bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydrological and morphological responses in the São Francisco River Basin (Northeast Brazil) resulting from river damming and climate changes in a tropical region
Authors: Gomes Pedro Victor Oliveira , Figueiredo Felipe Torres , Fambrini Gelson Luís , Pupim Fabiano , Grohmann Carlos Henrique , Vedana Luiz Alberto , Franco Luisa Sampaio 
Published: October 2024

AbstractThe São Francisco River in Northeast Brazil has seen hydrological and morphological changes due to extensive damming and climate change over the past century. In this study, we examine the influence of human activities and natural fluctuations in precipitation on the hydrological patterns of the basin and the morphological responses of the lower course of the river (LOW‐SF) to these alterations over a span of several decades. The findings indicate a decrease in water release by 41% from 1995 to 2013 and 54% from 2013 to 2018, solely attributed to human actions. Furthermore, the operation of the reservoirs of the large dams resulted in a reduction in hydrological seasonality. The changing hydrological regime caused morphological changes that resulted in an expansion of the exposed subaerial fluvial bars in the LOW‐SF and a reduction in channel width. As a result, the abandonment of small secondary channels occurred, leading to the cessation of inundation in previously buried elevated portions of bars, even during certain seasons. Another important factor was the spread of morphological changes in the LOW‐SF, which started from the areas farthest from the last dam in the series of large dams, the Xingó Dam, and spread to the nearby regions. This is due to the lack of major tributaries in the semiarid region of the LOW‐SF. The integrated assessment presented in this study illustrates both natural and anthropogenic influences. Moreover, in light of projected declines in precipitation, it is anticipated that natural phenomena could result in a substantial 73% decrease in water flow by the mid‐20th century. This climatic scenario will lead to increased utilization of hydroelectric plants and more stringent control of water flow downstream of the dam cascade, intensifying the already documented adverse effects and posing the possibility of novel morphological adaptations.
Sustainable Maize Storage Technology Adoption in Ghana: Implications for Postharvest Losses, Farm Income, and Income Inequality
Authors: Adams Faizal , Donkor Emmanuel , Quaye Jonathan , Jantuah Anthony Adusei , Etuah Seth 
Published: October 2024

ABSTRACTThe Purdue Improved Crop Storage (PICS) bag, a sustainable post‐harvest storage technology, can address the high postharvest losses that are a major threat to economic development, food security and the environment in Africa. However, there is limited empirical research on this technology. This study therefore aims to fill this knowledge gap by analysing the factors influencing the diffusion and adoption rates of PICS bags and estimates the impact of the technology adoption on postharvest losses, farm income and income inequality in the Ashanti region of Ghana. The results show that less than 20% of farmers adopt the PICS bag, suggesting low adoption despite the widespread exposure of 51.75%. The technology adoption rate could be increased by 20% if all the farmers were exposed to it. It reduces postharvest losses by 14.2%–19.1%, increases farm income by 89.7%–91.2% and reduces income inequality by 51.33%. These findings suggest that promoting the technology can stimulate sustainable rural development by improving farmers' welfare.
How Do Household Coping Strategies Evolve With Increased Food Insecurity? An Examination of Nigeria's Food Price Shock of 2015–2018
Authors: Quinton Justin , Jenkins Glenn P. , Olasehinde‐Williams Godwin 
Published: October 2024

ABSTRACTFaced with a significant devaluation of its currency and a surge in food prices, the Nigerian government prohibited the use of foreign currency for food imports. This essentially blocked the importation of numerous food items under the guise of stimulating the domestic output of these staples. Consequently, food prices in Nigeria increased despite a global decline in food prices, and the incidence and severity of food insecurity escalated. This study examines the changes in the types and severity of coping mechanisms for food insecurity resulting from the food price shock caused by the oil price crash, currency devaluation, and restrictions on foreign exchange. Nigeria's General Household Survey Panel data from 2012 and 2015, during periods of high oil prices, is compared with data from 2018 when oil prices had remained low, the currency had been devalued, and the treasury had been depleted. Alongside detailed descriptive statistics, logistic and hurdle regressions are employed for statistical analysis. Findings indicate a rise in the percentage of Nigerian households grappling with food insecurity from 2015 to 2018. During this period, 68.7% of households resorted to at least one coping mechanism, 31.8% adopted six or more coping strategies, and 43.2% resorted to severe coping strategies. The issue stems not primarily from natural disasters or conflicts but from a failure in macroeconomic and agricultural economic policies. Our findings confirm that these policies come at great cost, particularly to female‐headed households, single‐parent households, households headed by elderly people, and other vulnerable populations, pushing them deeper into food insecurity.
Mapping Age Differences in Brain Energy Metabolites and Metabolic Markers of Cellular Membrane Production and Degradation With 31P Magnetic Resonance Spectroscopy
Authors: Raz Naftali , Daugherty Ana M. , Khatib Dalal , Dahle Cheryl L. , Rajan Usha , Zajac‐Benitez Caroline , Stanley Jeffrey A. 
Published: October 2024

ABSTRACTUsing Phosphorus Magnetic Resonance Spectroscopy (31P MRS), we examined five metabolites associated with brain energy cycle, and cellular membrane production and degradation in 11 brain regions of 48 children (age 6–15), and 80 middle‐aged and older adults (age 52–87). Levels of phosphomonoesters (PMEs) and phosphodiesters (PDEs), gamma plus alpha adenosine triphosphate (γαATP), phosphocreatine (PCr) and inorganic phosphate (Pi), were residualized on the total amplitude value. PMEs were greater in children compared to adults, whereas PDEs showed the opposite age difference. Higher γαATP and lower Pi were found in children compared to adults. The age group differences were particularly salient in the association cortices and anterior white matter. Among children, age correlated negatively with PMEs and positively with PDEs in association cortices. Compared to children, adults had lower intracellular pH. The results suggest reduction in membrane synthesis and increase in membrane degradation in adolescents and to a greater degree in adults compared to younger children. Concomitant reduction in γαATP and increase in Pi are consistent with reduced energy consumption in adolescents and further drop in middle‐aged and older adults, although it is impossible to distinguish declines in energy supply from reduced demand due to shrinking neuropil, without longitudinal studies.
Depression and related factors among patients with post‐COVID‐19 conditions: Cross‐sectional, hospital‐based study
Authors: Binh Nguyen Thanh , Thuan Tran Thien , Luc Nguyen Hoang Tan , Bang Ho Tat , Trinh Le Thi Diem 
Published: October 2024

AbstractBackground and AimsThe COVID‐19 crisis has significantly impacted public health, particularly mental health. This study aims to determine the prevalence of depression and related factors among patients with post‐COVID‐19 conditions in an outpatient clinic at a tertiary referral hospital in Southern Vietnam.MethodsA cross‐sectional survey was conducted among 410 patients with post‐COVID‐19 conditions in an outpatient clinic at the University Medical Center Ho Chi Minh City. A convenience sampling method was used to screen for depression using the Patient Health Questionnaire‐9 (PHQ‐9).ResultsA total of 410 patients participated in the study. Depression was observed in 23.7% of respondents, categorized as mild (80.4%), moderate (16.5%), or severe (3.1%) based on PHQ‐9 scores. Factors influencing depression included age 50 years or older, religion, education level, full‐time employment, marital status, family contact, use of anti‐inflammatory drugs, hospital admission due to COVID‐19, chronic diseases, hypertension, and post‐COVID‐19 symptoms (shortness of breath, palpitations, fatigue, headache, abdominal pain, brain fog, insomnia, and loss of appetite). The most common symptoms reported were cough, dyspnea, shortness of breath, fatigue, and loss of appetite. A p‐value of less than 0.05 indicated statistical significance.ConclusionThe prevalence of depression among patients with post‐COVID‐19 conditions in the outpatient clinic was high. Improving mental health and quality of life, alongside the prevention and treatment of COVID‐19, should remain public health priorities.
Macrophages in the inflammatory response to endotoxic shock
Authors: Zhao Xinjie , Wang Mengjie , Zhang Yanru , Zhang Yiyi , Tang Haojie , Yue Hongyi , Zhang Li , Song Dan 
Published: October 2024

AbstractBackgroundEndotoxic shock, particularly prevalent in intensive care units, represents a significant medical challenge. Endotoxin, upon invading the host, triggers intricate interactions with the innate immune system, particularly macrophages. This activation leads to the production of inflammatory mediators such as tumor necrosis factor‐alpha, interleukin‐6, and interleukin‐1‐beta, as well as aberrant activation of the nuclear factor‐kappa‐B and mitogen‐activated protein kinase signaling pathways.ObjectiveThis review delves into the intricate inflammatory cascades underpinning endotoxic shock, with a particular focus on the pivotal role of macrophages. It aims to elucidate the clinical implications of these processes and offer insights into potential therapeutic strategies.ResultsMacrophages, central to immune regulation, manifest in two distinct subsets: M1 (classically activated subtype) macrophages and M2 (alternatively activated subtype) macrophages. The former exhibit an inflammatory phenotype, while the latter adopt an anti‐inflammatory role. By modulating the inflammatory response in patients with endotoxic shock, these macrophages play a crucial role in restoring immune balance and facilitating recovery.ConclusionMacrophages undergo dynamic changes within the immune system, orchestrating essential processes for maintaining tissue homeostasis. A deeper comprehension of the mechanisms governing macrophage‐mediated inflammation lays the groundwork for an anti‐inflammatory, targeted approach to treating endotoxic shock. This understanding can significantly contribute to the development of more effective therapeutic interventions.
Crystallinity‐controlled volatility tuning of ZrO2 memristor for physical reservoir computing
Authors: Lee Dae Kyu , Noh Gichang , Oh Seungmin , Jo Yooyeon , Park Eunpyo , Kim Min Jee , Woo Dong Yeon , Wi Heerak , Jeong YeonJoo , Jang Hyun Jae , Kim Sangbum , Lee Suyoun , Kang Kibum , Kwak Joon Young 
Published: October 2024

AbstractMemristors have been emerging as promising candidates for computing systems in post‐Moore applications, particularly electrochemical metallization‐based memristors, which are poised to play a crucial role in neuromorphic computing and machine learning. These devices are favored for their high integration density, low power consumption, rapid switching speed, and significant on/off ratio. Despite advancements in various materials, achieving adequate electrical performance—characterized by threshold switching (TS) behavior, spontaneous reset, and low off‐state resistance—remains challenging due to the limitations in conductance filament control within the nanoscale resistive switching layer. In this study, we introduce an efficient method to control the ZrO2 crystallinity for tunable volatility memristor by establishing the filament paths through a simple thermal treatment process in a single oxide layer. The effect of ZrO2 crystallinity to create localized filament paths for enhancing Ag migration and improving TS behavior is also investigated. In contrast to its amorphous counterpart, crystallized ZrO2 volatile memristor, treated by rapid thermal annealing, demonstrates a steep switching slope (0.21 mV dec–1), a high resistance state (25 GΩ), and forming‐free characteristics. The superior volatile performance is attributed to localized conductive filaments along low‐energy pathways, such as dislocations and grain boundaries. By coupling with enhanced volatile switching behavior, we believe that the volatility is finely tuned to function as short‐term memory for reservoir computing, making it particularly well‐suited for tasks such as audio and image recognition.image
SKYQUANT 3D: Quantifying Vascular Anatomy With an Open‐Source Workflow for Comprehensive Analysis of Volumetric Optoacoustic Angiography Data
Authors: Korobov Artemii , Besedovskaia Zlata , Petrova Elizaveta , Kurnikov Alexey , Glyavina Anna , Orlova Anna , Nemirova Svetlana , Druzhkova Irina , Sirotkina Marina , Shirshin Evgeny , Gorin Dmitry , Xi Lei , Razansky Daniel , Subochev Pavel 
Published: October 2024

ABSTRACTEfficient visualization of the vascular system is of key importance in biomedical research into tumor angiogenesis, cerebrovascular alterations, and other angiopathies. Optoacoustic (OA) angiography offers a promising solution combining molecular optical contrast with high resolution and deep penetration of ultrasound. However, its hybrid nature implies complex data collection and processing workflows, with significant variability in methodologies across developers and users. To streamline interoperability, we introduce SKYQUANT 3D, a Python‐based set of instructions for the Thermo Fisher Scientific Amira/Avizo 3D Visualization & Analysis Software. Our workflow simplifies the batch processing of volumetric optoacoustic angiography images, extracting meaningful quantitative information while also providing statistical analysis and graphical representation of the results. Quantification performance of SKYQUANT 3D is demonstrated using functional preclinical and clinical in vivo 3D OA angiographic tests involving ambient temperature variations and repositioning of the imaged limb.
A Pair of Indicators for Characterizing Cerebral Microbleeds Based on Raman Spectrum and Two‐Photon Imaging
Authors: Su Xin , Wan Jianhui , Zheng Zixi , Xing Xinyue , Liu Shengde , Yang Shuxian , Zhong Liyun , Lu Xiaoxu 
Published: October 2024

ABSTRACTCerebral microbleeds (CMBs) lead to cognitive decline, linked to the axonal structure composed of phospholipid bilayers. Current methods are difficult to obtain in situ changes of biochemical component concentration during CMB. In this study, by Raman spectrum and two‐photon imaging, we achieve in situ changes in the information of biochemical components concentration during CMB. The overall concentration of phospholipids in the damaged tissue significantly decreases after CMB, forming a large region of low concentration, but the relative concentration of phosphatidylinositol (PI) increases, reflecting the inhibition role of the phosphatidylinositol 3 kinase/protein kinase B (PI3K/Akt) pathway. Accordingly, two‐photon images of neurons show a clear decrease in the number of axons, indicating a close correlation between phospholipid hydrolysis and axon damage, as well as cognitive impairment. Therefore, the decrease in phospholipid concentration and the increase in the PI concentration might serve as a pair of indicators for characterizing CMB and its relationship with cognitive decline.
Completely reducible super‐simple (v,4,4) $(v,4,4)$‐BIBDs and related constant weight codes
Authors: Chen Jingyuan , Yu Huangsheng , Abel R. Julian R. , Wu Dianhua 
Published: October 2024

AbstractA design is said to be super‐simple if the intersection of any two blocks has at most two elements. A design with index is said to be completely reducible, if its blocks can be partitioned into nonempty collections , such that each together with the point set forms a design with index unity. In this paper, it is proved that there exists a completely reducible super‐simple (CRSS) balanced incomplete block design (‐BIBD for short) if and only if and or . A ‐ary constant weight code (CWC) of length with weight and distance is denoted as a code. The maximum size of a code is denoted as , and the codes achieving this size are called optimal. CRSS designs with index are closely related to ‐ary CWCs. By using the results of CRSS ‐BIBDs, s are determined for all .
The Neutrophil Percentage‐to‐Albumin Ratio as a Biomarker for All‐Cause and Diabetes‐Cause Mortality Among Diabetes Patients: Evidence From the NHANES 1988–2018
Authors: Jing Yuanyuan , Tian Bowen , Deng Wenzhen , Ren Ziyu , Xu Xunmei , Zhang Dongmin , Zeng Jing , Liu Dongfang 
Published: October 2024

ABSTRACTBackgroundNeutrophil percentage‐to‐albumin ratio (NPAR) was significantly correlated with diabetes‐related complications. There are little data about NPAR and mortality risk in individuals with diabetes.MethodsThis study included 3858 diabetes patients from the National Health and Nutrition Examination Survey (NHANES) conducted from 1988 to 2018. Using a restricted cubic spline (RCS), the relationship between the NPAR and mortality risk was shown. Multivariable Cox regression models were used to evaluate the relationship between the NPAR and diabetes‐cause and all‐cause death. An examination of the time‐dependent receiver operating characteristic curve (ROC) was used to assess how well the NPAR predicted survival outcomes.ResultsAmong 3858 diabetes individuals, a total of 1198 (31.1%) died over a mean follow‐up of 7.86 years; of these, 326 (8.4%) had diabetes‐related deaths and 872 (22.6%) had deaths from other causes. The RCS regression analysis showed a positive linear association between the NPAR and all‐cause and diabetes‐cause mortality. High NPAR group had a significantly higher risk of all‐cause and diabetes‐cause mortality in univariate and multivariate analysis. Compared with low NPAR group, high NPAR group had a low survival rate of diabetes cases in all‐cause death and diabetes‐cause mortality with area under the curve of the 3‐, 5‐, and 10‐year ROC curve being 0.725, 0.739, and 0.734 for all‐cause mortality and 0.754, 0.752, and 0.745 for diabetes‐cause mortality, respectively.ConclusionIn summary, we examined 3858 diabetes patients from NHANES database (1998–2018) and suggested NPAR as a biomarker for all‐cause and diabetes‐cause mortality prediction.
Relationships between women in leadership at predoctoral and senior administration levels in United States dental schools
Authors: Wilkinson Emma , Kulkarni Roopali , Ying Gui Shuang , Augello Patrick , Boesze‐Battaglia Kathleen , Sheridan Olivia , France Katherine 
Published: October 2024

ABSTRACTPurposeTo determine the relationship between woman leadership at senior administrative and predoctoral levels in United States (US) dental schools and assess if this relationship is affected by school characteristics.MethodsA 23‐question survey was created and distributed to each US accredited dental school (2023). Data regarding the gender of the school's dean, senior administrators, and student leaders, as well as school characteristics were gathered. Data were organized in Excel. Descriptive statistics were performed using mean and standard deviation for continuous measures and using count and percent for categorial measures. Statistical comparisons were performed using analysis of variance (ANOVA), Fisher's Exact, or Chi‐squared tests for comparison of proportions.Results32 dental schools provided analyzable data for this project (44.4% response rate). The most common senior administrative position held by a woman was the dean of student affairs (71.9%). For every surveyed school with a woman dean (n = 11, 34.4%), at least one other senior administrative position was held by a woman. There was no statistical significance between the year of school establishment, geographic region, gender of the dean, or prevalence of women administrators and students in leadership roles. The number of women students in leadership roles was close to the national enrollment trends for gender.ConclusionsIncluded US dental school data showed no relationship between women in leadership at the senior administrative and predoctoral levels. To keep leadership‐minded students interested in dental academics throughout their careers, further studies are needed to identify the most important factors influencing careers in academic dentistry.
Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long‐term cropping systems
Authors: Dhaliwal Jashanjeet Kaur , Panday Dinesh , Robertson G. Philip , Saha Debasish 
Published: October 2024

AbstractSoil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003–2019) of measurements at the Kellogg Biological Station Long‐Term Ecological Research (LTER)/Long‐Term Agroecosystem Research (LTAR) site to better understand the controls of N2O emissions in four corn–soybean–winter wheat rotations employing conventional, no‐till, reduced input, and biologically based/organic inputs. We used a random forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2‐day precipitation, water‐filled pore space, and soil nitrate and ammonium concentrations. The model explained 29%–42% of daily N2O flux variability in the test data, with greater predictability for the corn phase in each system. The long‐term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the conventional system, the model identified ammonium (>15 kg N ha−1) and daily air temperature (>23°C) as the most influential variables; in the no‐till system, climate variables such as precipitation and air temperature were important variables. In low‐input and organic systems, where red clover (Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; before soybean) cover crops were integrated, nitrate was the predominant predictor of N2O emissions, followed by precipitation and air temperature. In low‐input and biologically based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long‐term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.