

Remaining useful life (RUL) prediction of bearings is significantly important to ensure reliable operation of bearings. In practice, it is routinely impossible to obtain the full life cycle degradation data of bearings that needs to be used in prediction. The accuracy of the RUL prediction of bearings is often affected by incomplete degradation data. Regarding this situation, this paper proposes a multi-sensor three-stage RUL prediction framework based on the one-dimensional convolutional ordered neuron long short-term memory (1DCNN-ON-LSTM) neural network. Firstly, 1DCNN is used to extract spatial features adaptively from multi-sensor’s data and fuse them into one-dimensional feature. Next, the unsupervised hierarchy mechanism of time series information based ON-LSTM is developed to determine the ‘initial degradation stage point’ and ‘rapid degradation stage point’ of the bearing from the one-dimensional feature. Once the signal features collected by sensors input to the model reach the degradation stage point, select the corresponding sensitive features as input and construct the 1DCNN-ON-LSTM model that performs RUL prediction after the degradation stage point to improve the prediction accuracy of the model. Based on the proposed hierarchy mechanism, the bearings’ operation process is divided into three operation stages: normal stage, initial degradation stage and rapid degradation stage. Finally, the experiments verify that the proposed method can effectively divide the operation stages of bearings to predict the RUL and improve the generalization ability and prediction accuracy of the model.
A lightweight high-resolution algorithm based on deep learning for layer-wise defect detection in laser powder bed fusion
Authors: Yan Hualin , Cai Jian-Feng , Zhao Yingjian , Jiang Zimeng , Zhang Yingjie , Ren Hang , Zhang Yuhui , Li Huaping , Long Yu
Published: November 2023

The quality of the powder bed is critical in the laser powder bed fusion (LPBF) process, and defects in the powder bed likely affect the quality of the final part. With the development of artificial intelligence technology, machine learning methods have been widely applied in powder-bed defect detection. However, to achieve high-precision defect detection, it is often necessary to construct complex network models and use high-resolution powder bed image data. To address these issues, this study used an off-axis industrial camera to capture layer-wise powder bed image data and proposed a defect detection model based on YOLOv7x and channel pruning to achieve defect identification and localization of powder bed patch images. Furthermore, an end-to-end defect detection pipeline based on image processing methods was proposed to detect defects in layer-wise powder bed images. Finally, the gradient-based class activation map technique (Grad CAM++) was used to analyze the interpretability of the detection results of the model. The results indicated that the proposed model was more lightweight than other models (YOLOv7x, Faster R-CNN, and SSD), with a model size of only 12.4MB. The average time for detecting powder bed image patches was significantly reduced to only 3.4 ms, and the average detection accuracy was as high as 97.4%. This demonstrates that the proposed detection method has the advantages of faster detection speed, higher detection accuracy, and simpler models, providing a reference for the real-time online detection of powder bed defects.
Effects of tissue heterogeneity and comparisons of collapsed cone and Monte Carlo fast neutron patient dosimetry using the University of Washington clinical neutron therapy system (CNTS)
Authors: Moffitt Gregory B , Sandison George A , Argento David C , Emery Robert , Wootton Landon S , Parvathaneni Upendra , Liao Jay J , Laramore George E , Stewart Robert D
Published: November 2023

Fast neutron therapy is a high linear energy transfer (LET) radiation treatment modality offering advantages over low LET radiations. Multileaf collimator technology reduces normal-tissue dose (toxicity) and makes neutron therapy more comparable to MV x-ray treatments. Published clinical-trial and other experiences with fast neutron therapy are reported. Early comparative studies failed to consider differences in target-dose spatial conformality between x-ray and neutron treatments, which is especially important for organs-at-risk close to tumor targets. Treatments planning systems (TPS) for high-energy neutrons lag behind TPS tools for MV x-rays, creating challenges for comparative studies of clinical outcomes. A previously published Monte Carlo model of the University of Washington (UW) Clinical Neutron Therapy System (CNTS) is refined and integrated with the RayStation TPS as an external dose planning/verification tool. The collapsed cone (CC) dose calculations in the TPS are based on measured dose profiles and output factors in water, with the absolute dose determined using a tissue-equivalent ionization chamber. For comparison, independent (external) Monte Carlo simulation computes dose on a voxel-by-voxel basis using an atlas that maps Hounsfield Unit (HU) numbers to elemental composition and density. Although the CC algorithm in the TPS accurately computes neutron dose to water compared to Monte Carlo calculations, calculated dose to water differs from bone or tissue depending largely on hydrogen content. Therefore, the elemental composition of tissue and bone, rather than the material or electron density, affects fast neutron dose. While the CC algorithm suffices for reproducible patient dosimetry in fast neutron therapy, adopting methods that consider tissue heterogeneity would enhance patient-specific neutron dose accuracy relative to national standards for other types of ionizing radiation. Corrections for tissue composition have a significant impact on absolute dose and the relative biological effectiveness (RBE) of neutron treatments compared to other radiation types (MV x-rays, protons, and carbon ions).
Collective behavior of self-propelled particles with multiple delays in cross-domain scenario
*
Authors: Zhou Yongjian , Wang Tonghao , Peng Xingguang
Published: November 2023

In cross-domain scenarios, the simultaneous presence of multiple sensing delays exerts a profound influence on collective behavior. Motivated by this, our paper presents a system based on self-propelled particles that consists of two swarms containing two intra-swarm sensing delays and an inter-swarm sensing delay. Three state emerges from the system, namely translating state, ring state, and rotating state. Employing mean field approximation and bifurcation analysis, we theoretically examine the parameter space’s boundaries that govern these three states. Our detailed findings emphasize that within the translating and rotating states, variations in the two intra-swarm delays can lead to the separation of the two swarms. Meanwhile, the extent of separation is influenced by the inter-swarm delay. Finally, we conduct numerical simulations to validate the accuracy of our theoretical derivations.
New variable separation solutions and localized waves for (2+1)-dimensional nonlinear systems by a full variable separation approach
Authors: Quan Jingfeng , Tang Xiaoyan
Published: November 2023

A full variable separation approach is firstly proposed for (2+1)-dimensional nonlinear systems by extending the well-established multilinear variable separation approach through the assumption that the expansion function is composed of full variable separated functions, namely, functions with respect to only one spacial or temporal argument. Taking the (2+1)-dimensional Boiti-Leon-Manna-Pempinelli equation, the Nizhnik-Novikov-Veselov equation and the dispersive long wave equation as examples, new full variable separation solutions are obtained with several arbitrary one dimensional functions. Especially, a common formula for some suitable physical quantities is discovered. By taking the arbitrary functions in different explicit expressions, the solutions can be used to describe plentiful novel nonlinear localized waves, which might be non-travelling waves as the spacial and temporal variables are fully separated into different functions. In particular, some new hybrid solitary waves, which can pulsate periodically, appear and/or decay with an adjustable lifetime, are discovered through the on-site interactions between a doubly periodic wave and a ring soliton, a four-humped dromion and a four-humped lump, and a doubly periodic wave and a cross type solitary wave. Nonlinear wave structures and their dynamical behaviours are discussed and graphically displayed in detail.
Triple crossing positivity bounds, mass dependence and cosmological scalars: Horndeski theory and DHOST
Authors: Xu Hao , Zhou Shuang-Yong
Published: November 2023

Scalars are widely used in cosmology to model novel phenomena such as the late-time cosmic
acceleration. These are effective field theories with highly nonlinear interactions, including
Horndeski theory/generalized galileon and beyond. We use the latest fully crossing symmetric
positivity bounds to constrain these cosmological EFTs. These positivity bounds, based on
fundamental principles of quantum field theory such as causality and unitarity, are able to
constrain the EFT coefficients both from above and below. We first map the mass dependence of the
fully crossing symmetric bounds, and find that a nonzero mass generically enlarges the positivity
regions. We show that fine-tunings in the EFT construction can significantly reduce the viable
regions and sometimes can be precarious. Then, we apply the positivity bounds to several models in
the Horndeski class and beyond, explicitly listing the ready-to-use bounds with the model
parameters, and discuss the implications for these models. The new positivity bounds are found to
severely constrain some of these models, in which positivity requires the mass to be
parametrically close to the cutoff of the EFT, effectively ruling them out. The examples include
massive galileon, the original beyond Horndeski model, and DHOST theory with unity speed of
gravity and nearly constant Newton's coupling.
Resonant contribution of the three-body decay process
in perturbative QCD*
Authors: Lü 吕 Gang 刚 , Zhang 张 Chang-Chang 畅畅 , Zhao 赵 Yan-Lin 艳琳 , Zhang 张 Li-Ying 丽英
Published: November 2023

We investigate CP violation in the decay process

by considering the interference effects of

,

, and

within the framework of the perturbative QCD method (P refers to π, K, η, and

pseudoscalar mesons). We analyze the mixings of

,

, and

and provide the amplitudes of the quasi-two-body decay processes. The CP violation for the

decay process is obvious in the ranges of the three vector meson interferences. Meanwhile, the localized CP violation can be found to compare with the experimental results from the three-body decay process at the LHC in the near future.
From masses and radii of neutron stars to EOS of nuclear matter through neural network*
Authors: Wu 武 Zehan 则晗 , Wen 文 Dehua 德华
Published: November 2023

The equation of state (EOS) of dense nuclear matter is a key factor for determining the internal structure and properties of neutron stars. However, the EOS of high-density nuclear matter has great uncertainty, mainly because terrestrial nuclear experiments cannot reproduce matter as dense as that in the inner core of a neutron star. Fortunately, continuous improvements in astronomical observations of neutron stars provide the opportunity to inversely constrain the EOS of high-density nuclear matter. Several methods have been proposed to implement this inverse constraint, including the Bayesian analysis algorithm, the Lindblom's approach, and so on. Neural network algorithm is an effective method developed in recent years. By employing a set of isospin-dependent parametric EOSs as the training sample of a neural network algorithm, we set up an effective way to reconstruct the EOS with relative accuracy using a few mass-radius data. Based on the obtained neural network algorithms and according to the NICER observations on masses and radii of neutron stars with assumed precision, we obtain the inversely constrained EOS and further calculate the corresponding macroscopic properties of the neutron star. The results are basically consistent with the constraint on EOS in Huth et al. [Nature 606, 276 (2022)] based on Bayesian analysis. Moreover, the results show that even though the neural network algorithm was obtained using the finite parameterized EOS as the training set, it is valid for any rational parameter combination of the parameterized EOS model.
Application of Generalized Poisson Regression for the development of modeling motorcycle accidents based on rider characteristics
Authors: Dinnullah R N I , Abusini S , Fitriani R , Marjono
Published: November 2023

Motorcycles are a mode of transportation that has experienced many traffic accidents in developing countries. This incident can occur intentionally or not and cause great loss of life and property. Therefore, this work aims to develop a model of the number of motorcycle accidents based on driver characteristics using Generalized Poisson Regression in East Java Province, Indonesia. The modeling can identify the relationship between the number of motorcycle accidents with variables that contribute to accident based on driver characteristics. This characteristic is a combination of socioeconomic factors and movements. Research analysis includes descriptive statistics and accident modeling using Generalized Poisson Regression Models. Model parameter values are estimated using the Maximum Likelihood Estimation (MLE) approach. The optimal solution for parameter estimation uses the Newton-Raphson algorithm. The results found two models and then selected the best model. Based on the parameter significance test, the population density, the percentage of low education, the gender ratio, and the percentage of accident perpetrators without a driver’s license significantly impact the number of motorcycle accidents in East Java Province.
Investigation of the negative speed’s effect on the base of the braitenberg vehicle
Authors: Zhou Tong
Published: November 2023

The Braitenberg vehicle has been applied to various areas. However, it’s noticeable that Braitenberg assumes the vehicle’s speed always remain positive, which implies that certain behaviors, such as moving backward is unlikely to be achieved. The purpose of this paper is to investigate the combination of positive speed and negative speed on the basis of the Braitenberg vehicle and analyze its effects on the vehicle’s behaviors. Three functions are used: a simple non-continuous function, a linear function and an inverse proportional function. Trajectories resulting from each are categorized into certain behaviors and discussed.
Simulation and discussion of typical radio frequency filters
Authors: Chen Xueying
Published: November 2023

The demand for filters is increasing as the frequency bands for 5G expand. RF filters become the segment with the largest market share of RF front-end chips. More crowded frequency bands, as well as thinner and lighter communication equipment, necessitate higher filter performance. In this paper, several technologies for the implementation of Radio Frequency filter are presented. Essentially three types are considered: (i) Lumped Element (LC) Filter and Integrated Passive Devices (IPD) technology; (ii) Acoustic Wave Filter; and (iii) a composite filter design that combines acoustic and IPD technologies. Benefits and drawbacks of these diverse configurations in terms of their technical performance and current applications are examined, and several models are presented and simulated using ADS software.
A comparison of FLC MPPT techniques and HC MPPT techniques for photovoltaic systems
Authors: Li Yikai
Published: November 2023

This study aims to examine the behaviour of various maximum power point tracking (MPPT) methods used with PV systems. The methodologies of hill climbing (HC) and fuzzy logic controller (FLC) are assessed in this paper. PV module and DC/DC boost converter models were simulated using PSIM and Simulink software with various MPPT strategies. The PSIM and Simulink software programmes were founder throughout the FLC MPPT method’s development. To employ each software for specific system components, the co-simulation was conducted. The effectiveness of the various MPPT approaches was assessed in response to rapidly varying weather conditions. The results show that for most of the tested MPPT approaches’ usual working ranges, FLC outperforms the HC MPPT approach in transient behavior and constant.
Review of current mechanical design in agricultural end effector
Authors: Guo Bingqing
Published: November 2023

Agricultural robots have become increasingly crucial in precise agriculture. This paper reviews recent developments in end-effectors applied in the robotic harvesting of fruits and vegetables. The control and harvest function of the end-effector is the focus. Different structures are categorized based on their properties. Advantages and limitations in each category are introduced. For the collection method, the hard-grab method is very popularly for low difficulties and the soft one can protect the fruits adequately and can harvest different fruits of similar size; double-finger type is used widely with the advantages of low cost, while the multi-finger type has the much higher stability. The collection method is divided into the cutting and twisting methods. The former is applied for low difficulties but may spread diseases among plants; therefore, thermal cutting, namely using high temperature to separate stem and crop, and the twisting method is used. Overall, different types of end-effectors show various advantages. With consideration of the target crop physical properties, a proper decision for the harvester can be made.
Comparison and analysis of different ECG denoising methods
Authors: Zhou Weiheng
Published: November 2023

With the improvement of medical level, electrocardiogram (ECG) is widely used for disease diagnosis. A lot of pathological and physiological information is contained in the ECG, which can be used to record the point activity of normal human heart and diagnose various heart disease. However, the acquired ECG signals are always contaminated with noise which caused by acquisition equipment or other circumstance. Therefore, Efficient denoising method is very important. In this paper, three typical ECG signal denoising methods are listed, including FIR filtering, wavelet filtering and EMD filtering. In this paper, the principles of the three filtering methods are introduced in detail, and their effects are compared. By comparison, it intuitively shows the processing effects of each method on ECG signals. Meanwhile, a simple Butterworth filter is designed to denoise a standard wave, which represents the logic knowledge related to denoising. It is very significant for the medical signal processing field and help to research more effective signal processing methods.
Comparison and analysis of various deep learning models for super-resolution reconstruction of turbulent flows
Authors: Yin Hang
Published: November 2023

Single image super-resolution (SR) has become a promising research topic, with many deep learning-based models invented to reconstruct high-fidelity high-resolution (HR) images from low-resolution (LR) images. Motivated by a large amount of turbulent flow field data collected by experimental measurements and numerical simulation, researchers begin investigating the application of these data-driven deep learning models to conduct SR reconstruction of LR flow field data. Due to the limitations of experimental equipment and computing power, sometimes researchers can only obtain LR data. However, deep learning models can quickly reconstruct HR spatial-temporal turbulent data from LR data so that researchers can easily conduct further qualitative and quantitative analyses. This article reviews the development of flow field data SR reconstruction models and the problems encountered from the two aspects of network structure and loss function definition. Finally, we propose the research direction of applying the conditional generative adversarial network (cGAN) to turbulent flow SR reconstruction since seldom study has been conducted in this field.
xCovNet: A wide deep learning model for CXR-based COVID-19 detection
Authors: Jana Aryyama Kumar , Paul Rudrendu Kumar
Published: November 2023

The high death toll and economic impact of the COVID-19 pandemic emphasize the need for effective population screening technologies. The high cost, limited availability, and slow nature of CT scans and PCR-based tests renders them impractical for frequent use among the general public. As chest X-ray (CXR) imaging is fast and economical, a high accuracy CXR-based test would be well-suited for such screenings. Deep learning algorithms are widely used to aid medical image diagnoses. We use a collection of state-of-the-art pre-trained deep neural network models with additional layers to detect the COVID-19 cases from a sample of healthy, COVID-19, and pneumonia patients. We observed models trained with concatenated features of multiple pre-trained deep learning architectures outperform the individual and ensemble models. Our final model obtained a recall of greater than 98% and a precision of greater than 95% on two separate datasets. The wide architecture of xCovNet may contribute to its robust behavior, providing a systematic approach to construct a reliable deep learning model for emerging datasets.
Does Tobacco Smoking Increase Social Isolation? A Mendelian Randomization Study
Authors: Matsuyama Yusuke , Tabuchi Takahiro
Published: November 2023

In this study, we aimed to investigate the causal effect of smoking on social isolation among older adults in England. Data from older adults of European ancestry who participated in 1 or more waves of the English Longitudinal Study of Ageing, from wave 1 (2002/2003) to wave 9 (2018/2019), were analyzed (n = 43,687 observations from 7,008 individuals; mean age = 68.50 years). The effect of current smoking on social isolation (ranging from 0 to 5) was estimated by 2-stage least squares regression using a polygenic score (PGS) for smoking cessation as the instrument. A low PGS for smoking cessation predicted current smoking (per 1–standard-deviation lower PGS, coefficient = 0.023, 95% confidence interval (CI): 0.015, 0.030; F = 36.420). The second-stage regression showed that current smoking increased social isolation by 1.205 points (95% CI: 0.308, 2.101). The association was larger for persons with higher socioeconomic backgrounds: 2.501 (95% CI: −0.024, 5.026) and 0.696 (95% CI: −0.294, 1.686) for those with higher and lower educational levels, respectively. This study showed that current smoking instrumented by a PGS for smoking cessation was associated with social isolation. Assuming that the PGS served as a valid instrument in this study, the findings support an effect of smoking on social isolation.
A systematic literature review to explore sustainable energy development practices in Mozambique
Authors: Lazaro Samuel Aires Master , Baba Vanessa Fathia
Published: November 2023

This study thoroughly evaluates sustainable energy practices in Mozambique, identifies suitable activities and suggests future research directions. The authors meticulously detail the research tasks undertaken to achieve the primary objective of the study, including organizing articles by publication year, journal and conference papers; identifying the most frequently cited articles; and recognizing countries that have made significant contributions to the concept of sustainable energy. The study highlights the most relevant sustainable energy development practices for Mozambique, identifies suitable activities and suggests future research directions. Through rigorous analysis, six significant areas of sustainable energy development were identified, including renewable energy (RE) resources, environmental science, social sciences, computer science, management and accounting, and Earth and planetary sciences. The study used Scopus as the selected multidisciplinary peer-reviewed citation database on 20 February 2023, resulting in 76 publications. The study has been conducted nationwide for several months and thoroughly investigates various resources such as hydro, wind, solar, biomass and geothermal energy. It achieves this by evaluating and characterizing the power generation potential of each RE resource and, in addition, identifying and examining numerous projects at the technical and economic feasibility level to promote the potential of projects and the advantages of RE for the sustainable development of Mozambique. The findings indicate that for sustainable energy development in Mozambique, it is crucial to introduce more policies to support the effectiveness of RE systems while involving the private sector. To achieve this, measures such as reducing investment risks, guaranteeing investment returns and establishing a transparent regulatory framework are required. These steps will attract substantial investments, resolve conflicts and motivate key stakeholders to actively participate in the process.
Timing of suture removal to reduce scarring in skin surgery: a randomized assessor-blinded feasibility trial
Authors: Richards Ellen , Brown Alistair , Chottianchaiwat Subhanitthaya , Frewen John , Powell Roy , McGrath Emily
Published: November 2023

Timing of suture removal after excision skin surgery varies, with few studies analysing the factors that contribute to poor wound healing and cosmesis. Here, we performed a pilot study to compare suture removal at 7 days or 10 days and its effect on healing and overall appearances of scars including the presence of suture marks.
Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA)
Authors: Holm Marianne , MacWright William R , Poudyal Nimesh , Shaw Alina , Joh Hea Sun , Gallagher Patrick , Kim Jong-Hoon , Shaikh Affan , Seo Hye Jin , Kwon Soo Young , Prifti Kristi , Dolabella Brooke , Taylor Ben E W , Yeats Corin , Aanensen David M , Stelling John , Marks Florian
Published: November 2023

Background

In 2015, the UK government established the Fleming Fund with the aim to address critical gaps in surveillance of antimicrobial resistance (AMR) in low- and middle-income countries in Asia and Africa. Among a large portfolio of grants, the Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was awarded with the specific objective of expanding the volume of historical data on AMR, consumption (AMC), and use (AMU) in the human healthcare sector across 12 countries in South and Southeast Asia.

Methods

Starting in early 2019, the CAPTURA consortium began working with local governments and >100 relevant data-holding facilities across the region to identify, assess for quality, prioritize, and subsequently retrieve data on AMR, AMC, and AMU. Relevant and shared data were collated and analyzed to provide local overviews for national stakeholders as well as regional context, wherever possible.

Results

From the vast information resource generated on current surveillance capacity and data availability, the project has highlighted gaps and areas for quality improvement and supported comprehensive capacity-building activities to optimize local data-collection and -management practices.

Conclusions

The project has paved the way for expansion of surveillance networks to include both the academic and private sector in several countries and has actively engaged in discussions to promote data sharing at the local, national, and regional levels. This paper describes the overarching approach to, and emerging lessons from, the CAPTURA project, and how it contributes to other ongoing efforts to strengthen national AMR surveillance in the region and globally.
Pharmacokinetics and Safety of Twice-daily Ritonavir-boosted Atazanavir With Rifampicin
Authors: Gausi Kamunkhwala , Mugerwa Henry , Siccardi Marco , Montanha Maiara Camotti , Lamorde Mohammed , Wiesner Lubbe , D’Avolio Antonio , McIlleron Helen , Wilkins Edmund , De Nicolò Amedeo , Maartens Gary , Khoo Saye , Kityo Cissy , Denti Paolo , Waitt Catriona
Published: November 2023

Background

Critical drug-drug interactions (DDI) and hepatotoxicity complicate concurrent use of rifampicin and protease inhibitors. We investigated whether dose escalation of atazanavir/ritonavir could safely overcome the DDI with rifampicin.

Methods

DERIVE (NCT04121195, EDCTP) was a dose-escalation trial in people with human immunodeficiency virus (HIV) on atazanavir/ritonavir-based antiretroviral therapy (ART) in Uganda. Four intensive pharmacokinetic (PK) visits were performed: PK1 300/100 mg OD (baseline); PK2 300/100 mg OD with rifampicin 600 mg; PK3 300/100 mg twice a day (BID) with rifampicin 600 mg OD; PK4 300/100 mg BID with rifampicin 1200 mg OD. Dolutegravir 50 mg BID throughout the study period ensured participants remained protected from subtherapeutic atazanavir concentrations. The data were interpreted with noncompartmental analysis. The target minimum concentration was atazanavir's protein-adjusted IC90 (PA-IC90), 0.014 mg/L.

Results

We enrolled 26 participants (23 female) with median (range) age 44 (28–61) years and weight 67 (50–75) kg. Compared with PK1, atazanavir Ctau, and AUC were significantly reduced at PK2 by 96% and 85%, respectively. The escalation to BID dosing (PK3) reduced this difference in Ctau, and AUC24 to 18% lower and 8% higher, respectively. Comparable exposures were maintained with double doses of rifampicin. Lowest Ctau during PK1, PK3, and PK4 were 12.7-, 4.8-, and 8.6-fold higher than PA-IC90, respectively, whereas 65% of PK2 Ctau were below the limit of quantification (0.03 mg/L), hence likely below PA-IC90. No participant developed significant elevation of liver enzymes, reported a serious adverse event (SAE) or experienced rebound viraemia.

Conclusions

Twice daily atazanavir/ritonavir during rifampicin co-administration was well tolerated and achieved plasma concentrations above the target.

Clinical Trials Registration

NCT04121195. Registered on 09 October 2019, https://clinicaltrials.gov/ct2/show/NCT04121195.
Fourth Chromosome Resource Project: a comprehensive resource for genetic analysis in Drosophila that includes humanized stocks
Authors: Stinchfield Michael J , Weasner Brandon P , Weasner Bonnie M , Zhitomersky David , Kumar Justin P , O’Connor Michael B , Newfeld Stuart J
Published: November 2023

The fourth chromosome is the final frontier for genetic analysis in Drosophila. Small, heterochromatic, and devoid of recombination the fourth has long been ignored. Nevertheless, its long arm contains 79 protein-coding genes. The Fourth Chromosome Resource Project (FCRP) has a goal of facilitating the investigation of genes on this neglected chromosome. The project has 446 stocks publicly available at the Bloomington and Kyoto stock centers with phenotypic data curated by the FlyBase and FlyPush resources. Four of the five stock sets are nearly complete: (1) UAS.fly cDNAs, (2) UAS.human homolog cDNAs, (3) gene trap mutants and protein traps, and (4) stocks promoting meiotic and mitotic recombination on the fourth. Ongoing is mutagenesis of each fourth gene on a new FRT-bearing chromosome for marked single-cell clones. Beyond flies, FCRP facilitates the creation and analysis of humanized fly stocks. These provide opportunities to apply Drosophila genetics to the analysis of human gene interaction and function. In addition, the FCRP provides investigators with confidence through stock validation and an incentive via phenotyping to tackle genes on the fourth that have never been studied. Taken together, FCRP stocks will facilitate all manner of genetic and molecular studies. The resource is readily available to researchers to enhance our understanding of metazoan biology, including conserved molecular mechanisms underlying health and disease.
Catalytic activity of the Bin3/MePCE methyltransferase domain is dispensable for 7SK snRNP function in Drosophila melanogaster
Authors: Palumbo Ryan J , Yang Yuan , Feigon Juli , Hanes Steven D
Published: November 2023

Methylphosphate Capping Enzyme (MePCE) monomethylates the gamma phosphate at the 5′ end of the 7SK noncoding RNA, a modification thought to protect 7SK from degradation. 7SK serves as a scaffold for assembly of a snRNP complex that inhibits transcription by sequestering the positive elongation factor P-TEFb. While much is known about the biochemical activity of MePCE in vitro, little is known about its functions in vivo, or what roles—if any—there are for regions outside the conserved methyltransferase domain. Here, we investigated the role of Bin3, the Drosophila ortholog of MePCE, and its conserved functional domains in Drosophila development. We found that bin3 mutant females had strongly reduced rates of egg-laying, which was rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 promotes fecundity by repressing P-TEFb. bin3 mutants also exhibited neuromuscular defects, analogous to a patient with MePCE haploinsufficiency. These defects were also rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 and MePCE have conserved roles in promoting neuromuscular function by repressing P-TEFb. Unexpectedly, we found that a Bin3 catalytic mutant (Bin3Y795A) could still bind and stabilize 7SK and rescue all bin3 mutant phenotypes, indicating that Bin3 catalytic activity is dispensable for 7SK stability and snRNP function in vivo. Finally, we identified a metazoan-specific motif (MSM) outside of the methyltransferase domain and generated mutant flies lacking this motif (Bin3ΔMSM). Bin3ΔMSM mutant flies exhibited some—but not all—bin3 mutant phenotypes, suggesting that the MSM is required for a 7SK-independent, tissue-specific function of Bin3.
Chinese experts’ consensus guideline on preimplantation genetic testing of monogenic disorders
Authors: Yan Liying , Cao Yunxia , Chen Zi-Jiang , Du Jie , Wang ShuYu , Huang Hefeng , Huang Jin , Li Rong , Liu Ping , Zhang Zhe , Huang Yu , Lin Ge , Pan Hong , Qi Hongbo , Qian Weiping , Sun Yun , Wu Lingqian , Yao Yuanqing , Zhang Bo , Zhang Cuilian , Zhao Shuyun , Zhou Canquan , Zhang Xue , Qiao Jie
Published: November 2023

Recent developments in molecular biological technologies and genetic diagnostic methods, accompanying with updates of relevant terminologies, have enabled the improvements of new strategies of preimplantation genetic testing for monogenic (single gene) disorders (PGT-M) to prevent the transmission of inherited diseases. However, there has been much in the way of published consensus on PGT-M. To properly regulate the application of PGT-M, Chinese experts in reproductive medicine and genetics have jointly developed this consensus statement. The consensus includes indications for patient selection, genetic and reproductive counseling, informed consent, diagnostic strategies, report generation, interpretation of results and patient follow-ups. This consensus statement serves to assist in establishment of evidence-based clinical and laboratory practices for PGT-M.