bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insomnia, Short Sleep, and Their Treatments: Review of Their Associations with Weight
Authors: Allison Kelly C. , Parnarouskis Lindsey , Moore Molly D. , Minnick Alyssa M. 
Published: May 2024

Abstract
Purpose of Review
Insomnia and short sleep have been linked with weight gain and obesity. However, these findings have not been consistent across studies. We review recent evidence for the association between insomnia, short sleep, and weight gain, as well as the relationship between behavioral and pharmacological treatments for sleep and weight.

Recent Findings
The relationship between insomnia and obesity is mixed, with stronger associations between insomnia with short sleep and obesity than other presentations of insomnia. Short sleep is associated with weight gain. Z-drugs and benzodiazapines do not appear to impact weight, but many antidepressants and antipsychotics that are used for insomnia treatment do cause weight gain.

Summary
The relationships between insomnia and short sleep with weight gain and obesity are inconsistent. More prospective trials are needed to identify mediators and moderators of this relationship to better develop and deliver effective interventions for both sleep and weight problems.
Systemic immune markers and infection risk in preterm infants fed human milk fortified with bovine colostrum or conventional fortifier, a secondary analysis of the FortiColos trial
Authors: Bæk Ole , Muk Tik , Aunsholt Lise , Zachariasen Gitte , Sangild Per Torp , Nguyen Duc Ninh 
Published: May 2024

Abstract
Background
For very preterm infants, human milk is often fortified with formula products based on processed bovine milk. Intact bovine colostrum (BC), rich in anti-inflammatory milk factors, is considered an alternative. We investigated if BC affects anti-inflammatory/TH2 immunity and infection risk in very preterm infants.

Methods
For a secondary analysis of a multicenter, randomized controlled trial (NCT03537365), very preterm infants (26–31 weeks gestation, 23% small for gestational age, SGA) were randomized to receive BC (ColoDan, Biofiber, Denmark, n = 113) or conventional fortifier (PreNAN, Nestlé, Switzerland, n = 116). Infection was defined as antibiotic treatment for five or more consecutive days and 29 cytokines/chemokines were measured in plasma before and after start of fortification.

Results
In general, infection risk after start of fortification was associated with low gestational age, SGA status and antibiotics use prior to fortification. Adjusted for confounders, infants fortified with BC showed more infection episodes (20 vs 12%, P < 0.05) and higher cumulative infection risk (hazard ratio, HR 1.9, P = 0.06), particularly for SGA infants (HR 3.6, P < 0.05). Additionally, BC-fortified infants had higher levels of TH2-related cytokines/chemokines (IL-10, MDC, MCP4) and reduced levels of cytokines related to TH1/TH17-responses (IL-15, IL-17, GM-CSF). The differences were most pronounced in SGA infants, displaying higher levels of TH2-related IL-4, IL-6, and IL-13, and lower interferon-γ and IL-1α levels in the BC group.

Conclusion
Infants fortified with BC displayed a delayed shift from TH2- to TH1-biased systemic immunity, notably in SGA infants, possibly influenced by multiple confounding factors, alongside elevated antibiotic use, suggesting increased susceptibility to infection.
Depressive symptoms—Not a predictor for five-year mortality in patients with subjective cognitive decline, non-amnestic and amnestic mild cognitive impairment
Authors: Gerschmann Alexander , Lehrner Johann 
Published: May 2024

SummaryThe main aim of the present study is to evaluate the influence of depressive symptoms on mortality in patients with SCD (subjective cognitive decline), naMCI (non-amnestic mild cognitive impairment), and aMCI (amnestic mild cognitive impairment). Additional factors (age, sex, years of school attendance, and neuropsychological performance) were considered to determine the impact on survival probability. A monocentric retrospective data analysis based on adjusted patient protocols (n = 1221) from the observation period 1998–2021, using the Cox Proportional Hazards model, assessed whether depressivity had an explanatory value for survival, considering SCD as the reference level in relation to naMCI and aMCI. Covariates were included blockwise. Cox regression revealed that depressiveness (Beck Depression Inventory, Geriatric Depression Scale) did not make a significant contribution as a risk factor for mortality in all five model blocks, BDI-II with HR 0.997 [0.978; 1.02] and GDS-15 with HR 1.03 [0.98; 1.08]. Increasing age with HR 1.09 [1.07; 1.11] and male sex with HR (inverted) 1.53 [1.17; 2.00] appeared as risk factors for increased mortality across all five model blocks. aMCI (vs. SCD) with HR 1.91 [1.33; 2.76] showed a significant explanatory value only up to the fourth model block. By adding the six dimensions of the Neuropsychological Test Battery Vienna in the fifth model block, the domains attention and perceptual speed with HR 1.34 [1.18; 1.53], and executive functions with HR 1.24 [1.11; 1.39], showed substantial explanatory values for survival. Accordingly, no tendency can be attributed to depressiveness as a risk factor on the probability of survival, whereas the influence of certain cognitive dimensions, especially attention and perceptual speed, and executive functions, can be seen as protective for survival.
First report of Stemphylium vesicarium causing leaf blight of onion in Slovakia
Authors: Kádasi Horáková Miriam , Barta Marek , Tancik Jan , Pastirčák Martin , Pastirčáková Katarína 
Published: May 2024

AbstractDuring the 2022 growing season, commercial crops of onion (Allium cepa cv. Medusa) were found to be affected by an extensive leaf blight in south western Slovakia. The pathogen present on diseased leaves was isolated and identified as Stemphylium vesicarium through morphological and molecular analyses, utilizing three DNA markers (ITS, tef1-α, and β-tubulin). A detailed description and illustration of the fungus are provided. Although this pathogen is already present in Slovakia, this is the first record of S. vesicarium causing leaf blight on A. cepa in the country. Pathogenicity tests with a fungal isolate were performed on three local cultivars of onion plants in the laboratory, indicating varying susceptibility of the cultivars to S. vesicarium.
The Undescribed Juvenile Maxilla from Contrebandiers Cave, Morocco—A Study on Middle Stone Age Facial Growth
Authors: Freidline Sarah E. , Gunz Philipp , Alichane Hajar , Oujaa Aïcha , Ben-Ncer Abdelouahed , El Hajraoui Mohamed Abdeljalil , Hublin Jean-Jacques 
Published: May 2024

Abstract
In 2009, renewed excavations at the Middle Stone Age (MSA) site of Contrebandiers Cave, Morocco, yielded a skull and partial skeleton of a child dated to Marine Isotope Stage 5. While much of the cranium was found shattered, the midface remained largely intact. In this study, we virtually reconstructed the maxilla and quantified its shape using three-dimensional geometric morphometric methods and compared it to an extensive sample of non-adult and adult Eurasian Neanderthals and Homo sapiens spanning the Middle Pleistocene to Holocene. We used developmental simulations to predict the adult shape of the Contrebandiers maxilla by simulating development along three ontogenetic trajectories: Neanderthal, African, and Levantine early H. sapiens and Holocene H. sapiens. Our results confirm the H. sapiens-like morphology of the Contrebandiers fossil. Both shape and size align it with other North African MSA fossils and Late Pleistocene humans from Qafzeh, Israel. Interestingly, the evaluation of the ontogenetic trajectories suggests that during late ontogeny the facial growth pattern of the Contrebandiers and the Qafzeh children is more similar to that of Neanderthals than it is to recent humans. This suggests that the unique facial growth pattern of Homo sapiens post-dated the MSA. This study is an important step in addressing ontogenetic variability in the African MSA, a period characterized by the origins, emergence, and dispersal of our species, but poorly understood because of the fragmentary and scant human fossil record.
The co-occurrence of SAT, hypophysitis, and Schnitzler syndrome after COVID-19 vaccination: the first described case
Authors: Szklarz Michał , Gontarz-Nowak Katarzyna , Kieroński Aleksander , Golon Krystian , Górny Jan , Matuszewski Wojciech , Bandurska-Stankiewicz Elżbieta 
Published: May 2024

AbstractSubacute thyroiditis (also known as granulomatous thyroiditis, giant cell thyroiditis, de Quervain's disease, or SAT) is an inflammatory disease of the thyroid gland, usually spontaneously remitting, that lasts for weeks to months. However, recurrent forms sometimes occur which may have a genetic basis. In our paper, we have focused on the pathogenetics, symptoms, and treatment of SAT. We have described the 17-month disease course of a woman with persistent recurrent steroid-resistant SAT. SAT was well established and the patient's symptoms were not only recurrent neck pain with fever, but also recurrent chronic urticaria, which are symptoms that fulfil the criteria for the diagnosis of Schnitzler syndrome. Schnitzler syndrome occurred after vaccination with COVID-19 in the mechanism of ASIA syndrome. In our patient, Schnitzler syndrome involved the thyroid gland, causing persistent subacute thyroiditis, and the pituitary gland, causing transient swelling of the pituitary, which, to our knowledge, is the first reported case in the literature. Also unprecedented, as far as we know, is the fact that we performed thyroidectomy in the above patient, which reduced systemic inflammation and caused SAT to resolve, although only the inclusion of anakinra treatment resulted in resolution of the underlying condition.
Advancing language models through domain knowledge integration: a comprehensive approach to training, evaluation, and optimization of social scientific neural word embeddings
Authors: Stöhr Fabian 
Published: May 2024

AbstractThis article proposes a comprehensive strategy for training, evaluating, and optimizing domain-specific word2vec-based word embeddings, using social science literature as an example. Our primary objectives are: (1) to train the embeddings utilizing a corpus of social science text, (2) to test their performance against domain-unspecific embeddings using our developed intrinsic and extrinsic evaluation strategy, and (3) to enhance their performance even further by using domain knowledge. As an integral part of this approach, we present SociRel-461, a domain-knowledge dictionary designed for the intrinsic evaluation and subsequent refinement of social science word embeddings. Using a dataset of 100,000 full-text scientific articles in sociology, we train multiple vector space models, which we then benchmark against a larger, pre-trained general language embedding model as part of our extrinsic evaluation. Furthermore, we developed a transfer learning multi-label classification task for extrinsic evaluation. Our findings reveal that domain-specific embeddings outperform their domain-unspecific counterparts in both intrinsic and extrinsic evaluations. We also investigated the retrofitting post-processing method to enhance domain-unspecific embeddings with the domain knowledge embedded in SociRel-461. While retrofitting does not enhance our domain-specific vector space models, it significantly improves the performance of the domain-unspecific embeddings. This highlights the potential of retrofitting for the transfer of domain knowledge to domain-unspecific embeddings. Our results emphasize the importance of utilizing domain-specific word embeddings for better performance in domain specific transfer learning tasks, as they outperform conventional embeddings trained on everyday language.
Review of the analytical network-averaging: part I — theoretical foundation
Authors: Itskov Mikhail , Khiêm Vu Ngoc 
Published: May 2024

AbstractThe analytical network-averaging, an elegant homogenization scheme, has been proposed in Khiêm and Itskov (J. Mech. Phys. Solids 95:254–269, 2016) to capture a wide range of mechanical phenomena in soft materials. These phenomena include nonlinear elasticity observed in unfilled rubbers, anisotropic damage behaviors in mechanoresponsive elastomers, phase transition occurring in natural rubbers, cross-effect of damage in double-network hydrogels, and irreversible fiber sliding in textile reinforcements. While the effectiveness of the analytical network-averaging has been evidenced through various illustrative examples, a thorough exposition of the theory remains elusive, primarily due to the concise nature preferred in conventional scientific articles and the specific thematic emphasis of individual publications. In the first part of this review series, an exhaustive theoretical examination of the analytical network-averaging concept is provided. Such theory postulates the presence of an orientational distribution function of material directions, such as fibers or polymer chains. Utilizing this distribution function, microscopic strain measures essential for solving homogenized boundary value problems can be obtained by averaging of macroscopic strain measures. It is interesting that in all scenarios, analytical derivation of the microscopic strain measures can always be obtained. Thus, such analytical homogenization scheme offers physically based invariants that automatically guarantee realistic behaviors (such as non-affine deformation, material objectivity and material symmetry) in stress response functions. This is particularly important in the age of data science and machine learning as it allows for the choice of stress hypothesis without limitations, while ensuring a priori interpretability of results.
Distinct biophysical and chemical mechanisms governing sucrose mineralization and soil organic carbon priming in biochar amended soils: evidence from 10 years of field studies
Authors: Zhang Haoli , Ma Tao , Wang Lili , Yu Xiuling , Zhao Xiaorong , Gao Weida , Van Zwieten Lukas , Singh Bhupinder Pal , Li Guitong , Lin Qimei , Chadwick David R. , Lu Shenggao , Xu Jianming , Luo Yu , Jones David L. , Jeewani Peduruhewa H. 
Published: May 2024

AbstractWhile many studies have examined the role of biochar in carbon (C) accrual in short-term scale, few have explored the decadal scale influences of biochar on non-biochar C, e.g., native soil organic C (SOC) and added substrate. To address this knowledge gap, soils were collected from decade-old biochar field trials located in the United Kingdom (Cambisol) and China (Fluvisol), with each site having had three application rates (25–30, 50–60 and 75–100 Mg ha−1) of biochar plus an unamended Control, applied once in 2009. We assessed physicochemical and microbial properties associated with sucrose (representing the rhizodeposits) mineralization and the priming effect (PE) on native SOC. Here, we showed both soils amended with biochar at the middle application rate (50 Mg ha−1 biochar in Cambisol and 60 Mg ha−1 biochar in Fluvisol) resulted in greater substrate mineralization. The enhanced accessibility and availability of sucrose to microorganisms, particularly fast-growing bacterial genera like Arenimonas, Spingomonas, and Paenibacillus (r-strategists belonging to the Proteobacteria and Firmicutes phyla, respectively), can be attributed to the improved physicochemical properties of the soil, including pH, porosity, and pore connectivity, as revealed by synchrotron-based micro-CT. Random forest analysis also confirmed the contribution of the microbial diversity and physical properties such as porosity on sucrose mineralization. Biochar at the middle application rate, however, resulted in the lowest PE (0.3 and 0.4 mg of CO2-C g soil−1 in Cambisol and Fluvisol, respectively) after 53 days of incubation. This result might be associated with the fact that the biochar promoted large aggregates formation, which enclosed native SOC in soil macro-aggregates (2–0.25 mm). Our study revealed a diverging pattern between substrate mineralization and SOC priming linked to the biochar application rate. This suggests distinct mechanisms, biophysical and physicochemical, driving the mineralization of non-biochar carbon in a field where biochar was applied a decade before.
Distant supervision knowledge extraction and knowledge graph construction method for supply chain management domain
Authors: Huang Feiyue , Cheng Lianglun 
Published: May 2024

AbstractAs the core competitiveness of the national industry, large-scale equipment such as ships, high-speed rail and nuclear power equipment, their production process involves in-depth personalization. It includes complex processes and long manufacturing cycles. In addition, the equipment’s supply chain management is extremely complex. Therefore, the development of a supply chain management knowledge graph is of significant strategic significance. It not only enhances the synergistic effect of the supply chain management but also upgrades the level of intelligent management. This paper proposes a distant supervision knowledge extraction and knowledge graph construction method in the supply chain management of large equipment manufacturing, which achieves digital and structured management and efficient use of supply chain management knowledge in the industry. This paper presents an approach to extract entity-relation knowledge using limited samples. We achieve this by establishing a distant supervision model. Furthermore, we introduce a fusion gate mechanism and integrate ontology information, thereby enhancing the model’s capability to effectively discern sentence-level semantics. Subsequently, we promptly modify the weights of input features using the gate mechanism to strengthen the model’s resilience and address the issue of vector noise diffusion. Finally, an inter-bag sentence attention mechanism is introduced to integrate different sentence bag information at the sentence bag level, which achieves more accurate entity-relation knowledge extraction. The experimental results prove that compared with the latest distant supervision method, the accuracy of relation extraction is improved by 2.8%, and the AUC value is increased by 3.9%, effectively improving the quality of knowledge graph in supply chain management.
Efficient decomposition shooting method for tackling two-point boundary value models
Authors: Bakodah H. O. , Alzahrani Kholoud A. , Alzaid N. A. , Almazmumy Mariam H. 
Published: May 2024

AbstractThis research aims to present an efficient numerical method to find approximate numerical solutions for ordinary differential equations (ODEs), specifically, the class of two-point boundary value models. This approach is predicated on coupling the shooting method and the decomposition method, which the method is named as Efficient Decomposition Shooting Method (EDSM). Thus, we provide the complete outline of EDSM, and thereafter, apply it to some test models, comprising linear and nonlinear models. Further, the results are then validated by comparing them to the exact solution and other computational methods. Thus, the proposed method performs excellently over its peers, and is found to converge rapidly to the available exact solution with a good precision.
The Dynamic Bifurcation for the Granulation Convection in Cylindrical Coordinates
Authors: Li Junyan , Li Limei , Wu Ruili 
Published: May 2024

Abstract
This work formulates the simplified governing equations for granulation convection system in cylindrical coordinates by using the differential operator theory on Riemann manifold. We consider the case where the granulation convection system is under the influence of the control parameters R and E, Where R depends on the temperature difference and E is related to the magnetic field. Furthermore, we show that the simplified governing equations bifurcate from a trivial steady state solution, as the control parameters cross certain critical values. Notably, we are able to derive a RE-phase diagram in the case of two control parameters R and E, compared with the system without the influence of the control parameter E. In addition, our research shows that the difference of temperature and the magnetic field both accelerates the granulation convection.
Graph attention networks unveil determinants of intra- and inter-city health disparity
Authors: Liu Chenyue , Fan Chao , Mostafavi Ali 
Published: May 2024

AbstractUnderstanding the determinants underlying variations in urban health status is important for informing urban design and planning, as well as public health policies. Multiple heterogeneous urban features could modulate the prevalence of diseases across different neighborhoods in cities and across different cities. This study examines heterogeneous features related to socio-demographics, population activity, mobility, and the built environment and their non-linear interactions to examine intra- and inter-city disparity in prevalence of four disease types: obesity, diabetes, cancer, and heart disease. Features related to population activity, mobility, and facility density are obtained from large-scale anonymized mobility data. These features are used in training and testing graph attention network (GAT) models to capture non-linear feature interactions as well as spatial interdependence among neighborhoods. We tested the models in five U.S. cities across the four disease types. The results show that the GAT model can predict the health status of people in neighborhoods based on the top five determinant features. The findings unveil that population activity and built-environment features along with socio-demographic features differentiate the health status of neighborhoods to such a great extent that a GAT model could predict the health status using these features with high performance. The results also show that the model trained on one city can predict health status in another city with high performance, allowing us to quantify the inter-city similarity and discrepancy in health status. The model and findings provide novel approaches and insights for urban designers, planners, and public health officials to better understand and improve health disparities in cities by considering the significant determinant features and their interactions.
Performance analysis of power conditioning and distribution module for microsatellite applications
Authors: Bensaada M. , Della Krachai S. , Metehri F. , Kerrouche KDE. , Mebrek MA. , Beldjehem M. , Arezki F. 
Published: May 2024

AbstractAlgeria’s micro-satellite, Alsat-1b, was successfully launched into a 680 km low Earth orbit onboard a PSLV-C35 rocket from Sriharikota, South India, on September 26, 2016. The spacecraft was conceived, built and launched as part of an 18-month technology transfer programme between Algeria’s Algerian Space Agency (ASAL) and the United Kingdom’s Surrey Satellite Technology Limited (SSTL). This document details the Power Conditioning and Distribution Module’s (PCM-PDM) design and performance in orbit, critical component of a satellite electrical power system, responsible for converting, regulating and distributing power to various subsystems and payloads. The PCM-PDM developed and produced by SSTL was subjected to rigorous testing simulating harsh space conditions to assess its performance. The results of this comprehensive analysis indicate that the module can effectively withstand extreme environmental factors and function optimally in challenging settings. The analysis focused on the PCM-PDM’s ability to provide reliable and efficient power conditioning and distribution to the satellite, including its load management capabilities, overcurrent protection, protection against undervoltage and critical mode operations. The results of the performance analysis showed that the PCM-PDM met the required specifications and demonstrated reliable and efficient operation in different modes of the satellite’s mission. The study highlights the importance of careful design and rigorous testing of the PCM-PDM to ensure the reliable and efficient operation of the satellite and its payloads.