bluuebunny/crossref_metadata_2025 huggingface dataset:
Precursory Signals to Injection Induced Fault Reactivation in the Laboratory Using Active Ultrasonic Monitoring Methods
Authors: Veltmeijer A. , Naderloo M. , Pluymakers A. , Barnhoorn A.
Published: February 2024

Induced earthquakes are still highly unpredictable, and often caused by variations in pore fluid pressure. Monitoring and understanding the mechanisms of fluid‐induced fault slip is essential for seismic risk mitigation and seismicity forecasting. Fluid‐induced slip experiments were performed on critically stressed faulted sandstone samples, and the evolution of the actively sent ultrasonic waves throughout the experiment was measured. Two different fault types were used: smooth saw‐cut fault samples at a 35° angle, and a rough fault created by in situ faulting of the samples. Variations in the seismic slip velocity and friction along the fault plane were identified by the coda of the ultrasonic waves. Additionally, ultrasonic amplitudes show precursory signals to laboratory fault reactivation. Our results show that small and local variations in stress before fault failure can be inferred using coda wave interferometry for time‐lapse monitoring, as coda waves are more sensitive to small perturbations in a medium than direct waves. Hence, these signals can be used as precursors to laboratory fault slip and to give insight into reactivation mechanisms. Our results show that time‐lapse monitoring of coda waves can be used to monitor local stress changes associated with fault reactivation in this laboratory setting of fluid‐induced fault reactivation. This is a critical first step toward a method for continuous monitoring of natural fault zones, contributing to seismic risk mitigation of induced and natural earthquakes.
CD97 inhibits osteoclast differentiation via Rap1a/ERK pathway under compression
Authors: Wang Wen , Wang Qian , Sun Shiying , Zhang Pengfei , Li Yuyu , Lin Weimin , Li Qiwen , Zhang Xiao , Ma Zhe , Lu Haiyan
Published: February 2024

Acceleration of tooth movement during orthodontic treatment is challenging, with osteoclast-mediated bone resorption on the compressive side being the rate-limiting step. Recent studies have demonstrated that mechanoreceptors on the surface of monocytes/macrophages, especially adhesion G protein-coupled receptors (aGPCRs), play important roles in force sensing. However, its role in the regulation of osteoclast differentiation remains unclear. Herein, through single-cell analysis, we revealed that CD97, a novel mechanosensitive aGPCR, was expressed in macrophages. Compression upregulated CD97 expression and inhibited osteoclast differentiation; while knockdown of CD97 partially rescued osteoclast differentiation. It suggests that CD97 may be an important mechanosensitive receptor during osteoclast differentiation. RNA sequencing analysis showed that the Rap1a/ERK signalling pathway mediates the effects of CD97 on osteoclast differentiation under compression. Consistently, we clarified that administration of the Rap1a inhibitor GGTI298 increased osteoclast activity, thereby accelerating tooth movement. In conclusion, our results indicate that CD97 suppresses osteoclast differentiation through the Rap1a/ERK signalling pathway under orthodontic compressive force.
All-optical image denoising using a diffractive visual processor
Authors: Işıl Çağatay , Gan Tianyi , Ardic Fazil Onuralp , Mentesoglu Koray , Digani Jagrit , Karaca Huseyin , Chen Hanlong , Li Jingxi , Mengu Deniz , Jarrahi Mona , Akşit Kaan , Ozcan Aydogan
Published: February 2024

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.
High-yield and rapid isolation of extracellular vesicles by flocculation via orbital acoustic trapping: FLOAT
Authors: Rufo Joseph , Zhang Peiran , Wang Zeyu , Gu Yuyang , Yang Kaichun , Rich Joseph , Chen Chuyi , Zhong Ruoyu , Jin Ke , He Ye , Xia Jianping , Li Ke , Wu Jiarong , Ouyang Yingshi , Sadovsky Yoel , Lee Luke P. , Huang Tony Jun
Published: February 2024

Extracellular vesicles (EVs) have been identified as promising biomarkers for the noninvasive diagnosis of various diseases. However, challenges in separating EVs from soluble proteins have resulted in variable EV recovery rates and low purities. Here, we report a high-yield ( > 90%) and rapid ( < 10 min) EV isolation method called FLocculation via Orbital Acoustic Trapping (FLOAT). The FLOAT approach utilizes an acoustofluidic droplet centrifuge to rotate and controllably heat liquid droplets. By adding a thermoresponsive polymer flocculant, nanoparticles as small as 20 nm can be rapidly and selectively concentrated at the center of the droplet. We demonstrate the ability of FLOAT to separate urinary EVs from the highly abundant Tamm-Horsfall protein, addressing a significant obstacle in the development of EV-based liquid biopsies. Due to its high-yield nature, FLOAT reduces biofluid starting volume requirements by a factor of 100 (from 20 mL to 200 µL), demonstrating its promising potential in point-of-care diagnostics.
Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications
Authors: Fan Xiwei , Sun Antonia Rujia , Young Reuben S. E. , Afara Isaac O. , Hamilton Brett R. , Ong Louis Jun Ye , Crawford Ross , Prasadam Indira
Published: February 2024

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study
Authors: Mellor Stephanie , Timms Ryan C. , O’Neill George C. , Tierney Tim M. , Spedden Meaghan E. ,   The MELD Project Consortium, Spitzer Hannah , Ripart Mathilde , Whitaker Kirstie , Napolitano Antonio , De Palma Luca , De Benedictis Alessandro , Foldes Stephen , Zhang Kai , Hu Wenhan , Mo Jiajie , Likeman Marcus , Davies Shirin , Güttler Christopher , Lenge Matteo , Cohen Nathan T. , Tang Yingying , Wang Shan , Chari Aswin , Tisdall Martin , Bargallo Nuria , Conde-Blanco Estefanía , Pariente Jose Carlos , Pascual-Diaz Saül , Delgado-Martínez Ignacio , Pérez-Enríquez Carmen , Lagorio Ilaria , Abela Eugenio , Mullatti Nandini , O’Muircheartaigh Jonathan , Vecchiato Katy , Liu Yawu , Caligiuri Maria Eugenia , Sinclair Ben , Vivash Lucy , Willard Anna , Kandasamy Jothy , McLellan Ailsa , Sokol Drahoslav , Semmelroch Mira , Kloster Ane G. , Ribeiro Letícia , Yasuda Clarissa , Rossi-Espagnet Camilla , Hamandi Khalid , Tietze Anna , Barba Carmen , Guerrini Renzo , Gaillard William Davis , You Xiaozhen , Wang Irene , González-Ortiz Sofía , Severino Mariasavina , Striano Pasquale , Tortora Domenico , Kälviäinen Reetta , Gambardella Antonio , Labate Angelo , Desmond Patricia , Lui Elaine , O’Brien Terence , Shetty Jay , Jackson Graeme , Duncan John S. , Winston Gavin P. , Pinborg Lars H. , Cendes Fernando , Cross J. Helen , Baldeweg Torsten , Adler Sophie , Brookes Matthew J. , Wagstyl Konrad , Barnes Gareth R.
Published: February 2024

When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant’s potential lesion sites provided the best compromise of robustness against modelling or measurement error.
DNA barcoding of Notopterygii Rhizoma et Radix (Qiang-huo) and identification of adulteration in its medicinal services
Authors: Liu Zhen-Wen , Zhou Jing
Published: February 2024

Safety concerns, stemming from the presence of complex and unpredictable adulterants, permeate the entire industrial chain of traditional Chinese medicines (TCMs). The Notopterygii Rhizoma et Radix (NReR) from the Apiaceae family, commonly known as “Qiang-huo”, is a widely used herbal medicine. The recent surge in its demand has given rise to a proliferation of counterfeit and substituted products in the market. Traditional identification presents inherent limitations, while DNA mini-barcoding, reliant on sequencing a short-standardized region, has received considerable attention as a new potential means to identify processed medicinal materials. In this study, we constructed a comprehensive Internal Transcribed Spacer 2 (ITS2) matrix encompassing genuine NReR and their commonly found adulterants for the first time. Leveraging this matrix, we conducted a thorough assessment of the genetic profiles and sources of NReR available in the Chinese herbal medicine market. Following established DNA barcoding protocols, the intra-specific genetic divergences within NReR species were found to be lower than the inter-specific genetic divergences from other species. Among the 120 samples that were successfully amplified, ITS2 exhibits an outstanding species-level identification efficiency of 100% when evaluated using both the BLASTN and neighbor-joining (NJ) tree methods. We concluded that ITS2 is a mini-barcode that has shown its potential and may become a universal mini-barcode for the quality control of “Qiang-huo”, thereby ensuring the safety of clinical medication.
A comprehensive study of Al-Cu-Mg system reinforced with nano-ZrO2 particles synthesized by powder metallurgy technique
Authors: Moustafa Essam B. , Aljabri Abdulrahman , Abushanab Waheed S. , Ghandourah E. , Taha Mohammed A. , Khoshaim Ahmed B. , Youness Rasha A. , Mohamed S. S.
Published: February 2024

More focus has recently been placed on enhancing the strength, elastic modulus, coefficient of thermal expansion (CTE), wear and corrosion resistance, and other qualities of aluminum (Al) alloys by varying the quantity of ceramics added for a range of industrial uses. In this regard, Al-4.2-Cu-1.6Mg matrix nanocomposites reinforced with nano-ZrO2 particles have been created using the powder metallurgy approach. The microstructure and particle size distributions of the produced powders were analyzed using a diffraction particle size analyzer, XRD, TEM, and SEM. To achieve good sinterability, the powders were compacted and sintered in argon. The sintered nanocomposites' mechanical, elastic, and physicochemical characteristics were measured. Additionally, the behavior of corrosion, wear, and thermal expansion were examined. The results showed a decrease in the particle sizes of the Al-Cu-Mg alloy by adding ZrO2 nanoparticles up to 45.8 nm for the composite containing 16 wt.% ZrO2. By increasing the sintering temperature to 570 °C, the densification of nanocomposites was enhanced. Also, the coefficient of thermal expansion and wear rate remarkably decreased by about 28 and 37.5% by adding 16 wt.% ZrO2. Moreover, microhardness yield, strength, and Young’s modulus were enhanced to 161, 145, and 64%, respectively, after adding 16 wt.% ZrO2. In addition, increasing the exposure time was responsible for decreasing the corrosion rate for the same sample.
Ultra-low volume intradermal administration of radiation-attenuated sporozoites with the glycolipid adjuvant 7DW8-5 completely protects mice against malaria
Authors: Watson Felicia N. , Shears Melanie J. , Kalata Anya C. , Duncombe Caroline J. , Seilie A. Mariko , Chavtur Chris , Conrad Ethan , Cruz Talavera Irene , Raappana Andrew , Sather D. Noah , Chakravarty Sumana , Sim B. Kim Lee , Hoffman Stephen L. , Tsuji Moriya , Murphy Sean C.
Published: February 2024

Radiation-attenuated sporozoite (RAS) vaccines can completely prevent blood stage Plasmodium infection by inducing liver-resident memory CD8+ T cells to target parasites in the liver. Such T cells can be induced by ‘Prime-and-trap’ vaccination, which here combines DNA priming against the P. yoelii circumsporozoite protein (CSP) with a subsequent intravenous (IV) dose of liver-homing RAS to “trap” the activated and expanding T cells in the liver. Prime-and-trap confers durable protection in mice, and efforts are underway to translate this vaccine strategy to the clinic. However, it is unclear whether the RAS trapping dose must be strictly administered by the IV route. Here we show that intradermal (ID) RAS administration can be as effective as IV administration if RAS are co-administrated with the glycolipid adjuvant 7DW8-5 in an ultra-low inoculation volume. In mice, the co-administration of RAS and 7DW8-5 in ultra-low ID volumes (2.5 µL) was completely protective and dose sparing compared to standard volumes (10–50 µL) and induced protective levels of CSP-specific CD8+ T cells in the liver. Our finding that adjuvants and ultra-low volumes are required for ID RAS efficacy may explain why prior reports about higher volumes of unadjuvanted ID RAS proved less effective than IV RAS. The ID route may offer significant translational advantages over the IV route and could improve sporozoite vaccine development.
A new HaCV-EBHSV recombinant lagovirus circulating in European brown hares (Lepus europaeus) from Catalonia, Spain
Authors: Almeida Tereza , Lopes Ana M. , Estruch Josep , Rouco Carlos , Cavadini Patrizia , Neimanis Aleksija , Gavier-Widén Dolores , Le Gall-Reculé Ghislaine , Velarde Roser , Abrantes Joana
Published: February 2024

In 2020/2021, several European brown hare syndrome virus (EBHSV) outbreaks were recorded in European hares (Lepus europaeus) from Catalonia, Spain. Recombination analysis combined with phylogenetic reconstruction and estimation of genetic distances of the complete coding sequences revealed that 5 strains were recombinants. The recombination breakpoint is located within the non-structural protein 2C-like RNA helicase (nucleotide position ~ 1889). For the genomic fragment upstream of the breakpoint, a non-pathogenic EBHSV-related strain (hare calicivirus, HaCV; GII.2) was the most closely related sequence; for the rest of the genome, the most similar strains were the European brown hare syndrome virus (EBHSV) strains recovered from the same 2020/2021 outbreaks, suggesting a recent origin. While the functional impact of the atypical recombination breakpoint remains undetermined, the novel recombinant strain was detected in different European brown hare populations from Catalonia, located 20–100 km apart, and seems to have caused a fatal disease both in juvenile and adult animals, confirming its viability and ability to spread and establish infection. This is the first report of a recombination event involving HaCV and EBHSV and, despite the recombination with a non-pathogenic strain, it appears to be associated with mortality in European brown hares, which warrants close monitoring.
Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes
Authors: Zou Daoyang , Xu Tianwen
Published: February 2024

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.
Multi-modality trajectory prediction with the dynamic spatial interaction among vehicles under connected vehicle environment
Authors: Jin Lisheng , Liu Xingchen , Wang Yinlin , Han Zhuotong , Guo Baicang , Luo Guofeng , Xu Xinliang
Published: February 2024

Compared to non-connected vehicle environments, the connected vehicle environment establishes vehicle interconnection through communication technologies, resulting in more complex interaction, network topologies, and large-scale inputs. This complexity renders traditional trajectory prediction models, which rely primarily on inputting historical information of the target vehicle, inadequate for handling the complex and dynamic interactive lane-changing scenarios in connected vehicle environments. In a connected vehicle environment, it is necessary to propose a more targeted and stable lane-changing behavior prediction method based on vehicle traveling characteristics. Taking into account dynamic spatial interaction among vehicles, this study proposes a multi-modality trajectory prediction model called STA-LSTM to perform analysis on the potential interactive behaviors among vehicles under connected vehicle lane-changing scenarios, and specifically to expand the multi-modality feature input of the vehicle trajectory prediction model. The spatial grid occupancy method is used to model the interactions between vehicles. A space-dimensional attention mechanism is introduced to adaptively match the influencing weights of the surrounding vehicles with the target vehicle and to improve the interactive information extraction method. In addition, the attention module is incorporated into the LSTM decoder from the time dimension so that the established model can identify significant historical hidden features during each trajectory decoding process. To account for the uncertainty of trajectory prediction, the vectors of vehicle interactions are incorporated into contextual information to improve the reliability of prediction results and the robustness of the established model. Compared with conventional baseline models, the proposed model exhibited lower root mean square error (RMSE) and negative log-likelihood (NLL) values, and the RMSE values at different prediction times of 1s, 2s, 3s, 4s, and 5s are 0.46m, 1.15m, 1.89m, 2.84m, and 4.05m, respectively. This indicates that the proposed model can accurately predict the interactions between vehicles and the travel paths of surrounding target vehicles.
The detrimental effects of heavy metals on tributaries exert pressure on water quality, Crossocheilus aplocheilus, and the well-being of human health
Authors: Subhanullah Muhammad , Hassan Nazim , Ali Sajid , Saleh Ibrahim A. , Ilyas Muhammad , Rawan Bakht , Ullah Waheed , Iqbal Babar , Okla Mohammad K. , Alaraidh Ibrahim A. , Fahad Shah
Published: February 2024

The escalating presence of heavy metals (HMs) in the Panjkora River water and their impact on fish pose a significant challenge to both the ecological community and human health. Consequently, a study was conducted with the primary aim of elucidating their influence on human health-related issues. To address this, the concentrations of heavy metals, including arsenic (As), cadmium (Cd), iron (Fe), manganese (Mn), lead (Pb), and zinc (Zn), in both water and the fish species Crossocheilus diplocheilus were investigated across various locations within the study area. The quantification of HMs concentration was carried out utilizing an atomic absorption spectrophotometer. The highest concentration in water was found as 0.060 mg/L for Pb and lowest for Fe, whereas the highest concentration in fish was 2.028 mg/kg for Pb and lowest for As. Human health risk associated with fish eating was evaluated by using health risk indices (HRI) for non-carcinogenic health risks and targeted cancer risk (TR) for carcinogenic health risks. The values of the health risk index (HRI) were found greater than 1 except Fe (0.0792), Zn (0.782), and Mn (0.541). The highest mean HRI > 1 was recorded for As (62.99), Cd (26.85), and Pb (10.56). This implies that fish consumption from river Panjkora is not safe up to some extent. Similarly, the TR value for As, Cd, and Pb was found 2.8 $$\times {10}^{-2}$$

×

10

-
2

, 1.6 $$\times {10}^{-2}$$

×

10

-
2

, 2.8 ×$${10}^{-3}$$

10

-
3

which showed cancer risk. There is a detected risk to human health associated with the consumption of fish from the Panjkora River. The government must implement adaptive measures to address this significant issue of water pollution in the study area. Additionally, there is a need for further extensive and prolonged research studies in this context.
Rheophytic Osmunda lancea (Osmundaceae) exhibits large flexibility in the petiole
Authors: Shiba Masayuki , Fukuda Tatsuya
Published: February 2024

The riparian zone, found alongside rivers and streams, is a unique habitat characterized by its vulnerability to sudden floods following intense rainfall. To cope with these challenging conditions, a specific group of plants with linear and lanceolate lamina have adapted to thrive in these environments. Despite their unique ability to withstand the forceful water flow, the specific adaptive characteristics of the petioles, which support the lamina remain unknown. Our morphological, anatomical, and mechanical analyses on the petioles of Osmunda lancea (Osmundaceae) along the river and an inland sister species of O. japonica revealed that the petioles of O. lancea had a larger cell volume in subepidermal cortex and were more flexible than those of O. japonica.
Prevalence and associated factors of worry for cancer in patients with a Barrett’s esophagus
Authors: van der Ende-van Loon M. C. M. , Oude Nijhuis R. A. B. , Curvers W. L. , Schoon E. J.
Published: February 2024

Although the risk of cancer progression in a Barrett’s esophagus (BE) is very low, worrying about cancer is known as an important factor affecting HRQoL. The aim of this study was to determine the proportion of BE patients with high levels of worry for cancer, to compare outcomes of patients endoscopically treated for BE neoplasia (DBE), non-dysplastic BE patients (NDBE) and patients with reflux symptoms, and to examine associated factors. We performed a cross sectional, exploratory, self-administered questionnaire study using the cancer worry scale, and the reflux disease questionnaire. A total of 192 DBE patients, 213 NDBE patients and 111 refractory reflux symptom patients were included from October 2019 until July 2021, 76.8% of BE participants were male and aged 66.9 years. High cancer worry was reported in 40.6% of the DBE patients and 36.2% of NDBE patient. Reflux patients scored statistically significant worse with 56.6% stated high cancer worry. Positive correlations were found between reflux symptoms and cancer worry in NDBE patients and reflux patients. In DBE patients’ negative correlations were found between higher cancer worry and younger age as well as a family history of esophageal carcinoma. A clinically significant group of BE patients reported high cancer worry, which was associated with reflux symptoms in NDBE patients and a younger age and a (family) history of esophageal carcinoma diagnosis in BE patients treated for (early) neoplasia. Physicians should communicate about the actual cancer risk, which leads to greater patient understanding and therefore may have a positive impact on health outcomes.
Impact of frailty severity and severe pain on cognitive function for community-dwelling older adults with arthritis: a cross-sectional study in Korea
Authors: Baek Wonhee , Suh Yujin , Ji Yoonjung
Published: February 2024

Pain is a major symptom of arthritis in older adults, often leading to frailty and cognitive decline. However, few studies have investigated the relationship among pain, frailty, and cognitive function in older adults with arthritis. This study aimed to investigate the factors influencing cognitive function and the impact of frailty severity and pain on cognitive function in older adults with arthritis using a Korean population-based dataset. This cross-sectional descriptive study involved the secondary data of 1089 participants from the seventh and eighth waves of the Korean Longitudinal Study on Aging. We examined general characteristics, health behaviors, health conditions (including severe pain and frailty), and cognitive function. Participants were categorized based on the presence or absence of pain severity and frailty status as follows: robust, only severe pain, only prefrail, prefrail with severe pain, only frail, and frail with severe pain. Multiple linear regression analysis was performed to establish correlations between groups and cognitive function. The only-prefrail group was the largest (19.7%) among participants experiencing either pain or frailty. Advanced age, sex, level of education, and visual and hearing impairments were significantly associated with cognitive function. Compared to the robust group, only prefrail (β = -1.54, confidence interval [CI] = − 2.33; − 0.76), prefrail with severe pain (β = − 2.69, CI = − 3.52; − 1.87), only frail (β = − 4.02, CI = − 5.08; − 2.97), and frail with severe pain (β = − 5.03, CI = − 5.99; − 4.08) groups were associated with lower Mini-Mental State Examination scores. The study confirmed that severe pain alone does not significantly impact cognitive function in older adults with arthritis. To prevent cognitive decline in this group, assessment of both pain and frailty severity is essential to predict high-risk groups and provide appropriate interventions, such as transfer to hospitals or primary clinics according to the severity of pain and frailty.
Bilateral passive thermal management for dynamical temperature regulation
Authors: Li Bingyao , Zeng Sicheng
Published: February 2024

Space heating and cooling of buildings account for $$\sim $$
∼
 30% of energy consumed globally. As a result, efforts to reduce the carbon footprint associated with building temperature regulation are crucial to achieving sustainability goals. Passive radiative cooling and sun heating are two promising innovations that can help reduce the energy consumption associated with building temperature regulation. However, these methods are constrained by factors such as climate zones and seasonal changes. In this work, we demonstrate numerically that bilateral photonic metamaterials enabled by vanadium dioxide (VO2) nanoparticles embedded into polyethylene nanogratings can achieve dynamically modulate solar absorptance at one side in winter and achieve radiative cooling on another side. In cold weather, the solar absorptance of this metastructure can change from 0.93 to 0.2 at a critical temperature when VO2 changes from a metallic to an insulating state. This metastructure consists of broadband transparent polyethylene (PE) gratings on the reflective silver (Ag) gratings with the same period and filling ratio. These gratings are deposited on top of the Polydimethylsiloxane (PDMS) thin film. The VO2 nanoparticles enable dynamic solar absorptance modulation for winter space heating, while the PDMS with strong infrared emittance derived from molecular vibrations over the atmospheric window for summer radiative cooling. Temperature response simulations validate that this bilateral design achieves   6 °C subambient temperature drop at noontime in the summer and stabilizes its temperature around 22 °C during the daytime in the winter. This passive dynamical thermal regulation technique can be deployed for energy-saving targets of buildings, vehicles, and greenhouses in areas with large temperature fluctuations.
Inadequate dietary diversity practices and associated factors among pregnant adolescents in the West Arsi Zone, Central Ethiopia: a community-based cross-sectional study
Authors: Tesfaye Adane , Gerbaba Mulusew , Tamiru Dessalegn , Belachew Tefera
Published: February 2024

The aftermath of dietary modifications made during pregnancy has the most substantial effects on nutritional status and birth results, despite the important influence of nutritional reserves. Numerous studies have been conducted on dietary practices and their determinants among pregnant women; however, there is a gap in evidence among pregnant adolescents. Therefore, this study sought to close this gap by examining dietary practices and associated factors among pregnant adolescents in the West Arsi Zone, Central Ethiopia. This community-based cross-sectional study was conducted among 459 pregnant adolescents between February and March 2023. Cluster sampling was used for selecting pregnant adolescents. Structured questionnaires were used for data collection. The data were entered into the Kobo toolbox and exported to SPSS version 25 software for analysis. Dietary diversity was assessed using the 24-h dietary recall method. Binary and multivariable logistic regression analyses were used to identify independent predictors of dietary practices. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to identify the factors associated with the outcome variables. A p value ≤ 0.05 indicated statistical significance. The prevalence of inadequate dietary practices among the pregnant adolescents was 78.4% (95% CI 74.3%, 82.8%), and a level of nutritional knowledge [AOR = 2.4, 95% CI (1.82–4.74]; an unfavorable attitude toward dietary diversity [AOR = 4.3, 95% CI 2.9–5.83]; a food insecurity status [AOR = 8.7, 95% CI 2.37–10.24]; and a low perceived severity of poor dietary practices [AOR = 4.7, 95% CI 3.26–5.47]. These factors were significantly associated with inadequate dietary practices among pregnant adolescents. The most frequently consumed foods were starchy foods (81.3%) and pulses (79%), and the least consumed foods were meat (2.8%) and fruits (3.48%). The magnitude of inadequate dietary practices was high, and it was significantly associated with educational, behavioral, and economic status. Nutritional interventions focused on communicating nutritional behavioral changes and strengthening sustainable income-generating strategies are recommended to improve the dietary practices of pregnant adolescents.
Surgical treatment of distal radius fractures: impact on forearm rotation in non-elderly patients
Authors: Kong Lingde , Li Chenfei , Bai Jiangbo , Lu Jian
Published: February 2024

Forearm rotation restriction (FRR) is common after surgery for distal radius fractures (DRFs). The aim of the current study was to investigate the effect of DRFs on forearm rotation. This retrospective study reviewed patients with DRFs who underwent surgical treatment from January 2019 to December 2021. The patients' basic data and radiographic parameters were analyzed. Forearm rotation, including pronation and supination, was assessed using a standard goniometer. The Patient-Rated Wrist Evaluation (PRWE) score was evaluated, and the incidence of FRR at the 6-month follow-up was recorded. Univariate and multivariate logistic regression analyses were performed to identify risk factors correlated with FRR. A total of 127 patients with DRFs were included in this study. After surgery, 46 cases were considered to have FRR, with a rate of 36.2%, while the remaining 81 cases (63.8%) did not have FRR. The PRWE scores were 22.8 ± 5.2 and 17.9 ± 4.2 in the FRR group and non-FRR group, respectively, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that the involvement of the sigmoid notch (OR, 2.88; 95% CI 1.49–5.56), post-operative volar tilt < 0° (OR, 2.16; 95% CI 1.34–3.50), and post-operative ulnar variance > 0 mm (OR, 1.37; 95% CI 1.06–1.78) were independently associated with the incidence of FRR. The FRR is associated with an increased PRWE score and may have had some impact on the patient's daily life. Fractures involving the sigmoid notch, dorsal angulation, and radial shortening deformity were found to be correlated with the incidence of FRR. Preoperative risk notification and intraoperative preventive measures are necessary for these patients.
A hybrid bio-inspired sandwich structures for high strain rate energy absorption applications
Authors: Ghanbari Jaafar , Panirani Pezhman N.
Published: February 2024

Due to its advantages in terms of enhancing the performance of structures in the desired applications, the bio-inspired design approach has recently attracted the interest of researchers in a number of engineering disciplines. A hybrid bio-inspired design is suggested for the sandwich structures to absorb the energy of the blast loads in the current study. The sandwich structure's core, which often has a regular grid pattern resembling a honeycomb structure, is crucial to how well the panel absorbs energy. In order to achieve the best results, we first chose the structure of the core grid by taking into account potential 2D grids (polygons and multi-pointed stars) through Genetic Algorithm optimization. Next, we combined a bio-inspired bi-tubular thin-walled structure with the core grid to take advantage of its high energy absorption capacity. Finally, the performance of the suggested design is compared with four frequently implemented ones. The results show that the hybrid design has better energy absorption characteristics compared with the bionic and conventional designs presented in the literature.
Red pepper drying with a double pass solar air heater integrated with aluminium cans
Authors: Admass Zigale , Salau Ayodeji Olalekan , Mhari Bimrew , Tefera Ewnetu
Published: February 2024

In this paper, an experimental evaluation of a newly developed flat plate double pass solar air heater combined with aluminum cans for drying red pepper was presented. The proposed solar dryer system was designed, modeled, and evaluated. Solar air heater trials were carried out using the absorber’s top and bottom plate and aluminum cans for red pepper drying at Bahir Dar, Ethiopia. To test the solar dryer, 100 pieces of red paper were obtained from the Bahir Dar region of Ethiopia for the purpose of experimentation. Microsoft Excel was used to perform statistical analysis of eleven mathematical models. The results show that the mixed-mode solar greenhouse dryer takes less time to dry red pepper than the open solar dryer. In the midday, the solar insolation reached 973 W/m2and the minimum solar insolation was 220 W/m2 and air is expelled at a rate of 0.0383 kg/s. According to the experimental results, the dryers chamber temperature ranged from 30.9 to 54 °C, while the ambient temperature was between 22.6 and 28.2 °C. The mixed-mode double pass achieves up to 46% and 28% efficiency when used with aluminum can dryers and conventional open sun dryers, respectively. A drying rate of 0.0003395 kg/s was achieved for the open sun dryer system and 0.0000365 kg/s for the mixed mode solar dryer. Using mixed-mode and open-sun solar dryers, the logarithmic model was found to be most effective in explaining the red pepper behavior. Furthermore, a comparison was made between the experimental and predicted moisture ratios through the calculation of the coefficient of determination (R2), the reduced chi-square (X2), and the root mean square error (RMSE). The results show that the logarithmic model achieved the highest value of the correlation coefficient (R2), which was determined to be 0.9978 and 0.9989, while the logarithmic model achieved the lowest value of Chi-square (X2).
Multi‐hop anonymous payment channel network based on onion routing
Authors: Wang Caimei , Ren Yudong , Wu Zhize
Published: February 2024

Payment channel networks (PCNs) are one of the most promising off‐chain solutions to the blockchain scalability problem. However, most current payment channel schemes suffer from overly ideal routing assumptions or fail to provide complete path privacy protection. To address the above problems, the multi‐hop anonymous and privacy‐preserving PCN scheme are analyzed and a multi‐hop anonymous PCN based on onion routing is proposed based on it. The scheme removes the routing assumptions of the original scheme, designs an onion routing‐based payment channel network, and modifies the way relay nodes construct elliptic curve discrete logarithmic problems to resist wormhole attacks. Finally, the security analysis shows that the scheme in this paper has atomicity, relational anonymity and resistance to wormhole attacks. The latest bilinear pairing anonymous multi‐hop payment (EAMHL+) scheme is used to compare communication and computing overhead. The results show that the scheme in this paper requires less communication overhead and is more efficient in terms of computational overhead when the average hop number of the payment channel network is 3 hops and the network diameter is 6 hops.
A hybrid U‐shaped and transformer network for change detection in high‐resolution remote sensing images
Authors: Wu Huapeng , Yuan Mengxue , Zhan Tianming
Published: February 2024

Deep convolutional neural networks based remote sensing change detection has recently shown significant performance improvement. However, small region changes and global‐local features in high‐resolution remote sensing images are not fully explored. This paper introduces a hybrid U‐shaped and transformer network for change detection in high‐resolution remote sensing images. Specifically, a UNet++‐based backbone to facilitate feature learning across different scales. In addition, we introduce a transformer‐based feature fusion module for extracting long‐range dependencies, which can enhance the representation ability of the network. Furthermore, the introduced efficient channel attention mechanism can efficiently calibrate the feature representation and concentrate on more important feature information. Thanks to the above designs, the proposed method enjoys a strong ability to extract local and global features for remote sensing change detection. Extensive experimental results on different remote sensing images show that our method can achieve superior performance in comparison with state‐of‐the‐art change detection methods.
Evaluation method for insulation degradation of power transformer windings based on incomplete internet of things sensing data
Authors: Qu Yuehan , Zhao Hongshan , Zhao Shice , Ma Libo , Mi Zengqiang
Published: February 2024

This paper proposes a novel evaluation method to address the challenge of evaluating insulation degradation in power transformer windings based on incomplete online Internet of Things (IoT) sensing data. The method leverages the Wasserstein Slim Generative Adversarial Imputation Network with Gradient Penalty algorithm to fill the irregularly missing power transformer IoT perception data, including voltage, current, temperature, and partial discharge. Subsequently, electrical, thermal, and mechanical performance degradation damage indicators for transformer winding insulation are constructed using the filled and complete IoT perception data. By applying the tensor fusion algorithm, the characteristics of these degradation damage indicators are fused, leading to the development of a comprehensive degradation evaluation index for the winding insulation. The evaluation of the winding insulation degradation state is achieved through the minimum quantization error method. The proposed method is validated using the real‐world transformer IoT perception data, and the experimental results demonstrate its ability to accurately assess the degree of winding insulation degradation, regardless of the presence of random or continuous irregularities in IoT sensing data.
Particle method and quantization-based schemes for the simulation of the McKean-Vlasov equation
Authors: Liu Yating
Published: February 2024

In this paper, we study three numerical schemes for the McKean-Vlasov equation {dXt=b(t,Xt,μt)dt+σ(t,Xt,μt)dBt,∀t∈[0,T],μt is the probability distribution of Xt, where X0 : (Ω, F, ℙ) → (ℝd, B(ℝd)) is a known random variable. Under the assumption on the Lipschitz continuity of the coefficients b and σ, our first result proves the convergence rate of the particle method with respect to the Wasserstein distance, which extends previous work [M. Bossy and D. Talay, Math. Comput. 66 (1997) 157–192.] established in a one-dimensional setting. In the second part, we present and analyse two quantization-based schemes, including the recursive quantization scheme (deterministic scheme) in the Vlasov setting, and the hybrid particle-quantization scheme (random scheme inspired by the K-means clustering). Two simulations are presented at the end of this paper: Burgers equation introduced in [M. Bossy and D. Talay, Math. Comput. 66 (1997) 157–192.] and the network of FitzHugh- Nagumo neurons (see [J. Baladron, D. Fasoli, O. Faugeras and J. Touboul, J. Math. Neurosci. 2 (2012) 1–50.] and [M. Bossy, O. Faugeras and D. Talay, J. Math. Neurosci. 5 (2015) 1–23.]) in dimension 3.
Robust object detection for autonomous driving based on semi-supervised learning
Authors: Chen Wenwen , Yan Jun , Huang Weiquan , Ge Wancheng , Liu Huaping , Yin Huilin
Published: February 2024

Deep learning based on labeled data has brought massive success in computer vision, speech recognition, and natural language processing. Nevertheless, labeled data is just a drop in the ocean compared with unlabeled data. How can people utilize the unlabeled data effectively? Research has focused on unsupervised and semi-supervised learning to solve such a problem. Some theoretical and empirical studies have proved that unlabeled data can help boost the generalization ability and robustness under adversarial attacks. However, current theoretical research on the relationship between robustness and unlabeled data limits its scope to toy datasets. Meanwhile, the visual models in autonomous driving need a significant improvement in robustness to guarantee security and safety. This paper proposes a semi-supervised learning framework for object detection in autonomous vehicles, improving the robustness with unlabeled data. Firstly, we build a baseline with the transfer learning of an unsupervised contrastive learning method—Momentum Contrast (MoCo). Secondly, we propose a semi-supervised co-training method to label the unlabeled data for retraining, which improves generalization on the autonomous driving dataset. Thirdly, we apply the unsupervised Bounding Box data augmentation (BBAug) method based on a search algorithm, which uses reinforcement learning to improve the robustness of object detection for autonomous driving. We present an empirical study on the KITTI dataset with diverse adversarial attack methods. Our proposed method realizes the state-of-the-art generalization and robustness under white-box attacks (DPatch and Contextual Patch) and black-box attacks (Gaussian noise, Rain, Fog, and so on). Our proposed method and empirical study show that using more unlabeled data benefits the robustness of perception systems in autonomous driving.