bluuebunny/crossref_metadata_2025_split huggingface dataset:
Managing Resources for Shared Micromobility: Approximate Optimality in Large-Scale Systems
Authors: Akturk Deniz , Candogan Ozan , Gupta Varun 
Published: October 2024

We consider the problem of managing resources in shared micromobility systems (bike sharing and scooter sharing). An important task in managing such systems is periodic repositioning/recharging/sourcing of units to avoid stockouts or excess inventory at nodes with unbalanced flows. We consider a discrete-time model; each period begins with an initial inventory at each node in the network, and then, customers (demand) materialize at the nodes. Each customer picks up a unit at the origin node and drops it off at a randomly sampled destination node with an origin-specific probability distribution. We model the above network inventory management problem as an infinite horizon discrete-time discounted Markov decision process (MDP) and prove the asymptotic optimality of a novel mean-field approximation to the original MDP as the number of stations becomes large. To compute an approximately optimal policy for the mean-field dynamics, we provide an algorithm with a running time that is logarithmic in the desired optimality gap. Lastly, we compare the performance of our mean field-based policy with state-of-the-art heuristics via numerical experiments, including experiments using Austin scooter-sharing data. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02023 .
Coordination in Dynamic Teams: Investigating a Learning–Productivity Trade-Off
Authors: Mayo Anna T. , Woolley Anita Williams , John Liny , March Christine , Witchel Selma , Nowalk Andrew 
Published: October 2024

The rapid growth in the use of teams and multiple team membership has led more organizations to structure work around dynamic teams, characterized by short lifespans and fluid membership boundaries. This approach to organizing work makes it difficult for teams to work efficiently or to support the learning and growth of members. Given the importance of productivity and learning, we ask how these processes can be supported in dynamic teams. We do so in a randomized controlled field experiment conducted with 91 teams in a teaching hospital, a context in which physician trainees must learn while providing patient care in dynamic teams of care providers. We randomly assigned physician teams, or “core” teams, to launch their work with an intervention focused either on internal coordination among the core team members or on external coordination with a changing cast of external contributors such as nurses and specialists. We measured resulting levels of internal and external coordination over teams’ week-long lifespans and observed that external coordination was associated with improved team efficiency, whereas internal coordination was associated with improved individual learning. Post hoc exploratory analysis suggested that individual learning was highest when teams achieved high levels of both internal and external coordination, and it was positively correlated with improvement in the team’s patients’ average length of hospital stay. We discuss the implications of the demonstrated causal effects of team launches, along with our exploratory findings, for the management of dynamic teams and the opportunities to mitigate potential trade-offs between learning and productivity. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.16729 .
Windswept deformity of the knee: prevalence and predictive factors in osteoarthritic and healthy populations
Authors: Moore Joss , van de Graaf Victor A. , Wood Jil A. , Humburg Peter , Colyn William , Bellemans Johan , Chen Darren B. , MacDessi Samuel J. 
Published: October 2024

AimsThis study examined windswept deformity (WSD) of the knee, comparing prevalence and contributing factors in healthy and osteoarthritic (OA) cohorts.MethodsA case-control radiological study was undertaken comparing 500 healthy knees (250 adults) with a consecutive sample of 710 OA knees (355 adults) undergoing bilateral total knee arthroplasty. The mechanical hip-knee-ankle angle (mHKA), medial proximal tibial angle (MPTA), and lateral distal femoral angle (LDFA) were determined for each knee, and the arithmetic hip-knee-ankle angle (aHKA), joint line obliquity, and Coronal Plane Alignment of the Knee (CPAK) types were calculated. WSD was defined as a varus mHKA of < -2° in one limb and a valgus mHKA of > 2° in the contralateral limb. The primary outcome was the proportional difference in WSD prevalence between healthy and OA groups. Secondary outcomes were the proportional difference in WSD prevalence between constitutional varus and valgus CPAK types, and to explore associations between predefined variables and WSD within the OA group.ResultsWSD was more prevalent in the OA group compared to the healthy group (7.9% vs 0.4%; p < 0.001, relative risk (RR) 19.8). There was a significant difference in means and variance between the mHKA of the healthy and OA groups (mean -1.3° (SD 2.3°) vs mean -3.8°(SD 6.6°) respectively; p < 0.001). No significant differences existed in MPTA and LDFA between the groups, with a minimal difference in aHKA (mean -0.9° healthy vs -0.5° OA; p < 0.001). Backwards logistic regression identified meniscectomy, rheumatoid arthritis, and osteotomy as predictors of WSD (odds ratio (OR) 4.1 (95% CI 1.7 to 10.0), p = 0.002; OR 11.9 (95% CI 1.3 to 89.3); p = 0.016; OR 41.6 (95% CI 5.4 to 432.9), p ≤ 0.001, respectively).ConclusionThis study found a 20-fold greater prevalence of WSD in OA populations. The development of WSD is associated with meniscectomy, rheumatoid arthritis, and osteotomy. These findings support WSD being mostly an acquired condition following skeletal maturity.Cite this article: Bone Jt Open 2024;5(10):879–885.
Machine Learning Evaluation of Fruit Ripeness with Multidimensional Sparse-Dataset Calibration
Authors: Ueno Shinya , Sakai Osamu , Morimoto Takuya 
Published: October 2024

HighlightsThis article provides a machine-learning method for estimation of sugar content in target fruit using color appearance.Complex networks based on multidimensional datasets work effectively for color sensor calibration and data rebalancing.Beyond datapoint sparsity in datasets, estimation accuracy in sugar content is assured when an unsupervised-learning algorithm classifies the multidimensional datapoints composed of fruit color and relevant quantities.Abstract. In agriculture, harvests of fruits and vegetables depend on their ripeness, in which farmers should rely not only on the eye-sensed outlook but rigorously on constituents inside the targets, like sugar content. So far, detail measurements on the outlook color of fruits have been widely reported to detect suitable harvest times, where non-destructive instruments, which are costly in general agriculture fields, work well for color estimation whose resolution level is much higher than human eyes. In this study, we propose a scheme with a calibration procedure for sugar content prediction from outlook-color quantities, which is applicable even if a sensor includes systematic errors in output signals or the base dataset includes some datapoint sparsity. Most multidimensional data, which are both in agriculture and in other general cases, are imperfect in terms of several aspects, but they can be useful when we take appropriate sparsity detection and setting of rebalancing weights into account for machine learning procedures. We newly introduce a complex-network method for this purpose, and after the color calibration, we successfully obtain accurate hue and chroma, which are quantities representing a position on calibrated color coordinate, to predict °Brix sugar content in Japanese pears. Keywords: Asian pear, Color Elements, Fruit Ripening, °Brix Sugar Content, OHD.
Apple Leaf Disease Detection Based on Lightweight YOLOv8-GSSW
Authors: Zeng Wei , Pang Jicheng , Ni Kaicheng , Peng Peng , Hu Ruoyu 
Published: October 2024

HighlightsModify the YOLOV8 backbone network to reduce model calculation complexity and parameter amount.Integrating the Slim-Neck design and the SA attention mechanism into the neck network to enhance the attention of target features and improve the weight of the target.Adoption of the WIoU loss function over the original CIoU to address the sample imbalance problem and accelerate model convergence.Abstract. In response to the challenges posed by the excessive number of parameters and the high computational complexity inherent in existing algorithms for apple leaf disease recognition, this study introduces an enhanced, lightweight detection algorithm, YOLOv8-GSSW. Building upon the YOLOv8n as the foundational model, this research innovates in several key areas. Initially, the algorithm employs a lightweight GSConv convolutional module to replace the standard convolutional modules within the backbone network, significantly reducing both the model’s computational complexity and its parameter count. Furthermore, the incorporation of the Slim-Neck design concept into the neck network module serves to bolster the model’s capabilities in feature processing and learning. This enhancement is further augmented by the integration of the SA attention mechanism within Slim-Neck, which amplifies the attention to target features and increases their weight by merging information across both spatial and channel dimensions. Finally, the original CIoU loss function is substituted with the WIoU loss function to address the issue of sample imbalance and accelerate the model’s convergence. Experimental results underscore the YOLOv8-GSSW algorithm’s superior performance, achieving a mean average precision (mAP) of 87.3% with a parameter volume of 2.7×106 and a model weight of 5.4 MB. Relative to the YOLOv8n benchmark model, this represents a 15.6% reduction in parameter volume and an 11.5% decrease in model size. The modifications introduced in this algorithm not only facilitate more convenient application in practical scenarios for apple leaf disease detection but also render the algorithm well-suited for deployment on edge devices. Keywords: Apple leaves, Disease detection, Lightweight, YOLOv8n.
Reduction of Emission and Fuel Consumptions based on Mingled Nano Additives in Biodiesel
Authors: N. Krishnamoorthy  , R. Sathishkumar  , S. Dhivakar  , N. Ramanan  
Published: October 2024

Using the lipids identified as well as extra residual cooking oil, vegetable, and animal fats, bio-diesel a substitute for fuels derived from petroleum can be produced. Since the 1970s oil crisis, there has been a resurgence of interest in using biodiesel as a fossil fuel substitute due to the fuel's rapidly rising prices, availability uncertainties, and growing environmental and greenhouse gas (GHG) concerns.To produce biodiesel, glycerin and fat or vegetable oil are separated chemically through a process termed transesterification. Glycerin, a valuable byproduct that is typically sold to be used in soaps and other products, and methyl esters, the chemical term for biodiesel, are the two products left over from the process. The industrial term for diesel derived from petroleum, petro diesel, and biodiesel have similar viscosities. Due to the nearly zero sulfur content,it is recommended to be used as an additive in diesel oil formulations to improve the lubricity of pure ultra-low sulfur diesel (ULSD).The current work focuses heavily on reducing emissions and fuel consumption in automobiles. In addition to lowering pollutants and fuel consumption, the transition metal oxide (Copper oxide) additions in nanocrystalline particle form aid in molecular combustion. To create a stable Nano fluid, soap nut biodiesel is combined with metal oxide additive and ultrasonicated. For our experimental investigation, single cylinder, air cooled, constant speed Kirloskar engine is used. The reduction of hydrocarbon (HC), carbon monoxide (CO) and nitrogen oxide (NOx) emissions is investigated. The highest break power of the biodiesel employed in the study is 3.82 KW, greater than the typical diesel's 3.23 KW. The result shows improved engine efficiency, reduced emissions, and better brake thermal efficiency.
Substance use patterns and negative urine opioid screen among patients on methadone treatment at a referral hospital in Nairobi, Kenya
Authors: Kuria Susan Wangeci , Kiburi Sarah Kanana , Ochieng Jackline , Mburu John Maina , Owiti Fredrick 
Published: October 2024

Background
Substance use is a global health concern, with opioids contributing significantly to the disease burden. In Kenya, Medically Assisted Therapy (MAT) programs using methadone have been implemented to address opioid use disorder. Despite the effectiveness of methadone, the concurrent use of other substances remains a critical challenge. This study aimed to assess substance use patterns at enrolment and evaluate the prevalence of negative urine opioid screens among patients attending a MAT clinic at a tertiary hospital in Kenya.

Methods
This retrospective cohort study analyzed data from the medical records of 713 patients enrolled in the MAT clinic between December 2014 and February 2018. Data on sociodemographic characteristics, concurrent substance use at enrolment, and urine opioid screen results at 6, 12, 18, and 24 months were collected. Multivariate analyses were performed to identify factors associated with concurrent substance use, and the likelihood of achieving negative urine opioid screens.

Results
At enrolment into the MAT program, nearly all participants (712 out of 713) reported concurrent use of additional substances, with tobacco (91%) and cannabis (82.9%) being the most common. Concurrent substance use was significantly influenced by participants age, gender, education level, and route of administration of the substance. The program achieved an 81.3% retention rate at 24 months. However, the prevalence of negative urine opioid screens was lower compared to other populations, with a gradual increase from 61.3% at 6 months to 81.4% at 24 months. Notably, male patients (HR = 1.411, 95% C.I. 1.063–1.873, p = 0.01700) and those receiving higher methadone doses (HR 7.052, 95% CI 3.408–14.593, p<0.0001) were more likely to achieve negative urine opioid screens.

Conclusions
This study reveals a high prevalence of concurrent substance use among patients enrolling in the MAT program in Kenya, which may affect their likelihood of achieving negative urine opioid screens. These findings underscore the need for methadone treatment programs to adopt comprehensive approaches that address all substance use disorders to improve treatment outcomes.
Acute cardiovascular responses of postmenopausal women to resistance training sessions differing in set configuration: A study protocol for a crossover trial
Authors: Nine Iván , Padrón-Cabo Alexis , Carballeira Eduardo , Rial-Vázquez Jessica , Rúa-Alonso María , Fariñas Juan , Giráldez-García Manuel , Iglesias-Soler Eliseo 
Published: October 2024

Background
Resistance training is hardly recommended for postmenopausal women to counteract negative effects of hormonal changes. However, some concern exists about the marked hemodynamic responses caused by high-load resistance exercises. In this regard, studies on young, healthy, physically active individuals suggest that set configuration can modulate acute cardiovascular, metabolic, and cardiac autonomic responses caused by resistance training sessions, but this has not yet been explored in postmenopausal women.

Methods
A sample of 60 physically active postmenopausal women (30 normotensive, 30 hypertensive) will participate in this crossover study. After a medical exam, ergometry, familiarization session, and two testing sessions, participants will complete three experimental sessions and one control session in a randomized order. Each experimental session includes 36 repetitions of four exercises (horizontal leg press, bench press, prone leg curl, and lat pull-down) differing in set configuration: 9 sets of 4 repetitions (i.e., 33% intensity of effort) with 45 s of inter-set recovery, 6 sets of 6 repetitions (50% intensity of effort) with 72 s, and 4 sets of 9 repetitions (75% intensity of effort) with 120 s; with 4 min rest between exercises. Before and immediately after each session, arterial stiffness, hemodynamic variables, cardiac autonomic modulation, baroreflex sensitivity, sympathetic vasomotor tone, and resting oxygen uptake will be evaluated. Furthermore, perceived effort, mechanical performance (e.g., power, velocity), heart rate, and lactatemia will be collected throughout sessions. The impact of set configuration on these variables will be analyzed, along with comparisons between normotensive and hypertensive women.

Discussion
Cardiovascular responses to resistance exercise have been scarcely studied in females, particularly postmenopausal women. The results of this study will provide information about the modulating role of set structure on metabolic and cardiovascular responses of normotensive and hypertensive postmenopausal women to resistance training.

Clinical trial registration
NCT05544357 on 7 December 2022.
Focus on form, forms, or meaning in grammar instruction: a study of Pakistani university EFL teachers’ cognition and practices
Authors: Ahmed Hafiz Nauman , Mahmood Saqib 
Published: October 2024

Abstract
Teacher cognition shapes teachers’ pedagogical decision-making and influences their teaching practices, including grammar instruction, even when their cognition and practices might be inconsistent. This study explores English language teachers’ cognition regarding grammar instruction and analyses (in)consistencies in teacher cognition and classroom practices. The study employed a structured questionnaire administered to over 210 teachers teaching English language to undergraduate classes at various universities in Pakistan. The results of the questionnaire were analysed using descriptive and inferential statistical analyses. The findings reveal that, despite using focus on forms (FonFs) instruction, teachers support focus on meaning (FonM) instruction, but consider focus on form (FonF) as the most suitable choice for language teaching. Moreover, the content and materials used by teachers reveal their actual classroom practices which tend to favour FonFs instruction, conflicting with their beliefs. This misalignment also indicates teachers’ insufficient knowledge of L2 learning theories and the intricate nature of their grammar cognition. The study implies the need for research on mediating factors in teacher cognition-practice and training programs promoting L2 theory and practical strategies.
Group work and translanguaging as coping strategies for content learning in English-medium higher education contexts
Authors: Alhassan Awad 
Published: October 2024

Abstract
English as a medium of instruction (EMI) has been increasingly used in Higher Education institutions in countries where English is spoken as a second or foreign language (ESL/EFL). Research over the last decade has predominantly focused on EMI implementation, perceptions, and attitudes of stakeholders towards EMI as well as the challenges experienced by both teachers and students. However, little research, thus far, has focused on the coping strategies used by students to overcome challenges and manage their EMI study. The present study duly aims to fill this gap and contribute to the advancement of EMI research and pedagogy in this under-researched area. The study particularly attempts to explore group work and translanguaging as coping strategies that students employ to overcome content learning challenges and succeed in their EMI study. The study adopted a qualitative methodology and semi-structured interviews were used as the main method of data collection. Twenty participants voluntarily took part in the study. The data were analysed thematically and inductively. Results showed that students utilised several coping strategies to overcome EMI learning challenges and described these strategies as being helpful for them to understand EMI subject content. The pedagogical implications are discussed.
Shared leadership strategies for languages education. A case of project-based learning at CLC in Poznan University of Technology
Authors: Strukowska Marta E. 
Published: October 2024

Abstract
This article explains how shared leadership can be recognised and established in project-based learning as a situated English practice. It specifically explores the task characteristics of Cox et al.’s (2003) leadership model, which illustrates the functional relations between the procedural features of project work and its outcomes. The result of the analysis is that project work underlies the collective and highly integrative potential of the group of students, transforming them into a community of practice. The findings indicate that factors contributing to facilitating shared leadership are the interdependence of tasks between individuals driven by intrinsic motivation to act and the low complexity of tasks. The analysis also suggests that, although low complexity tasks may weaken shared leadership, they maximise relevance, thereby minimising cognitive effort. Consequently, this response strategy can help boost collaboration.
Translanguaging in content assessment: voices, experiences and practices of EMI university students
Authors: Gülle Talip , Bayyurt Yasemin 
Published: October 2024

Abstract
While translanguaging has gained significant traction as a theory of language that holds implications for educational settings with students from various language backgrounds, its viability in content assessment remains an unresolved issue. Students in English-medium instruction (EMI) programs at a private university in Türkiye participated in content exams that did not impose any language constraints, and follow-up interviews were conducted to probe into the participants’ language-related EMI experiences and the factors that affected their language use in their responses. Student reports showed that L1 was used by instructors to explain complex concepts or when students’ comprehension was challenged. Students used both English and L1 materials for studying, and in group and individual work, a mix of English and L1 was common, driven by the aim of cognitive efficiency and overcoming language barriers. In the content exams, both monolingual and translingual practices were employed by the participants, and their language use was mainly associated with relative proficiency in L2, encoding-retrieval match, and compartmentalization of languages. The study demonstrates that students encounter challenges in L2 comprehension and production in lessons and exams and that offering language flexibility in content exams may serve as a temporary accommodation that allows fuller expression of content knowledge, particularly in time-constrained exams.