bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prolonged elevated heart rate and 90-Day mortality in acute pancreatitis
Authors: Xie Shan , Deng Fuxing , Zhang Nuobei , Wen Zhili , Ge Chenglong 
Published: April 2024

AbstractProlonged elevated heart rate (peHR) is recognized as a risk factor for poor prognosis among critically ill patients. However, there is currently a lack of studies investigating the association between peHR and patients with acute pancreatitis. Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database was used to identify patients with acute pancreatitis. PeHR was defined as a heart rate exceeding 100 beats per minute for at least 11 out of 12 consecutive hours. Cox regression analysis was used to assess the association between peHR and the 90-Day mortality. A total of 364 patients (48.9%) experienced a peHR episode. The 90-day mortality was 25%. PeHR is an independent risk factor for 90-day mortality (HR, 1.98; 95% CI 1.53–2.56; P < 0.001). KM survival curves exhibited a significant decrease in the survival rate at 90 days among patients who experienced a peHR episode (P < 0.001, 84.5% vs. 65.1%). We revealed a significant association of peHR with decreased survival in a large cohort of ICU patients with acute pancreatitis.
Ultrafast and efficient continuous flow organic synthesis with a modified extruder-grinder system
Authors: Hosseinchi Qareaghaj Omid , Ghaffarzadeh Mohammad , Azizi Najmedin 
Published: April 2024

AbstractThe study introduces a groundbreaking continuous system that combines an extruder and grinder to enable catalyst-free and solvent-free reactions under mild conditions. This temperature-controlled system facilitates the synthesis of highly functionalized chromenes, which have valuable applications in generating combinatorial libraries and complex target molecules. The newly developed mill extruder machine offers several advantages for industrial production on a large scale. It effectively reduces waste, saves energy, and enhances time efficiency. This system represents a significant advancement in the field, providing a new strategy for one-pot synthesis of various types of highly functionalized spirooxindoles and chromenes. Remarkably, these reactions can be accomplished within a short timeframe of 2–10 min, yielding impressive results of 75–98%. The results demonstrate superior performance compared to traditional reaction methods, making it an appealing tool and hotspot area of research in green chemistry.
Early automated detection system for skin cancer diagnosis using artificial intelligent techniques
Authors: Mahmoud Nourelhoda M. , Soliman Ahmed M. 
Published: April 2024

AbstractRecently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin cancer detection are painful, time-consuming, expensive, and may cause the disease to spread out. Dermoscopy is used for noninvasive diagnosis of skin cancer. Artificial Intelligence (AI) plays a vital role in diseases’ diagnosis especially in biomedical engineering field. The automated detection systems based on AI reduce the complications in the traditional methods and can improve skin cancer’s diagnosis rate. In this paper, automated early detection system for skin cancer dermoscopic images using artificial intelligent is presented. Adaptive snake (AS) and region growing (RG) algorithms are used for automated segmentation and compared with each other. The results show that AS is accurate and efficient (accuracy = 96%) more than RG algorithm (accuracy = 90%). Artificial Neural networks (ANN) and support vector machine (SVM) algorithms are used for automated classification compared with each other. The proposed system with ANN algorithm shows high accuracy (94%), precision (96%), specificity (95.83%), sensitivity (recall) (92.30%), and F1-score (0.94). The proposed system is easy to use, time consuming, enables patients to make early detection for skin cancer and has high efficiency.
Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria
Authors: Duru Stellamaris Chinenye , Echiegu Emmanuel Amagu , Anyadike Chinenye C. , Alaneme George Uwadiegwu , Okechukwu Michael Emeka 
Published: April 2024

AbstractThe indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0–30 cm and 30–60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0–30 cm and 30–60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716–0.751 (Cu), 2.981–3.327 (Fe), 23.464–30.113 (Zn), 1.115–1.21 (Pb), 2.6–2.912 (As), and 0.133–0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611–0.618 (Cu), 2.233–2.516 (Fe), 12.841–15.736 (Zn), 0.887–0.903 (Pb), 1.669–1.911 (As), and 0.091–0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.
Dynamic analysis of a fuzzy Bobwhite quail population model under g-division law
Authors: Ouyang Miao , Zhang Qianhong , Cai Mingji , Zeng Zihao 
Published: April 2024

AbstractThis paper is concerned with a kind of Bobwhite quail population model$$\begin{aligned} x_{n+1}=A+Bx_n+\frac{x_n}{x_{n-1}x_{n-2}},\ \ n=0,1,\cdots , \end{aligned}$$xn+1=A+Bxn+xnxn-1xn-2,n=0,1,⋯,where the parameters and initial values are positive parabolic fuzzy numbers. According to g-division of fuzzy sets and based on the symmetrical parabolic fuzzy numbers, the conditional stability of this model is proved. Besides the existence, boundedness and persistence of its unique positive fuzzy solution. When some fuzzy stability conditions are satisfied, the model evolution exhibits oscillations with return to a fixed fuzzy equilibrium no matter what the initial value is. This phenomena provided a vivid counterexample to Allee effect in density-dependent populations of organisms. As a supplement, two numerical examples with data-table are interspersed to illustrate the effectiveness. Our findings have been verified precise with collected northern bobwhite data in Texas, and will help to form some efficient density estimates for wildlife populations of universal applications.
Mapping urban well-being with Quality Of Life Index (QOLI) at the fine-scale of grid data
Authors: Dobrowolska Ewa , Kopczewska Katarzyna 
Published: April 2024

AbstractAccessibility of transport infrastructure, commercial amenities, recreational facilities, and green spaces is widely recognised as crucial to the well-being of urban residents. However, these features are often unevenly distributed across the geographical boundaries of a city, leading to disparities in the local quality of life. This study focuses on the city of Warsaw, Poland, and uses the aforementioned characteristics and the framework of the '15-min city' concept to construct a grid-level urban Quality of Life Index (QOLI) that facilitates comparisons between the city’s districts and local neighbourhoods. The results of our study reveal a “high-inside, low-outside” pattern of quality of life, characterised by higher standards of living in the central districts and lower standards at the city's periphery.
A self-supervised framework for cross-modal search in histopathology archives using scale harmonization
Authors: Maleki Danial , Rahnamayan Shahryar , Tizhoosh H. R. 
Published: April 2024

AbstractThe exponential growth of data across various medical domains has generated a substantial demand for techniques to analyze multimodal big data. This demand is particularly pronounced in fields such as computational pathology due to the diverse nature of the tissue. Cross-modal retrieval aims to identify a common latent space where different modalities, such as image-text pairs, exhibit close alignment. The primary challenge, however, often lies in the representation of tissue features. While language models can be trained relatively easily, visual models frequently struggle due to the scarcity of labeled data. To address this issue, the innovative concept of harmonization has been introduced, extending the learning scheme distillation without supervision, known as DINO. The harmonization of scale refines the DINO paradigm through a novel patching approach, overcoming the complexities posed by gigapixel whole slide images in digital pathology. Experiments conducted on diverse datasets have demonstrated that the proposed approach significantly enhances cross-modal retrieval in tissue imaging. Moreover, it exhibits vast potential for other fields that rely on gigapixel imaging.
Broadband unidirectional twin-element MIMO antenna scheme for mid-band 5G and WLAN laptops
Authors: Luadang Bancha , Janpangngern Pisit , Pookkapund Khanet , Dentri Sitthichai , Krairiksh Monai , Phongcharoenpanich Chuwong 
Published: April 2024

AbstractThis research proposes a broadband unidirectional twin-element multiple-input-multiple-output (MIMO) antenna scheme for mid-band 5G and WLAN applications. The twin-element antenna scheme comprises two single-element antennas, and each single-element antenna consists of a T-shaped hemispherical feeding patch, left- and right-arm radiating patches, and a conjoined triangular ground plane. The twin-element MIMO antenna scheme is integrated with a laptop model functioning as the reflector. The measured impedance bandwidth (|S11|, |S22|≤ − 6 dB) are 55.32%, covering 3.4–6.0 GHz, and the measured mutual coupling (|S12|) is less than − 15 dB. The measured gain at the center frequency (4.5 GHz) is 4.585 dBi. Besides, the measured xz- and yz-plane cross-polarization levels are below − 25 dB and − 15 dB, respectively. The half-power beamwidth (HPBW) in the xz-plane at 3.5, 4.5, and 5.5 GHz are 99°, 92.8°, and 84.2°, and the corresponding HPBW in the yz-plane are 102°, 78°, and 102°. The measured xz- and yz-plane back lobe levels are below − 15 dB across the entire operating frequency band (3.5–5.5 GHz). The radiation pattern of the twin-element MIMO antenna scheme is of unidirectionality. Furthermore, the envelope correlation coefficient and diversity gain of the twin-element antenna scheme are < 0.001 and > 9.99 dB, respectively. The proposed broadband unidirectional twin-element MIMO antenna scheme is thus operationally suitable for mid-band 5G/WLAN communication systems. Essentially, this research is the first to propose a broadband twin-element MIMO antenna scheme for mid-band 5G/WLAN applications.
Study of the changes in the microstructures and properties of grease using ball milling to simulate a bearing shear zone on grease
Authors: Ren Jia , Cai Haopeng , Zhao Gaiqing , Xu Zhuang , Wang Xiaobo 
Published: April 2024

AbstractThe effects of shear degradation on the microstructures and properties of grease were investigated using a planetary ball mill to simulate a bearing shear zone on grease. The microstructure, cone penetration, colloidal stability, rheological properties noise properties, water washout characteristics and low-temperature torque of lithium grease were characterized. The microstructure of the initial lithium grease is a three-dimensional network structure formed by the uniform fibers. The entanglement level is high. As the ball milling shear time increases, the network structure of lithium grease is destroyed and the fibers are sheared to become short. Eventually all of them become short fibers. The performance test of lithium grease reveal that the cone penetration increases, colloidal stability, structural strength, noise properties, water washout characteristics of lithium grease gradually decreased with the increase of ball milling shear time. Additionally, the low-temperature starting torque and running torque of the grease gradually decrease. This phenomenon occurs due to changes in the microstructure of lithium grease. The shear degradation of lithium grease was mainly divided into two stages: the rapid stage was the destruction of the thickener network structure and the fibers being shortened by shearing. The slow stage was the process in which short fibers were sheared into shorter fibers.
Factors affecting the work ability of nursing personnel with post-COVID infection
Authors: Tangsathajaroenporn Warunee , Panumasvivat Jinjuta , Wangsan Kampanat , Muangkaew Supang , Kiratipaisarl Wuttipat 
Published: April 2024

AbstractPost-COVID infection have raised concerns regarding their impact on nursing personnel’s work ability. This study aimed to assess the relationship between post-COVID infection and work ability among nursing personnel. A retrospective observational study from December 2022 to January 2023 involved 609 nursing personnel with a history of COVID-19 infection at a tertiary hospital. An online questionnaire measured post-COVID infection, personal and working factors, and the Work Ability Index (WAI). Long COVID was defined as the continuation or development of new symptoms 1 month post COVID-19 infection. Of 609 personnel, 586 showed post-COVID symptoms (fatigue, cough, difficulty breathing, etc.), with 73.72% in the short COVID group and 26.28% in the long COVID group. A significant association was found between WAI and post-COVID infection (aOR: 3.64, 95% CI 1.59–8.30), with the short COVID group had a significantly higher WAI than the long COVID group (mean difference 2.25, 95% CI 1.44–3.05). The factors related to work ability in the long COVID group were chronic diseases, work limitation, low job control (P < 0.05). Post-COVID infection, especially long COVID, adversely affect nursing personnel's work ability. Enhancing job control and addressing work limitations are crucial for supporting their return to work.
Quantum error channels in high energetic photonic systems
Authors: Hiesmayr B. C. , Krzemień W. , Bała M. 
Published: April 2024

AbstractIn medical applications—such as positron emission tomography (PET)—511 keV photons that experience Compton scattering are studied. We present a consistent framework based on quantum error-correction channels—intensively studied in quantum computing—to fully describe the quantum information-theoretic content of high energetic photons undergoing Compton scattering, characterized by the Klein–Nishina formula in unoriented matter. In this way, we can predict the expected spatial distribution of two or more, pure or mixed, polarization entangled or separable photons. This framework allows us to characterize the accessible and inaccessible information for different parameter ranges. It also answers the question of how to describe successive multi-photon scattering. In addition our formalism provides a complete framework for dealing with single and all multi-partite errors that can occur in the propagation, providing the basis for modeling future dedicated experiments that will then have applications in medicine, such as reducing errors in PET imaging or exploring possibilities for quantum-based diagnostic indicators.
DRA-Net: Medical image segmentation based on adaptive feature extraction and region-level information fusion
Authors: Huang Zhongmiao , Wang Liejun , Xu Lianghui 
Published: April 2024

AbstractMedical image segmentation is a key task in computer aided diagnosis. In recent years, convolutional neural network (CNN) has made some achievements in medical image segmentation. However, the convolution operation can only extract features in a fixed size region at a time, which leads to the loss of some key features. The recently popular Transformer has global modeling capabilities, but it does not pay enough attention to local information and cannot accurately segment the edge details of the target area. Given these issues, we proposed dynamic regional attention network (DRA-Net). Different from the above methods, it first measures the similarity of features and concentrates attention on different dynamic regions. In this way, the network can adaptively select different modeling scopes for feature extraction, reducing information loss. Then, regional feature interaction is carried out to better learn local edge details. At the same time, we also design ordered shift multilayer perceptron (MLP) blocks to enhance communication within different regions, further enhancing the network’s ability to learn local edge details. After several experiments, the results indicate that our network produces more accurate segmentation performance compared to other CNN and Transformer based networks.
Phosphodiesterase type 5 inhibitors related hearing impairment: a real world study based on the FDA adverse event reporting system
Authors: Zhang Xunyan , Xia Lu , Yang Qiang , Tang Pingxiu 
Published: April 2024

AbstractRecent studies focused on exploring phosphodiesterase type 5 inhibitors (PDE5Is)-related hearing impairment. This study aimed to comprehensively explore real-world hearing impairment associated with PDE5Is based on the US Food and Drug Administration Adverse Event Reporting System (FAERS). The characteristics and correlation of PDE5Is-related hearing impairment reported in the FAERS database from the fourth quarter of 2003 to the second quarter of 2023 were analyzed using disproportionality analysis. The Standardized Medical Dictionary for Regulatory Activities (MedDRA) Queries (SMQs) were used to analyze the adverse events (AEs) of hearing impairment. A total of 1,438 reported cases of hearing impairment were associated with four PDE5Is, revealing statistically significant reporting odds ratio (ROR), proportional reporting ratio (PRR), and information component (IC) with the SMQ. The average age of all patients was more than 55 years, over 70% of AEs were reported in men. Most of the reported cases were from the United States. Reports for all the drugs indicated an increase since 2008, except for avanafil. This study showed that the disability rates of PDE5Is were 8.14–40%, the rates of initial or prolonged hospitalization were 6.21–10.24%, and the rates of required intervention were 3.31–9.45%. The pharmacovigilance study identified a potential risk of hearing impairment associated with PDE5Is, indicating the need for continuous monitoring and appropriate management.
Effect of salinity on scytonemin yield in endolithic cyanobacteria from the Atacama Desert
Authors: Casero María Cristina , Herrero María Ángeles , De la Roche Juan Pablo , Quesada Antonio , Velázquez David , Cirés Samuel 
Published: April 2024

AbstractCyanobacteria inhabiting extreme environments constitute a promising source for natural products with biotechnological applications. However, they have not been studied in-depth for this purpose due to the difficulties in their isolation and mass culturing. The Atacama Desert suffers one of the highest solar irradiances that limits the presence of life on its hyperarid core to endolithic microbial communities supported by cyanobacteria as primary producers. Some of these cyanobacteria are known to produce scytonemin, a UV-screening liposoluble pigment with varied biotechnological applications in cosmetics and other industries. In this work we carried out a strain selection based on growth performance among 8 endolithic cyanobacteria of the genera Chroococcidiopsis, Gloeocapsa and Gloeocapsopsis isolated from non-saline rocks of the Atacama Desert. Then we investigated the influence of NaCl exposure on scytonemin production yield. Results in the selected strain (Chroococcidiopsis sp. UAM571) showed that rising concentrations of NaCl lead to a growth decrease while triggering a remarkable increase in the scytonemin content, reaching maximum values at 20 g L−1 of NaCl over 50-fold higher scytonemin contents than those obtained without NaCl. Altogether, these findings point out to cyanobacteria from the Atacama Desert as potentially suitable candidates for pilot-scale cultivation with biotechnological purposes, particularly to obtain scytonemin.
Mitigating urban heat island and enhancing indoor thermal comfort using terrace garden
Authors: Visvanathan Girish , Patil Kailas , Suryawanshi Yogesh , Meshram Vishal , Jadhav Shrikant 
Published: April 2024

AbstractThe United Nations advocates for sustainable urban planning and design, emphasizing green infrastructure initiatives to mitigate urban heat island effects and enhance the resilience and livability of cities globally. To address urban heat challenges, a study was conducted in Chennai, India, from April to June 2023. The study focused on assessing temperature dynamics on a building's terrace by comparing a well-maintained garden area with an exposed region. Temperature and humidity sensors were deployed in both the garden and exposed areas of the terrace, as well as within rooms beneath it, to monitor hourly temperature fluctuations. The findings indicate a significant reduction in internal room temperatures in areas with rooftop gardens, ranging from 4 to 11 °C, depending on the time of year and sun's position, compared to rooms with fully exposed roof configurations. Additionally, simulation studies were performed to validate these findings, suggesting that optimizing the distribution of soil beds and plant density across the roof could yield an additional temperature reduction of 3–4 °C, resulting in an overall difference of up to 14–15 °C. The study highlights the efficacy of rooftop gardens in providing cooling effects during daylight hours and maintaining temperature parity post-sunset. Through analysis of sensor data, the research elucidates the intricate relationship between green infrastructure and thermal comfort, offering insights for energy-efficient building design and resilient urban planning. The findings underscore the potential of rooftop gardens in fostering a more comfortable, energy-efficient, and sustainable urban living environment.