bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding identity salience and English as a Foreign Language teaching practices: A case study of multi‐subject generalist teachers
Authors: Alam Md. Saiful , Asmawi Adelina 
Published: September 2023

AbstractThe scarcity of teachers worldwide has led to educators teaching multiple subjects outside their area of expertise. This challenge of teaching out‐of‐field or multi‐subject instruction raises the need for (re)constructing the identity of multi‐subject generalist teachers (M‐SGTs). However, the matter has received little attention in current literature. This study aimed to explore the process by which M‐SGTs develop a salient identity as EFL teachers and how this identity impacts their practices in teaching EFL. To achieve this, a case‐study approach was employed, and six M‐SGTs from three private kindergarten schools in rural Bangladesh were selected using convenient sampling. Data were gathered from observation protocols, semi‐structured interviews, and documents. The interviews and observation protocols were transcribed and coded, while the documents were reviewed thematically and categorically in line with Kvale's recommendations. The results of this investigation highlight the complex and multifaceted nature of the development of salient identity as EFL teachers among M‐SGTs. The study reveals that M‐SGTs develop a strong identity as EFL teachers through negotiation, adaptation, subject selection, confidence, language acquisition experience, pre‐service pedagogical skills, social support, positive feedback and endorsement by principals. The study also finds that M‐SGTs' salient identity is reflected in their teaching practices that involve being role models, adapting English language instruction, employing interactivity, differentiation in pedagogy, comprehensive feedback, whole‐class teaching and the use of supplementary materials. This paper ends with an important implication.
Reinforced unscented Kalman filter for consensus achievement of uncertain multi‐agent systems subject to actuator faults
Authors: Borah Kaustav Jyoti , Kumar Krishna Dev 
Published: September 2023

AbstractIn this paper, actuator fault detection and reconstruction in consensus tracking of uncertain multi‐agent systems (MAS) is addressed. The communication is assumed to be connected undirected. An adaptive fault detection method is developed to detect actuator faults. A novel‐reinforced unscented Kalman filter (RUKF) is employed to reconstruct the faults by adjusting the noise covariance matrices of unscented Kalman filter (UKF) as well as to train neural network internal parameters by providing a set of previous measurements. A Chebyshev neural network (CNN) is incorporated to learn the uncertain plant. To prevent the neural network approximation errors a hyperbolic tangent function‐based robust control term is applied. The Lyapunov stability approach guarantees the stability of the proposed RUKF, which runs in conjunction with robust control method. Lastly, numerical simulations are presented to show the effectiveness of the proposed RUKF under actuator abrupt, intermittent, and transient fault conditions.
Stratified learning: A general‐purpose statistical method for improved learning under covariate shift
Authors: Autenrieth Maximilian , van Dyk David A. , Trotta Roberto , Stenning David C. 
Published: September 2023

AbstractWe propose a simple, statistically principled, and theoretically justified method to improve supervised learning when the training set is not representative, a situation known as covariate shift. We build upon a well‐established methodology in causal inference and show that the effects of covariate shift can be reduced or eliminated by conditioning on propensity scores. In practice, this is achieved by fitting learners within strata constructed by partitioning the data based on the estimated propensity scores, leading to approximately balanced covariates and much‐improved target prediction. We refer to the overall method as Stratified Learning, or StratLearn. We demonstrate the effectiveness of this general‐purpose method on two contemporary research questions in cosmology, outperforming state‐of‐the‐art importance weighting methods. We obtain the best‐reported AUC (0.958) on the updated “Supernovae photometric classification challenge,” and we improve upon existing conditional density estimation of galaxy redshift from Sloan Digital Sky Survey (SDSS) data.
Amorphous MoS2 Decorated Ni3S2 with a Core–shell Structure of Urchin‐Like on Nickel‐Foam Efficient Hydrogen Evolution in Acidic and Alkaline Media
Authors: Hu Mengliang , Qian Yuanpeng , Yu Shuhui , Yang Qingyao , Wang Zhinan , Huang Yishuai , Li Liping 
Published: September 2023

AbstractThe large‐scale commercialization of the hydrogen evolution reaction (HER) necessitates the development of cost‐effective and highly efficient electrocatalysts. Although transition metal sulfides, such as MoS2 and Ni3S2, hold great potential in the field of HER, their catalytic performance has been unsatisfactory due to incomplete exposure of active sites and poor electrical conductivity. In this work, via a simple hydrothermal strategy, amorphous MoS2 nanoshells in the form of urchin‐like MoS2‐Ni3S2 core‐shell heterogeneous structure is realized and in situ loaded on nickel foam (A‐MoS2‐Ni3S2‐NF). In particular, XPS analysis results show that the coupling of amorphous MoS2 and Ni3S2 makes the electrode surface exhibit electron‐abundant property, which will have a positive impact on HER catalytic activity. In addition, the fully exposed active site of amorphous MoS2 is another crucial factor contributing to its high catalytic performance of A‐MoS2‐Ni3S2‐NF electrode. In particular, at a current density of 10 mA cm⁻2, the overpotential of electrode is 95 mV (1.0 m KOH) and 145 mV (0.5 m H2SO4). This work highlights the importance of amorphous MoS2 and MoS2‐Ni3S2 of sea‐urchin core‐shell structure in optimizing HER performance, which provides an important reference for HER research.
Rational Design of Ion‐Conductive Layer on Si Anode Enables Superior‐Stable Lithium‐Ion Batteries
Authors: Wang Ziyang , Yao Meng , Luo Hang , Xu Changhaoyue , Tian Hao , Wang Qian , Wu Hao , Zhang Qianyu , Wu Yuping 
Published: September 2023

AbstractSilicon (Si) is considered a promising commercial material for the next‐generation of high‐energy density lithium‐ion battery (LIB) due to its high theoretical capacity. However, the severe volume changes and the poor conductivity hinder the practical application of Si anode. Herein, a novel core–shell heterostructure, Si as the core and V3O4@C as the shell (Si@V3O4@C), is proposed by a facile solvothermal reaction. Theoretical simulations have shown that the in‐situ‐formed V3O4 layer facilitates the rapid Li+ diffusion and lowers the energy barrier of Li transport from the carbon shell to the inner core. The 3D network structure constructed by amorphous carbon can effectively improve electronic conductivity and structural stability. Benefiting from the rationally designed structure, the optimized Si@V3O4@C electrode exhibits an excellent cycling stability of 1061.1 mAh g−1 at 0.5 A g−1 over 700 cycles (capacity retention of 70.0%) with an average Coulombic efficiency of 99.3%. In addition, the Si@V3O4@C||LiFePO4 full cell shows a superior capacity retention of 78.7% after 130 cycles at 0.5 C. This study opens a novel way for designing high‐performance silicon anode for advanced LIBs.
Theory of the third: A cybernetic approach to escalative conflict dynamics in business families
Authors: Nagel Lina , Roth Steffen , Kleve Heiko 
Published: September 2023

AbstractThis conceptual paper explores the surprising impact exerted by third elements on the escalation and de‐escalation of conflicts in business families. To this end, we draw on core concepts of Batesonian cybernetic theory to perform a reconceptualisation of pertinent literature on changing conflict dynamics gathered in family business research and consultancy. Based on this reconceptualisation, we identify explanations and key mechanisms for the impact of third elements on conflict dynamics. Our study thus contributes to research at the interface of family business research, conflict research and cybernetic theory development.
Biodegradation of septic tank fecal sludge using Priestia aryabhattai
Authors: Wardhani Widhowati Kesoema , Titah Harmin Sulistiyaning , Mardyanto Mas Agus , Soedjono Eddy Setiadi 
Published: September 2023

AbstractThe significant potential of microorganisms for fecal sludge degradation is an interesting area for investigation, primarily due to its current lack of attention. This study involved the identification of indigenous bacteria in septic tank fecal waste with the Polymerase Chain Reaction (PCR) 16S rRNA gene. Subsequently, selected bacteria strains were subjected to a potential assessment using a single method. Variables in this experiment included the addition of 2% (v/v) bacteria and sample sterilization. The results showed that the use of PCR 16S rRNA analysis led to the identification of Priestia aryabhattai, a member of the phylum Firmicutes, as the dominant species in the samples. This bacteria exhibited adaptability to both aerobic and anaerobic conditions. Sterile samples with the addition of P. aryabhattai 2% (v/v), showed the best removal efficiency percentages of 79.77%, 79.62%, 62.91%, and 70.48% for Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD), Total Suspended Solids (TSS), and Volatile Suspended Solids (VSS). Meanwhile, the total carbon and nitrogen decreased to 2895 mg/L C and 794.12 mg/L NH3‐N, respectively. Based on the results, Priestia aryabhattai has the potential to degrade organic waste but is not suitable for fecal sludge.
Performance of machine‐learning approach for prediction of pre‐eclampsia in a middle‐income country
Authors: Torres‐Torres J. , Villafan‐Bernal J. R. , Martinez‐Portilla R. J. , Hidalgo‐Carrera J. A. , Estrada‐Gutierrez G. , Adalid‐Martinez‐Cisneros R. , Rojas‐Zepeda L. , Acevedo‐Gallegos S. , Camarena‐Cabrera D. M. , Cruz‐Martínez M. Y. , Espino‐y‐Sosa S. 
Published: September 2023

ABSTRACTObjectivePre‐eclampsia (PE) is a serious complication of pregnancy associated with maternal and fetal morbidity and mortality. As current prediction models have limitations and may not be applicable in resource‐limited settings, we aimed to develop a machine‐learning (ML) algorithm that offers a potential solution for developing accurate and efficient first‐trimester prediction of PE.MethodsWe conducted a prospective cohort study in Mexico City, Mexico to develop a first‐trimester prediction model for preterm PE (pPE) using ML. Maternal characteristics and locally derived multiples of the median (MoM) values for mean arterial pressure, uterine artery pulsatility index and serum placental growth factor were used for variable selection. The dataset was split into training, validation and test sets. An elastic‐net method was employed for predictor selection, and model performance was evaluated using area under the receiver‐operating‐characteristics curve (AUC) and detection rates (DR) at 10% false‐positive rates (FPR).ResultsThe final analysis included 3050 pregnant women, of whom 124 (4.07%) developed PE. The ML model showed good performance, with AUCs of 0.897, 0.963 and 0.778 for pPE, early‐onset PE (ePE) and any type of PE (all‐PE), respectively. The DRs at 10% FPR were 76.5%, 88.2% and 50.1% for pPE, ePE and all‐PE, respectively.ConclusionsOur ML model demonstrated high accuracy in predicting pPE and ePE using first‐trimester maternal characteristics and locally derived MoM. The model may provide an efficient and accessible tool for early prediction of PE, facilitating timely intervention and improved maternal and fetal outcome. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Revisiting conservation units for the endangered mountain yellow-legged frog species complex (Rana muscosa, Rana sierrae) using multiple genomic methods
Authors: Byrne Allison Q. , Rothstein Andrew P. , Smith Lydia L. , Kania Hannah , Knapp Roland A. , Boiano Daniel M. , Briggs Cheryl J. , Backlin Adam R. , Fisher Robert N. , Rosenblum Erica Bree 
Published: September 2023

AbstractInsights from conservation genomics have dramatically improved recovery plans for numerous endangered species. However, most taxa have yet to benefit from the full application of genomic technologies. The mountain yellow-legged frog species complex, Rana muscosa and Rana sierrae, inhabits the Sierra Nevada mountains and Transverse/Peninsular Ranges of California and Nevada. Both species have declined precipitously throughout their historical distributions. Conservation management plans outline extensive ongoing recovery efforts but are still based on the genetic structure determined primarily using a single mitochondrial sequence. Our study used two different sequencing strategies – amplicon sequencing and exome capture – to refine our understanding of the population genetics of these imperiled amphibians. We used buccal swabs, museum tissue samples, and archived skin swabs to genotype frog populations across their range. Using the amplicon sequencing and exome capture datasets separately and combined, we document five major genetic clusters. Notably, we found evidence supporting previous species boundaries within Kings Canyon National Park with some exceptions at individual sites. Though we see evidence of genetic clustering, especially in the R. muscosa clade, we also found evidence of some admixture across cluster boundaries in the R. sierrae clade, suggesting a stepping-stone model of population structure. We also find that the southern R. muscosa cluster had large runs of homozygosity and the lowest overall heterozygosity of any of the clusters, consistent with previous reports of marked declines in this area. Overall, our results clarify management unit designations across the range of an endangered species and highlight the importance of sampling the entire range of a species, even when collecting genome-scale data.
Enacting multilingual learner core practices: a PST’s approximations of practice of mathematics language routines
Authors: Roberts Sarah A. , Olarte T. Royce 
Published: September 2023

AbstractThis study considered a preservice teacher’s (PST’s) attention to multilingual learner core practices within her approximations of practice of mathematics language routines during a secondary mathematics methods course. We used a framework of approximations of practice to understand how a PST enacted and developed an understanding of multilingual learner core practices. To provide a vision for what multilingual learner core practices can look like in nontraditional instructional contexts, we qualitatively analyzed four approximations of practice of mathematics language routines from a single PST during a single semester of a methods course. We share how she navigated the remote teaching context and engaged sample students in all of the multilingual learner core practices despite the challenges of the COVID-19 pandemic, providing an example of what these practices may look like in remote instruction. We also discuss how these multilingual learner core practices interact and complement one another. We consider possible implications, limitations, and future research directions.
Skills transfer from the DaVinci® system to the Hugo™ RAS system
Authors: Olsen Rikke Groth , Karas Vladimir , Bjerrum Flemming , Konge Lars , Stroomberg Hein Vincent , Dagnæs-Hansen Julia Abildgaard , Røder Andreas 
Published: September 2023

Abstract
Purpose
Recently, the robotic surgical system, Hugo™ was approved for clinical use. The transfer of skills is important for understanding the implementation of surgical innovation. We explored the transfer of skills from the DaVinci® to the Hugo™ by studying the learning curve and short-term patient outcomes during radical prostatectomy (RARP).

Methods
We examined the transfer of skills from one surgeon performing RARP from the first case with the Hugo™ system in April 2022. The surgeon had previously performed > 1000 RARPs using DaVinci®. Perioperative and clinical outcomes were collected for procedures on both Hugo™ and DaVinci®. Patient follow-up time was 3 months.

Results
Nineteen Hugo™ cases and 11 DaVinci® cases were recorded. No clinically relevant difference in procedure time was found when transferring to Hugo™. Patients operated using Hugo™ had more contacts postoperatively compared to the DaVinci®, all Clavien–Dindo (CD) grade 1 (53% vs 18%). Three patients from the Hugo™ group were re-admitted within 30 days with catheter malfunction (CD grade 1), infection without a focus (CD grade 2), and ileus due to a hernia in the port hole (CD grade 3b). The 3-month follow-up showed similar results in prostate-specific antigen levels (PSA) and erectile dysfunction between the two robotic systems, but a higher incidence of incontinence was found for the Hugo™.

Conclusion
We observed that the skills of an experienced robotic surgeon are transferable from DaVinci® to Hugo™ when performing RARP. No obvious benefits were found for using Hugo™ compared to DaVinci® for RARP although this needs confirmatory studies.
Bronchoscopy-Related Infection and the Development of Single-Use Bronchoscopy Technology
Authors: Logan N. , Yurosko C. , Mehta A. , Chhabria M. , Kennedy M.P. 
Published: September 2023

Abstract
Purpose of Review
Bronchoscopy-related infection is recognized as a leading healthcare hazard, and this review delves into its incidence, causes, and prevention.

Recent Findings
Due to both the recognition of the scale of bronchoscopy-related infection and the COVID-19 pandemic, single-use or disposable bronchoscopy (SUFB) technology has progressed beyond the ICU setting to the bronchoscopy suite. A review of data related to currently available scopes, bench-top, and clinical data is also presented.

Summary
Not only does SUFB technology provide a portable and immediately accessible bronchoscope for procedures in the ICU and endoscopy suite, it also is a sterile option for standard bronchoscopy procedures thus avoiding infection related to scope contamination. Cost-effectiveness comparisons vary between single-use and reusable scopes depending on calculated incidence of scope-related infection. Although no one should suffer an infection related to bronchoscopy, SUFB technology lacks proper comparison to reusable scope quality. In the meantime, the most important intervention is proper cleaning and assessment of reusable scopes for damage.
Concurrent Carbon Capture and Biocementation through the Carbonic Anhydrase (CA) Activity of Microorganisms -a Review and Outlook
Authors: Mwandira Wilson , Mavroulidou Maria , Gunn Michael J. , Purchase Diane , Garelick Hemda , Garelick Jonathan 
Published: September 2023

AbstractBiocementation, i.e., the production of biomimetic cement through the metabolic activity of microorganisms, offers exciting new prospects for various civil and environmental engineering applications. This paper presents a systematic literature review on a biocementation pathway, which uses the carbonic anhydrase (CA) activity of microorganisms that sequester CO2 to produce biocement. The aim is the future development of this technique for civil and (geo-)environmental engineering applications towards CO2-neutral or negative processes. After screening 248 potentially relevant peer-reviewed journal papers published between 2002 and 2023, 38 publications studying CA-biocementation were considered in the review. Some of these studies used pure CA enzyme rather than bacteria-produced CA. Of these studies, 7 used biocementation for self-healing concrete, 6 for CO2 sequestration, 10 for geotechnical applications, and 15 for (geo-)environmental applications. A total of 34 bacterial strains were studied, and optimal conditions for their growth and enzymatic activity were identified. The review concluded that the topic is little researched; more studies are required both in the laboratory and field (particularly long-term field experiments, which are totally lacking). No studies on the numerical modelling of CA-biocementation and the required kinetic parameters were found. The paper thus consulted the more widely researched field of CO2 sequestration using the CA-pathway, to identify other microorganisms recommended for further research and reaction kinetic parameters for numerical modelling. Finally, challenges to be addressed and future research needs were discussed.
LTACL: long-tail awareness contrastive learning for distantly supervised relation extraction
Authors: Yan Tianwei , Zhang Xiang , Luo Zhigang 
Published: September 2023

AbstractDistantly supervised relation extraction is an automatically annotating method for large corpora by classifying a bound of sentences with two same entities and the relation. Recent works exploit sound performance by adopting contrastive learning to efficiently obtain instance representations under the multi-instance learning framework. Though these methods weaken the impact of noisy labels, it ignores the long-tail distribution problem in distantly supervised sets and fails to capture the mutual information of different parts. We are thus motivated to tackle these issues and establishing a long-tail awareness contrastive learning method for efficiently utilizing the long-tail data. Our model treats major and tail parts differently by adopting hyper-augmentation strategies. Moreover, the model provides various views by constructing novel positive and negative pairs in contrastive learning for gaining a better representation between different parts. The experimental results on the NYT10 dataset demonstrate our model surpasses the existing SOTA by more than 2.61% AUC score on relation extraction. In manual evaluation datasets including NYT10m and Wiki20m, our method obtains competitive results by achieving 59.42% and 79.19% AUC scores on relation extraction, respectively. Extensive discussions further confirm the effectiveness of our approach.
Structural characterization of char during co-gasification from torrefied sludge and Yangchangwan bituminous coal
Authors: Zhang Xinsha , Bai Yonghui , Qin Jie , Shi Shengli , Liu Jiazhong , Wang Shuaibing , Zhao Minhui , Shi Guiming , Ye Changbing , Yu Guangsuo 
Published: September 2023

AbstractThe present study aims to investigate the physico-chemical structural evolution characteristics of char structure of CO2 atmosphere torrefaction pretreated sludge with Yangchangwan bituminous coal (YC) during co-gasification. The co-gasification reactivity of torrefied sludge and YC was measured using a thermogravimetric analyzer. The co-gasification reactivity of torrefied sludge with YC was thoroughly explored in depth by in situ heating stage microscope coupled with traditional characterization means of char sample (Scanning electron microscope, nitrogen adsorption analyzer, laser Raman spectroscopy). The results show that the gasification reaction rate of sludge treated under CO2 atmosphere and coal blended char was better than other char samples at 1100–1200 °C. The torrefied sludge under CO2 atmosphere promoted its thermal decomposition to the maximum extent, so that it eventually was transformed into a large number of small broken particles. The specific surface area and ID1/IG ratio of blended char of torrefied sludge under CO2 atmosphere and YC were 1.70 and 1.07 times higher than that of YC, respectively. The in situ technique revealed that YC char with the addition of torrefied sludge undergo gasification by shrinking core modes and the presence of obvious ash melting flow phenomenon. It was more obvious than that of YC.