bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of back-support exoskeletons with different functional mechanisms on trunk muscle activity and kinematics
Authors: Reimeir Benjamin , Calisti Maité , Mittermeier Ronja , Ralfs Lennart , Weidner Robert 
Published: April 2023

AbstractMusculoskeletal disorders constitute the leading work-related health issue. Mechanical loading of the lower back contributes as a major risk factor and is prevalent in many tasks performed in logistics. The study aimed to compare acute effects of exoskeletons with different functional mechanisms in a logistic task. Twelve young, healthy individuals participated in the study. Five exoskeletons with different functional mechanisms were tested in a logistic task, consisting of lifting, carrying, and lowering a 13 kg box. By using electromyography (EMG), mean muscle activities of four muscles in the trunk were analyzed. Additionally, kinematics by task completion time and range of motion (RoM) of the major joints and segments were investigated. A main effect was found forMusculus erector spinae,Musculus multifidus, andMusculus latissimus dorsishowing differences in muscle activity reductions between exoskeletons. Reduction in ES mean activity compared to baseline was primarily during lifting from ground level. The exoskeletons SoftExo Lift and Cray X also showed ES mean reduction during lowering the box. Prolonged task duration during the lifting phase was found for the exoskeletons BionicBack, SoftExo Lift, and Japet.W. Japet.W showed a trend in reducing hip RoM during that phase. SoftExo Lift caused a reduction in trunk flexion during the lifting phase. A stronger trunk inclination was only found during lifting from the table for the SoftExo Lift and the Cray X. In conclusion, muscle activity reductions by exoskeleton use should not be assessed without taking their designed force paths into account to correctly interpret the effects for long-term injury prevention.
Thunderstorm Nowcasting With Deep Learning: A Multi‐Hazard Data Fusion Model
Authors: Leinonen Jussi , Hamann Ulrich , Sideris Ioannis V. , Germann Urs 
Published: April 2023

AbstractPredictions of thunderstorm‐related hazards are needed in several sectors, including first responders, infrastructure management and aviation. To address this need, we present a deep learning model that can be adapted to different hazard types. The model can utilize multiple data sources; we use data from weather radar, lightning detection, satellite visible/infrared imagery, numerical weather prediction and digital elevation models. We demonstrate the ability of the model to predict lightning, hail and heavy precipitation probabilistically on a 1 km resolution grid, with a temporal resolution of 5 min and lead times up to 60 min. Shapley values quantify the importance of the different data sources, showing that the weather radar products are the most important predictors for all three hazard types.
Exploring the Factors Controlling the Long‐Term Trend (1988–2019) of Surface Organic Aerosols in the Continental United States by Simulations
Authors: Liu Yaman , Dong Xinyi , Emmons Louisa K. , Jo Duseong S. , Liu Yawen , Shrivastava Manish , Yue Man , Liang Yuan , Song Zigeng , He Xianqiang , Wang Minghuai 
Published: April 2023

AbstractObserved surface organic aerosols (OA) concentrations slightly increased in the western US (WUS) but significantly decreased in the eastern US (EUS) in summer, and continuously decreased in winter over the US region. To understand the driving factors for the long‐term surface OA trend, we apply a revised version of the Community Atmosphere Model version 6 with comprehensive tropospheric and stratospheric chemistry representation, considering the heterogeneous formation of isoprene‐epoxydiol‐derived secondary organic aerosols (SOAIE) and fast photolysis rate of monoterpene‐derived secondary organic aerosols (MTSOA) to diagnose the OA evolution in 1988–2019. Compared to older versions, the revised model better reproduces the climatology, seasonal cycle, and long‐term trend of surface OA as evaluated against the Interagency Monitoring of Protected Visual Environments measurements. We find the decrease in EUS summertime OA is likely attributed to the interplay between SOAIE and MTSOA. With anthropogenic emissions reduction, primary organic aerosols (POA) declined, SOAIE decreased along with sulfate, while MTSOA increased along with biogenic emissions driven by a warming climate. POA from wildfires with a significant trend of 2.9% yr−1 and considerable interannual variation of 62.8% drive the statistically insignificant but increasing WUS summertime OA, while anthropogenic POA dominates the decreasing wintertime OA in the US. Through sensitivity experiments, we find MTSOA show linear responses to the increasing monoterpenes emissions and negligible responses to NOx emissions reduction due to the mutual offsets between MTSOA components from different oxidation pathways. This study reveals the increasingly important role of MTSOA in summertime OA under a warming climate.
Exploring the Influence of 34S Fractionation From Emission Sources and SO2 Atmospheric Oxidation on Sulfate Source Apportionment Based on Hourly Resolution δ34S‐SO2/SO42−
Authors: Feng Xinxin , Chen Yingjun , Liu Zeyu , Feng Yanli , Du Huiyun , Mu Yujing , Chen Jianmin 
Published: April 2023

AbstractSulfate (SO42−) sources are unclear leading to the underestimation of its concentration in the model. Hourly resolution δ34S‐SO2 and δ34S‐SO42− values of three haze episodes (EP1‐EP3) were synchronously collected for the first time to quantify the influence of 34S fractionation from emission sources (e.g., coal combustion) and SO2 atmospheric oxidation on SO2/SO42− source apportionment. After considering the 34S fractionation from coal combustion and atmospheric oxidation, the reasonable and logical source contributions of SO42− were obtained, showing highly consistent with that of Positive Matrix Factorization model results. Considering the 34S fraction from atmospheric oxidation, the source apportionment of SO2/SO42− obtained by hourly resolution δ34S‐SO2 and δ34S‐SO42− can more accurately reflect the dynamic changes of emission sources. Traffic emissions (49%) and coal combustion (46%–65%) were the major contributors to SO2/SO42− in EP1 and EP2‐EP3, respectively. However, obvious deviations of coal combustion contribution were found without considering 34S fractionation from coal combustion. Especially for the northwest transmission channels in EP2‐EP3, the deviation values accounted for 17.1%–38.5% of secondary SO42−. Moreover, δ34S was considered as a more sensitive source indicator than SO2 concentration by the results comparison of 34S technique and air quality model (Nested Air Quality Prediction Model System), which can provide more reliable evidence for SO2 emission control.
Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings
Authors: Hicks Emily M. , Seah Carina , Cote Alanna , Marchese Shelby , Brennand Kristen J. , Nestler Eric J. , Girgenti Matthew J. , Huckins Laura M. 
Published: April 2023

AbstractMajor depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.
Intracellular carbon storage by microorganisms is an overlooked pathway of biomass growth
Authors: Mason-Jones Kyle , Breidenbach Andreas , Dyckmans Jens , Banfield Callum C. , Dippold Michaela A. 
Published: April 2023

AbstractThe concept of biomass growth is central to microbial carbon (C) cycling and ecosystem nutrient turnover. Microbial biomass is usually assumed to grow by cellular replication, despite microorganisms’ capacity to increase biomass by synthesizing storage compounds. Resource investment in storage allows microbes to decouple their metabolic activity from immediate resource supply, supporting more diverse microbial responses to environmental changes. Here we show that microbial C storage in the form of triacylglycerides (TAGs) and polyhydroxybutyrate (PHB) contributes significantly to the formation of new biomass, i.e. growth, under contrasting conditions of C availability and complementary nutrient supply in soil. Together these compounds can comprise a C pool 0.19 ± 0.03 to 0.46 ± 0.08 times as large as extractable soil microbial biomass and reveal up to 279 ± 72% more biomass growth than observed by a DNA-based method alone. Even under C limitation, storage represented an additional 16–96% incorporation of added C into microbial biomass. These findings encourage greater recognition of storage synthesis as a key pathway of biomass growth and an underlying mechanism for resistance and resilience of microbial communities facing environmental change.
Disorder-enabled Andreev reflection of a quantum Hall edge
Authors: Kurilovich Vladislav D. , Raines Zachary M. , Glazman Leonid I. 
Published: April 2023

AbstractWe develop a theory of charge transport along the quantum Hall edge proximitized by a superconductor. We note that generically Andreev reflection of an edge state is suppressed if translation invariance along the edge is preserved. Disorder in a “dirty” superconductor enables the Andreev reflection but makes it random. As a result, the conductance of a proximitized segment is a stochastic quantity with giant sign-alternating fluctuations and zero average. We find the statistical distribution of the conductance and its dependence on electron density, magnetic field, and temperature. Our theory provides an explanation of a recent experiment with a proximitized edge state.
Contrasting geochemical and fungal controls on decomposition of lignin and soil carbon at continental scale
Authors: Huang Wenjuan , Yu Wenjuan , Yi Bo , Raman Erik , Yang Jihoon , Hammel Kenneth E. , Timokhin Vitaliy I. , Lu Chaoqun , Howe Adina , Weintraub-Leff Samantha R. , Hall Steven J. 
Published: April 2023

AbstractLignin is an abundant and complex plant polymer that may limit litter decomposition, yet lignin is sometimes a minor constituent of soil organic carbon (SOC). Accounting for diversity in soil characteristics might reconcile this apparent contradiction. Tracking decomposition of a lignin/litter mixture and SOC across different North American mineral soils using lab and field incubations, here we show that cumulative lignin decomposition varies 18-fold among soils and is strongly correlated with bulk litter decomposition, but not SOC decomposition. Climate legacy predicts decomposition in the lab, and impacts of nitrogen availability are minor compared with geochemical and microbial properties. Lignin decomposition increases with some metals and fungal taxa, whereas SOC decomposition decreases with metals and is weakly related with fungi. Decoupling of lignin and SOC decomposition and their contrasting biogeochemical drivers indicate that lignin is not necessarily a bottleneck for SOC decomposition and can explain variable contributions of lignin to SOC among ecosystems.
Accounting for assay performance when estimating the temporal dynamics in SARS-CoV-2 seroprevalence in the U.S.
Authors: García-Carreras Bernardo , Hitchings Matt D. T. , Johansson Michael A. , Biggerstaff Matthew , Slayton Rachel B. , Healy Jessica M. , Lessler Justin , Quandelacy Talia , Salje Henrik , Huang Angkana T. , Cummings Derek A. T. 
Published: April 2023

AbstractReconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.
Latent generative landscapes as maps of functional diversity in protein sequence space
Authors: Ziegler Cheyenne , Martin Jonathan , Sinner Claude , Morcos Faruck 
Published: April 2023

AbstractVariational autoencoders are unsupervised learning models with generative capabilities, when applied to protein data, they classify sequences by phylogeny and generate de novo sequences which preserve statistical properties of protein composition. While previous studies focus on clustering and generative features, here, we evaluate the underlying latent manifold in which sequence information is embedded. To investigate properties of the latent manifold, we utilize direct coupling analysis and a Potts Hamiltonian model to construct a latent generative landscape. We showcase how this landscape captures phylogenetic groupings, functional and fitness properties of several systems including Globins, β-lactamases, ion channels, and transcription factors. We provide support on how the landscape helps us understand the effects of sequence variability observed in experimental data and provides insights on directed and natural protein evolution. We propose that combining generative properties and functional predictive power of variational autoencoders and coevolutionary analysis could be beneficial in applications for protein engineering and design.
Comprehensive assessment of the utilization of manure in China’s croplands based on national farmer survey data
Authors: Zhang Qingsong , Chu Yiyan , Yin Yulong , Ying Hao , Zhang Fusuo , Cui Zhenling 
Published: April 2023

AbstractChina’s rapid increase in mass excreta and its environmental discharge have attracted substantial attention. However, cropland as a main destination of excreta utilization has not been extensively evaluated. Here, a national survey was used to assess the utilization of manure in croplands across China. The data included the inputs of manure nitrogen (N), phosphorus (P), and potassium (K) for cereals, fruits, vegetables, and other crops, along with the manure proportion of total N, P, and K inputs at the county level. The results showed that the manure N, P, and K inputs were 6.85, 2.14, and 4.65 million tons (Mt), respectively, constituting 19.0%, 25.5%, and 31.1% of the total N, P, and K, respectively. The spatial distribution of the manure proportion of total inputs was lower in Eastern China and higher in Western China. The results provide a detailed description of the utilization of manure nutrients in agricultural areas throughout China, which will serve as basic support for policymakers and researchers involved in future agricultural nutrient management in China.
Insect visuomotor delay adjustments in group flight support swarm cohesion
Authors: Islam Md. Saiful , Faruque Imraan A. 
Published: April 2023

AbstractFlying insects routinely demonstrate coordinated flight in crowded assemblies despite strict communication and processing constraints. This study experimentally records multiple flying insects tracking a moving visual stimulus. System identification techniques are used to robustly identify the tracking dynamics, including a visuomotor delay. The population delay distributions are quantified for solo and group behaviors. An interconnected visual swarm model incorporating heterogeneous delays is developed, and bifurcation analysis and swarm simulation are applied to assess swarm stability under the delays. The experiment recorded 450 insect trajectories and quantified visual tracking delay variation. Solitary tasks showed a 30ms average delay and standard deviation of 50ms, while group behaviors show a 15ms average and 8ms standard deviation. Analysis and simulation indicate that the delay adjustments during group flight support swarm formation and center stability, and are robust to measurement noise. These results quantify the role of visuomotor delay heterogeneity in flying insects and their role in supporting swarm cohesion through implicit communication.
Understanding the impact of surface roughness: changing from FTO to ITO to PEN/ITO for flexible perovskite solar cells
Authors: Holzhey Philippe , Prettl Michael , Collavini Silvia , Mortan Claudiu , Saliba Michael 
Published: April 2023

AbstractSo far, single-junction flexible PSCs have been lacking in efficiency compared to rigid PSCs. Recently, > 23% have been reported. We therefore focus on understanding the differences between rigid and flexible substrates. One often neglected parameter is the different surface roughness which directly affects the perovskite film formation. Therefore, we adjust the layer thickness of SnO2 and the perovskite layers. Furthermore, we introduce a PMMA layer between the perovskite and the hole transporting material (HTM), spiro-MeOTAD, to mitigate shunting pathways. In addition, the multication perovskite Rb0.02Cs0.05FA0.77MA0.16Pb(I0.83Br0.17)3 is employed, resulting in stabilized performances of 16% for a flexible ITO substrate and 19% on a rigid ITO substrate.
In vitro PCR verification that lysozyme inhibits nucleic acid replication and transcription
Authors: Liu Lu , Jia Xu , Zhao Xiaoyang , Li Ting , Luo Ziren , Deng Ranxi , Peng Bijia , Mao Danting , Liu Hong , Zheng Qian 
Published: April 2023

AbstractLysozyme can kill bacteria by its enzymatic activity or through a mechanism involving its cationic nature, which can facilitate electrostatic interactions with the viral capsid, the negatively charged parts of nucleic acids, and polymerase, so binding to nucleic acids may be another biological function of lysozyme. Here, PCR was used as a research tool to detect the effects of lysozyme on the replication and transcription of nucleic acids after treatment in different ways. We found that lysozyme and its hydrolysate can enter cells and inhibit PCR to varying degrees in vitro, and degraded lysozyme inhibited nucleic acid replication more effectively than intact lysozyme. The inhibition of lysozyme may be related to polymerase binding, and the sensitivity of different polymerases to lysozyme is inconsistent. Our findings provide a theoretical basis for further explaining the pharmacological effects of lysozyme, such as antibacterial, antiviral, anticancer, and immune regulatory activities, and directions for the development of new pharmacological effects of lysozyme and its metabolites.
Numerical simulation and mathematical modeling for heat and mass transfer in MHD stagnation point flow of nanofluid consisting of entropy generation
Authors: Khan M. Riaz , Puneeth V. , Alqahtani Aisha M. , Alhazmi Sharifah E. , Beinane Sid Ahmed Ould , Shutaywi Meshal , Eldin Sayed M. , Alsenani Theyab R. 
Published: April 2023

AbstractThe primary goal of this article is to explore the radiative stagnation point flow of nanofluid with cross-diffusion and entropy generation across a permeable curved surface. Moreover, the activation energy, Joule heating, slip condition, and viscous dissipation effects have been considered in order to achieve realistic results. The governing equations associated with the modeling of this research have been transformed into ordinary differential equations by utilizing appropriate transformation variable. The resulting system of equations was solved numerically by using Bvp4c built-in package in MATLAB. The impact of involved parameters have been graphically examined for the diverse features of velocity, temperature, and concentration profiles. Throughout the analysis, the volume fraction is assumed to be less than $$5\%$$

5
%

while the Prandtl number is set to be $$6$$

6

. In addition, the entropy generation, friction drag, Nusselt, and Sherwood numbers have been plotted for describing the diverse physical aspects of the underlying phenomena. The major outcomes reveal that the curvature parameter reduces the velocity profile and skin friction coefficient whereas the magnetic parameter, temperature difference parameter, and radiation parameter intensify the entropy generation.
Self-healing perovskite solar cells based on copolymer-templated TiO2 electron transport layer
Authors: Lalpour Nakisa , Mirkhani Valiollah , Keshavarzi Reza , Moghadam Majid , Tangestaninejad Shahram , Mohammadpoor-Baltork Iraj , Gao Peng 
Published: April 2023

AbstractInorganic hole-transport materials (HTMs) such as copper indium disulfide (CIS) have been applied in perovskite solar cells (PSCs) to improve the poor stability of the conventional Spiro-based PSCs. However, CIS-PSCs' main drawback is their lower efficiency than Spiro-PSCs. In this work, copolymer-templated TiO2 (CT-TiO2) structures have been used as an electron transfer layer (ETL) to improve the photocurrent density and efficiency of CIS-PSCs. Compared to the conventional random porous TiO2 ETLs, copolymer-templated TiO2 ETLs with a lower refractive index improve the transmittance of input light into the cell and therefore enhance the photovoltaic performance. Interestingly, a large number of surface hydroxyl groups on the CT-TiO2 induce a self-healing effect in perovskite. Thus, they provide superior stability in CIS-PSC. The fabricated CIS-PSC presents a conversion efficiency of 11.08% (Jsc = 23.35 mA/cm2, Voc = 0.995, and FF = 0.477) with a device area of 0.09 cm2 under 100 mW/cm2. Moreover, these unsealed CIS-PSCs retained 100% of their performance after aging tests for 90 days under ambient conditions and even increased from 11.08 to 11.27 over time due to self-healing properties.