bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adsorption characteristics and mechanisms of Cd2+ from aqueous solution by biochar derived from corn stover
Authors: Chen Fang , Sun Yaosheng , Liang Chao , Yang Tianyu , Mi Shican , Dai Yehong , Yu Molin , Yao Qiang 
Published: October 2022

AbstractCorn stover could be pyrolysed to prepare biochar for removing pollutants in water and realizing the resource utilization of biomass. The aims of the present study were to investigate the optimal preparation and adsorption conditions of biochar and to reveal the adsorption characteristics and mechanisms of Cd2+ in water by biochar. For this purpose, with Cd2+ as the target pollutant, the pyrolysis conditions involved in the pyrolysis temperature, retention time, and heating rate were evaluated and optimized. Additionally, the characteristics, mechanisms and optimal adsorption conditions of Cd2+ by biochar were determined. A series of characterization techniques was employed, including scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and specific surface area analysis (SBET). The optimum pyrolysis parameters were a pyrolysis temperature of 700 °C, a retention time of 2.5 h, and a heating rate of 5 °C/min. Acid/base modification did not improve the adsorption capacity of biochar. The Langmuir and the Elovich model were the most suitable isotherm and kinetic models for equilibrium data, respectively. The maximum adsorption capacity fitted by Langmuir model was 13.4 mg/g. Furthermore, mineral precipitation and π electron interactions were shown to be the main adsorption mechanisms of Cd2+. The optimum adsorption conditions for Cd2+ in water were a CaCl2 electrolyte solution of 0.01 mol/L, a pH level of 6.7, and a biochar dosage of 0.4 g. Our results indicated that corn stover biochar was an appropriate approach for improving the status of water with Cd2+ contamination in the short term and for promoting a new perspective for the rational utilization of corn stover and the low-cost pollution control of heavy metals in water.
Comparison of TGSE-BLADE DWI, RESOLVE DWI, and SS-EPI DWI in healthy volunteers and patients after cerebral aneurysm clipping
Authors: Okuchi Sachi , Fushimi Yasutaka , Yoshida Kazumichi , Nakajima Satoshi , Sakata Akihiko , Hinoda Takuya , Otani Sayo , Sagawa Hajime , Zhou Kun , Yamao Yukihiro , Okawa Masakazu , Nakamoto Yuji 
Published: October 2022

AbstractDiffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air–bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip.
Ventilation improvement and evaluation of its effectiveness in a Japanese manufacturing factory
Authors: Kitamura Hiroko , Ishigaki Yo , Ohashi Hideaki , Yokogawa Shinji 
Published: October 2022

AbstractA coronavirus disease 2019 (COVID-19) cluster emerged in a manufacturing factory in early August 2021. In November 2021, we conducted a ventilation survey using the tracer gas method. Firstly, we reproduce the situation at the time of cluster emergence and examined whether the ventilation in the office was in a condition that increased the risk of aerosol transmission. Secondly, we verified the effectiveness of the factory’s own countermeasure implemented immediately after the August cluster outbreak. Furthermore, we verified the effectiveness of several additional improvement measures on the factory’s own countermeasures already installed in August. Under the conditions of the cluster emergence, the air changes per hour (ACH) value was 0.73 ACH on average. The ACH value was less than 2 ACH recommended by the Ministry of Health, Labour, and Welfare, suggesting an increased risk of aerosol transmission. The factory’s own countermeasures taken immediately in August were found to be effective, as the ACH value increased to 3.41 ACH on average. Moreover, it was confirmed that additional improvement measures on the factory’s own countermeasures increased the ACH value to 8.33 ACH on average. In order to prevent the re-emergence of COVID-19 clusters due to aerosol infection in the office, it was found that while continuing the factory’s own countermeasure, additional improvement measures should also be added depending on the number of workers in the room. In a company, it is important that workers themselves continue to take infection control measures autonomously, and confirming the effectiveness of the measures will help maintain workers’ motivation. We believe it is helpful that external researchers in multiple fields and internal personnel in charge of the health and safety department and occupational health work together to confirm the effectiveness of conducted measures, such as in this case.
Adaptation to host cell environment during experimental evolution of Zika virus
Authors: Grass Vincent , Hardy Emilie , Kobert Kassian , Talemi Soheil Rastgou , Décembre Elodie , Guy Coralie , Markov Peter V. , Kohl Alain , Paris Mathilde , Böckmann Anja , Muñoz-González Sara , Sherry Lee , Höfer Thomas , Boussau Bastien , Dreux Marlène 
Published: October 2022

AbstractZika virus (ZIKV) infection can cause important developmental and neurological defects in Humans. Type I/III interferon responses control ZIKV infection and pathological processes, yet the virus has evolved various mechanisms to defeat these host responses. Here, we established a pipeline to delineate at high-resolution the genetic evolution of ZIKV in a controlled host cell environment. We uncovered that serially passaged ZIKV acquired increased infectivity and simultaneously developed a resistance to TLR3-induced restriction. We built a mathematical model that suggests that the increased infectivity is due to a reduced time-lag between infection and viral replication. We found that this adaptation is cell-type specific, suggesting that different cell environments may drive viral evolution along different routes. Deep-sequencing of ZIKV populations pinpointed mutations whose increased frequencies temporally coincide with the acquisition of the adapted phenotype. We functionally validated S455L, a substitution in ZIKV envelope (E) protein, recapitulating the adapted phenotype. Its positioning on the E structure suggests a putative function in protein refolding/stability. Taken together, our results uncovered ZIKV adaptations to the cellular environment leading to accelerated replication onset coupled with resistance to TLR3-induced antiviral response. Our work provides insights into Zika virus adaptation to host cells and immune escape mechanisms.
Genomic evolution towards azole resistance in Candida glabrata clinical isolates unveils the importance of CgHxt4/6/7 in azole accumulation
Authors: Galocha Mónica , Viana Romeu , Pais Pedro , Silva-Dias Ana , Cavalheiro Mafalda , Miranda Isabel M. , Van Ende Mieke , Souza Caio S. , Costa Catarina , Branco Joana , Soares Cláudio M. , Van Dijck Patrick , Rodrigues Acácio G. , Teixeira Miguel C. 
Published: October 2022

AbstractThe increasing prevalence of candidosis caused byCandida glabratais related to its ability to acquire azole resistance. Although azole resistance mechanisms are well known, the mechanisms for azole import into fungal cells have remained obscure. In this work, we have characterized two hexose transporters inC. glabrataand further investigate their role as potential azole importers. Three azole susceptibleC. glabrataclinical isolates were evolved towards azole resistance and the acquired resistance phenotype was found to be independent ofCgPDR1orCgERG11mutations. Through whole-genome sequencing,CgHXT4/6/7was found to be mutated in the three evolved strains, when compared to their susceptible parents. CgHxt4/6/7 and the 96% identical CgHxt6/7 were found to confer azole susceptibility and increase azole accumulation inC. glabratacells, strikingly rescuing the susceptibility phenotype imposed byCgPDR1deletion, while the identified loss-of-function mutation inCgHXT4/6/7, leads to increased azole resistance. In silico docking analysis shows that azoles display a strong predicted affinity for the glucose binding site of CgHxt4/6/7. Altogether, we hypothesize that hexose transporters, such as CgHxt4/6/7 and CgHxt6/7, may constitute a family of azole importers, involved in clinical drug resistance in fungal pathogens, and constituting promising targets for improved antifungal therapy.
Spin-triplet pairing induced by near-neighbor attraction in the extended Hubbard model for cuprate chain
Authors: Qu Dai-Wei , Chen Bin-Bin , Jiang Hong-Chen , Wang Yao , Li Wei 
Published: October 2022

AbstractIn quantum materials, the electronic interaction and the electron-phonon coupling are, in general, two essential ingredients, the combined impact of which may drive exotic phases. Recently, an anomalously strong electron-electron attraction, likely mediated by phonons, has been proposed in one-dimensional copper-oxide chain Ba2−xSrxCuO3+δ. Yet, it is unclear how this strong near-neighbor attraction V influences the superconductivity pairing in the system. Here we perform accurate many-body calculations to study the extended Hubbard model with on-site Coulomb repulsion U > 0 and near-neighbor attraction V < 0 that could well describe the cuprate chain and likely other similar transition-metal materials with both strong correlations and lattice effects. We find a rich quantum phase diagram containing an intriguing Tomonaga-Luttinger liquid phase — besides the spin density wave and various phase separation phases — that can host dominant spin-triplet pairing correlations and divergent superconductive susceptibility. Upon doping, the spin-triplet superconducting regime can be further broadened, offering a feasible mechanism to realize p-wave superconductivity in realistic cuprate chains.
Multiplexed imaging mass cytometry reveals distinct tumor-immune microenvironments linked to immunotherapy responses in melanoma
Authors: Xiao Xu , Guo Qian , Cui Chuanliang , Lin Yating , Zhang Lei , Ding Xin , Li Qiyuan , Wang Minshu , Yang Wenxian , Kong Yan , Yu Rongshan 
Published: October 2022

Abstract
Background
Single-cell technologies have enabled extensive analysis of complex immune composition, phenotype and interactions within tumor, which is crucial in understanding the mechanisms behind cancer progression and treatment resistance. Unfortunately, knowledge on cell phenotypes and their spatial interactions has only had limited impact on the pathological stratification of patients in the clinic so far. We explore the relationship between different tumor environments (TMEs) and response to immunotherapy by deciphering the composition and spatial relationships of different cell types.

Methods
Here we used imaging mass cytometry to simultaneously quantify 35 proteins in a spatially resolved manner on tumor tissues from 26 melanoma patients receiving anti-programmed cell death-1 (anti-PD-1) therapy. Using unsupervised clustering, we profiled 662,266 single cells to identify lymphocytes, myeloid derived monocytes, stromal and tumor cells, and characterized TME of different melanomas.

Results
Combined single-cell and spatial analysis reveals highly dynamic TMEs that are characterized with variable tumor and immune cell phenotypes and their spatial organizations in melanomas, and many of these multicellular features are associated with response to anti-PD-1 therapy. We further identify six distinct TME archetypes based on their multicellular compositions, and find that patients with different TME archetypes responded differently to anti-PD-1 therapy. Finally, we find that classifying patients based on the gene expression signature derived from TME archetypes predicts anti-PD-1 therapy response across multiple validation cohorts.

Conclusions
Our results demonstrate the utility of multiplex proteomic imaging technologies in studying complex molecular events in a spatially resolved manner for the development of new strategies for patient stratification and treatment outcome prediction.
Decreased psychiatric symptomatology after the onset of COVID-19 in a longitudinal college mental health study
Authors: Dogan Asli Ercan , Kebapci Dilek , Ertan Oguz , Kalay Zeynepgul , Caki Nurdan Kozan , Sar Vedat , Yapici Eser Hale 
Published: October 2022

AbstractThe COVID-19 pandemic brings significant challenges for college students. This study aims to investigate changes in psychiatric symptomatology among them compared to the pre-pandemic period alongside their determinants. Data are collected before and 3 months after the onset of the pandemic from 168 students who applied to a college mental health center. Psychiatric symptomatology is assessed by the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Adult Attention Deficit Hyperactivity Disorder Self-Report Scale (ASRS). Possible vulnerability factors are screened by a survey on COVID-19-related health and social isolation status, Fear of COVID-19 Scale, Social Media Use Disorder Scale (SMDS), Distress Thermometer, Scoff Eating Questionnaire, and International Physical Activity Questionnaire Short-Form (IPAQ). Results show decreased PHQ-9, GAD-7, and ASRS scores at follow-up. Even though the screen time increases, SMDS scores significantly decline. SMDS have a direct effect on PHQ-9 and ASRS levels, in addition to an indirect effect through the Distress Thermometer. Higher SMDS scores predict higher anxious and depressive symptomatology in repeated assessments. Fear of COVID-19 scores have a direct effect on GAD-7 scores only. This study suggests that the stress level and psychiatric symptomatology of the students decreased significantly in the early phases of the pandemic. The level of social media use disorder should be taken into account while following college students with mental health symptoms.
MLfus: A real‐time forecasting architecture for low communication costs in electricity IoT based on ensemble learning
Authors: Li Wenjing , Zhang Nan , Liu Zhu , Ma Shiqian , Ke Huaqiang , Wang Jinfa , Chen Ting 
Published: October 2022

AbstractWith the application and popularity of Internet of Things (IoT) technology, real‐time prediction of time series data has become the focus of electricity IoT data governance. At present, most of the time‐series data prediction methods for the electricity IoT have the defect of being unable to process‐related information between sequences. What's worse, the mainstream data fusion methods all have the problem of limited data dimension. This paper proposes a decision‐level fusion architecture MLfus for multi‐source time‐series data generated under the distributed cloud edge structure of the electricity IoT. The model uses ensemble learning to make decisions and judgments on distributed time‐series data and integrates multi‐source data to make real‐time predictions. MLfus solves the problem of significantly biased predictions from a single model and excels in handling complex nonlinear problems. What's more, MLfus can reduce data and additional training requirements substantially by using decision‐level fusion. Experimental results show that MLfus has a clear advantage in the problem of real‐time electricity price prediction, providing better accuracy while reducing the communication burden.
A novel online method for locating fault coil in direct‐drive permanent magnet synchronous motor with inter‐turn short‐circuit fault using search coil array
Authors: Chen Hao , Zhang Nan , Gao Caixia , Xu Xiaozhuo , Feng Haichao , Si Jikai , Hu Yihua 
Published: October 2022

AbstractThis study presents a fault coil localisation approach for a direct‐drive permanent magnet synchronous motor (DDPMSM) with inter‐turn short‐circuit fault (ISF) using the search coil (SC) array. The SCs are wound around specific stator tooth of DDPMSM through the proposed SC array arrangement principle, which reduces the invasiveness of the fault coil localisation method. The SCs are classified as several search coil groups (SCGs), the differential between SC back electromotive forces (EMFs) in the same SCGs (δ1) and SC residual back EMF (δ2) are used as fault indicators for ISF localisation. The peak values extracted from δ1 and δ2 are the basis for diagnosing ISF. Hence, the proposed approach does not need a complicated signal processing algorithm, and it is less complex. First, the SC back EMF analytical model is developed to investigate the mapping relationship between the back EMF of each SC and fault coil location. Second, fault coil localisation indicators for ISF are analysed based on the proposed analytical model, and the exact ISF localisation approach is presented. Finally, two basic installation units and the arrangement principle of SC array in DDPMSM are proposed. Simulation and experimental results justify the effectiveness of the selected fault indicators and the feasibility of the proposed SC array for diagnosing ISF.
Alzheimer's disease classification using cluster‐based labelling for graph neural network on heterogeneous data
Authors: McCombe Niamh , Bamrah Jake , Sanchez‐Bornot Jose M. , Finn David P. , McClean Paula L. , Wong‐Lin KongFatt ,   Alzheimer's Disease Neuroimaging Initiative (ADNI)
Published: October 2022

AbstractBiomarkers for Alzheimer's disease (AD) diagnosis do not always correlate reliably with cognitive symptoms, making clinical diagnosis inconsistent. In this study, the performance of a graphical neural network (GNN) classifier based on data‐driven diagnostic classes from unsupervised clustering on heterogeneous data is compared to the performance of a classifier using clinician diagnosis as an outcome. Unsupervised clustering on tau‐positron emission tomography (PET) and cognitive and functional assessment data was performed. Five clusters embedded in a non‐linear uniform manifold approximation and project (UMAP) space were identified. The individual clusters revealed specific feature characteristics with respect to clinical diagnosis of AD, gender, family history, age, and underlying neurological risk factors (NRFs). In particular, one cluster comprised mainly diagnosed AD cases. All cases within this cluster were re‐labelled AD cases. The re‐labelled cases are characterized by high cerebrospinal fluid amyloid beta (CSF Aβ) levels at a younger age, even though Aβ data was not used for clustering. A GNN model was trained using the re‐labelled data with a multiclass area‐under‐the‐curve (AUC) of 95.2%, higher than the AUC of a GNN trained on clinician diagnosis (91.7%; p = 0.02). Overall, our work suggests that more objective cluster‐based diagnostic labels combined with GNN classification may have value in clinical risk stratification and diagnosis of AD.
Influence analysis of calculated horizontally layered soil parameters on grounding parameters
Authors: Dan Yihua , Yin Junjun , Yang Jian , Yang Huizhang 
Published: October 2022

AbstractCalculated parameters (soil layer resistivity, soil layer thickness, and the number of soil layers) of horizontally layered soil are usually obtained based on the measured apparent resistivity under different measurement distances, which are significant for the design, operation, and maintenance of grounding grids. Most existing calculation methods of soil parameters are just trying to make the calculation results approach the measurement data, ignoring the relationship among measurement data, the calculated soil parameters, and grounding parameters, which would increase the workload of the measurement. To better balance the distance range of the measurement data and the influence of the calculated horizontally layered soil on grounding parameters, this paper systematically studies the relationship among measured apparent soil resistivity, calculated horizontally layered soil parameters, and grounding parameters. The basic theories of apparent resistivity measurement, soil parameter calculation, and grounding parameter calculation are given, the influence of soil layer thickness on the measured apparent resistivity is studied, and the influence of the calculated soil parameters on the grounding resistance of different grounding models is analysed. Based on different scales of grounding grids, the results give a corresponding reference distance range of measured apparent soil resistivity. Therefore, this paper can help decrease the workload of soil resistivity measurement during grounding parameters analysis, which has far‐reaching engineering significance.
Effect of multiphase content on temperature‐dependent electrical conductivity in silicone rubber composites
Authors: Lin Ying , Liu Yuhao , Cao Bin , Xue Jianyi , Wang Liming , Wang Jianing , Ding Lijian 
Published: October 2022

AbstractTo investigate how the multiphase structures affect the electrical conductivity in semi‐crystalline polymer composites, herein, an accurate multiphase content calculation method is proposed and verified, which combines amorphous phase information in broadband dielectric spectroscopy and crystalline phase information in differential scanning calorimetry. Taken aluminium hydroxide (ATH) filled silicone rubber as an example, it is found that the rigid amorphous fraction (RAF) corresponding to the chains constrained by crystals (RAFcry) is not linearly increased with crystalline fraction (CF). Compared to non‐isothermal crystallisation, RAF caused by ATH/silicone rubber interface (RAFint) after isothermal crystallisation at 213 K changes little, while mobile amorphous fraction and RAFcry is attenuated and CF is strengthened. Based on the calculated structures of ATH filled silicone rubber, activation energy of conductivities during cooling is dominated by the thermal transition for conductive ions and shortened distance among the conductive ions through shrunk volumes of the amorphous phase. Our findings deepen the understanding of multiphase content in semi‐crystalline polymer composites and its relationship with electrical conductivity, which can be applied in manipulating electrical performance of semi‐crystalline polymers by fillers.