bluuebunny/crossref_metadata_2025 huggingface dataset:
An Node-Child Matrix-Based Algorithm to the Quickest Path Reliability Problem under Transmission Cost Constraints
Authors: Forghani-elahabad Majid , Alsalami Omar Mutab
Published: November 2023

The quickest path problem in the multistate flow networks, also known as the quickest path reliability problem (QPRP), aims at calculating the probability of transmitting a minimum of d units of flow/dat/commodity from a source node to a destination node through one single path within T units of time. Several exact and approximation algorithms have been proposed in the literature to address this problem. Most of the exact algorithms in the literature need prior knowledge of all the network’s minimal paths (MPs), which is considered a weak point. In addition to the time, the budget is always limited in real-world systems, making it an essential consideration in the analysis of systems’ performance. Hence, this study considers the QPRP under the cost constraints and provides an efficient approach based on the node-child matrix to address the problem without knowing the MPs. We show the correctness of the algorithm, compute its complexity results, illustrate it through a benchmark example, and conduct extensive experimental results on the known benchmarks and one thousand randomly generated test problems to demonstrate its practical superiority compared to the existing algorithms in the literature.
The Effect of Mice Adaptation Process on the Pathogenicity of Influenza A/South Africa/3626/2013 (H1N1)pdm09 Model Strain
Authors: Al Farroukh Mohammad , Kiseleva Irina , Stepanova Ekaterina , Bazhenova Ekaterina , Krutikova Elena , Tkachev Artem , Chistyakova Anna , Rekstin Andrey , Puchkova Ludmila , Rudenko Larisa
Published: November 2023

Influenza virus strain A/South Africa/3626/2013 (H1N1)pdm09 (SA-WT) is a non-mouse-adapted model strain, which has naturally high pathogenic properties for mice. It has been suggested that the high pathogenicity of this strain for mice could be due to the three strain-specific substitutions in the polymerase complex (Q687R in PB1, N102T in PB2, and E358E/K heterogeneity also in PB2). To evaluate the role of these replacements, SA-WT was passaged five times in mouse lungs, and the genome of the mouse-adapted version of the SA-WT strain (SA-M5) was sequenced. SA-M5 lost E358E/K heterogeneity and retained E358, which is the prevalent amino acid at this position among H1N1pdm09 strains. Besides, in the hemagglutinin of SA-M5, two heterogeneous substitutions (G155G/E and S190S/R) were identified. Both viruses, SA-M5 and SA-WT, were compared for their toxicity, ability to replicate, pathogenicity, and immunogenicity for mice. In mice infected with SA-M5 or SA-WT strains, toxicity, virus titer in pulmonary homogenates, and mouse survival did not differ significantly. Contrarily, an increase in the immunogenicity of SA-M5 compared to SA-WT was observed. This increase could be due to the substitutions G155G/E and S190S/R in the HA of SA-M5. The prospects for using SA-M5 in studying the immunogenicity mechanisms were also discussed.
Radionuclide Removal from Aqueous Solutions by Oxidized Carbon Fabrics
Authors: Ioannidis Ioannis , Pashalidis Ioannis , Mulla Batuhan , Kotanidis Gkerman , Ioannou Kyriacos , Constantinides Georgios , Kostoglou Nikolaos , Rebholz Claus
Published: November 2023

The adsorption of actinide ions (Am(III) and U(VI)) from aqueous solutions by pristine and oxidized carbon fabrics has been investigated by means of batch experiments at different pH values (4, 7 and 9) and temperatures (25, 35 and 45 °C) under ambient atmospheric conditions. The experimental results indicate that both pH and fabric texture affect the adsorption rate and the relative removal efficiency, which results at 70% and 100% for Am(III) and U(VI), respectively. The Kd (L/kg) values for U(VI) have been generally found to be higher (2 < log10(Kd)< 3) than the corresponding values for the Am(III) adsorption (1.5 < log10(Kd) < 2). The data obtained from the experiments regarding the temperature effect imply that the relative adsorption for both actinides increases with temperature and that the adsorption is an endothermic and entropy-driven reaction. Application of the fabrics to remove the two actinides from contaminated seawater samples shows that both the relative removal efficiency and the Kd values decrease significantly due to the presence of competitive cations (e.g., Ca2+ and Fe3+) and complexing anions (CO32-) in the respective waters. Nevertheless, the removal efficiency is still remarkable (50% and 90% for Am(III) and U(VI), respectively), demonstrating that these materials could be attractive candidates for the treatment of radionuclide/actinide contaminated waters.
Organic and Inorganic Selenium Compounds Affected Lipidomic Profile of Spleen of Lambs Fed with Diets Enriched in Carnosic Acid and Fish Oil
Authors: Białek Małgorzata , Białek Agnieszka , Wojtak Wiktoria , Czauderna Marian
Published: November 2023

The purpose of these studies was to investigate effect of selenate (Se6), selenized yeast (SeYe) and carnosic acid (CA) supplementation to the diet containing fish oil (F-O) and rapeseed oil (R-O) on contents of fatty acids (FA), malondialdehyde (MDA), tocopherols (Ts) and total cholesterol (TCh) in lambs’ spleens. 24 male lambs (4 groups per 6 animals) have been fed: the control diet - the basal diet (BD) enriched in F-O and R-O; the CA diet - BD enriched in F-O, R-O and CA; the SeYeCA diet - BD enriched in F-O, R-O, CA and SeYe; the Se6CA diet - BD enriched in F-O, R-O, CA and Se6. Dietary modifications affected profiles of FA in spleens. The SeYeCA and Se6CA diets increased the docosapentaenoic acid preference in Δ4-desaturase, hence the higher content of docosahexaenoic acid was found in spleens of SeYe- or Se6-treated lambs than in spleens of animals receiving the CA and control diets. Experimental diets reduced the level of atherogenic FA in the spleen in comparison with the control diet. The experimental diets supplemented with SeYe or Se6 increased levels of TCh and Ts in spleens in comparison with the CA and control CA diets. The present studies documented that Se6, SeYe and CA influenced the metabolism of FA, Ts and cholesterol in spleens.
Connecting Global Modes of Variability to Climate in High Mountain Asia
Authors: Massoud Elias , Lim Young-Kwon , Andrews Lauren , Girotto Manuela
Published: November 2023

Oscillations in global modes of variability (MoV) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic Oscillation (AO), Eurasian teleconnection, Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (Nino34), with winter and summer climate in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2-m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, but also using a lagged correlation analysis to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and Central China in both winter and summer and a positive correlation in Western China in summer. PRECTOT has a positive correlation with all MoV in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results pinpoint different time-windows and specific regions within HMA that exhibit high correlation between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.
Effect of surface Pt doping on the reactivity of the Au(111) surface towards methanol dehydrogenation: a first-principles Density Functional Theory investigation
Authors: Demirtas Merve , Ustunel Hande , Toffoli Daniele
Published: November 2023

The surprisingly high catalytic activity of gold has been known
to the heterogeneous catalysis community since the mid-1980s.
Significant effort has been directed towards improving the reactivity of these
surfaces towards important industrial reactions. One such strategy is
the introduction of small amounts of other metals to create Au-based
surface alloys. In this work, we investigate the synergistic effect of
Pt doping of the Au(111) surface towards decreasing the activation
barrier of the methanol dehydrogenation elementary step, within
first-principles density functional theory. To this aim we construct
several models of \ce{Pt}-doped Au(111) surfaces, including a full
\ce{Pt} overlayer and monolayer. The effect of \ce{Pt} surface doping
is then investigated via the computation of adsorption energies of the
various chemical species involved in the catalytic step, and the
estimation of activation barriers of methanol dehydrogenation. Both
electronic and strain effects induced by \ce{Pt} surface doping concur
in substantially lowering the activation energy barrier of this
important reaction elementary step. Morever, in the presence of
preadsorbed atomic oxygen, \ce{Pt} surface doping can be used to
reduce the activation energy for methanol dehydrogenation to as low as
0.1 eV.
A Containerized Service-based Integration Framework for Heterogeneous Geospatial Models
Authors: Zhu Lilu , Wang Yang , Kong Yunbo , Hu Yanfeng , Huang Kai
Published: November 2023

With the rapid development of Earth observation and information technology, people are increasingly able to access geospatial models. Geospatial models, based on principles of geography, utilize mathematical, statistical, as well as computer science methods to interpret and predict geographic phenomena. These models can be applied in the fields such as urban planning, environmental protection, traffic management to help decision-makers solve geography-related problems. However, integrating different geospatial models to collaboratively solve complex geographic problems still faces significant obstacles due to heterogeneity in model structure, dependencies, and running modes. In this study, we propose a containerized service-based integration framework for heterogeneous geospatial models (GeoCSIF). GeoCSIF consists of three main components: (1) Model encapsulation. It breaks down complicated geospatial models into independently manageable model units, and builds as unified service packages with a templated constraint method. (2) Model orchestration. It achieves an optimal combination of large-scale models with complex dependencies using a prioritization-based orchestration method. (3) Model publication. It incorporates heuristics into the model scheduling process, which can provide adaptive deployment for different model runs. Finally, a prototype system was developed to validate the effectiveness and progressiveness of GeoCSIF by the integrating process of heterogeneous flood disaster models.
Strontium-Doped Mesoporous Bioactive Glass Loading Bisphosphonates Inhibit Osteoclast Differentiation and Prevent Osteoporosis in Ovariectomized Mice
Authors: Zhou Zhi , Huo Shicheng , Li Zhanchun
Published: November 2023

Postmenopausal osteoporosis, a metabolic bone disease associated with aging and that affects bones throughout the body, is emerging as an urgent public health concern and imposes a substantial healthcare burden on society. The clinical application of bisphosphonate, the primary treatment for osteoporosis, is limited owing to the drug’s severe complications. Herein, we investigate the synthesis and utilization of strontium-doped mesoporous bioactive glass loaded with alendronate (ALN@Sr-MBG) as a novel therapeutic agent for osteoporosis, to explore its potential as an alternative to alendronate (ALN). Strontium-doped mesoporous bioactive glass (Sr-MBG) was synthesized using the sol-gel method, while ALN@Sr-MBG was obtained by incorporating Sr-MBG into an alendronate saturated solution. The bioactivities of ALN@Sr-MBG, including biotoxicity, inflammation inhibition, and anti-osteoclast differentiation, were investigated in vitro using CCK-8, flow cytometry, tartrate-resistant acid phosphatase (TRAP) staining, and RT-PCR assays. Animal models were established by surgically removing the ovaries from non-pregnant female C57/BL mice, followed by weekly intraperitoneal injections of ALN@Sr-MBG, ALN, or excipients. After 8 weeks, the mice femurs were extracted and analyzed through Micro-CT scanning, and hematoxylin-eosi, osteoblastic, and osteogenic staining. The in vitro findings demonstrated that ALN@Sr-MBG displayed enhanced biological efficacy compared to ALN in terms of inflammation inhibition, osteogenesis promotion, and osteoclastogenesis inhibition. Furthermore, micro-CT analysis revealed that ALN@Sr-MBG significantly augmented bone mineral density (BMD), bone volume fraction (BV/TV), trabecular number (Tb.N), and trabecular thickness (Tb.Th), while reducing trabecular separation (Tb.Sp) and structural model index (SMI) in mice with ovariectomy-induced osteoporosis. The osteoblast and osteogenic staining results indicate the enhanced bioactivities of ALN@Sr-MBG in promoting bone formation and inhibiting bone resorption compared to ALN. In vitro and in vivo assessments further confirmed that ALN@Sr-MBG exhibits superior anti-osteoporotic bioactivity compared to ALN. The study findings confirm the potential of ALN@Sr-MBG as a novel alternative therapy to ALN and drug candidate for the treatment of osteoporosis.
Dynamic Assessment of Urban Carrying Capacity Load Number Using the Enhanced UCCLN Model
Authors: Liponhay Marissa Pastor , Valerio Alyssa , Fornan Glydel , Alis Christian , Monterola Christopher P.
Published: November 2023

The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity then becomes crucial for tourist-oriented cities. This study focused on Baguio City, the "Summer Capital of the Philippines," attracting large crowds on holidays and actively promoting various events on non-holidays, thereby having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, load number (LN) changes for different temporal contexts are calculated based on spatial indicators grouped into air, traffic, economy, and waste. The city experiences the worst pressures on air quality during holidays with $99.23\%$ districts under very high to critical levels followed by regular and days with events. However, the total LN is balanced by favorable economic conditions with only $9.23\%$ at critical. EUCCLN effectively pinpoints areas experiencing critical states at any time, advocating targeted government monitoring. We demonstrate that Night Time Light, for places with no economic data available, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that EUCCLN monitoring urban pressures can easily be expanded to nowcasting with real-time data.
High-Mobility Topological Semimetals as Novel Materials for Huge Magnetoresistance Effect and New Type of Quantum Hall Effect
Authors: Zivieri Roberto , Lumetti Stefano , Létang Jérémy
Published: November 2023

During the last decades the quantitative description of electrical and magnetotransport properties of solid-state materials has been a remarkable challenge in materials science. Recently, the discovery of a novel class of materials, the topological semimetals, has led to a growing interest for the full understanding of their magnetotransport properties. In this review, the strong interplay among topology, band structure and carrier mobility in recently discovered high carriers mobility topological semimetals is discussed and their effect on their magnetotransport properties is outlined. The huge magnetoresistance effect, especially in the Hall transverse configuration, and a new version of a three-dimensional quantum Hall effect observed in high-mobility Weyl and Dirac semimetals are reviewed. The design of novel quantum sensors based on solid-state semimetals is also encouraged.
A Review of Photovoltaic Failure and Degradation Mechanisms
Authors: Al Mahdi Hussain , Leahy Paul G , Alghoul Mohammad , Morrison Alan P.
Published: November 2023

With the global increase of photovoltaic (PV) modules deployment in recent years, the need to explore and realize their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures can be minor and cause no critical harm if within the expected range. Others, may start mildly and then deteriorate faster to become catastrophic, especially in harsh environments. This paper conducts a state-of-the-art literature review to scan PV failures, types, and their root cause based on PV’s constructed components (from protective glass to junction-box). It outlines the hazardous consequences beyond PV module failures, describing what harm they can bring to the PV system. As we delve into the literature, it becomes clear that every component is vulnerable to certain types of failures; some can deteriorate within themselves, and others infect further PV components resulting in emerging more severe failures. In the end, the review briefly summarises PV failure detection techniques, emphasising electrical characterization techniques, and disclosing the need to engage more electrical parameters. Most importantly, this review can prepare the stage for the PV research community to identify the most prevalent degradation processes. This, in turn, encourages researchers to investigate them throughout modelling and experimental studies to forecast them at the early onset in order to protect the PV systems from hazardous malfunctions.
A Peculiar Case of Newly Diagnosed Lymphoma in a Patient with Systemic Lupus Erythematous Presenting with Hypercalcemia: A Case Report
Authors: Rahmanian Ehsan , Nekooeizadeh Pegah , Shahriarirad Reza
Published: November 2023

Background: Systemic lupus erythematous (SLE) is an autoimmune, episodic, and chronic disease that can affect multiple organs in the body and consequently it can present with variety of sign and symptoms. Hypercalcemia is a considered to be a rare presentation in patients with systemic lupus erythematous. In this case report we present a patient with SLE flare up who presented with hypercalcemia, which her overlapping manifestations endured a challenging diagnosis of lymphoma.Case Presentation: A 41-year-old man with a ten-year history of SLE presented to us with symptoms of SLE flare up. During laboratory evaluation, high calcium level was detected which was unresponsive to the treatment. Bone marrow revealed marginal B cell lymphoma as the ultimate diagnosis. He was started on R-CHOP chemotherapy regimen, and reported relative improvement in clinical and laboratory conditions during follow-ups.Conclusion: Our case is the first report of concurrent SLE flare up, with a diagnosis of lymphoma and a primary clinical presentation of hypercalcemia. Physicians should be aware of the fact that patients with SLE flare up can present with hypercalcemia and lymphoma as concomitant conditions that needs further exploration.
Clinical, Histopathological and Molecular Spectrum of Cutaneous Lesions in Myelodysplastic Syndrome and Myeloproliferative Neoplasms (MDS/MPN): A Review and A Proposed Classification
Authors: Prieto-Torres Lucía , Requena Luis , Rodríguez-Pinilla Socorro Maria
Published: November 2023

Myeloid neoplasms and acute leukemias include different entities that have been recently re-classify taking into account molecular and clinicopathological features. The myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN) category comprises a heterogeneous group of hybrid neoplastic myeloid diseases characterized by the co-occurrence of clinical and pathologic features of both myelodysplastic and myeloproliferative neoplasms. The most frequent entity in this category is chronic myelomonocytic leukemia (CMML) which is, after acute myeloid leukemia (AML), the main myeloid disorder prone to develop cutaneous manifestations. Skin lesions associated with myelodysplastic and myeloproliferative neoplasms include a broad clinical, histopathological and molecular spectrum of lesions, poorly understood and without a clear-cut classification in the current medical literature. The aim of this review is to describe and classify the main clinical, histopathological and molecular patterns of cutaneous lesions in the setting of MDS/MPN in order to improve the diagnostic skills of dermatologists, hematologist and pathologist who deal with these patients.
Discrete Ripplet-II Transform Feature Extraction and Metaheuristic-Optimized Feature Selection for Enhanced Glaucoma Detection in Fundus Images Using LS-SVM
Authors: Sharma Santosh Kumar , Muduli Debendra , Rath Adyasha , Dash Sujata , Panda Ganapati
Published: November 2023

Recently, significant progress has been made in developing computer-aided diagnosis (CAD) systems for identifying glaucoma abnormalities using fundus images. Despite their drawbacks, methods for extracting features such as wavelets and their variations, along with classifier like support vector machines (SVM), are frequently employed in such systems. This paper introduces a practical and enhanced system for detecting glaucoma in fundus images. This system adresses the chanallages encountered by other existing models in recent litrature. Initially, we have employed contrast limited adaputive histogram equalization (CLAHE) to enhanced the visualization of input fundus inmages. Then, the discrete ripplet-II transform (DR2T) employing a degree of 2 for feature extraction. Subsequently, a golden jackal optimization algorithm (GJO) employed to select the optimal features to reduce the dimension of the extracted feature vector. During the classification stage the least square support vector machine (LS-SVM) with three kernels called as linear, polynomial and radial basis function(RBF), for classifying of fundus images as glaucoma or healthy. The proposed method is validated with the current state-of-the-art models on two standard datasets, namely, G1020 and ORIGA. The results obtained from our experimental result demonstrate that our best suggested approach DR2T+GJO+LS-SVM-RBF obtains better classification accuracy 93.38% and 97.31% for G1020 and ORIGA dataset with less number of features. It establishes a more concise network structure when contrasted with traditional classifiers.
An Improved 3D OPC Method for the Fabrication of High-Fidelity Micro Fresnel Lenses
Authors: Peng Fei , Sun Chao , Wan Hui , Gui Chengqun
Published: November 2023

Based on three-dimensional optical proximity correction (3D OPC), recent advancements in 3D lithography have enabled the high-fidelity customization of 3D micro-optical elements. However, micron-to-millimeter scale structures represented by Fresnel lens design bring more stringent requirements for 3D OPC, which poses significant challenges to the accuracy of models and the efficiency of algorithms. Thus, a lithographic model based on optical imaging and photo-chemical reaction curve is developed in this paper, and a sub-domain division method with a statistics principle is proposed to improve the efficiency and accuracy of 3D OPC. Both the simulation and the experimental results showed the superiority of the proposed 3D OPC method in the fabrication of the Fresnel lenses. The computation memory requirements of the 3D OPC are reduced to below 1 %, and the profile error of the fabricated Fresnel lens reduced 79.98%. Applying the Fresnel lenses to an imaging system, the average peak signal to noise ratio (PSNR) of the image increased by 18.92 %, and the average contrast of the image enhanced by 36 %. We believe the proposed 3D OPC method can be extended to the fabrication of vision-correcting ophthalmological lenses.
Antifungal Activity of Streptomyces spp. Extracts in vitro and on Post-harvest Tomato Fruits Against Plant Pathogenic Fungi
Authors: Montesdeoca-Flores David Tomás , Hernández-Bolaños Eduardo , León-Barrios Milagros , Hernández-Amador Eduardo , Díaz-González Selene , Abreu-Acosta Néstor , Luis-Jorge Juan Cristo
Published: November 2023

Plant pathogenic fungi are the most important cause of losses in agriculture. In the face of the overuse of synthetic fungicides, natural products are an encouraging alternative to control these plant pathogenic fungi. In this study, we tested the antifungal capacity of metabolites produced by strains of the genus Streptomyces against the plant pathogenic fungi Alternaria alternata, Botrytis cinerea and Fusarium oxysporum. In addition, we investigated the feasibility of applying these metabolites in a postharvest setting for the control of B. cinerea on cherry tomato fruits. The results revealed the ability of the strains, especially Streptomyces netropsis, to inhibit the growth of plant pathogenic fungi and, in some cases, the sporulation of these fungi. In addition, we observed an interesting phenomenon in which Streptomyces strains physically encapsulated the mycelium of the fungi, which contributed to their inhibition. Finally, the protective activity of S. netropsis extract on Cherry tomato fruits infected with B. cinerea was demonstrated. In conclusion, this research opens the door to studies on the understanding of physical microbial interactions in natural environments and holds promise in agriculture, especially in the protection of agricultural products during the post-harvest stage as a safer and more sustainable alternative.
Transformer Text Classification Model for Arabic Dialects that Utilizes Inductive Transfer
Authors: Baniata Laith H. , Kang Sangwoo
Published: November 2023

In the realm of the five-category classification endeavor, there has been limited exploration into applied techniques for classifying Arabic text. These methods have primarily leaned on singletask learning, incorporating manually crafted features that lack robust sentence representations. Recently, the Transformer paradigm has emerged as a highly promising alternative. However, when these models are trained using single-task learning, they often face challenges in achieving outstanding performance and generating robust latent feature representations, especially when dealing with small datasets. This issue is particularly pronounced in the context of the Arabic dialect, which has a scarcity of available resources. Given these constraints, this study introduces an innovative approach to dissecting sentiment in Arabic text. This approach combines Inductive Transfer (INT) with the Transformer paradigm to augment the adaptability of the model and refine the representation of sentences. By employing self-attention SE-A and feed-forward sub-layers as a shared Transformer encoder for both the five-category and three-category Arabic text classification tasks, this proposed model adeptly discerns sentiment in Arabic dialect sentences. The empirical findings underscore the commendable performance of the proposed model, as demonstrated in assessments of the Hotel Arabic-Reviews Dataset, the Book Reviews Arabic Dataset, and the LARB dataset.
Will Urbanization Affect the Low-Carbon Efficiency of Agriculture?—Based on Empirical Evidence from the Yellow River Basin
Authors: Song Xinyan , Wang Chengyue , Liu Wenxin
Published: November 2023

The improvement of agricultural low-carbon efficiency is an important path to promote the realization of the "double carbon" goal in the Yellow River Basin. In the context of rapid urbanization development, it is of great significance to explore whether the promotion of urbanization will affect the agricultural low-carbon efficiency. Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this paper uses super-DEA model, three-dimensional kernel density model and Markov chain model to measure and analyze the spatio-temporal evolution of agricultural low-carbon efficiency in the Yellow River Basin, on this basis, the panel Tobit model is used to analyze the relationship between urbanization and low-carbon efficiency in agriculture. The results show that: (1) The level of agricultural low-carbon efficiency in the Yellow River Basin is low and has not reached the effective state, showing a slow downward trend in general, among which, the agricultural low-carbon efficiency in the lower reaches is higher than that in the middle reaches, and the upper reaches is the lowest. (2) The agricultural low-carbon efficiency in the Yellow River Basin has a negative trend of transferring to the low level on the whole, and tends to maintain the original state level, and it is difficult to realize the leapfrog transfer between states. Agricultural low-carbon efficiency has obvious spatial spillover effect and "club convergence" phenomenon, high efficiency area has a positive driving effect on the neighborhood area, while low efficiency area has a negative impact on the neighborhood area. (3) The level of urbanization has a significant positive impact on the low-carbon efficiency of agriculture in the upper, middle and lower reaches of the Yellow River Basin, which plays an important role in promoting the green development of agriculture. Finally, based on the above research conclusions, relevant policy recommendations were put forward, in order to provide references for promoting the improvement of low-carbon agricultural efficiency and promoting high-quality agricultural development in the Yellow River Basin.
Hubble Diagram Test of SN1a Supernovae and High Redshift Gamma Ray Bursts: Data Analysis of the Log(z)/µ, ln(z+1)/T(d) and Linear Photon Flight Time T/(z+1) Scales. – Comparison of Observational Data with Model Calculations.
Authors: Marosi Laszlo
Published: November 2023

Hubble diagrams are examined for SN1a supernovae in the redshift range z = 0.01–1.3 and for gamma ray bursts in the range z = 0.034–8.1. It is shown that in the low redshift range, the Hubble diagram shows an innate equivocality between the ΛCDM and the tired light model. This means that the strong agreement between the z/µ data, calculated with the parameters of the ΛCDM model, and the experimentally measured z/µ values cannot be considered as definite evidence for the expansion hypothesis. The exponential function , which is characteristic of the tired light redshift mechanism, fits the data with similarly high accuracy. Hence, on the premise of low redshift data, a decision for or against either model is completely arbitrary. The Hubble diagram for high redshift gamma ray bursts shows poor agreement with the ΛCDM model, but concurs with the exponential energy decay following from the tired light redshift hypothesis.
Least-Cost-Path and Closest Facility Analysis for Generating District Heating Networks on a Communal Level
Authors: Strzałka Aneta , Malicki Jacek , Blachowski Jan
Published: November 2023

Due to an urgent need for reducing the fast progressing climate changes, a rapid, standardized and replicable solution for the infrastructure restructuring of heat demand coverage of buildings at district and city level must be developed. As more and more communities in Europe, especially in Germany, are obligated to have plans for coverage of heat demand, city planners, energy agencies seek a tool, which will help them to design the first drafts of heating network routes, which can supply whole districts and cities with renewable energy. ArcGIS Pro Tools like Least-Cost-Path-Analysis (LCPA) and Closest Facility (CF) allow to find the shortest and “cheapest” way between the heat source and heat consumers in the analyzed areas. Starting from the community level, through the district, county, voivodeship and whole country levels, the replication of the methods for generating district heating (DH) network infrastructure can be achieved. The proposed LCPA and CF based methods help to design the most suitable and efficient DH networks in the analyzed areas. As only few open-source data input, like street networks and building footprints are needed, the methods can be implemented in all communities of the country of Poland. In this paper one example of one community of Wroclaw county, called Siechnice and surroundings is presented.
Knowledge on Stroke Recognition and Management Among Emergency Department Healthcare Professionals in the Republic of Cyprus
Authors: Rossis Christos , Michail Koralia A. , Middleton Nicos , Karanikola Maria , Papathanassoglou Elizabeth , Mpouzika Meropi
Published: November 2023

Data show that ischemic stroke is one of the leading causes of death and disability worldwide. Knowledge of ischemic stroke-related guidelines is vital for health care professionals working in the Emergency Departments (EDs) because it affects the early diagnosis and timely treatment to combating stroke. We aimed to explore knowledge regarding the recognition and management of the ischemic stroke among Greek-Cypriot emergency health care personnel (nurses and physicians). A descriptive cross-sectional correlation study was implemented from November 2019 to April 2020 across 4 private and 7 public EDs in Cyprus. Data were collected with the use of a self-reported questionnaire, developed by the research team. 255 nurses [Response Rate (RR): 74.1%] and 26 physicians (RR; 47.3%) completed the questionnaire. The participants gave a correct answer to an average of 12.9 statements from a total of 28 (SD: 4.2) with nurses and physicians scoring a mean of 12.9 (SD:4.1) and 15,7 (SD: 4) respectively. Participating hospitals scored an average of 10.3 to 14.1. Participants with previous training scored an average of 1.45 addi-tional correct answers. Greek-Cypriot health care professionals in EDs reported poor to moderate knowledge about ischemic stroke highlighting the need for targeted and continuous education, and further study of factors related with this may be of interest. Also, development and implementation of evidence-based protocols and enhanced education regarding ischemic stroke should be considered essential interventions for emergency health care professionals.
Protective Effects of Whey Protein Hydrolysate, Treadmill Exercise, and Their Combination Against Scopolamine-induced Cognitive Deficit in Mice
Authors: Chang Yeok Boo. , Jung Eun-Jin , Suh Hyung Joo. , Choi Hyeon-Son
Published: November 2023

In this study, the potential of whey protein hydrolysate (WPH) containing LDIQK peptide and treadmill exercise to prevent cognitive decline was investigated along with the neuroprotective mechanisms. Cognitive dysfunction was induced in mice by 1 mg/kg scopolamine, followed by administration of WPH at 100 and 200 mg/kg and/or treadmill exercise at 15 m/min for 30 min five days per week. Both WPH administration and treadmill exercise significantly improved memory in mice with scopolamine-induced cognitive impairment, which was attributed to several key mechanisms, including a reduction in oxidative stress based on decreased levels of reactive oxygen species and malondialdehyde in the brain tissue and an increase in acetylcholine by increasing choline acyltransferase and decreasing acetylcholine esterase levels. Exercise and WPH also exerted neuroprotective effects by inhibiting the hyperphosphorylation of tau protein, enhancing the expression of brain-derived neurotrophic factor, and inhibiting apoptosis by reducing the Bax/Bcl2 ratio in conjunction with downregulation of the mitogen-activated protein kinase pathway. Moreover, the impact of WPH and treadmill exercise extended to the gut microbiome, suggesting a potential link with cognitive improvement. These findings suggest that both WPH intake and treadmill exercise are effective strategies for mitigating cognitive impairment, providing promising avenues for treating neurodegenerative diseases.
A Study on Refraction Error Compensation Method for Underwater Spinning Laser Scanning 3D Imaging
Authors: Zhang Jinghui , Wang Yuhang , Zhang Tao , Yang Kai , Zhang Jian , Wang Xinyu
Published: November 2023

Laser scanning 3D imaging technology, because it can get accurate three-dimensional surface data, has been widely used in the search for wrecks and rescue operations, underwater resource development, and other fields. At present, the conventional underwater rotating laser scanning imaging system maintains a relatively fixed light window. However, in low-light situations underwater, the rotation of the scanning device causes some degree of water fluctuation, which warps the light strip data that the system sensor receives about the object's surface. To solve the problem, this research studies an underwater 3D scanning and imaging system that makes use of a fixed-light window and a spinning laser (FWLS). A refraction error compensation algorithm is investigated that is based on the fundamentals of linear laser scanning imaging and the dynamic refraction mathematical model is established by the motion of the imaging device. During the imaging process, the incident angle between the laser and the light window varies due to the scanning mode of the system. The experimental results show that the reconstruction radius error is reduced by 60% (from 2.5 mm to about 1 mm) when the measurement data for a standard sphere with a radius of 20 mm are compensated. Moreover, the compensated point cloud data exhibits a higher degree of correspondence with the model of the standard spherical point cloud. This study has a specific reference value for the refractive error analysis of an underwater laser scanning imaging system, and it provides certain research ideas for the subsequent refractive error analysis of various scanning imaging modalities.
Predicting the risk of heatstroke: Development of a highly accurate model
Authors: Nemoto Mio , Hirabayashi Satoshi , Sato Seisho , Fujii Akihiro , Nojiri Hidetoshi , Ihara Tomohiko
Published: November 2023

In Japan, a heat health warning system is in operation to reduce heat-related mortality and morbidity caused by global climate change. However, warnings are issued uniformly throughout the country under the same conditions, resulting in low accuracy in some areas. To reduce heat-related mortality and morbidity, accurate models for predicting the number of people transported by ambulance due to heatstroke, a precursor to death, must be developed. This study compared three methods for predicting heatstroke risk: multiple regression analysis, a generalised additive model, and time-stratified case-crossover analysis (TC). Heatstroke susceptibility is likely to depend on year-wise trends and sensitivity to training data. Most previous models, however, only tested a small amount of training data. In this study, we looked into the best number of years to use as training data. Error-influencing factors in the training data were identified by comparing the errors of each method. The TC errors were significantly less sensitive to the training data than the others (p <0.01). When data from three to four years after the most recent data were included, the accuracy of all three methods tended to decrease. Consequently, a highly accurate prediction model with low sensitivity to training data was developed using the odds ratios produced by TC, which was impossible with previous models. This modelling approach will help improve heat-health warning systems, reducing heatrelated mortality and morbidity and can be used to make each area safer in the future.
Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus
Authors: Zhang Yajuan , Cui Yi , Li Yijun , Lu Hongliang , Huang He , Sui Jiaru , Guo Zhihua , Miao Danmin
Published: November 2023

Background: The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidity.The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide targets for prevention and intervention into depression and anxiety.
Methods: This study used a cross-sectional design with data from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depression and anxiety was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Expected influence (EI) and bridge expected influence(BEI) indices were calculated for each symptom.
Results: The prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. “Feeling blue/depressed”, “Nervousness or anxiety”, “Uncontrollable worry”, “Trouble relaxing”, and “Worry too much” had the highest EI values. “Nervousness or anxiety” and “Everything was an effort” exhibited the highest BEI values.
Conclusion: Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or suffer from depressive and anxiety symptoms.
An evidential deep learning framework for assessment of mammograms
Authors: Gudhe Raju Naga , Mazen Sudah , Sund Reijo , Kosma Veli-Matti , Behravan Hamid , Mannermaa Arto
Published: November 2023

In this study, we present an evidential deep learning framework called MV-DEFEAT, incorporating the strength of Dempster-Shafer evidential theory and subjective logic, for various mammogram assessment tasks, including mammogram density assessment, BIRADS scoring, and mammogram finding as normal/benign/malignant. The framework combines evidence from multiple mammogram’s views to mimic a radiologist’s decision-making process. We conducted experiments on two open-source digital mammogram datasets, VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography and the Digital Database for Screening Mammography (DDSM), which include 5,000 and 1,975 mammogram examinations, respectively. Our results showed that MV-DEFEAT achieves weighted macro-average area under the receiver operating characteristic curves (AUCs) of 98.92 ± 0.007 and 86.53 ± 0.051 for mammogram density assessment on the VinDr-Mammo and DDSM datasets, respectively, which are considerably better than a state-of-the-art multi-view deep learning method with AUCs of 86.38 ± 0.258 and 70.62 ± 0.261. In addition, MV-DEFEAT demonstrated strong generalization for mammogram density assessment on two independent and unseen datasets, the Chinese Mammography Database (CMMD) and Virtual Tissue Biobank (VTB). Furthermore, we demonstrated the efficient feature representation of the MV-DEFEAT that could be transferred to a breast cancer stage classification task using the unseen Kuopio Osteoporosis Risk Factor and Prevention study (OSTPRE) dataset. Our results enhance trust in using deep learning algorithms to assess mammograms in clinical settings.
Pacemakers of extreme floods during warmer and wetter climates of the “Wild Nile” stage
Authors: Blanchet Cecile , Ionita Monica , Ramisch Arne , Tjallingii Rik , Brauer Achim , Laruelle Louison , Bagge Meike , Klemann Volker
Published: November 2023

Understanding how large river systems will respond to an invigorated hydrological cycle as simulated under higher global temperatures is a pressing issue. We present here a 1500 yr-long annually-laminated (varved) record that tracks the seasonal discharge of the Nile River during the wetter- and warmer-than-present Early Holocene. This unique record depicts the mobilization of large amounts of sediments during strong summer floods that probably rendered the Nile valley inhabitable. More frequent and rapid switching between extreme (strong and weak) floods between 9.2 and 8.5 ka BP indicate highly instable fluvial dynamics. On interannual timescales, flood variability is paced by El Niño-Southern Oscillation while multi-decadal oscillatory modes drive the changes in extreme flood events. These pacemakers are also identified in Nile flow records from the Common Era, which demonstrates their stationarity under different climatic conditions.
Alternative Approach for Deriving an Unconventional Distance Protection Algorithm
Authors: Araújo Marcos R.
Published: November 2023

This work presents an alternative approach for deriving an unconventional distance protection algorithm suitable for long single-circuit transmission lines. Such approach is based on the application of Kirchhoff's Laws to a system modeled in the frequency domain. The electric power system considered and the steps of the protection algorithm deduction approach are detailed. As a result, the same input signals from the literature are obtained, which demonstrates the adequacy of such methodology to different systems.
Effectiveness of a blended school-based mindfulness program for the prevention of co-rumination and internalizing problems in Dutch secondary school girls: a Cluster Randomized Controlled Trial
Authors: Vuijk Patricia , Bul Kim , Buil Marieke , Rauws M , Curie Keshia , Amesz Char , Weerheijm R , Riper Heleen
Published: November 2023

Background: A growing body of literature indicates that adolescent girls who talk with close friends about interpersonal problems or worries in an excessive, speculative way and with an intense focus on distress (i.e., co-rumination) are at heightened risk for developing internalizing symptoms and disorders as well as reduced friendship quality. However, to date, there are no prevention programs available that target high levels of co-rumination between adolescent girls. As such, we developed the blended school-based mindfulness prevention program Happy Friends, Positive Minds (HFPM) that targets co-rumination at the dyadic level, i.e., between two close female friends. The aim of this trial is to evaluate the effectiveness of HFPM to reduce co-rumination and internalizing problems and to enhance wellbeing and social-emotional behavior in Dutch adolescent girls.
Methods: A cluster Randomized Controlled Trial (cRCT) will be conducted to evaluate HFPM effectiveness. We will recruit 160 female friendship dyads (n = 320 girls) aged 13 to 15 years who will be characterized by high levels of self-reported co-rumination. The cRCT has two arms: (1) an intervention condition in which 160 girls (80 friendship dyads) will receive the 14-week HFPM program, and (2) a control condition in which 160 girls (80 dyads) will receive care-as-usual (CAU). Data will be collected at baseline (T0: October 2023), during the program (T1: December 2023; T2: February 2024; T3: April 2024), immediately after the program (T4: July 2024) and at one-year follow-up (T5: July 2025). Participant-level self-reported risk for (early onset) depression and anxiety, self-reported and observed co-rumination, self- and friend-reported friendship quality, self-reported positive and negative affect, self-reported interpersonal responses to positive affect and self-reported anhedonia symptoms will be the outcome variables.
Discussion: This study will provide insights into the short-term and long-term effects of the HFPM program on girls’ internalizing problems, wellbeing and social-emotional behavior.
Trials registration: International Standard Randomized Controlled Trials, identifier: ISRCTN54246670. Registered on 27 February 2023.