bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance Analysis of IRS-Assist Dual-hop Wireless Communication System
Authors: Jana Moumita , Kumar Sanjay 
Published: August 2024

Abstract

The IRS-assist or smart radio environment technique is a widely developing technology that network providers can use to establish sustained connectivity between end-user terminals and central data units for the next-generation wireless standards. This article introduced a simple and more accurate link-switching technique for dual-hop communication: a single link-switching threshold (SLST) algorithm to provide an uninterrupted linkage between the transceiver terminals. Depending on the severity of the communicating channel under a dual-hop system, links can do auto switches between themselves and furnish continuous connectivity between end-user terminals. Due to a discrete number of phase shifts of the IRS elements, phase and quantization errors are induced in the channel; the proposed system can also optimize the phase and quantization errors. Besides, this work investigates improving the physical layer performance of the dual-hop wireless communication system under the combined effect of phase shift and quantization error with the introduction of the SLST method. For this particular, three performance metrics have been encountered: the outage probability (OP), average bit error rate (ABER), and average capacity (bits/sec/Hz). A new, more accurate mathematical framework using the Meijer’G function has been constructed to evaluate worthwhile analytical derivation. Under analytical calculation, we have assumed the primary link experienced with common Rayleigh fading and the IRS-assist link (IAL) experienced with Nakagami-m distribution due to a large number of reflecting elements in the system. The proposed dualhop system furnishes noteworthy benefits for each performance metric rather than individual links. Moreover, the suitable selection of quantization level and a number of reflecting elements confirm the exhibition of satisfactory outcomes and minimize the channel hardness of the system. Additionally, numerical simulation results from MATLAB, using Monte Carlo simulation, have been added to validate the analytical outcomes for every performance measure.
Research on recognition and localization method of maize weeding robot based on improved YOLOv5
Authors: Zhao Lijun , Jia Yunfan , Yin Wenke , Li Zihuan , Liu Chuandong , Luo Hang , Hu Xin , Huang Hua , Li Qiang , Lv Cheng , Li Bin 
Published: August 2024

Abstract

In response to the challenge posed by low recognition accuracy in rugged terrains with diverse topography as well as feature recognition agricultural settings. This paper presents an optimized version of the YOLOv5 algorithm alongside the development of a specialized laser weeding experimental platform designed for precise identification of corn seedlings and weeds. The enhanced YOLOv5 algorithm integrates the effective channel attention (CBAM) mechanism while incorporating the DeepSort tracking algorithm to reduce parameter count for seamless mobile deployment. Ablation test validate our model's achievement of 96.2% accuracy along with superior mAP values compared to standard YOLOv5 by margins of 3.1% and 0.7%, respectively. Additionally, three distinct datasets capturing varied scenarios were curated; their amalgamation resulted in an impressive recognition rate reaching up to 96.13%. Through comparative assessments against YOLOv8, our model demonstrates lightweight performance improvements including a notable enhancement of 2.1% in recognition rate coupled with a marginal increase of 0.2% in mAP value, thus ensuring heightened precisionand robustness during dynamic object detection within intricate backgrounds.
Integrating LoD-Based 3D Modeling of Locally Characterized Residential Buildings in Indian Cities: A Framework Utilizing Customized CityGML
Authors: Katwala Sweata , Vyas Anjana 
Published: August 2024

Abstract

This study investigates the application of 3D modelling to represent urban features in Indian cities, highlighting its potential in improving spatial understanding and data precision. With a focus on residential buildings, the research develops a robust framework for creating 3D models of varying levels of detail (LoDs) using CityGML as a standardized format. Utilizing tools such as ArcGIS Pro, Sketch Up, and FME, a LoD 3 model is successfully generated for a specific area, achieving a notable 91% accuracy upon validation. Practical applications are demonstrated through the evaluation of solar and rainwater harvesting potential within the modelled area, illustrating 3D models’ efficacy of in analysing real-world scenarios. This initial success suggests broader applications across entire cities d diverse building typologies, offering significant insights for urban planning and resource management in the Indian context.
Does Intellectual Humility Leadership Lead to a Win-Win? ---- The impact of leadership style on Thriving at Work and Work Performance of the New Generation Employees
Authors: Niu Aiwen , Gao Changchun 
Published: August 2024

Abstract

As the career maturity and self-awareness of new generation employees increase, they seek not only material rewards but also well-being and meaning in their work. Based on the SOR (Stimulus-Organism-Response) theory, this study takes intellectual humility leadership as the breakthrough point and positive work attitude as the mediating path to construct a model of antecedents for the thriving at work and work performance of new generation employees. To this end, this study adopts a questionnaire survey method to carry out empirical work. By collecting 518 valid questionnaires, an SEM model is established to examine the mechanisms and boundary conditions of the impact of intellectual humility leadership.The study finds that: Firstyly, Intellectual humility leadership can enhance the thriving at work and work performance of new generation employees by fostering a positive work attitude; Secondly, Employee core self-evaluation moderates the relationship between intellectual humility leadership and both positive work attitude and work performance. However, with respect to thriving at work, the moderating effect of employee core self-evaluation on intellectual humility leadership is not significant.This study provides empirical support for a deeper understanding of the impact mechanism of leadership on the thriving at work and work performance of new generation employees. It also offers practical management insights for building a positive, healthy, and efficient work culture, thereby enhancing the overall competitiveness of the organization.
A winter cold nights pattern in the Northern Hemisphere lands: Circum−hemisphere teleconnection of extreme cold events
Authors: Wang Ning , Li Jianping , Wang Hao , Li Hao , Wu Zixiang , Zhao Hongyuan 
Published: August 2024

Abstract

This study discovers a teleconnection of winter cold nights (TN10p) in the Northern Hemisphere lands, termed as the Circum–hemisphere teleconnection (CHT) of extreme cold events (CHTe). The CHTe exhibits five distinct centers of action situated in the Southeastern North America, Baffin Bay Coast, Northern Europe, Middle East–North Africa, and Eastern Siberia. Notably, it displays significant interannual (~3a) and decadal (~10a) variabilities. Besides, the differences between the CHTe and several known atmospheric and oceanic modes are also illustrated in terms of the occurrence year, physical nature, temporal variability, and spatial structure. Meanwhile, a new atmospheric teleconnection pattern in the troposphere, named as the CHT, corresponds to the atmospheric circulation associated with the CHTe. During the positive CHTe events, the positive CHT events occur, resulting in significant positive geopotential height anomalies (GHTa) over the Central North Atlantic, Western Europe and Songhua River as well as significant negative GHTa over Greenland and Caspian Sea, and vice versa. Compared with the horizontal advections, vertical convections and diabatic heating, the CHT may mainly influence the local TN10p anomalies by modulating atmospheric thickness anomalies over five regions of the CHTe.
Mechanisms of increasing multidrug resistance in Staphylococcus hominis isolated from clinical materials
Authors: Szemraj Magdalena , Glajzner Paulina , Olszowiec Kamila , Sienkiewicz Monika 
Published: August 2024

Abstract

The treatment of infections caused by Staphylococcus hominis remains a challenge, mainly due to the increasing resistance of these bacteria to antibiotics. The aim of the study was to determine antibiotic resistance in 62 strains S. hominis isolated from clinical materials, and to identify the molecular basis of resistance to antibiotics. Forty-six strains were both methicillin-resistant and harbored the mecA gene. Twenty-three of these strains had mec complex A and ccr complex AB1. Such a combination of the mec and ccr complexes does not correspond to any cassettes that have been demonstrated so far. However, over 80% of the tested strains were multidrug-resistant, of which as many as 12 were resistant to at least seven antibiotics. More than a half of strains harbored the tetK, acc(6’)-Ie aph(2”), and ant(4’)-I genes. erm(C) was the most common resistant gene to antibiotics from the MLS group. Two strains had as many as five antibiotic resistance genes from the tested groups (erm(C), msr(A), msr(B), mph(C), lnu(A)). The presence of the vga gene encoding resistance to streptogramins A was detected in one strain. All of strains were sensitive to vancomycin. However, 11 of them had reduced sensitivity to this antibiotic and eight of them were characterized by a heterogeneous resistance profile to this antibiotic. Our results clearly shows increasing threat of S. hominis caused by their multi-resistance. Moreover, these bacteria can constitute a reservoir of resistance genes for more pathogenic bacteria.
Yield estimation of pomegranate based on deep learning YOLO model
Authors: wang haiying , peng xi , huoyan zhou 
Published: August 2024

Abstract

Pomegranates from Mengzi City, Yunnan Province, are renowned for their nutritional value and flavor, boosting the local economy. Traditional yield prediction relies on manual sampling, which is costly and inefficient. This study proposes an intelligent prediction method using the YOLOv5 deep learning model.Mobile phones captured images of pomegranate trees from four directions to construct a dataset. These images were cropped and labeled for training the YOLOv5 model. The model achieved an 89% recognition accuracy and a 0.94 effectiveness score, accurately identifying and counting pomegranate fruits.Data visualization and model inference estimated the fruit quantity, with predicted values being 91.7% of the actual yield at a confidence level above 0.25. The average yield per tree was estimated at 103.1 kg, closely matching the actual 105.9 kg. This method offers robust data support for rapid and accurate yield estimation, outperforming traditional methods in efficiency and accuracy.
Multi-scale attention encoding-dynamic decoding network for short-term precipitation forecasting
Authors: Du Xianjun , Guo Hangfei 
Published: August 2024

Abstract

Short-term precipitation forecasting is a critical task in the fields of meteorology and hydrology. To overcome the limitations of traditional forecasting methods in handling complex meteorological phenomena and the issue of cumulative errors in image sequence prediction by recurrent neural networks, a short-term precipitation forecasting method called multi-scale attention encoding-dynamic decoding network (MAEDDN) has been developed. It predicts future precipitation by learning the spatiotemporal features of the input data. Within the encoding process, convolutional blocks with spatial and channel attention are utilized for encoding, and a multi-scale fusion module is employed to address the challenge of capturing both small-scale and large-scale information in precipitation distribution simultaneously. In the short-term precipitation processes to address the generation and dissipation. In the decoding process, a dynamic decoding network is proposed to flexibly select the decoding process based on the learned intensity distribution and change trends from the past input data Experiments are conducted by using the precipitation data from the open-source SEVIR dataset, and comparisons are made with the best methods reported so far. The experimental results reveal that: (1) MAEDDN enhances the forecasting capability in areas with high-intensity precipitation, and (2) MAEDDN outperforms other models in terms of the resolution of predicted image sequences. The constructed multi-scale attention encoding captures the complex relationships in meteorological data more effectively, while the dynamic decoding adapts the decoding process based on different scenarios, resulting in more accurate prediction outcomes.
Apoptotic body based biomimetic hybrid nanovesicles to attenuate cytokine storms for sepsis treatment
Authors: Lan Hongbing , Zhou Zhanhao , Hu Qian , Xie Qi , Li Xiaonan , Tian Tianyi , Wang Yi , Yang Conglian , Kong Li , Fu Dehao , Guo Yuanyuan , Zhang Zhiping 
Published: August 2024

Abstract

Sepsis is a severe immune response to pathogens that causes high mortality with limited treatment options. It is characterized by the hyperactivation of macrophages and cytokine storms. Given the anti-inflammatory properties of M2 macrophages derived apoptotic bodies (AB) and their specific uptake by macrophages, a novel approach is employed to combine AB with artificial liposomes to create apoptotic body based biomimetic hybrid nanovesicles (L-AB). The L-AB effectively inherit "eat me" signaling molecules on the surface of the AB, facilitating their targeted uptake by macrophages in both in vitro and in vivo settings. Utilizing this mechanism for the delivery of dexamethasone demonstrates efficient distribution of the drug to inflammatory tissues in septic mice, where it is selectively internalized by macrophages, thereby mitigating excessive macrophage activation and tissue damage, and ultimately increasing the survival rate of septic mice. Taken together, the apoptotic body biomimetic nanovesicles represent a potentially drug delivery system capable of specifically targeting macrophages for the treatment of sepsis.
Exploration of oxidative stress-related hub genes in idiopathic pulmonary fibrosis by integrating bioinformatics analysis
Authors: Huang Jizhen , Su Li , Wu Dandan , Yuan Mengqin 
Published: August 2024

Abstract

Idiopathic pulmonary fibrosis (IPF) characterized by a poor prognosis is a chronic and fatal interstitial lung disease. Oxidative stress has great impacts on the initiation and development of IPF. The aim of the present study was to determine oxidative stress-related hub genes for the diagnosis and intervention of IPF. The gene expression profile of IPF (GSE10667, GSE32537, GSE110147, and GSE213001 datasets) were collected from the GEO database. The differentially expressed oxidative stress-related genes (DEOSRGs) were screened on the basis of the common DEGs, oxidative stress related genes from GeneCard database and module genes from WGCNA. Four hub DEOSRGs (ENC1, EPHA3, FMO1, and GPX8) were further identified using the LASSO analysis and SVM-RFE algorithms, and validated by external datasets (GSE24206 and GSE53845). The ROC analysis revealed that the four hub DEOSRGs had diagnostic values with excellent specificity and sensitivity. The CIBERSORT analysis revealed that T cells CD4 memory activated, T cells regulatory (Tregs) and Dendritic cells resting might be related to the progress of IPF. In conclusion, the present study shows that ENC1, EPHA3, FMO1, and GPX8 may be considered as novel diagnostic biomarkers and therapeutic targets for IPF.
Estimation of groundwater recharge using different methods, supported by radon measurement and lineament density analysis: Southern sections of the western Afar rift margin and associated rift floor
Authors: Gidafie Dereje , Nedaw Dessie , Azagegn Tilahun , Abebe Bekele , BABA Alper 
Published: August 2024

Abstract

The aim of this study was to quantify the spatial and temporal groundwater recharge of the southern sections of the western Afar rift margin and the associated rift floor. Several methods were used, including water balance, WetSpass, Chloride mass balance (CMB) and baseflow separation, supported by radon measurements and lineament density analysis. The first three methods result in mean annual groundwater recharge rates of 114.39 mm/year, 100.88 mm/year and 92.37 mm/year, respectively. The base flow separation approach conducted at the rift margin, particularly at the outlets of the marginal grabens gives a higher recharge rate (136.7 mm/year) than the other methods, suggesting that additional groundwater may be flowing from the adjacent plateau, while the rift floor has a lower value (17.86 mm/year) due to various geological and structural features. The recharge value of the CMB approach is lower, indicating that the groundwater has a higher chloride concentration than from precipitation alone. The spatial distribution of groundwater recharge from the WetSpass model shows that the rift margin has higher groundwater recharge due to moderate to high annual precipitation. The geology consists of alluvial deposits of sand and gravel underlain by highly fractured basalt and ignimbrite as well as transverse structures with SW-NE, NW-SE and W-E orientations. The low annual rainfall and the lacustrine deposits, on the other hand, lead to low groundwater recharge in the rift floor. However, the presence of NE-SW and W-E trending transverse structures connecting the marginal grabens and the rift floor promotes groundwater flow from the former to the latter, resulting in moderate to high groundwater recharge at the rift floor. The results of this study highlight the need to use different groundwater recharge estimation techniques to understand and capture potential recharge mechanisms and obtain an acceptable estimate of recharge, especially in regions with arid to semi-arid climates and active tectonic areas such as the western rift margin and associated Afar rift floor.
A 13.06 Ma widespread ignimbrite in the Pannonian Basin captured a snapshot of abrupt paleogeographic changes in Central Paratethys
Authors: Karátson Dávid , Lahitte Pierre , Portnyagin Maxim , Palotai Márton , Józsa Sándor , Márton Emő , Tóth Emőke , Erdei Boglárka , Nomade Sebastien , Nemeth Karoly , Iván Levente , Krasznai Márton , Vörös Fanni , Biró Tamás , Paquette Jean-Louis , Hír János , Prakfalvi Péter , Kiss János , Pécskay Zoltán , Hencz Mátyás 
Published: August 2024

Abstract

Voluminous Miocene silicic volcanism sourced mainly from the extensional Pannonian Basin played a major role in the evolution of Central Paratethys. Here, we identify a widely distributed (> 3150 km 2 ) member of the Upper Rhyolite Tuff, called the Dobi Ignimbrite, with a precise sanidine/plagioclase 40Ar/39Ar age of 13.064 ± 0.065 Ma (~ Badenian/Sarmatian boundary in Central Paratethys chronology) and distinctive glass geochemistry. Its calculated minimum volume (~ 200 km3) implies a VEI ≥ 7 eruption. The ignimbrite was emplaced on land, as it contains leaves and tree trunks in the basal layer—that we correlate with the Badenian/Sarmatian ‘volcanic floras’ of Hungary—, while the strongly phreatomagmatic character and free-floating foraminifer content in the ignimbrite suggest a marine environment at the source vent. These finds show a rapid environmental change from a long Mid-Miocene terrestrial period in the northern Pannonian Basin to a late Badenian marine incursion.
Temperature Induces Brain-intake Shift of Recombinant High-density Lipoprotein after Traumatic Brain Injury
Authors: Huang Jialin , Peng Yidong , Wang Xin , Gu Xiaokun , Yi Yao , Wang Wenye , He Zhenghui , Ma Zixuan , Feng Qiyuan , Qi Wenlan , Hui Jiyuan , Gong Ru , Weng Weiji , Jiang Gan , Li Jin , Jiang Jiyao , Feng Junfeng 
Published: August 2024

Abstract

Traumatic brain injury (TBI) is one of the leading public health concerns in the world. Therapeutic hypothermia is routinely used in severe TBI, and pathophysiological hyperthermia, frequently observed in TBI patients, has an unclear impact on drug transport in the injured brain due to a lack of study on its effects. We investigated the effect of post-traumatic therapeutic hypothermia at 33oC and pathophysiological hyperthermia at 39oC on brain transport and cell uptake of neuroprotectants after TBI. Recombinant high-density lipoprotein (rHDL), which possesses anti-inflammatory, antioxidant activity, and blood-brain barrier (BBB) permeability, was chosen as the model drug. First, we found that mild hypothermia and hyperthermia impaired rHDL transport to the brain and lesion targeting in controlled cortical impact mice. Second, we investigated the temperature-induced rHDL uptake shift by various brain cell types. Mild hypothermia impeded the uptake of rHDL by endothelial cells, neurons, microglia, and astrocytes. Hyperthermia impeded the uptake of rHDL by endothelial cells and neurons while promoting its uptake by microglia and astrocytes. In an attempt to understand the mechanisms behind the above phenomena, it was found that temperature induced brain-intake shift of rHDL through the regulation of LDLR and LRP1 stability in brain cells. We therefore reported the full view of the temperature-induced brain-intake shift of rHDL after TBI for the first time. It would be of help in coordinating pharmacotherapy with temperature management in individualization and precision medicine.