bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effective lane detection on complex roads with convolutional attention mechanism in autonomous vehicles
Authors: Maddiralla Vinay , Subramanian Sumathy 
Published: August 2024

AbstractAutonomous Vehicles (AV’s) have achieved more popularity in vehicular technology in recent years. For the development of secure and safe driving, these AV’s help to reduce the uncertainties such as crashes, heavy traffic, pedestrian behaviours, random objects, lane detection, different types of roads and their surrounding environments. In AV’s, Lane Detection is one of the most important aspects which helps in lane holding guidance and lane departure warning. From Literature, it is observed that existing deep learning models perform better on well maintained roads and in favourable weather conditions. However, performance in extreme weather conditions and curvy roads need focus. The proposed work focuses on presenting an accurate lane detection approach on poor roads, particularly those with curves, broken lanes, or no lane markings and extreme weather conditions. Lane Detection with Convolutional Attention Mechanism (LD-CAM) model is proposed to achieve this outcome. The proposed method comprises an encoder, an enhanced convolution block attention module (E-CBAM), and a decoder. The encoder unit extracts the input image features, while the E-CBAM focuses on quality of feature maps in input images extracted from the encoder, and the decoder provides output without loss of any information in the original image. The work is carried out using the distinct data from three datasets called Tusimple for different weather condition images, Curve Lanes for different curve lanes images and Cracks and Potholes for damaged road images. The proposed model trained using these datasets showcased an improved performance attaining an Accuracy of 97.90%, Precision of 98.92%, F1-Score of 97.90%, IoU of 98.50% and Dice Co-efficient as 98.80% on both structured and defective roads in extreme weather conditions.
Mouse models to investigate in situ cell fate decisions induced by p53
Authors: Lieschke Elizabeth , Thomas Annabella F , Kueh Andrew , Atkin-Smith Georgia K , Baldoni Pedro L , La Marca John E , Young Savannah , Huang Allan Shuai , Ross Aisling M , Whelan Lauren , Kaloni Deeksha , Tai Lin , Smyth Gordon K , Herold Marco J , Hawkins Edwin D , Strasser Andreas , Kelly Gemma L 
Published: August 2024

AbstractInvestigating how transcription factors control complex cellular processes requires tools that enable responses to be visualised at the single-cell level and their cell fate to be followed over time. For example, the tumour suppressor p53 (also called TP53 in humans and TRP53 in mice) can initiate diverse cellular responses by transcriptional activation of its target genes: Puma to induce apoptotic cell death and p21 to induce cell cycle arrest/cell senescence. However, it is not known how these processes are regulated and initiated in different cell types. Also, the context-dependent interaction partners and binding loci of p53 remain largely elusive. To be able to examine these questions, we here developed knock-in mice expressing triple-FLAG-tagged p53 to facilitate p53 pull-down and two p53 response reporter mice, knocking tdTomato and GFP into the Puma/Bbc3 and p21 gene loci, respectively. By crossing these reporter mice into a p53-deficient background, we show that the new reporters reliably inform on p53-dependent and p53-independent initiation of both apoptotic or cell cycle arrest/senescence programs, respectively, in vitro and in vivo.
PCPE-1, a brown adipose tissue-derived cytokine, promotes obesity-induced liver fibrosis
Authors: Hsiao Yung Ting , Yoshida Yohko , Okuda Shujiro , Abe Manabu , Mizuno Seiya , Takahashi Satoru , Nakagami Hironori , Morishita Ryuichi , Kamimura Kenya , Terai Shuji , Aung Tin May , Li Ji , Furihata Takaaki , Tang Jing Yuan , Walsh Kenneth , Ishigami Akihito , Minamino Tohru , Shimizu Ippei 
Published: August 2024

AbstractMetabolic dysfunction-associated steatohepatitis (MASH, previously termed non-alcoholic steatohepatitis (NASH)), is a major complication of obesity that promotes fatty liver disease. MASH is characterized by progressive tissue fibrosis and sterile liver inflammation that can lead to liver cirrhosis, cancer, and death. The molecular mechanisms of fibrosis in MASH and its systemic control remain poorly understood. Here, we identified the secreted-type pro-fibrotic protein, procollagen C-endopeptidase enhancer-1 (PCPE-1), as a brown adipose tissue (BAT)-derived adipokine that promotes liver fibrosis in a murine obesity-induced MASH model. BAT-specific or systemic PCPE-1 depletion in mice ameliorated liver fibrosis, whereas, PCPE-1 gain of function in BAT enhanced hepatic fibrosis. High-calorie diet-induced ER stress increased PCPE-1 production in BAT through the activation of IRE-1/JNK/c-Fos/c-Jun signaling. Circulating PCPE-1 levels are increased in the plasma of MASH patients, suggesting a therapeutic possibility. In sum, our results uncover PCPE-1 as a novel systemic control factor of liver fibrosis.
CHC22 clathrin recruitment to the early secretory pathway requires two-site interaction with SNX5 and p115
Authors: Greig Joshua , Bates George T , Yin Daowen I , Briant Kit , Simonetti Boris , Cullen Peter J , Brodsky Frances M 
Published: August 2024

AbstractThe two clathrin isoforms, CHC17 and CHC22, mediate separate intracellular transport routes. CHC17 performs endocytosis and housekeeping membrane traffic in all cells. CHC22, expressed most highly in skeletal muscle, shuttles the glucose transporter GLUT4 from the ERGIC (endoplasmic-reticulum-to-Golgi intermediate compartment) directly to an intracellular GLUT4 storage compartment (GSC), from where GLUT4 can be mobilized to the plasma membrane by insulin. Here, molecular determinants distinguishing CHC22 from CHC17 trafficking are defined. We show that the C-terminal trimerization domain of CHC22 interacts with SNX5, which also binds the ERGIC tether p115. SNX5, and the functionally redundant SNX6, are required for CHC22 localization independently of their participation in the endosomal ESCPE-1 complex. In tandem, an isoform-specific patch in the CHC22 N-terminal domain separately mediates binding to p115. This dual mode of clathrin recruitment, involving interactions at both N- and C-termini of the heavy chain, is required for CHC22 targeting to ERGIC membranes to mediate the Golgi-bypass route for GLUT4 trafficking. Interference with either interaction inhibits GLUT4 targeting to the GSC, defining a bipartite mechanism regulating a key pathway in human glucose metabolism.
Histone demethylase KDM2A recruits HCFC1 and E2F1 to orchestrate male germ cell meiotic entry and progression
Authors: Feng Shenglei , Gui Yiqian , Yin Shi , Xiong Xinxin , Liu Kuan , Li Jinmei , Dong Juan , Ma Xixiang , Zhou Shunchang , Zhang Bingqian , Yang Shiyu , Wang Fengli , Wang Xiaoli , Jiang Xiaohua , Yuan Shuiqiao 
Published: August 2024

AbstractIn mammals, the transition from mitosis to meiosis facilitates the successful production of gametes. However, the regulatory mechanisms that control meiotic initiation remain unclear, particularly in the context of complex histone modifications. Herein, we show that KDM2A, acting as a lysine demethylase targeting H3K36me3 in male germ cells, plays an essential role in modulating meiotic entry and progression. Conditional deletion of Kdm2a in mouse pre-meiotic germ cells results in complete male sterility, with spermatogenesis ultimately arrested at the zygotene stage of meiosis. KDM2A deficiency disrupts H3K36me2/3 deposition in c-KIT+ germ cells, characterized by a reduction in H3K36me2 but a dramatic increase in H3K36me3. Furthermore, KDM2A recruits the transcription factor E2F1 and its co-factor HCFC1 to the promoters of key genes required for meiosis entry and progression, such as Stra8, Meiosin, Spo11, and Sycp1. Collectively, our study unveils an essential role for KDM2A in mediating H3K36me2/3 deposition and controlling the programmed gene expression necessary for the transition from mitosis to meiosis during spermatogenesis.
The unfolded protein response regulates ER exit sites via SNRPB-dependent RNA splicing and contributes to bone development
Authors: Zahoor Muhammad , Dong Yanchen , Preussner Marco , Reiterer Veronika , Shameen Alam Sabrina , Haun Margot , Horzum Utku , Frey Yannick , Hajdu Renata , Geley Stephan , Cormier-Daire Valerie , Heyd Florian , Jerome-Majewska Loydie A , Farhan Hesso 
Published: August 2024

AbstractSplicing and endoplasmic reticulum (ER)-proteostasis are two key processes that ultimately regulate the functional proteins that are produced by a cell. However, the extent to which these processes interact remains poorly understood. Here, we identify SNRPB and other components of the Sm-ring, as targets of the unfolded protein response and novel regulators of export from the ER. Mechanistically, The Sm-ring regulates the splicing of components of the ER export machinery, including Sec16A, a component of ER exit sites. Loss of function of SNRPB is causally linked to cerebro-costo-mandibular syndrome (CCMS), a genetic disease characterized by bone defects. We show that heterozygous deletion of SNRPB in mice resulted in bone defects reminiscent of CCMS and that knockdown of SNRPB delays the trafficking of type-I collagen. Silencing SNRPB inhibited osteogenesis in vitro, which could be rescued by overexpression of Sec16A. This rescue indicates that the role of SNRPB in osteogenesis is linked to its effects on ER-export. Finally, we show that SNRPB is a target for the unfolded protein response, which supports a mechanistic link between the spliceosome and ER-proteostasis. Our work highlights components of the Sm-ring as a novel node in the proteostasis network, shedding light on CCMS pathophysiology.
Retinoic acid-induced protein 14 links mechanical forces to Hippo signaling
Authors: Jeong Wonyoung , Kwon Hyeryun , Park Sang Ki , Lee In-Seob , Jho Eek-hoon 
Published: August 2024

AbstractCells sense and respond to various mechanical forces from the extracellular matrix primarily by modulating the actin cytoskeleton. Mechanical forces can be translated into biochemical signals in a process called mechanotransduction. Yes-associated protein (YAP) is an effector of Hippo signaling and a mediator of mechanotransduction, but how mechanical forces regulate Hippo signaling is still an open question. We propose that retinoic acid-induced protein 14 (RAI14) responds to mechanical forces and regulates Hippo signaling. RAI14 positively regulates the activity of YAP. RAI14 interacts with NF2, a key component of the Hippo pathway, and the interaction occurs on filamentous actin. When mechanical forces are kept low in cells, NF2 dissociates from RAI14 and filamentous actin, resulting in increased interactions with LATS1 and activation of the Hippo pathway. Clinical data show that tissue stiffness and expression of RAI14 and YAP are upregulated in tumor tissues and that RAI14 is strongly associated with adverse outcome in patients with gastric cancer. Our data suggest that RAI14 links mechanotransduction with Hippo signaling and mediates Hippo-related biological functions such as cancer progression.
Amorphous Li2O–LiI–MoO3 solid electrolytes: mechanochemical synthesis and application to all-solid-state batteries
Authors: Fujita Yushi , Otono Tomoya , Asakura Taichi , Ding Jiong , Tsukasaki Hirofumi , Mori Shigeo , Motohashi Kota , Sakuda Atsushi , Hayashi Akitoshi 
Published: August 2024

Amorphous-type Li2O–LiI–MoO3 solid electrolytes prepared using a mechanochemical method exhibit a high ionic conductivity of 10−5 S cm−1 at 25 °C, sufficient ductility to densify by pressing at room temperature, and stability to Li metals.
Inhibition of Norovirus GII.4 binding to HBGAs by Sargassum fusiforme polysaccharide
Authors: Sun Yiqiang , Liang Meina , Wu Mingjiang , Su Laijin 
Published: August 2024

Abstract
Norovirus (NoV) is the main pathogen that causes acute gastroenteritis and brings a heavy socio-economic burden worldwide. In this study, five polysaccharide fractions, labeled pSFP-1-5, were isolated and purified from Sargassum fusiforme (S. fusiforme). In vitro experiments demonstrated that pSFP-5 significantly prevented the binding of type A, B and H histo-blood group antigens (HBGAs) to NoV GII.4 virus-like particles (NoV GII.4 VLPs). In addition, in vivo experiments revealed that pSFP-5 was effective in reducing the accumulation of NoV in oysters, indicating that pSFP-5 could reduce the risk of NoV infection from oyster consumption. The results of transmission electron microscopy showed that the appearance of NoV GII.4 VLPs changed after pSFP-5 treatment, indicating that pSFP-5 may achieve antiviral ability by altering the morphological structure of the viral particles so that they could not bind to HBGAs. The results of the present study indicate that pSFP-5 may be an effective anti-NoV substance and can be used as a potential anti-NoV drug component.
Hyperspectral image restoration using noise gradient and dual priors under mixed noise conditions
Authors: Aetesam Hazique , Maji Suman Kumar , Prasath V. B. Surya 
Published: August 2024

AbstractImages obtained from hyperspectral sensors provide information about the target area that extends beyond the visible portions of the electromagnetic spectrum. However, due to sensor limitations and imperfections during the image acquisition and transmission phases, noise is introduced into the acquired image, which can have a negative impact on downstream analyses such as classification, target tracking, and spectral unmixing. Noise in hyperspectral images (HSI) is modelled as a combination from several sources, including Gaussian/impulse noise, stripes, and deadlines. An HSI restoration method for such a mixed noise model is proposed. First, a joint optimisation framework is proposed for recovering hyperspectral data corrupted by mixed Gaussian‐impulse noise by estimating both the clean data as well as the sparse/impulse noise levels. Second, a hyper‐Laplacian prior is used along both the spatial and spectral dimensions to express sparsity in clean image gradients. Third, to model the sparse nature of impulse noise, an ℓ1 − norm over the impulse noise gradient is used. Because the proposed methodology employs two distinct priors, the authors refer to it as the hyperspectral dual prior (HySpDualP) denoiser. To the best of authors' knowledge, this joint optimisation framework is the first attempt in this direction. To handle the non‐smooth and non‐convex nature of the general ℓp − norm‐based regularisation term, a generalised shrinkage/thresholding (GST) solver is employed. Finally, an efficient split‐Bregman approach is used to solve the resulting optimisation problem. Experimental results on synthetic data and real HSI datacube obtained from hyperspectral sensors demonstrate that the authors’ proposed model outperforms state‐of‐the‐art methods, both visually and in terms of various image quality assessment metrics.
A non‐intrusive method for friction and windage losses estimation in induction motors
Authors: Geravandi Moslem , Moradi Hassan 
Published: August 2024

AbstractIn the in‐service induction motors (IMs), friction and windage losses (FWL) value should be determined non‐intrusively. Hence, in the in‐service IMs, instead of measuring FWL, empirical equations are used to estimate FWL value. A novel technique is proposed for estimating the FWL value in low‐voltage three‐phase IMs based on obtained data from applying the no‐load test on 425 simulated IMs in the MATLAB software. The simulated IMs are 380 V, 50 Hz, with different numbers of poles in the power range of 0.37–400 kW. The FWL value for simulated IMs is calculated based on the IEEE 112 standard and by applying the no‐load test. Then, based on the dispersion of the obtained data from the no‐load test and using non‐linear regression, according to the number of IM poles for each number of poles, a third‐degree equation for FWL estimation is fitted to the test data. The proposed method to estimate the FWL value only needs the nominal output power listed on the IM nameplate. Also, unlike existing empirical relationships, the proposed approach estimates the FWL value for IMs with high accuracy and non‐intrusively. The effectiveness of the suggested technique is confirmed by simulation and practical results.
An improved approach for the evaluation of the environmental impact of nano‐modified insulating oils in electrical transformers
Authors: Chronis Ioannis , Tang Chao , Psomopoulos Constantinos S. 
Published: August 2024

AbstractNano‐modified electrical insulating fluids are a promising new family of insulating oils with enhanced characteristics. They can significantly improve many properties, such as fire point, breakdown voltage, partial discharge inception voltage and thermal conductivity etc. However, nanoparticles have raised concerns about the possible harm to human health and the ecosystems, but the environmental impact of nano‐modified insulating oils is far more complicated than that. Following the recent research results on the stability of nano‐modified particles, the authors introduce environmental aspects that have not attracted attention so far, such as the possible loss of stability of the insulating oil, mechanical erosion problems in parts of the electrical transformer and problems in recycling processes that may turn waste nano‐modified insulating oils into an unwanted feed stock for recycling industries. An improved method for the environmental risk assessment (RA) of nano‐modified insulating oils, based on an existing model for the RA of nanoparticles, is proposed. The authors reflect the complicated nature of the nanoliquids, mainly due to the stability of the element, which seems to have a paramount role on their environmental impact and is neglected by the current approach in RA.
Towards assessing reliability of next‐generation Internet of Things dashboard for anxiety risk classification
Authors: Siddiqui Shama , Khan Anwar Ahmed , Abdesselam Farid Nait , Qasmi Shamsul Arfeen , Akhundzada Adnan , Dey Indrakshi 
Published: August 2024

AbstractThe ubiquitous Internet of Things (IoT) and sensing technologies provide an interesting opportunity of remote health monitoring and disease risk categorisation of populations. An end‐to‐end architecture is proposed to facilitate real‐time digital dashboards to visualise general anxiety risks of patients, especially during a pandemic, such as COVID‐19. To collect physiological data related to anxiety (heart rate, blood pressure, and saturation of peripheral oxygen [SPO2]) and communicate them to a centralised dashboard, dubbed ‘X‐DASH’, a hardware prototype of the proposed architecture was developed using Node‐MCU and diverse sensors. The dashboard presents a smart categorisation of users' data, assessing their anxiety risks, to provide medical professionals and state authorities a clear visualisation of health risks in populations belonging to different regions. We categorised the risk levels as Normal, Mild, Moderate, Elevated, Severe, and Extreme, based on the collected physiological data and pre‐defined threshold values. The developed hardware prototype in this work was used to collect data from about 500 patients present at cardiac clinic of a leading general hospital in Karachi (Pakistan) and the anxiety risk levels were assigned based on pre‐defined threshold values. To validate the reliability of the X‐DASH, the personal physician of each patient was consulted and was requested to identify each of their anxiety risk levels. It was found that the risk levels suggested by X‐DASH, (based on data of heart rate, blood pressure, and SPO2 were more than 90% accurate when compared with diagnoses of physicians. Subsequently, packet loss, delay and network overhead for the platform was compared when using MQTT, CoAP and Modbus. Although MQTT has shown higher delays, but it is still recommended due to having a higher reliability.
Dispersion and rotation measures from fast radio burst (FRB) host galaxies based on the TNG50 simulation
Authors: Kovacs Timea Orsolya , Mao Sui Ann , Basu Aritra , Ma Yik Ki , Pakmor Ruediger , Spitler Laura G. , Walker Charles R. H. 
Published: August 2024

Context. Fast radio bursts (FRBs) are poised to become important cosmological tools in the near future, as the number of observed FRBs is increasing rapidly with multiple surveys underway. A large sample of FRBs will soon have available dispersion measures (DMs) and rotation measures (RMs), which can be used to study the cosmic baryon density and the intergalactic magnetic field. However, the observed DM and RM of FRBs consists of multiple contributions that must be quantified to estimate the DM and RM of the intergalactic medium (IGM).
Aims. In this paper, we estimate one such contribution to DM and RM, namely, of FRB host galaxies. We show how this contribution changes with redshift, galaxy type, and the stellar mass of the galaxies. We also investigate its dependence on galaxy inclination and on an FRB’s offset from the center of the galaxy.
Methods. Using the TNG50 simulation of the IllustrisTNG project, we selected 16 500 galaxies at redshifts of 0≤ ɀ ≤2, with stellar masses in the range of 9 ≤ log(M*/M⊙) ≤ 12. In each galaxy, we calculated the DM and RM contributions of 1000 sightlines; from these, we constructed the DM and RM probability density functions (PDFs).
Results. We find that the rest frame DM distributions of all galaxies at a given redshift can be fitted by a log normal function and its median and width increase as a function of redshift. The rest-frame RM distribution is symmetric, with a median RMhost,rf=0 rad m–2 and it can be fitted by a combination of a Lorentzian and two Gaussian functions. The redshift evolution of the distribution width can be fitted by a curved power law. The parameters of these functions change for different subsets of galaxies with different stellar mass, inclination, and FRB offset. These changes are due to an increasing ne with redshift, SFR, and stellar mass. We do find a more ordered B field at lower ɀ compared to higher ɀ, as suggested by the presence of more galaxies with B field reversals and B fields dominated by random B field at higher ɀ.
Conclusions. We estimated the FRB host DM and RM contributions, which can be used in the future to isolate the IGM contribution from the observed DM and RM of FRBs. We predict that to constrain a σRM,IGM of 2 rad m–2 to the 95% confidence level, we would need to observe 95 000 FRBs at ɀ = 0.5, but only 9 500 FRBs at ɀ = 2.