bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing helminth infection in some reproductive colonies of Southern Giant Petrel (Macronectes giganteus) from Antarctica
Authors: Fusaro Bruno , Capasso Sofia , Lorenti Eliana , Panisse Guillermo , Fuentes Lautaro , Fornillo María Valentina , Libertelli Marcela , Ansaldo Martin , Diaz Julia I. 
Published: January 2024

Abstract
The host/parasite relationship is a key tool for understanding the role of parasitism in the feeding ecology of Antarctic seabirds. Especially, birds with extensive migratory routes through isolated regions are particularly sensitive to new infections. Although research on parasitic diseases in Antarctic birds is sparse and information is fragmentary, an increasing number of studies are currently underway in this area. The present study aims to provide new information on parasitic helminths in the Southern Giant Petrel Macronectes giganteus in some nesting areas, integrating different parasitological techniques. A total of 126 faecal samples, 16 regurgitates and six dead individuals (five adults and one chick) were analysed for helminth parasites. Members of four helminth groups (Cestoda, Digenea, Nematoda, Acantocephala) represented the parasitic diversity of the Southern Giant Petrel in the studied localities. All dead birds analysed (P = 100%) harboured helminth parasites, additionally P = 49.2% of the fecal samples and P = 0.06% of the regurgitated individuals presented at least one of the different helminth groups found in the viscera. The combination of three diagnostic techniques allowed us to determine the presence of nine adult helminth species (Cosmocephalus obvelatus, Stegophorus macronectes, Stegophorus diomedeae, Contracaecum sp., Parorchites zederi, Tetrabothrius heteroclitus, Diphylobotrium sp., Corynosoma shackletoni, and Renicolidae). In addition, juvenile specimens of Tetrameres sp. and Anisakis sp. were found in the eviscerated host. We discuss the trophic relationships of the hosts and their influence in the helminth infestations. This study provides new knowledge about the parasitic diversity of the Southern Giant Petrel in its nestling areas with new records of helminth species in Antarctica.
An Accurate Calculation Method for Inductor Air Gap Length in High Power DC-DC Converters
Authors: Zeng Xiaohui , Chen Wei , Yang Lei , Chen Qingbin , Huang Yuping 
Published: January 2024

Abstract
High-power inductors are fundamental components in high-power DC-DC converters, with their performance being a crucial metric of converter efficiency. This paper presents an in-depth analysis of a novel calculation method for the air gap length in such inductors. Taking into account the effects of air gap diffusion and the winding magnetic field, an expression for the air gap diffusion radius is derived, focusing on a distributed air gap structure. Furthermore, models for calculating the air gap and winding reluctance are developed, grounded in electromagnetic field theory. An equivalent magnetic circuit model, formulated based on Kirchhoff's second law, facilitates the proposed method for air gap length calculation. This study also involves the development of 3D models for both discrete and decoupled integrated inductors. The comparison between simulation outcomes and calculated air gap lengths indicates a maximum error of less than 5%, with the minimum error being as low as 0.54%. Additionally, the discrepancy between calculated values and experimental measurements is found to be 1.11%. These results validate the accuracy and applicability of the theoretical analysis and calculation method, underscoring their significance in the design and optimization of high-power DC-DC converters.
Investigation of Temperature Effects on Wide Steel Box Girder of Suspension Bridge Based on Long-Term Monitoring Data
Authors: Wang Yanru , Zhang Guoliang , Liu Lang , Wang Xu , Zheng Shuqin , Huang Jin , FU BIN , Zhou Lei 
Published: January 2024

Abstract

The time-varying temperature distributions on bridge structures may remarkably change structural performance, which may result in differential strain/stress responses on structural members compared with the design conditions. Therefore, it is crucial to have a comprehensive understanding of temperature distributions and its effects on bridges. In this study, taking advantage of structural health monitoring technology, one-year field monitoring data collected from a long-span suspension bridge were used to investigate the temperature distributions and their effects on the steel box girder. Specifically, the distributions and probability statistics of temperatures on the top and bottom plates were firstly analyzed. Based on which, the transverse and vertical temperature differences on the box girder were further examined, moreover, the representative values of temperature differences for various return periods were calculated by exceedance probability method. At end, a temperature prediction method was proposed to simulated the temperature field distributions during bridge life cycle, to provide substantial temperature data for estimating future operation condition. The results of this study were beneficial to structural evaluation of in-service bridges to ensure their serviceability and integrity in the life cycle.
Tri-UNet: A Brain Age Prediction Method Based on Different Scale Features of Magnetic Resonance Imaging
Authors: Pang Yu , Cai Yihuai 
Published: January 2024

Abstract
In the process of human aging, significant age-related changes occur in brain tissue. To assist individuals in assessing the degree of brain aging, screening for disease risks, and further diagnosing age-related diseases, it is crucial to develop an accurate method for predicting brain age. This paper proposes a multi-scale feature fusion method called Tri-UNet based on the U-Net network structure, as well as a brain region information fusion method based on multi-channel input networks. These methods address the issue of insufficient image feature learning in brain neuroimaging data. They can effectively utilize features at different scales of MRI and fully leverage feature information from different regions of the brain. In the end, experiments were conducted on the Cam-CAN dataset, resulting in a minimum Mean Absolute Error (MAE) of 7.46. The results demonstrate that this method provides a new approach to feature learning at different scales in brain age prediction tasks, contributing to the advancement of the field and holding significance for practical applications in the context of elderly education.
The Mediating Effects of Self-worth and Interpersonal Communication on the Relationship between Metacognitive Ability and Self-directed Learning Ability among Nursing Students: A Cross-Sectional Study
Authors: Yin xiumin , Pan Minghao , He Lang , Li Yuting , Zheng Wenkai , Liang Juan 
Published: January 2024

Abstract
Background: To explore the relationship between metacognitive ability and self-directed learning ability of nursing students, along with the mediating effect of self-worth and interpersonal communication between them.
Methods: A total of 905 nursing undergraduates from 6 universities in Shaanxi Province were selected as the survey objects by convenient sampling method, and 851（94.03%）were effectively responsed. Metacognitive Assessment Inventory, Adolescent Sense of Self-worth Scale, Supportive Communication Scale and Self-directed Learning Ability Scale were used to evaluate the metacognitive ability, self-worth, interpersonal communication ability and self-directed learning ability of nursing students.
Results: （1） The results indicated that the metacognitive ability, self-worth, and interpersonal communication ability were all positively correlated with the self-directed learning ability (all P<0 .001). （2）The mediating effects of self-worth and interpersonal communication on metacognitive ability and self-directed learning were significant (all P < 0.001). （3）Metacognitive ability could have an indirect effect on self-directed learning through the self-worth and interpersonal communication ability intermediary chain.
Conclusions: Improving the metacognitive level and self-worth of nursing students and cultivating good interpersonal communication ability are conducive to improving the self-directed learning ability of nursing students.
The newly sequenced gnome of non-sourdough-derived Kazachstania humilis MAW1 in terms of identification of factors inhibiting bacterial growth
Authors: Mielecki Damian , Detman Anna , Aleksandrzak-Piekarczyk Tamara , Chojnacka Aleksandra , Widomska Małgorzata , Walczak Paulina , Grzesiuk Elżbieta , Sikora Anna 
Published: January 2024

Abstract

Background
Ascomycetous budding yeasts are ubiquitous environmental microorganisms that are of great importance in food production and medicine. As a consequence of recent intensive genomic research, the taxonomy of yeast is becoming more organized based on the identification of monophyletic taxa, and this includes genera important to humans, such as Kazachstania. Until now, Kazachstania humilis (previously Candida humilis) was regarded as a sourdough-specific yeast. In addition, any antibacterial activity has not been associated with this species.
Results
Previously, we isolated a yeast strain that impaired bio-hydrogen production in a dark fermentation bioreactor and also inhibited growth of Gram-positive (Clostridium butyricum, lactic acid bacteria strains) and Gram-negative (Escherichia coli, Citrobacter freundii, Klebsiella oxytoca, Pseudomonas putida) bacteria. Here, using next generation sequencing technologies, we sequenced the genome of this strain named K. humilis MAW1. This is the first sequenced genome of a K. humilis isolate not originating from a fermented food. This strain was examined by global phenotypic profiling, including carbon sources utilized and the influence of different stress conditions on growth. Using well-recognized bacterial model Escherichia coli AB1157 we show that K. humilis MAW1 cultivated in acidic medium inhibits bacterial growth by the disturbance of cell division, manifested by filament formation. Interestingly, under neutral (pH 7.0) conditions, stimulation of E. coli AB1157 growth was observed. To gain a greater understanding of inhibitory effect of K. humilis MAW1, we selected 23 yeast proteins with recognized toxic activity against bacteria and used them for Blast searches of the K. humilis MAW1 genome assembly. The resulting panel of genes present in K. humilis MAW1 genome included those encoding the 1,3-β-glucan glycosidase and the 1,3-β-glucan synthesis inhibitor that might disturb the bacterial cell envelope structures.
Conclusions
We have characterized a non-sourdough-derived strain of K. humilis, including its genome sequence. The revealed here pH-dependent ability to inhibit bacterial growth has not been previously recognized in this species. Our study contributes to (i) the building of genome sequence-based classification and identification systems and (ii) the understanding of the bacteria-yeast interactions puzzle in the terms of food fermentation processes and search for novel antimicrobial factors.
Cryogenic Brain-inspired Hyperdimensional In-Memory Computing using 5nm Ferroelectric FinFET
Authors: Parihar Shivendra Singh , Kumar Shubham , Chatterjee Swetaki , Pahwa Girish , Chauhan Yogesh Singh , Amrouch Hussam 
Published: January 2024

Abstract

The pursuit of large-scale quantum computing has captivated the scientific community, and the potential of cryogenic circuits using mature CMOS technologies represents a significant step forward in this quest. Nevertheless, the operation of circuits at cryogenic temperatures poses significant challenges due to the strict power and timing constraints. These challenges are compounded by the well-known Von Neumann bottleneck that plays a major role in limiting the throughput and energy efficiency of modern computing systems. To overcome such a bottleneck, In-Memory Computing (IMC) is rapidly emerging as a promising solution for creating hardware accelerators that go far beyond Von Neumann principles, offering substantial efficiency improvements. In this work, we investigate the effectiveness of cryogenic brain-inspired hyperdimensional IMC using emerging Ferroelectric (FE) technologies at the 5 nm node. To achieve that, we begin by characterizing commercial 5 nm FinFETs from room temperature (300 K) down to cryogenic temperature (10 K). Then, we carefully calibrate the first industry-standard cryogenic-aware compact model (BSIM-CMG) to accurately reproduce the measurements. Afterward, we incorporate a physics-based FE model within the BSIM-CMG model and calibrated it against FE capacitor measurements to realize Fe-FinFET devices operating from 300 K down to 10 K. Then, as proof of concept, we focus on 1×8 Ternary Content Addressable Memory (TCAM) array that we use to perform the language classification using brain-inspired hyperdimensional IMC. Our comprehensive analysis spans from investigating the delay, power, and energy efficiency of IMC-based TCAM all the way up to calculating error probabilities in which we compare the figure of merits obtained from the emerging Fe-FinFET against classical FinFET-based IMC.
Evaluation of immunohistochemical markers CD44 and PAX8 in diagnosis of Focal Segmental Glomerulosclerosis suspected cases and its differentiation from Minimal Change disease in patients with nephrotic syndrome
Authors: Salarvand Samaneh , Nili Fatemeh , Dehkhoda Farshid , Abdollahi Alireza , Alemzadeh Azin , Abedi Maryam 
Published: January 2024

Abstract

Background
Expression evaluation of specific markers PAX8 and CD44 on kidney podocyte cells or their progenitor cells can be very helpful in diagnosing and differentiating between types of podocytopathies. In present study, the positivity of immunohistochemical markers CD44 and PAX8 in parietal epithelial cells (PECs) was evaluated to diagnose suspected cases of Focal Segmental Glomerulosclerosis (FSGS) and differentiate it from minimal change disease (MCD).
Methods
This cross-sectional study was conducted on patients who underwent kidney biopsy due to nephrotic syndrome. 42 FSGS samples and 36 MCD samples were selected and biopsies were evaluated for CD44 and PAX8 markers. Suitable blocks for immunohistochemical staining that had enough tissue were selected and evaluated.
Results
The expression frequency of PAX8 marker in group with FSGS was estimated as 97.6% and in group with MCD as 52.8%, which was significantly higher in FSGS group. Also, regarding the expression of CD44, in two groups with FSGS and MCD, respectively, 1 + cases equal to 26.2% and 94.4%, 2 + cases equal to 40.5% and 5.6%, and 3 + cases equal to 33.3% and 0.0%, which indicated the higher intensity of CD44 expression in FSGS group compared to MCD.
Conclusions
The expression of CD44 in FSGS was influenced by patients age and a direct and significant relationship was observed. The increase in amount and intensity of two markers PAX8 and CD44 expression in PEC cells in patients with FSGS shows high sensitivity of these markers in diagnosis of FSGS and the decrease in expression level in MCD can play an important role in differentiating between types of podocytopathy disorders.
Potential biodiversity and antifungal activities of Amazonian actinomycetes isolated from rhizosphere of Inga edulis plants
Authors: Rodrigues Rafael de S. , Souza Antonia Q. Lima , Barbosa Anderson N. , Santiago Sarah Raquel S. Silva , Vasconcelos Aldenora dos S. , Barbosa Roneres D. , Alves Thalita Caroline L. , Cruz Jeferson C. , Silva Gilvan F. da , Bentes Jania L. da Silva , de Souza Afonso D. Leão 
Published: January 2024

Abstract
Actinobacteria are major producers of antibacterial and antifungal metabolites and are targets of increasing research in the search for substances of biotechnological interest, especially for use in medicine and agriculture. The Amazon is potentially rich in actinobacteria, in turn poorly studied. Thus, we prospected actinobacteria from the rhizosphere of the South America native plant Inga edulis, which produces edible fruits and is economically useful in the whole Amazon region. Among all 64 strains of actinobacteria isolated, 20 strains representing 16 morphogroups were subjected to morphological analysis, genotyping using the 16S rRNA gene, and dual-culture assays against pathogenic fungi of important agricultural plants in the region that also cause annual losses of millions of dollars to world agriculture. Using GenBank-NCBI and EzBioCloud data, 90% of the strains were identified as Streptomycesand 10% as Kitasatospora, indicating at least 16 specific species and possibly new species. All strains showed antagonisms for two or more different phytopathogens as Corysnepora cassiicola, Colletotrichum sp., Colletotrichum guaranicola, Pestalotiopsis sp., and Sclerotium coffeicola. The strains Streptomyces spp. LaBMicrA B270 and B280 stood out mainly against phytopathogens of the guarana plant (Paullinia cupana), an important crop for the regional economy and one of the best sources of caffeine in the world, whose powder is used in the food industry and traditional medicine. Furthermore, the acetate/isopropanol extract from the 10-day LaBMicrA B280 cultured medium presents fungistatic or fungicidal for all phytopathogens tested with a minimum inhibitory concentration (MIC) of 125 μg/mL.
ACE Insertion/Deletion Gene Polymorphisms with DM Type II and Metabolic Syndrome among Sample of Jordanians
Authors: Azayzeh Waleed , Alfreahat Ala' , Khader Khaled Omar , Almasri Mohamad-Said , Mahmoud Leena M. , Alsarayreh Miqdad , Jankhout Seif , Alqaisi Rashed O. , Alzawahreh Shaima' , Salah Dania W. , Daradkeh Abdallah , Zaghloul Ashraf A. , Kareem Heba M. Abd El , Dwairi Rami , Mahgoub Samir S. 
Published: January 2024

Abstract

Objective
MetS has gained an incredible interest worldwide on account of its increasing predominance with a prevalence rate of 14–32%, its incidence is increased by age for both genders. The present study was aimed to explore the relationship of angiotensin converting enzyme (ACE) insertion/deletion gene polymorphisms and the potential risk of development of diabetes mellitus type II and metabolic syndrome among a sample of Jordanians.
Materials and Methods
this case-control study included 148 type II diabetics; 127 MetS patients; and 241 normal subjects as a control group. ACE insertion/deletion gene polymorphisms were analyzed using PCR. Lipid profile, fasting blood glucose, and ACE activity was determined chemically. Apolipoprotein-A1 and plasma insulin levels were estimated by ELISA; and glycosylated hemoglobin was estimated by the micro-chromatographic method. Semiquantitative test strips were used for detecting microalbuminuria in urine.
Results
Regarding the criteria of metabolic syndrome, ID polymorphism was associated significantly with hypertension showing a positive risk ratio, microalbuminuria with positive risk ratios was associated significantly with II polymorphism and I allele, while, a significant negative risk ratios were shown between hypertension, microalbuminuria and DD polymorphism.
Conclusion
There is evidence that ID, II ACE gene polymorphisms and I allele may play a major role in the pathogenesis of metabolic syndrome along with diabetes mellitus type II in Jordanian population.
Improved YOLOv7-Based Multi-Target Tracking and Detection under Maritime Surveillance Scenario
Authors: Zhu Jiaqi , Chang Hung-Teng , Zhang Tao 
Published: January 2024

Abstract
As a maritime power, it is of great practical significance to strengthen coastal maritime surveillance technology. However, constrained by low-quality images and excessive noise in the marine environment, higher demands are placed on accurate ship tracking and detection. The YOLOv7 series detectors have been widely used in object detection for its speed and accuracy, but they suffer from the problem of difficulty in recognizing complex backgrounds and long-distance objects, especially in environments such as the ocean. Thus, to address these challenges, we propose an enhanced YOLOv7 object detection model. Firstly, we incorporate two layers of attention mechanisms to improve the Maxpool module in the YOLOv7 network model, aiming to reduce the feature loss caused by the feature processing procedure. Secondly, due to the common issue of missed detections in the detection of small objects, we introduce the SPD-Conv module at the neck layer to enhance the network's sensitivity to small-scale objects while reducing the impact of noise. Finally, we employ the DeepSORT tracking algorithm to improve the robustness of the network and enable real-time detection. Experimental results show that our proposed algorithm has a more impressive performance. The index of mAP is improved by 7.8\% and 1.3\% on different datasets. The source code of the proposed algorithm and related datasets presented in this paper have indeed been publicly released for further research.
Improving Sensitivity of Noninvasive Blood Glucose Microwave Sensor Via Substrate Selection
Authors: Zakaria Ahmed A. , Allam Ahmed , Asano Tanemasa , Abdel-Rahman Adel B. 
Published: January 2024

Abstract
This research paper presents a comprehensive overview of noninvasive blood glucose detection techniques and examines the differences between substrates used in various sensing methods. The study focuses on comparing the sensitivity of sensors based on two different substrates, Roger 4360G2 and Roger 4003C, in the context of glucose sensing. The results show that the substrate with Roger 4360G2, characterized by a dielectric constant (epsilon) of 6.15, exhibits a 3dB higher sensitivity compared to Roger 4003C, which has a dielectric constant (epsilon) of 3.38. This significant difference highlights the importance of substrate selection in achieving enhanced accuracy and precision for glucose sensing applications. Furthermore, the research investigates the impact of blood glucose levels on sensor measurements and compares them to a 25\% glucose concentration. By analyzing longitudinal measurements of individuals over time, the study reveals consistent blood glucose levels. These findings contribute to advancing glucose sensing technologies and improving the monitoring of blood glucose levels in individuals.
Influence of Climate Change on Vector-borne disease (Malaria) in India
Authors: Peri Subrahmanya Hari Prasad 
Published: January 2024

Abstract
Vector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial. This study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria's Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. The projections covered the period from January 1, 2020, to December 31, 2029. The estimated EIR for the years 2020–2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each ear 0.3 to 2.5 EIR/person/day decline is observed with a strong decline in rainfall ranging from 5 to 17 mm and associated high temperatures ranging from 0.03–0.03℃. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk. The observed decline in malaria risk is a positive development, but it is essential to exercise caution, especially in areas with heavy rainfall. This research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.