bluuebunny/crossref_metadata_2025_split huggingface dataset:
INVESTIGATION OF NEUTROPHILS UNDER TECHNOLOGICAL STRESS IN COWS BY METHODS OF LASER INTERFERENCE AND ELECTRON SCANNING MICROSCOPY
Authors: Deryugina Anna V. , Ivashchenko Marina N. , Metelin Vladislav B. , Kovylin Roman S. , Ignatiev Pavel S. 
Published: May 2024

Background. Intensive milk production technology creates a number of factors that can put an animal into a state of technological stress. The effect of stress is reflected in nonspecific resistance, which represents the body's ability to resist the effects of adverse factors by maintaining protective forces at the proper level. Neutrophils are one of the first protective cellular barriers that are rapidly mobilized when exposed to stress factors. To decipher the changes taking place in response to the action of stressors, the involvement of various evaluation tools is required. One of the possible methodological approaches is the use of various visualization methods that provide access to spatio-temporal information at the level of individual organelles and
Purpose. The study of the morpho-functional state of neutrophils under technological stress in cattle by laser interference and electron scanning microscopy.
Materials and methods. The work was carried out on 30 clinically healthy highly productive black-and-white cows. A combination of impacts was considered as technological stress: the rearrangement of animals and the change of service personnel. Neutrophils were analyzed by laser interference and electron scanning microscopy.
Results. A change in the morphological structure and functional activity of neutrophils after the action of technological stress is shown. The analysis of interferograms revealed an increase in the heterogeneity of neutrophils due to the appearance of degeneratively altered cell forms with an increase in the number of functionally active neutrophils. Electron scanning microscopy revealed the appearance of NEToses and neutrophils with emptied granules and vacuolization of the cytoplasm after technological stress.
Conclusion. The revealed morphofunctional changes in neutrophils prove the strain of adaptation mechanisms under technological stress. This circumstance must be taken into account in order to prevent disruption of the adaptive capabilities of the organism of highly productive animals.
ASSESSMENT OF THE LEVEL OF PAIN IN THE TREATMENT OF PLANTAR FASCIITIS BY EXTRACORPOREAL SHOCK WAVE THERAPY
Authors: Huseynova Ulkar Aslan , Kozlov Vasily V. 
Published: May 2024

Background. Patellofemoral pain syndrome (PFPS) is a clinical condition characterized by retropatellar and/or peripatellar pain associated with activities associated with stress on the lower extremities (for example, walking, running, jumping, climbing stairs, prolonged sitting and mobility, walking on stairs , squats on squats). Both active and sedentary people of any age. People with obesity and people who spend most of their time on their feet are more prone to this disease.
Purpose: comparison of serum levels of 25-hydroxyvitamin D in patients diagnosed with patellofemoral pain syndrome with healthy individuals who sought screening prior to initiation of sports.
Methods. Patients were examined retrospectively. The study involved 20 patients with patellofemoral pain syndrome and 40 healthy individuals who applied for examination before playing sports. Statistical analysis was used to evaluate the differences.
Results. The patients with patellofemoral pain syndrome had subnormal levels of 25-hydroxyvitamin D, averaging 18,5±7,1 ng/mL. The average level of vitamin D in healthy people was 28,9±10,6 ng/ml. The level of vitamin D in patients with patellofemoral pain syndrome was statistically significantly lower than in the healthy group (p<0,001).
Conclusion. Decreased serum levels of 25-hydroxyvitamin D in patients contribute to the pathophysiology of patellofemoral pain syndrome.
Changes in temperament, character and intensity of empathy in adolescents treated in a day care unit – pilot study
Authors: Modrzejewska Renata , Wasik Anna , Cofór-Pinkowska Paulina , Pac Agnieszka , Siwek Marcin 
Published: May 2024

Cel pracyCelem badania pilotażowego było porównanie poziomu empatii, cech temperamentu i charakteru przed i po 6 miesiącach leczenia w grupie pacjentów przebywających w oddziale dziennym psychiatrycznym w grupach zróżnicowanych pod względem rodzaju zaburzenia (internalizacyjne versus eksternalizacyjne).MetodaBadanie przeprowadzono w grupie 44 pacjentów (33 dziewcząt oraz 11 chłopców), w wieku 15–20 lat leczonych w latach 2016 - 2021 w Oddziale Dziennym Klinicznym Kliniki Psychiatrii Dorosłych, Dzieci i Młodzieży Szpitala Uniwersyteckiego w Krakowie. Zaburzenia eksternalizacyjne prezentowało 40% adolescentów a 60 % zaburzenia internalzacyjne. Do badań wykorzystano Skalę Empatii Davisa oraz Skalę Empatii Cohena oraz Inwentarz Cech Temperamentu i Charakteru TCI Cloningera.WynikiPółroczne leczenie w oddziale dziennym skutkowało istotnymi statystycznie zmianami w skali Fantazji ze Skali Empatii Davisa, podskal zależności od nagrody, samokierowania i autotranscendencji w Inwentarzu Cech Temperamentu i Charakteru w grupie nastolatków z zaburzeniami internalziacyjnymi. W grupie nastolatków z zaburzeniami eksternalizacyjnymi odnotowano zmiany na poziomie tendencji statystycznej w wartościach Skali Fantazji oraz skali unikania cierpienia w Inwentarzu Cech Temperamentu i Charakteru.WnioskiOtrzymane wyniki są zgodne z dostępnymi danymi mówiącymi o różnicach w profilach temperamentu i charakteru między rodzajami zaburzeń psychicznych oraz niekorzystnych dla zdrowia psychicznego konstelacjach cech, takich jak niska samosterowność, unikanie cierpienia, czy zależność od nagrody
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development
Authors: Yang Jin , Jiang Guangxin , Wang Yinan , Chen Ying 
Published: May 2024

Recent years have witnessed exponential growth in developing deep learning models for time series electricity forecasting in power systems. However, most of the proposed models are designed based on the designers’ inherent knowledge and experience without elaborating on the suitability of the proposed neural architectures. Moreover, these models cannot be self-adjusted to dynamically changed data patterns due to the inflexible design of their structures. Although several recent studies have considered the application of the neural architecture search (NAS) technique for obtaining a network with an optimized structure in the electricity forecasting sector, their training process is computationally expensive and their search strategies are not flexible, indicating that the NAS application in this area is still at an infancy stage. In this study, we propose an intelligent automated architecture search (IAAS) framework for the development of time series electricity forecasting models. The proposed framework contains three primary components, that is, network function–preserving transformation operation, reinforcement learning–based network transformation control, and heuristic network screening, which aim to improve the search quality of a network structure. After conducting comprehensive experiments on two publicly available electricity load data sets and two wind power data sets, we demonstrate that the proposed IAAS framework significantly outperforms the 10 existing models or methods in terms of forecasting accuracy and stability. Finally, we perform an ablation experiment to showcase the importance of critical components in the proposed IAAS framework in improving forecasting accuracy. History: Accepted by Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: J. Yang, G. Jiang, and Y. Chen were supported by the National Natural Science Foundation of China [Grants 72293562, 72121001, 72101066, 72131005, 71801148, and 72171060]. Y. Chen was supported by the Heilongjiang Natural Science Excellent Youth Fund [YQ2022G004]. Supplemental Material: The software ( Yang et al. 2023 ) that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0034 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0034 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms
Authors: Hu Yu Jeffrey , Rombouts Jeroen , Wilms Ines 
Published: May 2024

Practice- and policy-oriented abstract: The success of on-demand service platforms crucially hinges upon their ability to make fast and accurate demand forecasts so that its workers are always at the right time and location to serve customers promptly. Yet demand forecasting is challenging for several reasons. First, demand data are typically released as high-frequency streaming time series, which requires an algorithm that has a fast processing time. Second, a digital platform often operates in many different geographic regions, thereby giving rise to a large heterogeneous geographical collection of high-frequency demand streams that need to be forecast and requiring a scalable algorithm. Third, a platform business usually operates in an unstable, rapidly changing environment and faces irregular growth patterns, which requires agility when forecasting demand because slow reactions to such instabilities causes forecast performance to break down. We offer a novel forecast framework called fast forecasting of unstable data streams that is fast and scalable and automatically assesses changing environments without human intervention. We test our framework on a unique data set from a leading European on-demand delivery platform and a U.S. bicycle sharing system and find strong (i) forecast performance gains, (ii) financial gains, and (ii) computing time reduction from using our framework against several industry benchmarks.
Pooling and Boosting for Demand Prediction in Retail: A Transfer Learning Approach
Authors: Lei Dazhou , Qi Yongzhi , Liu Sheng , Geng Dongyang , Zhang Jianshen , Hu Hao , Shen Zuo-Jun Max 
Published: May 2024

Problem definition: How should retailers leverage aggregate (category) sales information for individual product demand prediction? Motivated by inventory risk pooling, we develop a new prediction framework that integrates category-product sales information to exploit the benefit of pooling. Methodology/results: We propose to combine data from different aggregation levels in a transfer learning framework. Our approach treats the top-level sales information as a regularization for fitting the bottom-level prediction model. We characterize the error performance of our model in linear cases and demonstrate the benefit of pooling. Moreover, our approach exploits a natural connection to regularized gradient boosting trees that enable a scalable implementation for large-scale applications. Based on an internal study with JD.com on more than 6,000 weekly observations between 2020 and 2021, we evaluate the out-of-sample forecasting performance of our approach against state-of-the-art benchmarks. The result shows that our approach delivers superior forecasting performance consistently with more than 9% improvement over the benchmark method of JD.com . We further validate its generalizability on a Walmart retail data set and through alternative pooling and prediction methods. Managerial implications: Using aggregate sales information directly may not help with product demand prediction. Our result highlights the value of transfer learning to demand prediction in retail with both theoretical and empirical support. Based on a conservative estimate of JD.com , the improved forecasts can reduce the operating cost by 0.01–0.29 renminbi (RMB) per sold unit on the retail platform, which implies significant cost savings for the low-margin e-retail business. History: This paper has been accepted as part of the 2023 Manufacturing & Service Operations Management Practice-Based Research Competition. Funding: This work was supported by the National Natural Science Foundation of China [Grant 71991462]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0453 .
Consistency of wound care in Leg Clubs
Authors: Hampton Sylvie 
Published: May 2024

Mr B had lost his wife of 65 years and was distraught, but he tried to move on with life. However, while playing football he injured his leg, which then developed into a venous ulcer that was to last for many years. Unfortunately, his care was inconsistent, and the wound was not progressing. He found the local Leg Club and decided to self-refer. He not only went on to achieve wound closure rapidly, but he found a social atmosphere in the club, made friends and learned how to prevent the wound from recurring. He felt that consistency of care was the reason for the rapid progress.
The effects of person-centred active rehabilitation on symptoms of suspected Chronic Traumatic Encephalopathy: A mixed-methods single case design
Authors: Hearn Rachael , Selfe James , Cordero Maria I. , Dobbin Nick 
Published: May 2024

Objective
The objective was to investigate the effectiveness of a person-centred active rehabilitation programme on symptoms associated with suspected Chronic Traumatic Encephalopathy (CTE). This was accomplished by (1) assessing the effect that a person-centred active rehabilitation programme had on participant symptoms, and (2) exploring how temporal contextual factors affected the participants’ experience with, and perceived effectiveness of, the active rehabilitation programme.

Methods
A twelve-month mixed-methods single case experimental research design was used with six cases (participants). Individual cases were involved in a 51-week study period including an initial interview and three-week baseline phase. Cases were then randomly allocated to one of two n-of-1 study designs (i.e., A-B, B-A, B-A, A-B or B-A, A-B, A-B, B-A) where A and B represent a non-intervention and intervention phase, respectively. Interviews were conducted regularly throughout the study whilst outcome measures were assessed at each follow-up. Analysis of the data included visual, statistical, and qualitative analysis.

Results
Visual and statistical analysis of cognitive and executive function, and mindful attention, demonstrated trivial-to-large effects with the summary reflecting positive or unclear results. A mixed picture was observed for mood and behaviour with effects considered trivial-to-large, and the summary demonstrating positive, unclear and negative effects. Qualitative analysis indicated a perceived improvement in outcome measures such as memory, attention, anxiety, and emotional control despite mixed quantitative findings whilst a clear impact of contextual factors, such as COVID-19, the political atmosphere, exercise tolerance, programme progression, and motivation were evident during the intervention.

Conclusions
This study has provided primary-level evidence to suggest active rehabilitation as a potential intervention for the management of suspected CTE symptoms. This study has also demonstrated the benefit of a person-centred approach to both clinical research and practice, particularly by considering contextual factors for a better understanding of an intervention effect.
Static palpation ain’t easy: Evaluating palpation precision using a topographical map of the lumbar spine as a reference
Authors: Hvidkær Inge Strøh , Harsted Steen , Hadizadeh Maliheh , O’Neill Søren , Kawchuk Gregory Neil , Nim Casper 
Published: May 2024

Introduction
Clinicians commonly use manual therapy to treat low back pain by palpating the spine to identify the spinous processes. This study aims to evaluate the ability of experienced clinicians to consistently locate the spinous processes from S1 to T12 through palpation. The results will be compared to topographical data representing the lumbar lordosis at baseline and four follow-up time points.

Materials and methods
In a prior prospective randomized trial, experienced clinicians used palpation to locate the lumbar spinous processes (S1—T12) and then digitized these locations in three-dimensional space. The same digitizing equipment was then used to continuously collect three-dimensional position data of a wheel that rolled along the back’s surface through a trajectory that connected the previously digitized locations of the spinous processes. This process was repeated at 4 days, 1, 4, and 12 weeks.
The resulting lordosis trajectories were plotted and aligned using the most anterior point in the lordosis to compare the locations of the spinous processes identified in different trials. This way, spinous palpation points could be compared to surface topography over time. Intra- and interrater reliability and agreement were estimated using intraclass correlations of agreement and Bland-Altman limits of agreement.

Results
Five clinicians palpated a total of 119 participants. The results showed a large degree of variation in precision estimates, with a mean total value of 13 mm (95%CI = 11;15). This precision error was consistent across all time points. The smallest precision error was found at L5, followed by S1 File, after which the error increased superiorly. Intra- and interrater reliability was poor to moderate.

Conclusions
Comparison of palpation results to a topographic standard representing the lumbar lordosis is a new approach for evaluating palpation. Our results confirm the results of prior studies that find palpation of lumbar spinous processes imprecise, even for experienced clinicians.
Association between human blood metabolome and the risk of gastrointestinal tumors
Authors: Lu Jiamin , Feng Yuqian , Guo Kaibo , Sun Leitao , Ruan Shanming , Zhang Kai 
Published: May 2024

Background
The prevalence of gastrointestinal tumors continues to be significant. To uncover promising therapeutic targets for these tumors, we rigorously executed a Mendelian randomization (MR) study to comprehensively screen the blood metabolomes for potential causal mediators of five frequently encountered gastrointestinal tumors (Liver Cancer, Colorectal Cancer, Esophageal Cancer, Gastric Cancer and Pancreatic Cancer).

Methods
We selected a comprehensive set of 137 distinct blood metabolites derived from three large-scale genome-wide association studies (GWASs) involving a total of 147827 participants of European ancestry. The gastrointestinal tumors-related data were obtained from a GWAS conducted within the Finnish study. Through meticulous MR analyses, we thoroughly assessed the associations between blood metabolites and gastrointestinal tumors. Additionally, a phenome-wide MR (Phe-MR) analysis was employed to investigate the potential on-target side effects of metabolite interventions.

Results
We have identified 1 blood metabolites, namely isovalerylcarnitine (ORlog10: 1.01; 95%CI, 1.01–1.02; P = 1.81×10−7), as the potential causal mediators for liver cancer. However, no potential pathogenic mediators were detected for the other four tumors.

Conclusions
The current systematic MR analysis elucidated the potential role of isovalerylcarnitine as a causal mediator in the development of liver cancer. Leveraging the power of Phe-MR study facilitated the identification of potential adverse effects associated with drug targets for liver cancer prevention. Considering the weighing of pros and cons, isovalerylcarnitine emerges as a promising candidate for targeted drug interventions in the realm of liver cancer prevention.
X-TED: Massive Parallelization of Tree Edit Distance
Authors: Fan Dayi , Lee Rubao , Zhang Xiaodong 
Published: May 2024

The tree edit distance (TED) has been found in a wide spectrum of applications in artificial intelligence, bioinformatics, and other areas, which serves as a metric to quantify the dissimilarity between two trees. As applications continue to scale in data size, with a growing demand for fast response time, TED has become even more increasingly data- and computing-intensive. Over the years, researchers have made dedicated efforts to improve sequential TED algorithms by reducing their high complexity. However, achieving efficient parallel TED computation in both algorithm and implementation is challenging due to its dynamic programming nature involving non-trivial issues of data dependency, runtime execution pattern changes, and optimal utilization of limited parallel resources.
Having comprehensively investigated the bottlenecks in the existing parallel TED algorithms, we develop a massive parallel computation framework for TED and its implementation on GPU, which is called X-TED. For a given TED computation, X-TED applies a fast preprocessing algorithm to identify dependency relationships among millions of dynamic programming tables. Subsequently, it adopts a dynamic parallel strategy to handle various processing stages, aiming to best utilize GPU cores and the limited device memory in an adaptive and automatic way. Our intensive experimental results demonstrate that X-TED surpasses all existing solutions, achieving up to 42x speedup over the state-of-the-art sequential AP-TED, and outperforming the existing multicore parallel MC-TED by an average speedup of 31x.
Regional prevalence and spatial modeling of hypertension in South Africa
Authors: Rudasingwa Guillaume , Cho Sung-il , Ishimwe Nancy Clemence 
Published: May 2024

Abstract

Background
In 2000, hypertension was the cause of nearly 47,000 deaths in South Africa. Since then, its prevalence has increased from 25% to over 40% of the population. Diabetes, sedentary lifestyle, diet, psychosocial stress, and certain medications are all risk factors for hypertension. The purpose of this research is to assess the regional prevalence and risk factors for hypertension, as well as to conduct spatial modeling of hypertension in South Africa.

Method
The study analyzed data from the 2016 South African Demographic and Health Survey, with a focus on participants aged 15 and older. Hypertension was defined as a diastolic blood pressure level of 90 mmHg or higher or a systolic blood pressure level of 140 mmHg or higher. Logistic regression analysis was employed to investigate significant factors associated with hypertension (p  ≤ 0.05). Additionally, ArcGIS was utilized to conduct spatial scans and hotspot analyses to identify regions with unusually high hypertension prevalence. Geostatistical modeling was performed using R.

Results
Hypertension was common in South Africa, accounting for 43.0%. The provinces of the Northern Cape, Eastern Cape, Free State, and Mpumalanga had a noticeably higher risk of hypertension with 55.7, 52.8, 52.4, and 50.7%, respectively. Older age, unmarried status, and diabetes or pre-diabetes were statistically associated with hypertension, with AOR [95% CI]: 2.32 [1.77–3.04], 1.63 [1.20–2.23], and 1.61 [1.12–2.31], respectively. Having an increased level of education and residing in the North West (0.45 [0.29–0.72]) and Limpopo (0.27 [0.17–0.43]) provinces showed to have a protective effect on hypertension. Significant hotspots of hypertension prevalence were detected among residents of coastal communities.