bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine learning model based on placental magnetic resonance imaging and clinical factors to predict fetal growth restriction
Authors: Wang Jida , Chen Zhuying , Zhang Hongxi , Li Weikang , Li Kui , Deng Meixiang , Zou Yu 
Published: August 2024

Abstract

Objectives
To create a placental radiomics-clinical machine learning model to predict FGR.
Materials and Methods
Retrospectively analyzed placental MRI and clinical data of 110 FGR cases and 158 healthy controls from two campuses of ZWH. 227 cases from Hubin campus were randomly divided into training (n = 182) and internal testing set (n = 45). 41 cases from Xiaoshan campus were included in external testing set. Placental MRI features were extracted from sagittal T2WI. Mann-Whitney U test, redundancy analysis, and LASSO were used to identify the radiomics signature, and the best-performing radiomics model was constructed by comparing eight machine learning algorithms. Clinical factors determined by univariate and multivariate analyses. A united model and nomogram combining the radiomics Rad-score and clinical factors were established. The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis.
Results
Of 1561 radiomics features, 10 strongly correlated with FGR were selected. The radiomics model using logistic regression performed best compared eight algorithms. 5 important clinical features identified by analysis. The united model demonstrated a good predictive performance in the training, internal testing and external testing sets, with AUC 0.941 (95% CI, 0.0.904–0.977), 0.899 (95% CI, 0.789–1) and 0.861 (95% CI 0.725–0.998), prediction accuracies 0.885, 0.844 and 0.805, precisions 0.871, 0.789 and 0.867, recalls 0.836, 0.833 and 0.684, and F1 scores 0.853, 0.811 and 0.765, respectively. The calibration and decision curves of the united model also showed good performance. Nomogram confirmed clinical applicability of the model.
Conclusions
The proposed placental radiomics-clinical machine learning model is simple yet effective to predict FGR.
Sodium ion conducting blended solid polymer electrolytes: Ion conduction and solid-state battery fabrication
Authors: Chandra Angesh 
Published: August 2024

Abstract

The present paper describes the ion conduction mechanism and solid-state battery fabrication of a new sodium (Na+) ion-conducting blended solid polymer electrolytes (BSPEs): (1-x) [70PEO:30NaCl] + x PVP where 0 ≤ x ≤ 15 wt.%. A recently established hot-press process has been used to synthesize the present BSPEs. The composition: 98(70PEO:30NaCl) + 2PVP yielded the highest ionic conductivity (σ ~ 3.7×10− 5 S.cm-1). Polymer salt/PVP complexation has been studied with the help of x-ray diffraction (XRD), differential scanning calorimetry (DSC) and thermo-gravimetric analysis (TGA). Measurements of ionic conductivity (σ), ionic mobility (µ), mobile ion concentration (n), ionic transference number (tion), and ionic drift velocity (vd) have all been used to elucidate the process of ion conduction. A solid-state polymer battery has been fabricated by using the highest ionic conductivity composition of BSPE. Solid-state battery characteristics have been investigated at room temperature under various load conditions.
Rev-erbα deletion promotes gastric cancer progression through attenuating DLAT and DLST induced cuproptosis
Authors: Wang Xiaoshan , Wu Yuwei , Wang Nana , Chen Mengding , Chen Feixu , Wang Zhengguang 
Published: August 2024

Abstract

Background
Cuproptosis is a unique copper-dependent cell death pathway. Nuclear receptor subfamily 1 group D member 1 (NR1D1/Rev-erbα) is a ligand-activated transcriptional regulator that is involved in regulating the development of circadian rhythm, lipid metabolism and immunity-associated diseases including cancer. However, the role of Rev-erbα in cuproptosis of gastric cancer (GC) cells remains poorly understood.
Methods
Functional assays both in vivo and in vitro were employed to explore the role of Rev-erbα on cell progression and cuproptosis, and its regulatory mechanism. Moreover, clinicopathological retrospective analysis explored the relationship of Rev-erbα with DLAT and DLST.
Results
Rev-erbα deletion promoted GC progression through cuproptosis. The Rev-erbα activator, GSK4112, inhibited GC progression through cuproptosis, and obtained a synergistical inhibitory effect with elesclomol. Mechanistically, Rev-erbα deletion promoted dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide S-succinyltransferase (DLST) expression through inhibiting DLAT oligomerization. Notably, this regulation was dependent on the DNA-binding domain (DBD) of Rev-erbα. Moreover, the combination of GSK4112 with elesclomol inhibited DLAT and DLST expression, and Rev-erbα SUMOylation. Furthermore, DLAT and DLST expression levels were associated with histological grade and tumor-node-metastasis stage in patients with GC. Thus, DLAT or DLST expression exhibit potential as independent biomarkers for predicting the prognosis of patients with GC. In addition, Rev-erbα expression was negatively correlated with DLAT and DLST expression, and high Rev-erbα and low DLAT expression, or high Rev-erbα and low DLST let to optimal levels of disease-free survival in patients with GC.
Conclusion
Rev-erbα exhibits potential in the treatment of GC.
Giant spin-orbit torque induced by spin Hall effect in amorphous Pt(P) alloys
Authors: Fukuma Yasuhiro , Shashank Utkarsh , Tomoda Takafumi , Mathew Arun Jacob , Vashisht Garima , Imai Koki , Kusaba Yu , Dong Chung Li , Chen Chi Liang , Horibe Yoichi , Ishimaru Manabu , Awano Hiroyuki , Asada Hironori 
Published: August 2024

Abstract

We report a giant spin-orbit torque (SOT) induced by spin Hall effect (SHE) in amorphous Pt(P) alloys, which is confirmed by magnetization switching and spin torque ferromagnetic resonance measurements. Pt(P) is fabricated by ion implantation technique using an energy of 10-30 keV with doses ranging from 2.5×1016 -10×1016 ions/cm2. The P-ion implantation process causes distortion and defects in the fcc structure of the as-deposited Pt layer and changes it to an amorphous structure as the accelerating energy as well as the dose increases, leading to a decrease in the electrical conductivity. However, we can obtain a higher spin Hall conductivity of 3.62 ×103 ℏ/2e Ω-1 cm-1 for Pt(P) as compared to that of 1.03 ×103 ℏ/2e Ω-1 cm-1 for pure Pt. The spin Hall efficiency θSH is drastically increased up to 1.17 for Pt(P) with 30 keV energy and dose of 7.5×1016 ions/cm2. We also observe a significant reduction in the critical current density of the SOT magnetization switching from 1.5 × 1011 A/m2 for pure Pt to 3.0 × 1010 A/m2 for Pt(P). Such a giant spin Hall effect can reduce the power consumption to control the magnetization by using SOT and therefore our findings may provide an alternate path to enhance θSH by using amorphous materials with a variety of elements, beyond the crystalline solids.
Implicit-information Embedding and Enhanced Spatial-Temporal Multi-Head Attention Transformer for Traffic Forecasting
Authors: Liu Shipeng , Wang Xingjian 
Published: August 2024

Abstract

Traffic flow prediction is a critical challenge in the field of intelligent transportation systems, as the accuracy of future traffic flow predictions directly impacts the efficiency of urban traffic systems. However, existing deep learning prediction models face several issues. Firstly, many methods concentrate solely on traffic flow data for embedding, overlooking the implicit information underlying these data, which includes human behavioral trends, traffic patterns within and around communities, urban weather conditions, semantic information, and temporal periodicity. Secondly, methods that employ the original multi-head self-attention mechanism calculate attention scores point by point in the temporal dimension without leveraging context, resulting in less accurate attention computation. Thirdly, existing methods struggle to handle both short-range and long-range spatial dependencies simultaneously in the spatial dimension. To address these issues, this paper proposes a method called IEEAFormer (Implicit-information Embedding and Enhanced Spatial-Temporal Multi-Head Attention Transformer). IEEAFormer introduces an embedding layer to capture implicit information in the input, replaces the traditional multi-head self-attention with Temporal-Environment-Aware self-attention in the temporal dimension to enable each node to perceive its contextual environment, and employs two unique graph mask matrices in the spatial dimension to capture both long-range and short-range dependencies. Validation results on four real-world traffic datasets demonstrate that the proposed IEEAFormer outperforms most comparable models in prediction performance.
Solar thermal resonant energy exchange desalination (STREED) for 24-hour, membrane-free, off-grid water treatment
Authors: Alabastri Alessandro , Schmid William , Machorro-Ortiz Aleida , Ye Qian , Nordlander Peter , Dongare Pratiksha , Halas Naomi 
Published: August 2024

Abstract

Freshwater scarcity is a pressing global issue exacerbated by climate change and growing populations. Current desalination technologies all face limitations: reverse osmosis requires grid electrical power and specialized membranes, thermal desalination is inefficient, and membrane systems are prone to fouling. Here we introduce Solar Thermal Resonant Energy Exchange Desalination (STREED), a robust, membrane-free and efficient solar thermal desalination approach. Utilizing the principle of Resonant Energy Transfer, the distillation efficiency can be maximized by matching the heat fluxes between interacting air and water fluids. Dynamic tuning of the flow rates in response to varying solar intensities significantly increases efficiency, extending freshwater production over 24-hour/day. We predict week-long freshwater productivity increases of 70% with an average Specific Water Productivity (SWP) between ~3 and ~5 L/kWh, depending on available solar irradiation. STREED adapts to fluctuating solar inputs, offering a scalable solution for decentralized, off-grid water treatment, crucial for remote communities facing water scarcity.
Compact multifilamentary circuit model for multilevel bipolar resistive switching in memristors
Authors: Busygin Alexander , Udovichenko Sergey , Maevsky Oleg , Pisarev Alexander , Ebrahim Abdulla 
Published: August 2024

Abstract

A rather simple compact multifilamentary circuit model of bipolar memristor resistive switching with controlled multilevel conductivity tuning in a metal oxide memristor is presented. The model differs from known circuit level models by simpler equations for current and state variable. Comparing to other papers, the total number of fitting parameters grows slower with an increase in filaments number. This corresponds to a faster and easier fitting process. The model was implemented in the SPICE code. The simple equivalent circuit of the memristor element will allow to reduce signal processing simulation time in large memristor arrays in comparison with circuits based on known compact models with one and several filaments.
Realization of the apology speech act by Egyptian HSL learners
Authors: Ibrahim Ahmed 
Published: August 2024

Abstract

This study investigated the apology speech act performed by Egyptian Hebrew learners as a second language and native Israeli Hebrew speakers. Two groups of participants were formed: 30 Egyptian participants (16 males and 14 females) and 30 Israeli participants (16 males and 14 females). The discourse completion test was chosen as an instrument for data collection. The data was analyzed based on the taxonomy of Olshtain and Cohen (1983) and Blum-Kulka et al. (1989) (CCSARP). The results of this study showed that the use of apology strategies by Egyptians was pragmatically appropriate for the responses of native Hebrew speakers in all situations. Furthermore, this study found significant similarities between Egyptians and Israelis in terms of their realization of apology strategies by demonstrating a wider use of all six apology strategies in most situations, although the percentages of apology strategies performed were slightly different between the two groups in some situations.
Animal and organoid models to elucidate the anti-fibrotic effect of steroid on biliary atresia
Authors: Liu Fangran , Lui Vincent Chi Hang , Wu Zhongluan , Blakeley Paul David , Tang Clara Sze Man , Tam Paul Kwong Hang , Wong Kenneth Kak Yuen , Chung Patrick Ho Yu 
Published: August 2024

Abstract

Purpose
We performed animal and organoid study to evaluate the anti-fibrotic effect of steroid on BA and the underlying patho-mechanism.
Methods
BA animal models were created by inoculation of mice on post-natal day 1 with Rhesus Rotavirus (RRV) They received either 20ul Phosphate-buffered saline (PBS) or steroid from day 21 to day 34. On day 34, their serum samples were collected for hormonal markers. Necrosis fibrosis and CK 19 expression in the liver were evaluated. Liver organoids were developed and their morphology as well as bulk RNA sequencing data were analyzed.
Results
Twenty-four mice developed BA features after RRV injection and were equally divided into steroid and PBS groups. On day 34, the weight gain of steroid group increased significantly than PBS group (p<0.0001). All mice in the PBS group developed liver fibrosis but only one mouse in the steroid group did. Serum bilirubin and liver parenchymal enzymes were significantly lower in steroid group. The morphology of liver organoids were different between the two groups. A total of 6359 differentially expressed genes were found between steroid group and PBS group.
Conclusion
Based on our findings obtained from RRV-induced BA animal and organoid models, steroid has the potential to mitigate liver fibrosis in BA.
Knowledge, Attitudes, and Practices regarding Anthrax among affected Communities, Kazo District, South-Western Uganda, May 2022
Authors: Senyange Shaban , Nsubuga Edirisa J. , Kwesiga Benon , Bulage Lilian , Ario Alex R. 
Published: August 2024

Abstract

Background
Anthrax is a priority zoonotic disease in Uganda. Despite health education about risks of eating meat from animals found dead, some areas including Kazo District, experience repeated anthrax outbreaks associated with this practice. We assessed the knowledge, attitudes, and practices (KAP) around anthrax and consumption of meat of animals found dead in previously-affected communities in Kazo District.
Methods
We conducted a mixed-methods study in six villages in Kazo District from May 23-June 4, 2022. We administered structured questionnaires to 200 systematically-sampled community respondents aged ≥ 18 years about anthrax-related KAP and experiences with livestock loss. We conducted focus group discussions with community members identified as anthrax case-patients in previous outbreaks and those whose animals died suddenly in the previous year. We assessed overall knowledge through a set of eight questions on anthrax; species affected, signs and symptoms, transmission and prevention in humans and animals. We scored participants’ responses to KAP questions as 1 = correct or 0 = incorrect; adequate knowledge score was ≥ 4. Qualitative data were analyzed using content analysis.
Results
Among 200 survey respondents, 65% were female; mean age was 45 (SD ± 17.7) years. In total, 94% had heard of anthrax, 70% knew it was zoonotic; 63% did not know any signs of anthrax in animals, though 73% knew transmission could occur through eating animals found dead. Only 16% said they had lost their livestock suddenly in the last year; of these, 21% consumed the meat and 53% buried the carcasses. Overall, 77% had adequate knowledge about anthrax. Qualitative data indicated that farmers did not vaccinate their animals against anthrax due to cost, and inadequate access to vaccine and veterinary services. Poverty, limited access to meat protein, and economic challenges were cited as drivers for consuming meat from animals found dead despite the risk.
Conclusion
Good knowledge about anthrax among residents of a repeatedly-affected community did not translate to safe practices. It may be difficult for affected communities to forego opportunities to eat meat from animals they find dead, even when they suspect possible danger. Compensating farmers for anthrax-positive carcasses in exchange for permitting safe animal disposal might reduce risk of transmission.
Examination of four L2 teachers’ pedagogical knowledge base in face-to-face and online classroom settings: Can academic degrees make a difference?
Authors: Goodarzi Ahmad , Rezai Afsheen , Ashkani Parisa 
Published: August 2024

Abstract

Teacher pedagogical knowledge base (PKB) has always attracted a great deal of attention in research concerning teachers’ cognition. However, the interplay between the second/foreign (L2) teachers' academic degrees and different classroom settings has remained under-explored. Hence, this study seeks to explore the influences of classroom settings (i.e., face-to-face vs. online) and academic TESOL degrees (i.e., B.A. vs. M.A. graduates) on shaping L2 teachers' PKB. In so doing, four L2 teachers working at four private English language institutes in Iran volunteered to participate in the research. Drawing upon an exploratory mixed-methods approach, qualitative and quantitative data were obtained using stimulated recall technique. The recalled pedagogical knowledge (PK) categories were analyzed across the two groups by extracting the PK categories, reporting their type and frequency, and running chi-square statistics. The findings showed no significant differences between the sum of pedagogical thoughts (PTs) of B.A. and M.A. L2 teachers in face-to-face classroom settings; however, there were minor differences in the rankings of PK categories between the groups of teachers. On the contrary, the L2 teachers holding M.A. outperformed their B.A. counterparts in generating PK categories in online classes. Moreover, it was revealed that both groups of teachers could produce new contextual PK categories when reflecting on their online classes. In tune with the findings, various suggestions were offered for designing teacher training courses that focus more on the practical side of L2 teachers’ PKB in face-to-face and online L2 teaching settings.
Monazite, lanthanide-rich glasses, and other trace elements in copper smelter slags: Constraints on critical metal behaviour in Si-Fe-rich melts
Authors: Gezzaz Hassan , Ciobanu Cristiana , Cook Nigel , Ehrig kathy , slattery ashley , wade benjamin , gilbert sarah , camporodriguez yuri 
Published: August 2024

Abstract

Furnace slags are potential new sources of critical metals. We undertook a micron- to nanoscale study that addresses speciation, distribution and associations of phases in flash furnace (FF, oxidised) and electric furnace (EF, reduced) slags from the Olympic Dam mining-smelting-refinery operation. Results enable understanding of the behaviour and partitioning of critical metals between melt and cooling crystalline phases in a controlled smelter environment that mimics Fe-Si-rich systems in Nature. Melts at ~1300 °C result in slags that differ in the relative proportions of component phases. Both FF and EF slags comprise major magnetite and two, compositionally distinct Si-Fe-rich glasses (glass-1 and -2); fayalite is a main component of EF slag. Glass-1 is rich in REE+Y (4.5–5.4 wt%, Ce2O3+La2O3) and contains dendritic monazite-(Ce). The EF slag crystallization sequence is: magnetite→fayalite+glass-1→monazite→glass-2. Immiscibility of REE in Si-Fe-rich melt is inferred from amorphous ‘monazite-like’ droplets. Chondrite-normalised fractionation patterns are defined by downwards-sloping LREE segments in both glasses. Partition coefficients are calculated for magnetite and fayalite relative to glasses. DREY for HREE exceeds those for LREE in all phases and fayalite has an order of magnetite higher DHREE than co-existing EF magnetite. Applying lattice strain models to experimental values show excellent fits for DHREE-model trends, even if lattice strain is not the sole factor controlling partitioning. Melt polymerisation, variable/unpredictable oxidation states, and constraints from specific crystallographic sites, also impact on observed trends. This study demonstrates that clues to element behaviour in the deep Earth are available from metallurgical plants.
Picture Fuzzy Einstein Interactive Weighted Averaging Aggregation Operator and Its Application in Multiple Attribute Decision-Making
Authors: Abdullah Siti Rohana Goh , Ahmad Muhammad Zaini 
Published: August 2024

Abstract

A Picture Fuzzy Set (PFS) is an effective tool for handling uncertainties and incomplete cognitive information, incorporating membership, hesitancy, non-membership, and refusal degrees to accommodate diverse viewpoints. The Einstein operation has demonstrated good performance in aggregating data within uncertain contexts, garnering attention in the picture fuzzy environment. However, the existing picture fuzzy Einstein aggregation operator has limitations, particularly when a Picture Fuzzy Number (PFN) possesses a non-membership degree of zero. This leads to an aggregated non-membership degree of zero, disregarding the influence of other non-zero non-membership degrees, rendering them independent. To address these issues, a new decision-making approach is proposed, employing Einstein’s operations for PFNs. The Picture Fuzzy Einstein Interactive Weighted Averaging (PFEIWA) operator are proposed and extensively discussed for its desirable properties. Furthermore, a novel approach referring to these operators in Multi-attribute Decision-Making (MADM) problems is presented. The proposed method applied to a sustainable beef supplier selection problem, and its performance is compared with existing methods. The results show consistent optimal rankings of alternatives, indicating superiority of the proposed operator in resolving MADM problems. The suggested operator is more convincing and suitable due to its ability to produce reasonable and reliable results by considering interactions between PFNs’ degrees.