bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent tendencies of extreme heat events in Italy
Authors: Settanta Giulio , Fraschetti Piero , Lena Francesca , Perconti Walter , Piervitali Emanuela 
Published: March 2024

Abstract
Over the last 20 years, several record-breaking events linked to high temperatures have enhanced the attention over extreme heat phenomena, especially during summer. Both 2022 and 2023 have been exceptional years in this regard. Heat waves, in particular, are a major natural hazard for the most fragile groups of the population. In order to address the points of impact, adaptation and future predictions, a quantitative analysis of all their specific aspects is necessary. These include the monitoring of their changes over time.
This study consists of a comprehensive analysis at national level of several temperature-extremes indices over Italy, including those specifically related to heat waves. The dataset is based upon a set of high quality daily maximum and minimum temperature records, from more than 250 ground-based weather stations. The time frame considered ranges from 1991 to 2020, providing information about the present Italian climate.
Two analysis are reported. One is targeted to find local features and is based on single stations data. The second one looks for a global signal related to heat extremes. The double level of the information (local and global) can be very useful in the comparison of results. The two methods are in agreement in describing an increasing presence of heat extremes, in terms of overall frequency, duration and intensity. Some areas appear as hot spots for the observed tendencies.
Surface Plasmon Resonance Biosensor with High Sensitivity for Detecting SARS-CoV-2
Authors: Bhatt Shiven , Bose Naina , Shushama Kamrun Nahar , Inum Reefat , Hasan K. B. M Rakib 
Published: March 2024

Abstract

This paper presents a novel surface plasmon resonance (SPR) biosensor based on Kretchmann configuration for detection of SARS-CoV-2. It combines Barium titanate (BaTiO 3 ) dielectric material on top of metal, also 2D material Tungsten Disulfide (WS 2 ) used alongside the traditional prism/metal/sensing layer setup. Sensitivity is enhanced by using BaTiO 3 on silver (Ag) and WS2 on BaTiO3. The integration of these emerging materials into conventional sensor structures has been thoroughly examined to optimize sensor performance. An analysis of key performance parameters has been conducted using the transfer matrix method (TMM) and Fresnel equations, including sensitivity, full width at half-maxima (FWHM), and figure of merit (FOM). The proposed sensor demonstrates an exceptional angular sensitivity of 450°/RIU, with a 3.5° FWHM and a 128.57/RIU FoM. Optimal sensitivity is achieved with a configuration comprising 1 layer of WS2 in addition to the metal layer. Our proposed SPR sensor shows more sensitivity for detecting SARS-CoV-2 than other proposed SPR sensors in literature. We also analyzed the electric field of the proposed biosensor with Finite Element Method based software and showed its future research aspect. SARS-CoV-2 has been successfully detected in patient samples due to the sensor's increased sensitivity at early stage of this disease.
Advanced Tobacco Foreign Object Detection via Optimized Network Architecture and Enhanced Multi-Scale Feature Integration
Authors: LI Yaqian , GUO GUO , LI Haibin , TENG Da , WANG Guancheng 
Published: March 2024

Abstract
The presence of impurities in finished tobacco leaves significantly affects the stability of cigarette quality during the packaging process.To solve the key technical problems that after the cutting process, these impurities become small in size and are similar in shape to the tobacco leaves, making accurate detection difficult. This paper proposes a method for detecting foreign objects in tobacco leaves based on an efficient network structure and multi-scale feature fusion.On one hand, the YOLOv5 (You Only Look Once version 5) network model is modified to extract features in a way that is more conducive to detecting small targets, while reducing the output heads to ensure the lightweight nature of the network. On the other hand, the backbone network and Neck structure are optimized to enable the detection network to obtain richer feature information while maintaining lightweight characteristics. Experimental results demonstrate that the algorithm proposed in this paper not only meets the real-time and lightweight requirements for industrial deployment but also improves accuracy and reduces false positive rates.
Human ovarian tissue xenotransplantation in 3D-printed tissue trapper basket integrated with human umbilical cord mesenchymal stem cells
Authors: Ayoubipour Mohammad , Eimani Hussein , Fathi Rouhollah , Verdi Abdolhussien shah , Zarrabi Morteza , Ashtiani Mohammad Kazemi , Tavana Somayeh , Moosavi Seyed Akbar , Tahaie Leila Sadat , Ayagh Zienab Ghezel , Halvai Majid , Nouri Masoumeh , Gerdkohi Parviz Gholmahammdi 
Published: March 2024

Abstract
Purpose
The primary objective was to develop an artificial ovary, using a 3D printed scaffold made of polylactic acid (PLA) material which could potentially be used for fertility preservation. In ovarian tissue (OT) transplantation, it was essential to prioritize follicle viability by promoting ideal angiogenesis at the back of neck muscle rats to improve the chances of successful follicle development.
Methods
The study involved transplanting human frozen-thawed ovarian cortical pieces into 3D-printed PLA polymer baskets, with or without human umbilical cord mesenchymal stem cells (HUC-MSCs). Four groups were formed: control, ovarian transplantation), OT in 3D-printed baskets without stem cells (OT + D), and OT in 3D-printed baskets with HUC-MSCs (OT + D + C). Eighteen rats were divided into three transplantation groups, and grafts were implanted into their back muscles. After one week, comparisons were made between OT, OT + D, and OT + D + C with control groups. Histological and gene expression analyses, including CX37, CX43, KL, GDF9, and VEGF, were conducted to evaluate factors like angiogenesis, cell proliferation, and follicle development.
Results
The result showed that OT + D had the highest follicular growth (99.5%) and transition rate (74.95%). OT + D + C showed increased follicular survival, reduced mortality (p < 0.0001), and a higher percentage of primordial follicles (59.1%). UCMSCs' paracrine secretions likely preserved the follicular reserve. Additionally, OT + D + C exhibited significantly increased blood vessel number and diameter (p < 0.0001) compared to other groups.
Conclusions
The study conducted a comprehensive evaluation, analyzing factors such as graft recovery, follicular density, stromal integrity, angiogenesis, and gene expression to understand transplantation outcomes fully. It found that a 3D basket scaffold facilitates ovarian follicle development by promoting angiogenesis and aiding maturation. Furthermore, when combined with stem cells, the scaffold enhances follicular preservation, preventing cell death and maintaining viability through paracrine secretions.
SIW based high performance bandpass filter loaded with Hilbert cells
Authors: Chaib Mohammed el amine , CHERIF Nabil , Boubakar Hichem , Abri Mehadji , Badaoui Hadjira 
Published: March 2024

Abstract
Resume
In this article, we proposed a band pass filter; the proposed filter is mainly based on a half mode substrate integrated waveguide (HMSIW). The proposed filter operates in S band with a measured transmitted bandwidth of 1.1 GHz. The proposed structure has dimensions, of 48.5 mm × 16 mm with a measured insertion loss of -1.2 dB. The upper stopband rejection range from 4 GHz to 8 GHz with an attenuation below -15 dB. The filter operates in a transmission bandwidth of [2.9 GHz - 4 GHz] with a fractional bandwidth (FBW) of 27.5 %. A good agreement is reported between the measured and simulated results.
Use of US BIRADS for the Differentiation of Male Breast Masses and Interobserver Agreement Assessment
Authors: Wang Di , Dang Meizheng , Wang Jing , huang pintong 
Published: March 2024

Abstract
Purpose
To investigate the efficiency of Breast Imaging Reporting and Data System (BIRADS) proposed by the American College of Radiology for male breast lesions and to evaluate assess inter-observer agreement.
Methods
Six breast radiologists were divided into three groups to retrospectively analyze 90 male breast nodules by BIRADS classifications. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated for comparative analysis. Interobserver agreement was assessed.
Results
The group II showed the higher specificity (75.9%) than other two groups while the group III showed the best AUC, sensitivity and accuracy, which were 0.904, 97.2%, 62.9% and 76.7%, respectively. Besides, the whole of three groups expressed excellent ICC on 2(0.934) category and good on BIRADS 3 (0.677) category. The ICC of 4a (0.379) was expressed as poor level. The categories of 4b (0.483) ,4c (0.521) and5(0.491) was expressed as fair level. Only group I had significant difference with the group III in diagnostic effectiveness of the same systems among three groups.
Conclusions
Male sex did not have a large impact on the diagnosis of BIRADS and use of US BIRADS lexicon shows excellent or good levels of concordance for mass characterizations. But a lower concordance respect to BIRADS classifications in BIRADS 4 categories.
Minocycline attenuates the development of neuropathic pain after spinal cord injury by inhibiting the Notch signaling pathway in the dorsolateral prefrontal cortex in mice
Authors: Li Chengcai , Huang Shaoxin , Zhou Wu , Xie Zhiping , Xie Shenke , Li Meihua 
Published: March 2024

Abstract
Previous studies on spinal cord injury (SCI) have mainly focused on the injury site, but the central nervous system (CNS) is a unified whole. SCI can lead to cerebral cortex atrophy, neuronal apoptosis in the brain, an inflammatory response and other pathophysiological changes, which may be important factors affecting the functional recovery and prognosis of patients. A large number of studies have confirmed that after SCI, there are significant changes in microglia and Notch signaling pathways at the injury site, but there have been fewer studies on the changes in the brain. In this study, we observed changes in microglia and the Notch signaling pathway in the dorsolateral prefrontal cortex (dlPFC) in a mouse model of SCI, and the effect of minocycline on these changes was also observed. The results showed that minocycline inhibited the activity of microglia and theNotch signaling pathway. The combination of minocycline and DAPT further inhibited the activity of microglia and Notch signaling pathway, and alleviated neuropathic pain, as indicated by anincrease in the paw withdrawal threshold (PWT) and prolongation of the paw withdrawal latency (PWL). Our results suggested that there are significant changes in the brain after SCI and that these changes in the dlPFC may be related to the occurrence and development of neuropathic pain.
Cardiopulmonary Exercise Testing in children and adolescents with repaired Tetralogy of Fallot
Authors: Danton Mark , Hadjisoteriou Anna , Noonan Patrick , Young David , Burns Paul 
Published: March 2024

Abstract
Introduction: By comparison with adults, cardiopulmonary exercise testing in children with Tetralogy of Fallot is limited, and its clinical application less validated. This study aimed to provide a comprehensive CPET profile in a child-adolescent population with repaired TOF, to explore cardiovascular mechanisms underpinning exercise intolerance and determine associations between CPET indices and clinical outcome.Methods Seventy-four CPETs were completed in 58 child and adolescents with repaired TOF (age 13.8 ± 2.4 years). CPET parameters were corrected for age, sex and body size using Blanchard formulae. At follow-up (4.9 years, IQR 3.5–7.9) clinical status and re-intervention was evaluated and CPET indices predicting these outcomes determined.Results Cohort VO2peak was within low-normal limits (% pred: 74.1% ± 15.4 ) with 15 patients (26%) displaying moderately-severe reduction (VO2peak < 65% pred). Oxygen uptake efficiency slope highly correlated with VO2peak (r = 0.94, p < 0.001) and was insensitive to exercise intensity. No significant change in CPET occurred in patients who underwent interval testing at 24 ± 14.5 months, although there was a variable response in VO2peak between individuals. Chronotropic response and heart rate-VO2 slope (indicator of stroke volume) predicted oxygen consumption: VO2peak (p < 0.001, R2 = 65.78%) and workload (p < 0.001, R2 = 52.32%). Adverse clinical status was associated with reduced workload (OR 0.97, p = 0.011). VE/VCO2 slope was steeper in those that died (39.2 SD 16.7 vs. 31.45 SD 5.06, p = 0.025). Twenty-four patients (43.8%) underwent RVOT intervention post-CPET which was associated with increased HR-VO2 slope (OR 1.042, p = 0.004).Conclusions In children and adolescents with repaired TOF important reduction in cardiopulmonary functioning were apparent in 25% of patients. Exercise intolerance was related to reduced chronotropic response and deficient stroke volume increment.
Characterisation of distance based topological descriptors for certain butterfly networks
Authors: Varghese Eddith Sarah , Xavier D Antony , Baby Annmaria 
Published: March 2024

Abstract
Interconnection networks are networks that portray structure of a system using vertices and edges. In order to determine the architecture of networks, topological indices are used in the study of QSPR/ QSAR. Topological indices are numerical quantities derived from chemical structures to predict the biochemical activities and physical, chemical and biological properties of compounds. In this article, we determine the analytical expressions for Szeged index, edge Szeged index, edge-vertex Szeged index and Padmakar Ivan index of Butterfly network and Augumented butterfly network.
Simulation and Evaluation of Collapsible Risk of Low Impact Development Rainwater System in Collapsible Loess Area
Authors: Jing Jing , Hou Jingming , Pan Zhan peng , Wang Tian , Li Xin yi , Chen Guang zhao , Sun Xue liang , Duan Chang hui 
Published: March 2024

Abstract

To assess the risk levels of collapse for various low-impact development (LID) measures used in constructing stormwater systems in collapsible loess areas, the high-efficiency and high-precision urban stormwater model (GAST) was used to analyze the risk of waterlogging. Combined with the time of waterlogging accumulation, a method is proposed to assess the collapse risk level of various LID measures by considering the correlation between the collapsibility coefficient and soil parameters. This method was then used to analyze the changing patterns of settlement risk levels in grassed swales and rain gardens under different rainfall return periods (P1=20a, P2=50a, P3=100a) and water accumulation durations (T1=0.5 day, T2=5 day). The findings indicate a direct correlation between the rainfall return periods and the level of risk for collapse. At P3=100a, 50% of the collapse risk level in the study region reaches level III. Nevertheless, when the water accumulation duration is 5 days, the percentage of places classified as category III increases to 75%. Although rain gardens are better than grass swales at storing water, they also increase the risk of collapse. Therefore, it is essential to carefully monitor the durability of rain gardens during long periods of frequent rainfall. The evaluation approach proposed in this research demonstrates a 75% accuracy rate, confirming it as an initial and reliable instrument for evaluating the risk associated with building low-impact development stormwater systems in collapsible loess areas. Moreover, it can be employed to conduct additional investigations of the collapsibility impacts of LID measures in places with collapsible loess.
Factors Affecting the Success of Intravesical Onabotulinum Toxin a Injection in the Treatment of Idiopathic Overactive Bladder
Authors: Degirmentepe Recep Burak , Culha Mehmet Gokhan , Karakanli Musab Umeyir , Sabuncu Kenan , Polat Emre Can , Baran Caner , Otunctemur Alper 
Published: March 2024

Abstract
Purpose: Onabotulinum toxin A injection is an option recommended by the guidelines in the treatment of overactive bladder (OAB) that is resistant to medical treatments. Although success does not occur in every patient, the factors affecting success are not clearly known. The aim of this study is to evaluate the factors affecting the success of onabotulinum toxin A injection in the treatment of idiopathic OAB.
Methods: Data of patients diagnosed with resistant idiopathic OAB and administered 100IU onabotulinum toxin A (BOTOX®, Allergan, Dublin, Ireland) between January 2019 and August 2023 were included in the study. Demographic data of the patients and duration of symptoms were recorded. The patients were followed up before the procedure and 1 month after the procedure using the overactive bladder symptom score (OABSS) inquiry form and 3-day bladder diaries. Patients who improved by 50% or more compared to the pre-procedure were considered satisfied with the treatment. Botox injection was applied to 20 points (5 IU per application) with a 22 Fr rigid cystoscope under sedoanesthesia in each patient.
Results: A total of 210 patients were included in the study. 80.5% of patients were women (169/210). The average age of the patients was 53.76±14.90 (19-87). Symptom duration was 39.82±22.28 (6-120) months. A total of 175 patients were diagnosed with wet type OAB (83.3%) and 35 patients were diagnosed with dry type OAB (16.7%). The mean OABSS score of the patients before the procedure was 9.18±1.31 (6-13), the mean daily micturition was 8.67±1.52 (6-15), the mean urge urinary incontinence (UI) attack was 2.57±1.28, the average of nocturia was 1.87±0.75 (0-4), and the average number of pads per day was 2.44±1.24 (0-5). The success rate after onabotulinum toxin injection was 82.4% (173/210).
Conclusion: The most important factors affecting the success of botulinum toxin A injection in the treatment of idiopathic OAB are affected by the high degree of complaint of the patient. Especially patients with high frequency of daily micturition complaints may not benefit from Botox treatment and may need advanced treatments.
GWAS determined genetic loci associated with callus induction in oil palm tissue culture
Authors: Htwe Yin Min , Shi Peng , Zhang Dapeng , Li Zhiying , Yu Qun , Wang Yong 
Published: March 2024

Abstract

Efficient callus induction is vital for successful oil palm tissue culture, yet identifying genomic loci and markers for early detection of genotypes with high potential of callus induction remains unclear. In this study, immature male inflorescences from 198 oil palm accessions (dura, tenera and pisifera) were used as explants for tissue culture. Callus induction rates were collected at one-, two- and three-months after inoculation (C1, C2 and C3) as phenotypes. Resequencing generated 11,475,258 high quality single nucleotide polymorphisms (SNPs) as genotypes. GWAS was then performed and correlation analysis revealed a positive association of C1 with both C2 (R=0.81) and C3 (R=0.50), indicating that C1 could be used as the major phenotype for callus induction rate. Therefore, only significant SNPs in C1 (including samples with and without callus) were identified to develop markers for screeningindividuals with high potential of callus induction. Among 21 significant SNPs (P ≤ 0.05) in C1, LD block analysis revealed 6 SNPs on chromosome 12 (Chr12) potentially linked to callus formation. Subsequently, 13 SNP markers were identified from these loci and electrophoresis results showed that marker C-12 at locus Chr12_12704856 can be used effectively to distinguish the GG allele, which showed the highest probability (69%) of callus induction. Furthermore, a rapid SNP variant detection method without electrophoresis was established via qPCR-based melting curve analysis. Our findings facilitated marker-assisted selection for specific palms with high potential of callus induction using immature male inflorescence as explant, aiding ortet palm selection in oil palm tissue culture.
Opinion-Tree-aware Prompt Tuning for Aspect Sentiment Quadruple Prediction
Authors: Yang Zhenyu , Li Zhijun , Liu Guojing , Zhang Zhibo , Li Xiaoyang 
Published: March 2024

Abstract

In recent years, Aspect Sentiment Quadruple Prediction (ASQP) has emerged as a prominent task in the field of aspect-based sentiment analysis. We observe complex dependencies among aspect sentiment elements, rendering traditional sequence-to-sequence (Seq2Seq) modeling for element extraction insufficiently rigorous. Additionally, despite the widespread application of Pre-trained Language Models (PLMs) in Aspect-Based Sentiment Analysis (ABSA), there is a significant gap when representing dependencies between sentiment elements, which involve complex structure-informed label classification, diverging from PLM's Masked Language Model (MLM) pre-training tasks. This gap limits the full potential of PLMs. To bridge this gap and better adapt to the structural information between sentiment elements, we propose a Opinion-Tree-aware Prompt Tuning (OTPT) method. This approach transforms traditional PLM Seq2Seq tasks into sequence-to-tree tasks, optimizing PLM potential. Specifically, we model sentiment elements as a tree structure, creating a dynamic virtual template and label words, integrating tree structure information as soft prompts, and conducting stepwise sentiment label classification. Extensive experiments show that our method achieves performance superior to baseline on two widely used datasets, demonstrating good robustness in handling cases of missing sentiment elements and complex multi-sentiment quadruples.
A Graph-Based Fusion Model Propagating Multimodal Information for Recommendation
Authors: Cormac Thaddeus , Fontaine Eamon , Roy Kunal Bhatia , Parker Sybilla 
Published: March 2024

Abstract
Multimedia data is inherently multimodal, encompassing information across various modalities like text, image, and audio. Each of these modalities represents a distinct method or perspective, forming a rich tapestry of data. In contrast to the structured data found in conventional databases, multimedia data presents distinctive features such as high dimensionality, content richness, and substantial storage requirements. Existing multimodal recommendation systems struggle to achieve rational results. The contributions of our paper are as follows. The traditional approach to representing multimodal knowledge graphs focuses solely on training embedding vectors through triples, neglecting the crucial process of fusing information from displayed multimodalities. This paper tackles this issue by ingeniously transforming the multimodal information fusion process in knowledge graphs into a graph-based information propagation process, introducing a novel model. Multimodal labeling, building on unimodal labeling, is introduced to characterize the multimodal semantic information within the video. Additionally, a multicore learning architecture is employed to amalgamate the semantics of multiple modalities, enabling the mapping of underlying multimodal features to a unified intermediate semantic space. This facilitates learning a similarity metric function between videos based on the intermediate semantic space. Extensive experiments are conducted on real datasets in this paper. The results demonstrate that our model surpasses current mainstream collaborative filtering-based recommendation algorithms, knowledge graph-based recommendation algorithms, and multimodal learning-based recommendation algorithms.