bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Patchouli Alcohol on Diarrhea-Predominant Irritable Bowel Syndrome are Correlated with Phenotypic Plasticity in Myenteric Neurons and the Targeted Regulation of Myosin Va
Authors: Yi Shu-Lin , Huang Zi-Tong , Liao Lu , Lu Yu-Lin , Lin Yu-Kang , Pei Ying , Chen Wan-Yu , Huang Chen , Cao Hong-Ying , Tan Bo
Published: October 2022

Patchouli alcohol (PA) has been widely used for the treatment of diarrhea-predominant irritable bowel syndrome (IBS-D) in traditional Chinese medicine, and the related mechanism remains to be fully understood. Our previous study has indicated that PA significantly reduced visceral sensitivity and defecation area in IBS-D rats. In this study, we prepared an IBS-D rat model and observed the dynamic intestinal motility and colonic longitudinal muscle and myenteric plexus (LMMP) neurons, as well as their subtypes at D14, D21, and D28. After PA administration, we observed the effects on the changes in intestinal motility, colonic LMMP neurons, and LMMP Myosin Va in IBS-D rats and their co-localization with inhibitory neurotransmitter-related proteins. The results indicated that PA treatment could alleviate IBS-D symptoms, regulate the abnormal expression of LMMP neurons, increase Myosin Va expression, up-regulate co-localization levels of Myosin Va with neuronal nitric oxide synthase (nNOS), and promote co-localization levels of Myosin Va with vasoactive intestinal polypeptide (VIP). In conclusion, this study demonstrated the neuropathic alterations in the colon of chronic restraint stress-induced IBS-D rat model. PA reversed the neuropathological alteration by affecting the transport process of nNOS and VIP vesicles via Myosin Va and the function of LMMP inhibitory neurons, and these effects were related to the mechanism of enteric nervous system (ENS) remodeling.
About this title - Conservation Palaeobiology of Marine Ecosystems
Authors: Nawrot R. , Dominici S. , Tomašových A. , Zuschin M.
Published: October 2022

The accelerating pace of global change requires better understanding of the long-term resilience and adaptive capacities of marine ecosystems. This volume brings together studies that demonstrate how combining palaeoecological records with other types of geohistorical data informs biodiversity conservation and ecosystem management by providing data on baseline community states.
One Tree Reef Foraminifera: a relic of the pre-colonial Great Barrier Reef
Authors: Bauder Yvette , Mamo Briony , Brock Glenn A. , Kosnik Matthew A.
Published: October 2022

Benthic Foraminifera are important elements of coral reef ecosystems and valuable proxies for monitoring reef health in the face of local, regional and global stressors. Here Foraminifera preserved in a sediment core from the One Tree Reef (OTR) lagoon on the southern Great Barrier Reef (GBR) are used to quantify ecological changes associated with European colonization (early 1800s) and the subsequent industrialization of Australia (1950s onward). Core samples are compared to published benthic grab samples from three reefs to compare spatial and temporal variation. Standard measures of richness, diversity and foraminiferal assemblage composition indicate significant differences between the Recent assemblages of OTR lagoon and those from Heron and Wistari reef lagoons. However, there is no discernible change in the OTR lagoon core assemblages from the last four centuries in any of the richness or diversity indices examined. While benthic grabs likely undersample infaunal Foraminifera relative to core samples, these foraminiferal assemblages indicate the OTR lagoon contains a living example of a pre-colonial GBR lagoon ecosystem. Without cores from Heron and Wistari it is unknown if their foraminiferal assemblages have changed due to recent anthropogenic activity or if they have always been distinct.
Virtuoso
: Energy- and Latency-aware Streamlining of Streaming Videos on Systems-on-Chips
Authors: Lee Jayoung , Wang Pengcheng , Xu Ran , Jain Sarthak , Dasari Venkat , Weston Noah , Li Yin , Bagchi Saurabh , Chaterji Somali
Published: October 2022

Efficient and adaptive computer vision systems have been proposed to make computer vision tasks, such as image classification and object detection, optimized for embedded or mobile devices. These solutions, quite recent in their origin, focus on optimizing the model (a deep neural network) or the system by designing an adaptive system with approximation knobs. Despite several recent efforts, we show that existing solutions suffer from two major drawbacks.
First
, while mobile devices or systems-on-chips usually come with limited resources including battery power, most systems do not consider the energy consumption of the models during inference.
Second
, they do not consider the interplay between the three metrics of interest in their configurations, namely, latency, accuracy, and energy. In this work, we propose an efficient and adaptive video object detection system—
Virtuoso
, which is jointly optimized for accuracy, energy efficiency, and latency. Underlying
Virtuoso
is a multi-branch execution kernel that is capable of running at different operating points in the accuracy-energy-latency axes, and a lightweight runtime scheduler to select the best fit execution branch to satisfy the user requirement. We position this work as a first step in understanding the suitability of various object detection kernels on embedded boards in the accuracy-latency-energy axes, opening the door for further development in solutions customized to embedded systems and for benchmarking such solutions.
Virtuoso
is able to achieve up to 286 FPS on the NVIDIA Jetson AGX Xavier board, which is up to 45× faster than the baseline EfficientDet D3 and 15× faster than the baseline EfficientDet D0. In addition, we also observe up to 97.2% energy reduction using
Virtuoso
compared to the baseline YOLO (v3)—a widely used object detector designed for mobiles. To fairly compare with
Virtuoso
, we benchmark 15 state-of-the-art or widely used protocols, including Faster R-CNN (FRCNN) [NeurIPS’15], YOLO v3 [CVPR’16], SSD [ECCV’16], EfficientDet [CVPR’20], SELSA [ICCV’19], MEGA [CVPR’20], REPP [IROS’20], FastAdapt [EMDL’21], and our in-house adaptive variants of FRCNN+, YOLO+, SSD+, and EfficientDet+ (our variants have enhanced efficiency for mobiles). With this comprehensive benchmark,
Virtuoso
has shown superiority to all the above protocols, leading the accuracy frontier at every efficiency level on NVIDIA Jetson mobile GPUs. Specifically,
Virtuoso
has achieved an accuracy of 63.9%, which is more than 10% higher than some of the popular object detection models, FRCNN at 51.1% and YOLO at 49.5%.
Association between Oxidative Stress Parameters and Hematological Indices in Breast Cancer Patients
Authors: Danesh Hiva , Ziamajidi Nasrin , Mesbah-Namin Seyed Alireza , Nafisi Nahid , Abbasalipourkabir Roghayeh
Published: October 2022

Background. Breast cancer is one of the leading causes of death in women worldwide. This causes an increase in free radicals, resulting in oxidative stress. The aim of this study was to determine the effect of breast cancer on oxidative stress and its relationship with hematological indices. Methods. This case-control study included 43 women with breast cancer and 37 age-matched healthy controls. Oxidative stress and its correlation with hematological profiles over seven months were evaluated. Finally, the data were compared between the two groups using the

t

-test and Pearson’s test, and the results were analyzed using the SPSS 24 software. Results. The results revealed that patients with breast cancer had significantly increased hemoglobin (HB), hematocrit (HCT), mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) levels compared with healthy subjects (

p
<
0.05

). In addition, oxidative stress parameters, such as superoxide dismutase (SOD), catalase (CAT), total oxidant status (TOS), and total antioxidant capacity (TAC), were significantly elevated. Glutathione peroxidase (GPX) and malondialdehyde (MDA) were significantly lower in patients with breast cancer than in the control group (

p
<
0.05

). Statistical significance in hematological indices showed a positive or negative correlation with oxidative stress parameters. Conclusion. Women with breast cancer showed a deranged complete blood count (CBC) pattern compared to healthy individuals.
Characterizing the Crosstalk of NCAPG with Tumor Microenvironment and Tumor Stemness in Stomach Adenocarcinoma
Authors: Xiang Zheng , Cha Genlan , Wang Yihao , Gao Jikai , Jia Jianguang
Published: October 2022

Background. Nonstructural maintenance of non-SMC condensin I complex subunit G (NCAPG) exerts critical effects on cancer progression. However, its biological roles in tumorigenesis and metastasis remain unclear. Thus, we aimed to assess the prognostic utility of NCAPG in stomach adenocarcinoma (STAD) and its potential as a tumor biomarker. Methods. Pan-cancer expression profile dataset from public databases and corresponding clinical information were extracted. Single-sample gene set enrichment analysis (ssGSEA) was performed for the evaluation of immune correlations pan-cancer. Subsequently, we focused on STAD and evaluated the methylation profiles, copy number variants (CNVs), and single nucleotide variants (SNVs). Immune features were analyzed between high and low NCAPG expression groups. Differential analysis was performed between high and low expression groups to identify differentially expressed genes (DEGs). Prognostic DEGs were screened by univariate analysis, and an NCAPG-based risk model was constructed based on the prognostic DEGs and LASSO analysis. Results. NCAPG expression in STAD was significantly and positively correlated with four immune checkpoints, namely, CTLA4, PDCD1, LAG3, and CD276, but was negatively correlated with the infiltration of most immune cells. High and low NCAPG expression groups had differential overall survival, tumor mutation burden, and differential enrichment of therapeutic-related pathways. An immune risk scoring model related to NCAPG expression and immune score was constructed which showed a favorable performance in predicting STAD prognosis as well as predicting the response to immunotherapy. In addition, we found a higher mRNA stemness index (mRNAsi) in the high-risk group and a positive correlation between NCAPG expression and mRNAsi. Conclusion. NCAPG was suggested to be involved in the regulation of tumor microenvironment in STAD. High NCAPG expression was related to high tumor stemness and good prognosis. The immune risk model had a potential to predict STAD prognosis and help directing therapeutic treatment.
A Case of Perforated Cholecystitis into a Parastomal Hernia
Authors: Seang Sereibanndith , Hort Amy , Gosal Preet K. S. , Richardson Mark
Published: October 2022

Introduction. Parastomal hernia is a common complication following an enterostomy. Gallbladder herniation into parastomal hernia is rare and may become symptomatic and inflamed and very rarely can lead to gallbladder perforation. We present the first case of gallbladder perforation inside a parastomal hernia with a unique skin change. Case Description. In this report, an 87-year-old female with a history of previous open cystectomy and ileal conduit formation, presented with right upper quadrant pain and worsening parastomal swelling. A computed tomography scan showed a parastomal herniation of the gallbladder, cholelithiasis, and possible early acute cholecystitis. Within 12 hours of admission, bile staining skin changes developed around her urostomy site which raised our suspicion of a perforated gallbladder. Biliary peritonitis was confirmed on laparoscopy the same day. We proceeded with an open midline cholecystectomy without hernia repair. The patient was well at her last follow-up. Discussion. A literature review found 14 published cases of incarcerated gallbladder hernia. This uncommon condition mainly affects elderly females. Ten cases were managed operatively, and four cases were managed nonoperatively, with good outcomes. Currently, no consensus on treatment guidelines exists. In a frail elderly patient, a nonoperative approach may be suitable. Operative management was indicated in this case due to clinical concerns of perforation due to developing skin changes. This cutaneous sign has not been previously documented in the literature. Conclusion. While rare, the gallbladder can herniate and become incarcerated inside a parastomal hernia. Bile staining of the skin should raise clinical suspicion of perforation. Management options depend on patient and pathology factors and can be nonoperative or operative, with or without hernia repair.
Finding the Number of Weak Homomorphisms of Paths
Authors: Pomsri Tawatchai , Wannasit Wannasiri , Panma Sayan
Published: October 2022

Let G and H be graphs. A mapping f from V(G) to V(H) is called a weak homomorphism from G to H if f(x) = f(y) or {f(x), f(y)} ∈ E(H) whenever {x, y} ∈ E(G). In this paper, we provide an algorithm to determine the number of weak homomorphisms of paths.
AI-Assisted Tuberculosis Detection and Classification from Chest X-Rays Using a Deep Learning Normalization-Free Network Model
Authors: Acharya Vasundhara , Dhiman Gaurav , Prakasha Krishna , Bahadur Pranshu , Choraria Ankit , M Sushobhitha , J Sowjanya , Prabhu Srikanth , Chadaga Krishnaraj , Viriyasitavat Wattana , Kautish Sandeep
Published: October 2022

Tuberculosis (TB) is an airborne disease caused by Mycobacterium tuberculosis. It is imperative to detect cases of TB as early as possible because if left untreated, there is a 70% chance of a patient dying within 10 years. The necessity for supplementary tools has increased in mid to low-income countries due to the rise of automation in healthcare sectors. The already limited resources are being heavily allocated towards controlling other dangerous diseases. Modern digital radiography (DR) machines, used for screening chest X-rays of potential TB victims are very practical. Coupled with computer-aided detection (CAD) with the aid of artificial intelligence, radiologists working in this field can really help potential patients. In this study, progressive resizing is introduced for training models to perform automatic inference of TB using chest X-ray images. ImageNet fine-tuned Normalization-Free Networks (NFNets) are trained for classification and the Score-Cam algorithm is utilized to highlight the regions in the chest X-Rays for detailed inference on the diagnosis. The proposed method is engineered to provide accurate diagnostics for both binary and multiclass classification. The models trained with this method have achieved 96.91% accuracy, 99.38% AUC, 91.81% sensitivity, and 98.42% specificity on a multiclass classification dataset. Moreover, models have also achieved top-1 inference metrics of 96% accuracy and 98% AUC for binary classification. The results obtained demonstrate that the proposed method can be used as a secondary decision tool in a clinical setting for assisting radiologists.
Effect of Cavitation with Vibration on the Powerhouse Structure of Bulb Turbines Installed in Hydropower Stations
Authors: S Praveen , S Marimuthu , S Manivannan , Das A Daniel , Kerga Gizachew Assefa
Published: October 2022

Hydro energy is one of the world’s most abundant and valuable renewable electricity sources. Hydropower is an important source since it is a clean, sustainable, and cost-effective source of energy. The most perilous characteristic that affects the performance of the hydraulic turbine and its allied parts is the cavitation phenomenon, which is clear as the increase of vapor bubbles in the liquid through any hydraulic turbine. Cavitation causes vibration, which is very harmful to turbine guide bearings and their supporting structures. Sometimes heavy vibration causes cracks in the civil structure of the powerhouse where the bulb turbines are installed. The performance of the bulb turbine and the stability of the powerhouse structure are studied with the effect of cavitation, vibration, and deformation of the turbine casing. Experimental measurements are used to determine at what force the shape of cavitation is very destructive and crucial when the local pressure is less than the vapor pressure of the flowing water, at which static pressure cavities begin to breed and ruin. This paper focuses on small hydropower stations with bulb turbine installations, which emphasized the performance improvement of these turbines by avoiding cavitation on the runner blades. Allowing some cavitation on these machines is also recommended, which is within repairable condition, and the cavitation pitting can be repaired during annual maintenance.
Application of Convolution Neural Network Algorithm Based on Intelligent Sensor Network in Target Recognition of Corn Weeder at Seedling Stage
Authors: Zhang Zhiyi , Li Shiyuan , Jia Jiakai , Zheng Zhiqi , Tian Hao
Published: October 2022

Grass damage in the seedling corn field has always been an important factor affecting the growth and development of crops. The existence of grass not only compresses the living space of corn seedlings but also easily causes insect damage. Therefore, it is essential for weeding in the seedling corn field. The existing weeding methods usually use manual or chemical herbicide spraying, which is not only time-consuming and laborious but also inefficient. With the development of artificial intelligence and modern agricultural technology, the use of robots for field weeding has become an effective means, which has attracted more and more attention of researchers at home and abroad. Therefore, based on the full investigation of the development of relevant technologies at home and abroad, this paper carried out the research on the real-time target recognition and ranging method of field weeding robot and proposed a target recognition method of weeding corn at the seedling stage by using an intelligent sensor network and deep learning convolution neural network. Among them, the intelligent sensor is mainly used for target ranging and obstacle avoidance, and CNN is mainly used for target recognition. Taking the images of corn seedlings and weeds in the seedling stage under natural environmental conditions as samples, the migration training is carried out through the depth network model of the COCO data set, and the convolution features are shared by the CNN depth network model and Fast-CNN depth network model. VGG and ResNet feature extraction networks are compared. The experimental results show that the CNN depth network model based on this paper has obvious advantages in rape and weed target recognition. The target recognition accuracy of rape and weeds can reach 87.64%, and the recall rate can reach 80.23%. Compared with other models, it has obvious advantages, which proves the effectiveness of this model.
ST-AGRNN: A Spatio-Temporal Attention-Gated Recurrent Neural Network for Traffic State Forecasting
Authors: Yang Jian , Li Jinhong , Wei Lu , Gao Lei , Mao Fuqi
Published: October 2022

Accurate traffic state prediction plays an important role in traffic guidance, travel planning, etc. Due to the existence of complex spatio-temporal relationships, there are some challenges in forecasting. Firstly, in terms of spatial correlation, some models only consider the road network structure information, and ignore the relative location relationships between nodes. Secondly, some models ignore the different impacts of nodes in the global road network on traffic. To solve these problems, we propose a new traffic state-forecasting model, namely, spatio-temporal attention-gated recurrent neural network (ST-AGRNN). In the proposed model, structure-based and location-based localized spatial features are obtained simultaneously by Graph Convolutional Networks (GCNs) and DeepWalk. The localized temporal features are obtained by gated recurrent unit (GRU). The attention-based approach is used to obtain global spatio-temporal features. Experimental validation is performed with two real-world public datasets, and the results show that the ST-AGRNN model outperforms the state-of-the-art methods.
A New Code-Based Linkable Threshold Ring Signature Scheme
Authors: Ren Fang , Xiu Haiyan , Ji Chuxin , Zheng Dong , Wu Ziyi
Published: October 2022

In this paper, we construct a new code-based linkable threshold signature scheme whose security is based on the hardness of the syndrome decoding problem and general syndrome decoding problem. We show that our scheme is secure in terms of existential unforgeability, anonymity, nonslanderability, and linkability. The complexity of the signature size proposed in this paper is

O

t

. Our method is particularly well suited for large free group voting systems. The greater the number of members in the ring, the more pronounced the advantage of the signature length is when compared to other schemes. That is, our scheme achieves a fixed length signature, independent of the number of ring members. In addition, our scheme has a very short public key, and the size is

O

N

.
Evaluating the Effect of Interactive Digital Presentations on Students’ Performance during Technology Class
Authors: Shatri Kyvete , Shala Lediana
Published: October 2022

The importance of this research was to highlight the use of interactive digital presentations in the classroom that allow students to interact with the lesson content, work independently, and answer various questions presented on these interactive slides. We used the Pear Deck add-on to create these interactive presentations. The research had a quasiexperimental design and was conducted with two seventh-grade classes in the primary school “Naim Frasheri” in Prishtina, where one of them played the role of the experimental group while the other had the role of the control group. Data collection instruments were used in two tests (pre-test and post-test), a questionnaire for students in the experimental class, and the method of observation in both classes. From the data collected from the questionnaire, we measured the positive effects on students’ motivation to learn and the positive effects on achievement were measured by testing students, while our attitudes as a teacher were reflected through the observation process. The results of this study have shown that the use of interactive digital presentations has a positive effect on the memorization of concepts and students’ engagement and that this kind of presentations are more efficient to use during the technology class compared to traditional learning methods.
Supervisory Control Scheme of a Wind Farm Connected to a Hybrid Microgrid
Authors: Benghanem Mustapha , AlKassem Abdulrahmane , Bensaber Abdelhaq Amar , Draou Azeddine
Published: October 2022

Nowadays, the generation of wind power combined with a battery energy storage system offers a viable solution for electricity supply to isolated areas with no access to the grid. However, the speed of the wind is unpredictable and the inherent nonlinearities of the wind turbine and generator system cause fluctuations in the voltage, power, and frequency. This paper proposes a new three-layered control technique applied to a wind farm that uses doubly-fed induction generators (DFIGs) connected to a remote hybrid microgrid. The first layer provides local control to each DFIG wind turbine based on a nonlinear and robust control strategy. The second layer coordinates and controls the flow of power between the turbine and the storage system to make sure that load demand is being satisfied and the desired limits of the state of charge are respected. Finally, and in the third layer, we implement a supervisory controller that will be responsible for the generation of the references for the active power as per the load demand. The proposed off-grid wind power system and battery storage and its three-layer hierarchical control scheme are simulated under MATLAB/Simulink environment and tested under various load and speed profiles. Through the numerous test data obtained, it has been shown that the control strategy under study is robust and effective.
Privacy-Enhanced Data Fusion for Federated Learning Empowered Internet of Things
Authors: Lin Qingxin , Xu Kuai , Huang Yikun , Yu Feng , Wang Xiaoding
Published: October 2022

IoT sensors have already penetrated into extremely broad fields such as industrial production, smart home, environmental protection, medical diagnosis, and bioengineering. Although efficient data fusion helps improve the quality of intelligent services provided by the Internet of things, because the perceived data carry the sensitive information of the perceived object, the data fusion process is prone to the risk of privacy leakage. To this end, in this paper, we proposed a privacy-enhanced federated learning data fusion strategy. This strategy adds Gaussian noise at different stages of federated learning to achieve privacy protection in the data fusion process. Experimental results show that this strategy provides better privacy protection while achieving high-precision IoT data fusion.
Apathy following Bilateral Deep Brain Stimulation of Subthalamic Nucleus and Globus Pallidus Internus in Parkinson’s Disease: A Meta-Analysis
Authors: Zhang Song , Zi Shumei , Xiong Sihuai , Peng Heng , Hu Kejia , He Hua
Published: October 2022

Parkinson’s disease (PD) is a progressive neurodegenerative disorder typically manifested by its motor symptoms. In addition, PD patients also suffer from many nonmotor symptoms (NMSs), such as apathy. Bilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) and the globus pallidus internus (GPi) are recommended as therapeutic interventions for PD, given their pronounced benefit in reducing troublesome dyskinesia. Apathy, a mood disorder recognized as a NMS of PD, has a negative impact on the prognosis of PD patients. However, the effect of STN-DBS and GPi-DBS on apathy is controversial. In the current meta-analysis, we analyzed apathy following bilateral STN-DBS and GPi-DBS in PD patients. Relevant literature was retrieved from public databases, including PubMed, Cochrane Library, and Embase. Studies were included in our analysis based on the following criterion: such studies should report apathy scores presurgery and postsurgery determined by using the Starkstein Apathy Scale or Apathy Evaluation Scale in patients receiving STN or GPi-DBS with at least three months of follow-up. Upon applying this strict criterion, a total of 13 out of 302 studies were included in our study. A mean difference (MD) and 95% confidence interval (CI) were calculated to show the change in apathy scores. We found a statistically significant difference between the presurgery and postsurgery scores in patients receiving STN-DBS (MD = 2.59, 95% CI = 2.23–2.96,

P
<
0.00001

), but not in patients receiving GPi-DBS (MD = 0.32, 95% CI = −2.78–3.41,

P
=
0.84

). STN-DBS may worsen the condition of apathy, which may result from the reduction of dopaminergic medication. In conclusion, STN-DBS seems to relatively worsen the condition of apathy compared to GPi-DBS. Further studies should focus on the mechanisms of postoperatively apathy and the degree of apathy in STN-DBS versus GPi-DBS.
Diagnostic Accuracy of Direct Immunofluorescence Test on Paraffin-Embedded Blocks in Comparison with Frozen Section Blocks in Renal Biopsies
Authors: Mohammadzadeh Sahand , Aghakhaninejad Fatemeh , Azad Fariborz , Derakhshan Dorna , Soleimani Neda
Published: October 2022

Background. In several published research, the evaluation of renal disorders using immunofluorescence on formalin-fixed, paraffin-embedded (FFPE) tissue sections versus immunofluorescence on frozen sections was compared. Each technique’s accuracy varies greatly. This study’s objective was to assess IF-P as a potential replacement for IF-F in the diagnosis of renal biopsy specimens. Materials and Methods. To show immunoglobulin IgA, IgG, IgM, and C3 immune deposits, proteinase K digestion of paraffin-embedded renal biopsy was standardized and used in 51 renal biopsies. Sensitivity, specificity, false-positive, and false-negative values were calculated. Results. IF-P showed a sensitivity of 93.1%, 76.9%, 63.6%, and 33.3%, and a specificity of 100%, 97.3%, 95%, and 100% for IgG, IgA, IgM, and C3, respectively. Compared to cases that had both routine IF and IF-P, 50 of 51 showed either the same amount of staining for the diagnostic immunoglobulin/complement or a small amount of difference. In most of the cases (49 of 51), diagnostic findings were found. Conclusion. IF-P is a sensitive and precise approach for assessing immune deposits in renal tissue biopsies. We come to the conclusion that IF-P serves as a beneficial salvage immunohistochemistry method for renal biopsies that do not contain enough cortical tissue for IF-F.
YAP Overexpression in Breast Cancer Cells Promotes Angiogenesis through Activating YAP Signaling in Vascular Endothelial Cells
Authors: Yan Yu , Song Qiang , Yao Li , Zhao Liang , Cai Hui
Published: October 2022

Purpose. The YAP signaling pathway is altered and implicated as oncogenic in human mammary cancers. However, roles of YAP signaling that regulate the breast tumor angiogenesis have remained elusive. Tumor angiogenesis is coordinated by the activation of both cancer cells and vascular endothelial cells. Whether the YAP signaling pathway can regulate the intercellular interaction between cancer cells and endothelial cells is essentially unknown. Methods. The effects of YAP on tumor angiogenesis, migration, and proliferation of vascular endothelial cells were evaluated in vitro. Expression of proteins and phosphorylating proteins involved in YAP, G13-RhoA, and PI3K/Akt signaling pathways was evaluated using the Western blotting, immunofluorescence staining, and immunohistochemistry analysis. In addition, the effects of YAP on breast cancer angiogenesis were evaluated in vivo by tumor xenograft mice. Results. We showed here that conditioned media from YAP overexpressed breast cancer cells (CM-YAP+) could promote angiogenesis, accompanied by increased tube formation, migration, and proliferation of human umbilical vein endothelial cells (HUVECs). Down regulation of YAP in HUVECs reversed CM-YAP+ induced angiogenesis. CM-YAP+ time-dependently activated YAP in HUVECs by dephosphorylating YAP and increasing nuclear translocation. We also identified that both G13-RhoA and PI3K/Akt signaling pathway were necessary for CM-YAP+ induced activation of YAP. Besides, connective tissue growth factor (CTGF) and angiopoietin-2 (ANG-2) acted as down-stream of YAP in HUVECs to promote angiogenesis. In addition, subcutaneous tumors nude mice model demonstrated that tumors overexpressed YAP revealed more neovascularization in vivo. Conclusion. YAP-YAP interaction between breast cancer cells and endothelial cells could promote tumor angiogenesis, supporting that YAP is a potential marker and target for developing novel therapeutic strategies against breast cancer.
Effect of Joule Heating and Thermal Radiation of MHD Boundary Layer Oldroyd‐B Nanofluid Flow with Heat Transfer over a Porous Stretching Sheet by Finite Element Method
Authors: Ullah Hakeem , Fiza Mehreen , Khan Kamal , Batool Shamaila , Ghufran S. M. , Al-Mekhlafi Seham M.
Published: October 2022

In this study, an incompressible two‐dimensional Oldroyd‐B nanofluid steady flow past a stretching sheet considering the outcomes of magneto‐hydrodynamics (MHD) and porous medium with magnetic, electrical, and thermal radiation effects is investigated. Using a similarity transformation, the governing equations in the form of partial differential equations (PDEs) are converted into a nonlinear ordinary differential equations (ODEs) system. The acquired system is numerically solved by the finite element method (FEM). The effects of physical parameters like Deborah numbers “β1” and “β2”, Brownian motion “Nb”, thermophoresis parameter “Nt”, Prandtl parameter “Pr”, Lewis number “Le”, thermal conductivity “k”, dynamic viscosity “μ”, magnetic and electric effects as “M” and “E1”, and thermal radiation effect “Rd” on the flow are studied in detail. For higher Nb values, regional Nusselt numbers are increasing in magnitude. The local Sherwood number’s size rises for high Nb numbers.
The Effect of GTAW Variants on Tensile and Microstructural Properties of AZ31B Magnesium Alloy Joints
Authors: Subravel V. , Padmanaban G. , Rajamurugan T. V. , Seeman M. , Chandrasekaran V. , Rajaganapathy C. , Lenin Haiter A.
Published: October 2022

In this investigation, an attempt is made to study the tensile and microstructural impact of different gas tungsten arc (GTA) welding processes of pulsed current, constant current, and magnetic arc oscillation welded AZ31B magnesium metal joints. These techniques were chosen because they have the potential to produce welds with high tensile strength and excellent microstructural integrity. Five joints were produced using each approach, each one employing a unique combination of parameters. According to the findings of this experiment, the joints that were manufactured utilising a welding process called magnetic arc oscillation yielded superior tensile qualities when compared to the properties of other joints. The improved tensile characteristics of these joints can be ascribed in a large part to the creation of smaller grains and surface hardness in the transition region, as well as uniformly dispersed precipitates.
Study on Life Satisfaction of the Elderly Based on Healthy Aging
Authors: Tian Hua , Chen Jie
Published: October 2022

The life satisfaction of the elderly is the key to subjective well-being and healthy aging. Many related studies are focused on the affected factors, including health status, economic level, social support, pension mode, social security, and intergenerational support, etc., but few are based on the macro perspective of healthy aging. This study constructed a healthy aging evaluation system with 6 dimensions, including 15 primary indicators and 57 secondary indicators, to evaluate the relationship between healthy aging and elderly life satisfaction. Results showed that the 13168 participants were, mainly, female (53.76%), 80–99 years old (47.99%), lived in rural areas (77.00%), married and living with their spouse (43.70%), and widowed (52.15%). 80.32% lived with household members. 70.37% elderly were satisfied with their lives. Specifically, there was no gender difference in life satisfaction of the elderly (

p
=
0.273

), but there were significant differences between groups of urban and rural (

p
<
0.001

), age groups of 65–79 and 80 older (

p
<
0.001

), marriage groups of unmarried and married (

p
<
0.001

), and types of elderly care of living alone and with others (

p
<
0.001

), respectively. Among the six dimensions of healthy aging, healthcare performed best and living environment dimension was the worst, which was an area that urgently needed to strengthen. The odds ratios (ORs) showed that the dimensions of social participation/social equity and economic finance played important roles in the well-being of the elderly. Under the macro background of healthy aging, how to take measures from the micro perspective of the healthy aging evaluation index system and ultimately improve the life satisfaction of the elderly and still needs to be explored in-depth.
Mathematical Modeling of Coronavirus Dynamics with Conformable Derivative in Liouville–Caputo Sense
Authors: Bonyah Ebenezer , Hammouch Zakia , Koksal Mehmet Emir
Published: October 2022

Coronavirus has become a serious global phenomenon in recent times and has negative effects on the entire world economy. In this study, a fractional mathematical model formulated in fractional conformable derivative is studied. The model hinges on the concept of mammal hosts and humans. The basic properties of the coronavirus model are investigated. The stability analysis is carried out as well as sensitivity analysis based on the reproduction number. Numerical simulation is undertaken to give impetus to the analytical results which indicate that both fractional conformable order derivative and fractional‐order derivative have serious consequences in numerical result outcomes.
Community‐Based Health Insurance Membership Renewal Rate and Associated Factors among Households in Gedeo Zone, Southern Ethiopia
Authors: Kaso Abdene Weya , Yohanis Yofitahe , Debela Berhanu Gidisa , Hareru Habtamu Endashaw
Published: October 2022

Background. Community‐based health insurance (CBHI) scheme is an emerging strategy to achieve universal health coverage and protect communities in developing countries from catastrophic financial expenditure at the service delivery point. However, high membership discontinuation from the CBHI scheme remained the challenge to progress toward universal financial protection in resource‐constrained countries. Therefore, this study assessed the community‐based health insurance membership renewal rate and associated factors in the Gedeo zone, Southern Ethiopia. Methods. We conducted a community‐based cross‐sectional study among households in the Yirga Chafe district, Gedeo zone, Southern Ethiopia, from September 10 to 30, 2021. We used a multistage simple random sampling to recruit 537 respondents. We entered data into Epi‐Info 7 and exported it to SPSS version 25 for analysis. We used a logistic regression model to determine factors associated with the CBHI scheme membership renewal. Variables with a P value of <0.05 and a 95% confidence level were considered to be significantly associated with the outcome variable. Results. We found the respondents’ CBHI membership renewal rate was 82.68%. Those who enrolled in the CBHI scheme >3years (AOR = 3.12; 95% CI: 1.40–6.97), having illnesses in the last three months (AOR = 2.97; 95% CI: 1.47–5.99), the CBHI premium affordability (AOR = 12.64; 95% CI: 3.25–49.38), good knowledge of the CBHI scheme (AOR = 21.11; 95% CI: 10.63–41.93), perceived quality of health service (AOR = 4.21; 95% CI: 1.52–11.68), and favorable attitude towards the CBHI scheme (AOR = 3.89, 95% CI: 1.67–9.04) were significantly associated with the CBHI program membership renewal rate. Conclusion. In our study, we found the magnitude of CBHI members who discontinued their CBHI scheme membership was high. Besides, we found that the affordability of the CBHI premium, respondents’ attitude, and knowledge of the CBHI program were predictor factors for dropout from the CBHI membership. Therefore, the government should consider the economic status of communities during setting the CBHI program contribution. Moreover, awareness creation through health education should be provided to improve participants’ knowledge and perception of the CBHI program.
Semisupervised Semantic Segmentation with Mutual Correction Learning
Authors: Xiao Yifan , Dong Jing , Zhou Dongsheng , Yi Pengfei , Liu Rui , Wei Xiaopeng
Published: October 2022

The semisupervised semantic segmentation method uses unlabeled data to effectively reduce the required labeled data, and the pseudo supervision performance is greatly influenced by pseudo labels. Therefore, we propose a semisupervised semantic segmentation method based on mutual correction learning, which effectively corrects the wrong convergence direction of pseudo supervision. The well-calibrated segmentation confidence maps are generated through the multiscale feature fusion attention mechanism module. More importantly, using internal knowledge, a mutual correction mechanism based on consistency regularization is proposed to correct the convergence direction of pseudo labels during cross pseudo supervision. The multiscale feature fusion attention mechanism module and mutual correction learning improve the accuracy of the entire learning process. Experiments show that the MIoU (mean intersection over union) reaches 75.32%, 77.80%, 78.95%, and 79.16% using 1/16, 1/8, 1/4, and 1/2 labeled data on PASCAL VOC 2012. The results show that the new approach achieves an advanced level.
Application of Cytochrome C-Related Genes in Prognosis and Treatment Prediction of Lung Adenocarcinoma
Authors: Tang Min , Li Guoqing , Chen Liang , Tu Jing
Published: October 2022

Lung adenocarcinoma (LUAD) is the most common subtype of nonsmall cell lung cancer. Cytochrome c (Cyt c), which is produced from mitochondria, interacts with a protein called Apaf-1 to form the heptameric apoptosome. This heptameric apoptosome then activates the caspase cascade, which ultimately results in the execution of apoptosis. The purpose of our research was to discover a new prognostic model that is based on cytochrome c-related genes (CCRGs) for LUAD patients. Through LASSO regression analysis conducted on the LUAD datasets included in the TCGA datasets, a CCRGs signature was created. The diagnostic accuracy of the multigene signature was verified by an independent source using the GSE31210 and GSE72094 datasets. The GO and KEGG enrichment analysis were performed. In this study, there were 159 differentially expressed CCRGs in the TCGA dataset, while there were 68 differentially expressed CCRGs in the GSE31210 dataset. Additionally, there were 57 genes that overlapped across the two datasets. Using LASSO and Cox regression analysis, a signature consisting of 12 differentially expressed CCRGs was developed from the total of 57 such genes. On the basis of their risk ratings, patients were categorized into high-risk and low-risk categories, with low-risk patients having lower risk scores and a greater likelihood of surviving the disease. Univariate and multivariate analyses both concluded that this signature is an independent risk factor for LUAD. ROC curves demonstrated that this risk signature is capable of accurately predicting the 1-year, 2-year, 3-year, and 5-year survival rates of patients who have LUAD. The infiltration of antigen-presenting cells was higher in the low-risk group, such as aDCs, DCs, pDCs, and iDCs. The expression of multiple immune checkpoints was significantly higher in the low-risk group, such as BTLA, CD28, and CD86. Finally, we showed that the signature can be used to predict the drug sensitivity of already available or under investigational drugs. Overall, patient classification and individualized therapy options may benefit from this study’s development of a powerful gene signature with high value for prognostic prediction in LUAD.
The Use and Preference of Functional Appliances among a Sample of Iraqi Orthodontists: A Web-Based Survey
Authors: Hussien Hiba M. , Altaee Zena Hekmat , Nahidh Mohammed , Al-Mayahi Sajid Chaffat Auliawi
Published: October 2022

Objectives. This study evaluated the use and preference of different types of functional appliances among a sample of Iraqi orthodontists. Materials and Methods. About 200 orthodontists were invited to fill out an online Google form questionnaire with multiple-choice questions. The questions were modified from previous England and Malaysian studies. The data were tabulated as frequency tables. Results. The response rate was 61%. About 91.80% of the participants used functional appliances, with the removable type being the most used. The twin block was thought to be the best compliance one but not the most used functional appliance. About 62% depended on the clinical observations in determining the growth spurt and asked patients to wear the appliance full-time except at meal time. The majority preferred a period of retention of about 4–6 months and frequent visits for adjustments. Conclusions. Removable functional appliances are the most frequently used among the studied sample.
Combined Phase Design Model for Multileg Roundabout Intersections
Authors: Mao Chengyuan , Wang Qin , Xu Wenjiao , Cheng Xin , Yang Shengde , Li Peiran
Published: October 2022

Multileg roundabout intersections are widely used in urban areas worldwide. However, its traffic organization and signal control are very complicated in the case of large traffic flow, and the signal optimization methods for conventional intersections are not suitable for applying directly to roundabouts due to the complexity of the operating process. Therefore, many scholars have focused on dedicated signal timing schemes for roundabouts, especially through tuning key parameters such as signal cycle and green light time. However, research and applications regarding variable phases at roundabouts are quite rare. To address this gap, this paper analyzes the traffic flow characteristics and capacity of multileg roundabouts and proposed a combined phase design model to achieve the maximum utilization of road capacity at roundabouts, which can generate the optimal phase scheme based on real-time traffic data. The feasibility of the combined phase design model is verified by a case study in Jinhua, China. The results indicate that the proposed combined phase design model can improve the applicability of actuated signal control and the reasonableness of signal timing for multileg roundabouts and thus further improve the roundabout efficiency.
An Unsupervised 3D Image Registration Network for Brain MRI Deformable Registration
Authors: Huang Min , Ren Guanyu , Zhang Shizheng , Zheng Qian , Niu Huiyang
Published: October 2022

In recent years, deep learning has made successful applications and remarkable achievements in the field of medical image registration, and the method of medical image registration based on deep learning has become the current research hotspot. However, the performance of convolutional neural networks may not be fully exploited due to neglect of spatial relationships between distant locations in the image and incomplete updates of network parameters. To avoid this phenomenon, MHNet, a multiscale hierarchical deformable registration network for 3D brain MR images, was proposed in this paper. This network was an unsupervised end-to-end convolutional neural network. After training, the dense displacement vector field can be predicted almost in real-time for the unseen input image pairs, which saves a lot of time compared with the traditional algorithms of independent iterative optimization for each pair of images. On the basis of the encoder-decoder structure, this network introduced the improved Inception module for multiscale feature extraction and expanding the receptive field and the hierarchical forecast structure to promote the update of the parameters of the middle layers, which achieved the best performance on the augmented public dataset compared with the existing four excellent registration methods.