bluuebunny/crossref_metadata_2025 huggingface dataset:
Transient fault creep on the Xidatan (Tibet) fault driven by viscoelastic relaxation following the 2001 Kokoxili earthquake
Authors: Zhao Dezheng , Qu Chunyan , Shan Xinjian , Bürgmann Roland , Chen Han , Materna Kathryn
Published: August 2022

Recent geodetic observations of shallow fault creep have illuminated increasingly complex, time-dependent slip behaviors, including quasi-steady creep and temporary accelerations, termed slow-slip events. We documented two decades of deformation on the Xidatan fault on the Tibetan Plateau measured by radar interferometry during 2003–2010 and 2015–2020 CE, to probe the temporal evolution of shallow creep and illuminate the underlying mechanisms. The geodetic observations reveal an ~80-km-long fault section with temporally decaying creep along the Xidatan fault, one of the current seismic gaps along the Kunlun fault. The transient creep is likely driven by postseismic deformation processes, dominated by viscoelastic relaxation after the 2001 Kokoxili earthquake, rather than triggered by the coseismic rupture. The transient creep behavior, indicating rate-strengthening frictional properties of the fault, contradicts the inference of locking along the Xidatan fault, based on geodetic imaging before the Kokoxili earthquake and on historical ruptures. We propose that, during the interseismic period, the frictionally unlocked shallow portions of the fault are located in the stress shadow cast by the deeper locked asperities, but they creep at resolvable rates when exposed to transient stress and stressing rate increases. We argue that stress interactions in the triple junction of the Kusai Hu, Xidatan, and Kunlun Pass faults promote complex slip behaviors throughout the earthquake cycle.
Chimeric antigen receptor T cell therapy for cancer: clinical applications and practical considerations
Authors: Maakaron Joseph E , Hu Marie , El Jurdi Najla
Published: August 2022

Chimeric antigen receptor T cells have revolutionized the treatment of hematological malignancies during the past five years, boasting impressive response rates and durable remissions for patients who previously had no viable options. In this review, we provide a brief historical overview of their development. We focus on the practical aspects of a patient’s journey through this treatment and the unique toxicities and current best practices to manage those. We then discuss the key registration trials that have led to approvals for the treatment of relapsed/refractory acute lymphoblastic leukemia (ALL), diffuse large B cell lymphoma (DLBCL), follicular lymphoma, mantle cell lymphoma (MCL), and multiple myeloma. Finally, we consider the future development and research directions of this cutting edge therapy.
Bone marrow mesenchymal stem cell-derived extracellular vesicles facilitate endometrial injury repair by carrying the E3 ubiquitin ligase WWP1
Authors: Wang Xinxin , Wu Junwei , Xie Ya , Liu Yanjie , Feng Wei , Zhang Lirong , Zhao Jing , Meng Hongyu , Chen Baohong , Zhao Qian , Guo Ruixia
Published: August 2022

Bone marrow mesenchymal stem cells-derived extracellular vesicles (BMSC-EVs) relieve endometrial injury. This study aimed to elucidate the BMSC-EV mechanism in alleviating endometrial injury. Endometrial injury model in vivo was induced using 95% ethanol, and endometrial epithelial cells (EECs) treated with mifepristone were applied as an endometrial injury model in vitro. After BMSCs and BMSC-EVs were isolated and identified, the BMSC-EV function was evaluated by hematoxylin–eosin and Masson staining, immunohistochemistry, quantitative real-time PCR, Cell Counting Kit-8 assay, flow cytometry, enzyme-linked immunosorbent assay, and Transwell and tubule formation assays. The BMSC-EV mechanism was assessed using Western blot, ubiquitination, and cycloheximide-chase assays. After isolation and identification, BMSC-EVs were effective in endometrial injury repair in vivo and facilitated EEC proliferation and repressed cell apoptosis in vitro; the EEC supernatants accelerated human umbilical vein endothelial cell proliferation, migration, and invasion and facilitated angiogenesis after endometrial injury in vitro. For the BMSC-EV mechanism, E3 ubiquitin ligase WWP1 in BMSC-EVs mediated the ubiquitination of peroxisome proliferator-activated receptor gamma (PPARγ), thus relieving the PPARγ inhibition on vascular endothelial growth factor expression. Furthermore, the WWP1 in BMSC-EVs alleviated endometrial injury in vitro and in vivo. BMSC-EVs facilitated endometrial injury repair by carrying WWP1.
Application of a multi-objective optimization model for the design of Piano Key Weirs with a fixed dam height
Authors: Azizi Koorosh , Kashani Ali R. , Ebrahimi Saman , Jazaei Farhad
Published: August 2022

Piano Key Weirs (PKWs) have recently been used as new or rehabilitation options in the world because of their advantages in hydraulic performance and construction costs. However, designing an efficient PKW is challenging due to a large and complex set of geometric and hydraulic parameters. Therefore, reaching an optimal PKW design depends on the examination of various geometric combinations and hydraulic parameters. In this study, we applied a multi-objective optimization model known as Non-dominated Sorting Genetic Algorithm-II to determine an optimal design by maximizing hydraulic discharge while minimizing the volume of the concrete. Here, we evaluated the capability of our approach in two separate case studies, one which represented as a rehabilitated weir and other as a new design. Both studies show that the developed approach could significantly reduce the concrete volume per unit of discharge. Moreover, the results show similar patterns in terms of the hydro-economic behavior of the model, which were discussed in three distinguished regions. The unique characteristics of these regions were elaborated, and their most cost-effective values of design parameters were identified. Finally, we discussed how the proposed model and findings of this study could be used for improving the preliminary design of PKWs in practice.
Study of B, $$B_s$$ mesons using heavy quark effective theory
Authors: Gandhi Keval , Rai Ajay Kumar
Published: September 2022

Inspired by the lower statistical information in the bottom sector, in this paper, we calculate the masses and the strong decays of excited B and $$B_s$$

B
s

mesons in the framework of heavy quark effective theory (HQET). Using an effective chiral Lagrangian approach based on heavy quark spin-flavor and light quark chiral symmetry, we explore the flavor independent parameters $$\varDelta _F^{(c)} = \varDelta _F^{(b)}$$

Δ
F

(
c
)

=

Δ
F

(
b
)

and $$\lambda _F^{(c)} = \lambda _F^{(b)}$$

λ
F

(
c
)

=

λ
F

(
b
)

to calculate the masses of experimentally unknown bottom mesons. Our predictions are consistent with the available experimental results and other theoretical studies. Their strong decay to the ground state bottom mesons plus light pseudoscalar mesons is calculated in terms of the square of the couplings $$g_H$$

g
H

, $$g_S$$

g
S

, $$g_T$$

g
T

, $$g_X$$

g
X

, $$g_Y$$

g
Y

, and $$g_R$$

g
R

. The weighted average value of the couplings $$g_H$$

g
H

, $$g_S$$

g
S

and $$g_T$$

g
T

is obtained in the charm sector (Phys. Rev. D 86: 054024, 2012) by fitting the calculated decay widths with experimental measurements, which will be used in the present study to analyze the strong decays of excited open bottom mesons. Moreover, the ratio of the decay rates is also predicted, which can be countered with future experimental data.
Mechanical, thermodynamic properties and phase transition in crystal CaZn2 under high pressure — a DFT study
Authors: Guo Ying , Zhang Xukai , Wang Jiali , Li Jun
Published: August 2022

In this work, a detailed study of the structural, mechanical and thermodynamic changes in CaZn2 under pressure range of 0–40 GPa is performed, and two different exchange correlations (XC) of GGA-PBE and LDA are used. It is found that the enthalpy values imply that CaZn2 undergoes a phase transition from CeCu2-type phase to Laves phase at 3.45 GPa with XC of GGA-PBE and 1.43 GPa with LDA, which is consistent with previous experiments and parts of theoretical conclusions. Furthermore, the elastic stability criterion is used to study the elastic constants of CaZn2 under different pressures, confirming the stability of the CaZn2 structure from 0 GPa to 40 GPa. Finally, the thermodynamic properties of CaZn2 under pressures are comprehensively studied in detail.
End-to-End Automated UI Testing Workflow for Web Sites with Intensive User–System Interactions
Authors: Oguz Ramazan Faruk , Erdem Izzettin , Olmezogullari Erdi , Aktas Mehmet S.
Published: August 2022

The user interface (UI) is the software component with which the end users interact the most in the mobile and web world today. Therefore, when evaluating end-user satisfaction with a software, besides the functional features, the possibilities provided by the UIs are significant. End-user interfaces offer several capabilities today, necessitating a complex structure. Examples include interfaces developed in technologies such as Google Flutter and React. Therefore, we foresee a need for UI testing business workflows allowing comprehensive testing of UIs to improve customer satisfaction. Within the scope of this research, we propose an end-to-end approached automated UI testing business workflow for testing UI components on websites with intense user actions.
Morita contexts and the projective socle property
Authors: Paykan Kamal
Published: August 2022

A ring [Formula: see text] is called a left [Formula: see text]-ring if its left socle, [Formula: see text], is projective. Equivalently, [Formula: see text] is left [Formula: see text]-ring if the right annihilator of every maximal left ideal is of the form [Formula: see text], where [Formula: see text] is an idempotent in [Formula: see text]. In this paper, we characterize when a (trivial) Morita context or a generalized triangular matrix ring is a left [Formula: see text]-ring. Examples to illustrate and delimit the theory are provided.
Wilhelm von Waldenfels (2-3-1932–12-3-2021), a pioneer of quantum probability
Authors: Accardi Luigi
Published: August 2022

This paper is a short account of some of the scientific achievements of Wilhelm von Wldenfels with particular attention to the contributions he gave to quantum probability, a field in which he was one of the pioneers.
Universality theorems for asymmetric spaces
Authors: Alimov A. R.
Published: August 2022

Spaces with asymmetric metric and asymmetric norm are considered. It is shown that any metrizable separable asymmetrically normed linear space [Formula: see text] can be isometrically isomorphic imbedded, as an affine linear manifold, into the classical space [Formula: see text] with uniform norm [Formula: see text]. A similar result is obtained for spaces of density [Formula: see text]. For spaces with asymmetric metric, it is shown that each such space of density [Formula: see text] is isometric to a part of the space [Formula: see text] with the asymmetric seminorm [Formula: see text], where [Formula: see text].
Remote Sensing Image Registration Via Cyclic Parameter Synthesis and Spatial Transformation Network
Authors: Chen Ying , Li Xianjing , Wang Wei , Wang Jiahao , Zhang Wencheng , Shi Yanjiao , Zhang Qi
Published: August 2022

Aiming at the problems of insufficient feature extraction ability, many mismatching points and low registration accuracy of some remote sensing image registration algorithms, this study proposes a remote sensing image registration algorithm via cyclic parameter synthesis spatial transformation network. (1) We propose a feature extraction network framework combined with the improved spatial transformation network and improved Densely Connected Networks (DenseNet), which can focus on important areas of images for feature extraction.This framework can effectively improve the feature extraction ability of the model, so as to improve the model accuracy. (2) In the matching stage, we design the coarse filter and fine filter double filter architecture. Thus, the false matching points are effectively filtered out, which not only improves the robustness of the model but also improves the registration accuracy. Compared with the two traditional methods and two deep learning methods, the experimental results of this model are better in many indexes.
2-Nil submodules of modules over commutative rings
Authors: Mahdou Najib , Moutui Moutu Abdou Salam , Yetkin Celikel Ece
Published: August 2022

In this paper, we extend the notion of 2-nil ideal introduced by Yetkin Celikel in [E. Yetkin Celikel, 2-nil ideals of commutative rings, Bulletin of the Belgian Mathematical Society Simon Stevin 28 (3) (2021).] to 2-nil submodule which is a subclass of 2-absorbing primary submodules. Let [Formula: see text] be an [Formula: see text]-module and [Formula: see text] be a proper submodule of [Formula: see text]. We say that [Formula: see text] is a 2-nil submodule of [Formula: see text] if whenever [Formula: see text], [Formula: see text] and [Formula: see text], then [Formula: see text] or [Formula: see text] or [Formula: see text] We study the properties of this concept and establish several characterizations. We also investigate the 2-nil ideals of amalgamation. The obtained results yield new original families of examples of 2-nil ideals.
Introducing MOWSCER Method for Multiple Criteria Group Decision-Making: A New Method of Weighting in the Structure of Cause and Effect Relationships
Authors: Davoudabadi Reza , Mousavi Seyed Meysam , Zavadskas Edmundas Kazimieras , Dorfeshan Yahya
Published: August 2022

One of the most remarkable subjects in multi-criteria group decision-making (MCGDM) is determining the weight and importance of criteria. The weighting methods based on inputs are categorized in the manifold group. This paper presents a novel method for weighting the criteria in a network structure. This approach, namely MOWSCER, is used when the relationships among the criteria are modeled by a cause-and-effect directed graph. The directed graph demonstrates the cause and effect relationship among criteria. In the presented method, the criteria are divided into three groups. The basic idea of the criteria segmentation is derived from European Foundation for Quality Management (EFQM). These groups include (1) effect criteria, (2) cause criteria, and (3) connector criteria. Then, the connector criteria are allocated fewer weights than the other two types. In other words, the introduced method follows two purposes of decreasing criteria number and appropriate allocating of weights among remaining criteria. Accordingly, first, the connector criteria are detected, so they are assigned less weight, and remained criteria are allocated a proper weight according to their importance. Furthermore, a new weighting method for determining the weights of decision makers (DMs) in group decision-making problems is presented to achieve a comprehensive manner. In the end, to prove the practicality of the proposed method, the weights of criteria and DMs are computed in a case study and two illustrative examples. Besides, to confirm the accuracy of that, it is compared with the DEMATEL method.
Enhanced Thermal Conductivity of Polyimide Insulation Materials Through Boron Nitride Nanosheets Modified by Silver Nanoparticles
Authors: Liu Peidong , Hu Xiaodan , Wu Xinjian , Zhong Yining , Song Shihui , Chang Shuquan , Zhang Haiqian , Zhang Xiaohong
Published: August 2022

Polyimide (PI) is an important engineering material, but its poor thermal conductivity limits its application in the field of electronic packaging. In this work, we prepared boron nitride nanosheets (BNNSs) and boron nitride nanosheets/silver nanoparticles (BNNSs/AgNPs) hybrid fillers which combined successfully with the PI matrix by in-situ polymerization to produce high-thermal-conductivity PI composites. The results showed that when the filler addition was 20[Formula: see text]wt.%, the composites had the best overall performance, and the thermal conductivities of the BNNSs/PI and BNNSs/AgNPs/PI composite films were 0.863[Formula: see text]W[Formula: see text]m[Formula: see text] and 1.175[Formula: see text]W[Formula: see text][Formula: see text][Formula: see text]m[Formula: see text][Formula: see text][Formula: see text][Formula: see text]K[Formula: see text], respectively, which improved 506% and 726%, respectively, compared with pure PI. Furthermore, the volume resistivity of the composites is higher than 10[Formula: see text], indicating an excellent insulating property. At the same time, when used as the thermal interface material (TIM) for light-emitting diode (LED) chips, the composites have significantly improved heat dissipation effect and excellent mechanical properties at 75∘C, which are expected to be widely used in the field of electronic packaging.
Dynamic Learning in Large Matching Markets
Authors: Kalvit Anand , Zeevi Assaf
Published: August 2022

We study a sequential matching problem faced by large centralized platforms where "jobs" must be matched to "workers" subject to uncertainty about worker skill proficiencies. Jobs arrive at discrete times (possibly in batches of stochastic size and composition) with "job-types" observable upon arrival. To capture the "choice overload" phenomenon, we posit an unlimited supply of workers where each worker is characterized by a vector of attributes (aka "worker-types") sampled from an underlying population-level distribution. The distribution as well as mean payoffs for possible workerjob type-pairs are unobservables and the platform's goal is to sequentially match incoming jobs to workers in a way that maximizes its cumulative payoffs over the planning horizon. We establish lower bounds on the regret of any matching algorithm in this setting and propose a novel rate-optimal learning algorithm that adapts to aforementioned primitives online. Our learning guarantees highlight a distinctive characteristic of the problem: achievable performance only has a second-order dependence on worker-type distributions; we believe this finding may be of interest more broadly.
Deploying the Minimum Number of Rechargeable UAVs for a Quarantine Barrier
Authors: Zhu Xiaojun , Han Zhouqing , Tang Shaojie , Xu Lijie , Dong Chao
Published: September 2022

To control the rapid spread of COVID-19, we consider deploying a set of Unmanned Aerial Vehicles (UAVs) to form a quarantine barrier such that anyone crossing the barrier can be detected. We use a charging pile to recharge UAVs. The problem is scheduling UAVs to cover the barrier, and, for any scheduling strategy, estimating the minimum number of UAVs needed to cover the barrier forever. We propose breaking the barrier into subsegments so that each subsegment can be monitored by a single UAV. We then analyze two scheduling strategies, where the first one is simple to implement and the second one requires fewer UAVs. The first strategy divides UAVs into groups with each group covering a subsegment. For this strategy, we derive a closed-form formula for the minimum number of UAVs. In the case of insufficient UAVs, we give a recursive function to compute the exact coverage time and give a dynamic-programming algorithm to allocate UAVs to subsegments to maximize the overall coverage time. The second strategy schedules all UAVs dynamically. We prove a lower and an upper bound on the minimum number of UAVs. We implement a prototype system to verify the proposed coverage model and perform simulations to investigate the performance.
Exogenous pericyte delivery protects the mouse kidney from chronic ischemic injury
Authors: Song Turun , Zhu Xiang-Yang , Eirin Alfonso , Jiang Yamei , Krier James D. , Tang Hui , Jordan Kyra L. , Lerman Amir , Lerman Lilach O.
Published: September 2022

Our study demonstrates a novel pericyte-based therapy for the injured kidney. The beneficial effect of pericyte delivery appears to be mediated by ameliorating oxidative stress, inflammation, cellular apoptosis, and senescence in the stenotic kidney and improved tissue hypoxia, vascular loss, fibrosis, and tubular atrophy. Our data may form the basis for pericyte-based therapy, and additional research studies are needed to gain further insight into their role in improving renal function.
SLC41A1 knockout mice display normal magnesium homeostasis
Authors: Ilenwabor Barnabas P. , Franken Gijs A. C. , Sponder Gerhard , Bos Caro , Racay Peter , Kolisek Martin , Hoenderop Joost G. J. , de Baaij Jeroen H. F.
Published: September 2022

SLC41A1 has been hypothesized to mediate Mg2+ extrusion in the distal convoluted tubule and thus regulate Mg2+ homeostasis. This study investigated the role of SLC41A1 in Mg2+ homeostasis in vivo using a transgenic mouse model. Our results demonstrate that SLC41A1 is not required to maintain normal Mg2+ balance in mice. We also show that SLC41A3 is more important than SLC41A1 in regulating systemic Mg2+ levels.
Clonal hematopoiesis, somatic mosaicism, and age-associated disease
Authors: Evans Megan A. , Walsh Kenneth
Published: September 2022

Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.
A Hybrid Algorithm of Ant Colony and Benders Decomposition for Large-Scale Mixed Integer Linear Programming
Authors: Shan Tingting , Qiu Zhaoxuan
Published: August 2022

The mixed integer linear programming (MILP) has been widely applied in many fields such as supply chain management and robot control, while how to develop a more efficient algorithm to solve large-scale MILP is still in discussion. This study addresses a hybrid algorithm of the ant colony and Benders decomposition to improve the efficiency. We firstly introduce the design of our algorithm, in which the Benders algorithm decomposes the MILP into a master problem and a slack problem, the ant colony algorithm generates initial solutions for the master problem, and heuristic rules obtain feasible solutions for the slack problem. Then, the computational experiments are carried out to verify efficiency, with a benchmark test and some medium-large scale examples. Compared with other algorithms like CPLEX, GUROBI, and traditional ACA, our algorithm shows a better performance with a 0.3%–4.0% optimality gap, as well as a significant decrease of 54.3% and 33.6% on average in the CPU time and iterations, respectively. Our contribution is to provide a low-workload, time-saving, and high-accuracy hybrid algorithm to solve MILP problems with a large amount of variables, which can be widely used in more commercial solvers and promote the utilization of the artificial intelligence.
[Retracted] The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
Authors: Li Fangfang , Gu Le , Xu Hongchao
Published: September 2022

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate data resources and rich and reliable educational technology means for online public mental health education in colleges and universities. This paper comprehensively uses a variety of methods such as qualitative and quantitative analysis, case and empirical analysis, literature analysis, and artificial intelligence technology. Artificial intelligence technology has been closely integrated with online public mental health education in colleges and universities. The model systematically analyzes the optimization methods of artificial intelligence technology methods for the online public mental health education system in colleges and universities, and constructs an innovation system for online public mental health education in colleges and universities. Based on the comprehensive analysis of artificial intelligence and public health in colleges and universities, this paper further proposes the application of artificial intelligence technology in online public mental health education in colleges and universities. On this basis, the model conducts an in‐depth analysis of artificial intelligence technology and the online public mental health innovation system. The model supports the development of ideological and political teaching in colleges and universities through various forms such as idea innovation, path innovation, carrier innovation, and mechanism innovation.
A Self-Powered Sport Sensor Based on Triboelectric Nanogenerator for Fosbury Flop Training
Authors: Geng Fengjie , Huo Xiaoliang
Published: September 2022

Due to the high efficiency of low-frequency mechanical energy harvesting, wearable and flexible self-powered sport sensor based on triboelectric nanogenerators (TENGs) have become the hot research topic. Thus, we report a flexible and wearable cotton fabric (CF) coated with carbon oil- (CO-) based TENG (CC-TENG) with low processing costs, good electrical properties, and long working life. Meanwhile, we use a piece of flexible, microfibre-woven CF as the substrate for the CO. Moreover, the fibre surface characteristics of the cotton fabric provide higher surface roughness, which can make the TENG device work better. In detail, the CO layer serves as the triboelectric material and conductive electrode. According to the results, the CC-TENG shows good reliability, and the electric energy generated by CC-TENG can drive low-power electronic devices. Significantly, CC-TENG device can be applied to fosbury flop training to obtain training data and motion information monitoring, which will promote the wearable intelligent sports device.
Detection and Analysis of Human Cells Based on Artificial Neural Network
Authors: Yao Jun , Yuan Hongji
Published: August 2022

The detection and classification of histopathological cell images is a hot topic in current research. Medical images are an important research direction and are widely used in computer-aided diagnosis, biological research, and other fields. A neural network model based on deep learning is also common in medical image analysis and automatic detection and classification of tissue and cell images. Current medical cell detection methods generally do not consider that the yield is affected by other factors in the topological region, which leads to inevitable errors in the accuracy and generalization of the algorithm; at the same time, the current medical cell imaging methods are too simple to predict the classification markers, which affect the accuracy of cell image classification. This study introduces the concepts of two kinds of neural networks and then constructs a cell recognition model based on the convolution neural network principle and staining principle. In the experimental part, we developed three groups of experiments using the same equation as the experiment and tested the best cell recognition model proposed in this study.
Spatial Distribution, Seasonal Dynamics, and Sex Ratio of Lycorma delicatula (Hemiptera: Fulgoridae) Adults on Tree of Heaven
Authors: Liu Houping , Hunter Matthew
Published: August 2022

The spatial distribution and seasonal dynamics of the spotted lanternfly (Lycorma delicatula) on tree of heaven (Ailanthus altissima) were studied in Pennsylvania through weekly sampling of 30 trees (6 sites, 5 trees/site) from 27 July to 8 November 2020. Adults found on each tree were separated into six within-tree positions (lower trunk, middle trunk, upper trunk, first branch, second branch, and above second branch) by four directions (East, South, West, and North). In total, 78,796 adults were counted at the six study sites during the 15-week period. Significant differences in total adult count were found among trees, with a mean of 2,627 (254–12,023) adults/tree. Study site, tree diameter, and cardinal direction had no significant impact on adult spatial distribution. However, significantly more adults were found on the middle (1077), the lower (865), and the upper trunk (337) compared with the first (194), the second (93), and above second branches (60). Most adults were congregated on the lower and middle trunks. Seasonal dynamics followed adult development and migration patterns in the field, with peak populations observed in weeks 35 (24–30 August) and 37 (7–13 September) before declining. Female-based sex ratios ranged from 77.3 to 100% according to weekly monitoring of the lower 1 m trunk of 10 trees at 2 sites (5 trees/site) for 12 weeks from 17 August to 8 November, with 7,356 females and 197 males counted, respectively. Impact factors such as attack patterns, intraspecific congregation, adult seasonality, and sexual dimorphism in host selection are discussed.
Chemical Analysis of Hematite Ore Collected from Pokhari, Nawalparasi, Nepal
Authors: Gharti Ram Bahadur , Oli Hari Bhakta , Bhattarai Deval Prasad
Published: August 2022

Iron is the principal raw material for steel industries and Hematite is a principal ore of iron. Quantitative and qualitative estimation of iron in its ores is a crucial factor before its extraction. In this work, quantitative chemical analysis of iron was carried out from the collected seventy-two hematite samples from Pokhari, Nawalparasi. Sampling of the hematite ore was performed by channel sampling method. Chemical analysis was carried out by gravimetric, titrimetric, UV-Vis spectrophotometric and atomic absorption spectroscopic methods. The findings of different parameters in percentage areas follows: loss on ignition (1.76 ± 0.17), silica (47.06 ± 4.01), and iron (36.75 ± 2.50) by titrimetric analysis. Based on the chemical analysis, the Fe content in the collected hematite sample is in intermediate range. Thus, for the profitable iron extraction, other factors such as coverage of ores, extraction costs, and market value should be considered.
Analysis of Balance of Income and Expenditure and Optimal Retirement Age of Pension Insurance Co-Ordination Account Based on Improved Machine Learning Algorithm
Authors: Yan Shi , Zhou Yaodong , Zhang Youlu
Published: August 2022

Since the turn of the twenty-first century, the issue of aging has gained international attention. Both developed and developing nations are currently dealing with this issue. To ensure the sustained and healthy growth of the economy and society in the face of an aging society, it is especially important to establish a scientific old-age insurance system and a reasonable retirement system. We are all aware that the key indicators for the state to control the old-age insurance system in the old-age insurance system are the income and expenditure balance of the old-age insurance pooling account and the analysis of the ideal retirement age. In this paper, a better machine algorithm is used. By independently learning the rules present in a large amount of data and gaining new experience and knowledge, machine learning (ML) can increase computer intelligence and give computers decision-making abilities comparable to those of humans. In general, a machine learning algorithm uses the laws it derives from data to predict unknown data after automatically analysing the data. This study’s findings suggest that the ideal retirement age and life expectancy are positively correlated, with the ideal retirement age’s growth rate 12.57 percent higher than that of life expectancy.
HPV‐Induced MiR‐21 Promotes Epithelial Mesenchymal Transformation and Tumor Progression in Cervical Cancer Cells through the TGFβ R2/hTERC Pathway
Authors: Han Ying , Li Qiuhong , Ling Chenqi , Jin Ming , Li Dongdong , Zhong Jie , Wang Li
Published: September 2022

Cervical cancer (CC) is a common malignant tumor in women. It ranks first among the malignant tumors of woman reproductive organs and is one of the most important cancers in the world. Current studies suggest that human papillomavirus (HPV) infection, especially high‐risk persistent infection, is the basic cause of cervical precancerous lesions and cervical cancer. MicroRNA‐21 (miR‐21) plays a role similar to oncogenes in the occurrence and growth of malignant tumors and can be developed as a potential target for treating malignant tumors. Recently, the study of the mechanism of malignant invasion and metastasis has made great progress. The current consensus is that the invasion and metastasis of malignant tumors is a complicated biological process with multistep and multigene control; the process of epithelial mesenchymal transition (EMT) may be the initial event of invasion and metastasis of epithelial malignant tumors. EMT means that epithelial cells obtain the characteristics of mesenchymal cells, which has main characteristics such as the loss of epithelial cell characteristics and the achievement of mesenchymal cell features, and then induce epithelial cells to acquire the ability of migration and invasion, and participate in many physiological and pathological processes of human body, including embryogenesis, organ differentiation, tissue inflammation, and wound healing. Research has proved that miR‐21 is associated with the invasion and metastasis of cervical cancer, and its specific mechanism has not been completely clear; EMT exerts a significant effect on the invasion and metastasis of epithelial malignant tumors; we speculate whether miR‐21 regulates the EMT process of cervical cancer cells. ELISA and RT‐PCR studied HPV‐induced cervical cancer cells, and it was found that HPV may induce miR‐21 to pass through the TGF β R2/hTERC pathway which promotes epithelial stromal transformation and tumor progression of cervical cancer cells.
Shafting Misalignment Malfunction Quantitative Diagnosis Based on Speed Signal SVD-HT and CSF-PPSO-ESN Method
Authors: Yu Zhen , Yu Wancheng
Published: August 2022

Aiming at the quantitative diagnosis of shafting misalignment malfunction, a novel method based on speed signal with singular value decomposition and Hilbert transform (SVD-HT) and cubic spline fitting-Pareto particle swarm optimization-echo state network (CSF-PPSO-ESN) method is proposed. The malfunction diagnosis mechanism based on the speed signal is obtained by constructing the shaft misalignment malfunction model. Then, the SVD-HT and CSF-PPSO-ESN methods are applied to obtain the relationship between the shaft misalignment malfunction and the amplitude of the time and the rotation frequency (fr) component of the speed signal. The parameters of the CSF-PPSO-ESN method are settled according to the shaft misalignment malfunction and the fr component of the speed signal. The accuracy of the proposed method is verified by using the fr component of the speed signal and the trained CSF-PPSO-ESN to obtain the value of the shaft misalignment malfunction. The repeating experimental results show that the diagnosing error of the shaft misalignment malfunction can reach less than ±10 μm. The method presented in this paper provides a novel way to diagnose shaft misalignment malfunction quantitatively.
Improved Efficient Privacy-Preserving Certificateless Provable Data Possession Scheme for Cloud Storage
Authors: Li Xiuguang , Li Ruifeng , Wang Xu An , Niu Ke , Li Hui , Yang Xiaoyuan
Published: August 2022

Cloud storage technology is evolving at a high speed; effectively auditing the cloud data’s integrity has become a focal point. Recently, Ming and Shi proposed a certificateless integrity auditing scheme with a privacy protection function. The scheme used the certificateless cryptosystem to solve the certificate management problem of the auditing schemes based on public key infrastructure and the key escrow problem of the identity-based auditing schemes. Although their scheme is novel and efficient, we found that their scheme was not secure and could not achieve integrity auditing of cloud data. The malicious cloud server can generate the proof through the blocks and tags sent by the user. On the basis of the original scheme, we propose an improved auditing scheme; our new scheme is more secure and effective. In addition, for the problem of idle tags in the existing cloud data integrity auditing scheme, we propose the idea of intermediate tags and we applied the idea to the improved scheme to improve audit efficiency.
IOT-Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms
Authors: Rokade Ashay , Singh Manwinder , Arora Sandeep Kumar , Nizeyimana Eric
Published: August 2022

In the farming industry, the Internet of Things (IoT) is crucial for boosting utility. Innovative agriculture practices and medical informatics have the potential to increase crop yield while using the same amount of input. Individuals can benefit from the Internet of Things in various ways. The intelligent farms require the creation of an IoT-based infrastructure based on sensors, actuators, embedded systems, and a network connection. The agriculture sector will gain new advantages from machine learning and IoT data analytics in terms of improving crop output quantity and quality to fulfill rising food demand. This paper described an intelligent medical informatics farming system with predictive data analytics on sensing parameters, utilizing a supervised machine learning approach in an intelligent agricultural system. The four essential components of the proposed approach are the cloud layer, fog layer, edge layer, and sensor layer. The primary goal is to enhance production and provide organic farming by adjusting farming conditions as per plant needs that are considered in experimentation. The use of machine learning on acquired sensor data from a prototype embedded model is investigated for regulating the actuators in the system. Then, an analytics and decision-making system was built at the fog layer, employing two supervised machine learning approaches including classification and regression algorithms using a support vector machine (SVM) and artificial neural network (ANN) for effective computation over the cloud layer. The experimental results are evaluated and analyzed in MATLAB software, and it is found that the classification accuracy using SVM is much better as compared to ANN and other state of art methods.
A Fast Data Transmission Method of Vehicle-Road Cooperative Communication Based on the Clustering Algorithm
Authors: Wang Weifeng , Wang Zijian , Xu Yang , Yao Xinpeng , Ma Yulin
Published: September 2022

In order to improve the security and stability of data transmission in vehicle-road cooperative communication and reduce the error rate of data transmission, a fast data transmission method based on the clustering algorithm is proposed. First, the multisensor information acquisition method of the vehicle networking is used to realize data acquisition and data structure analysis of the vehicle-road cooperative communication, and a data transmission channel model for vehicle-road cooperative communication is constructed. The interference suppression in the data transmission process of the vehicle-road cooperative communication is realized by the matched filter detection algorithm. Then, according to the symbol characteristic distribution of the vehicle-road cooperative communication channel, the baud interval equalization method is used to realize the piecewise equalization adjustment of data transmission for the vehicle-road cooperative communication. With the adaptive error compensation and channel fading suppression, the K-means clustering algorithm is used to carry out the coordinated adjustment to data packets during the rapid data transmission of the vehicle-road cooperative communication. Finally, the adaptive control of data transmission for the vehicle-road cooperative communication is carried out according to the dynamic distribution characteristics of the clustering center so as to reduce the influence of channel fading and intersymbol interference caused by channel spread. The simulation results show that the bit error rate of this method is kept at about 0.05, and the data transmission rate continues to increase, most of which remain above 0.95. This method has strong anti-interference ability for the rapid data transmission of vehicle-road cooperative communication, with lower communication bit error rate, less end-to-end time delay, and higher stability and accuracy of data transmission.
Forced Eruption: Alternative Treatment Approach to Restore Teeth with Subgingival Structure
Authors: Kermanshah Hamid , Najafrad Elmira , Valizadeh Sara
Published: September 2022

The management of teeth with deep caries, fracture, or perforation in the cervical third of the root is an integral part of dental practice. Orthodontic extrusion preserves the natural root system and may convert the tooth indicated for extraction into useful tooth with good prognosis and a low risk of failure. Orthodontic tooth eruption can be an alternative to treatment such as surgical crown lengthening, especially in esthetic areas, and provides more favorable conditions for prosthodontic coronal restorations by guaranteeing proper sealing and esthetics and preserving periodontal tissue health. The aim of this case report was to explain a multidisciplinary approach that successfully preserve and treat the teeth with subgingival carious lesion. This innovative method is cost-effective and can be easily done with the equipment available in any office.
Postmarketing Reevaluation of Chinese Traditional Therapy Kangbingdu Oral Liquid in the Treatment of the Common Cold
Authors: Li Hongjiao , Ai Yanke , Zhao Tianyi , Zhang Di , Lv Xiaoying , Jia Shaoyan , Wen Zehuai , Li Guoxin , Wang Hongyu , Gao Feng , Li Shaohong , Ge Zhishan , Qin Yuning , Wang Zhenbiao , He Liyun
Published: September 2022

Background. Observational studies from China suggest that Kangbingdu oral liquid (KBD) may be effective in treating the common cold. Objective. Reevaluation of efficacy and safety of Kangbingdu oral liquid after marketing and expanding population. Design. Prospective, Pragmatic randomized controlled trial (Chictr.org.cn registration number: chiCTR-TRC-12002399). Setting. Eleven hospitals from 3 provinces in China. Patients were recruited through 11 centers, including 7 teaching hospitals, 2 University health services, one military clinic, and one community hospital. Patients. 2647 persons aged 18 to 75 years with Common cold. Intervention. Patients were randomly allocated to 2 groups: the treatment group Kangbingdu oral liquid (composed of 9 Chinese herbal medicines and honey) and the placebo group were divided into a standard-dose group of 10 ml every time, a middle dose group of 20 ml every time, high dose group of 30 ml every time, 3 times daily. Interventions and control were given for 5 days. Measurements. The primary outcome is the mean amount of total scores measured by the 11-primary symptoms: to observe the change of main symptoms from severe to disappear and to calculate and compare the mean amount of total scores after the periods of observation. Secondary outcomes are the disappearance rate of each symptom and the median time of body temperature returned to normal. Results. On day 5, the Kangbingdu liquid group had significant reductions in the mean amount of total scores measured by the 11-primary symptoms (7.39 [95% CI 7.26 to 7.51] compared to the placebo group (6.43 [95%: CI 6.24 to 6.62]). The Kangbingdu liquid can improve the remission rate of accompanying symptoms on day 5 including aversion to wind, aversion to cold, fever, cough, stuffy, runny nose, sore throat, muscular aches, headache, fatigue, and sweat (

P
<
0.0001

). Significant reductions in time of body temperature to return to normal in the Kangbingdu liquid group (P50, 48.33 [95% CI 46.00 to 52.50] compared with the control group (P50, 64.59 [95% CI 51.08 to 70.50] (

P
=
0.0022

). 13 (0.7%) participants in the Kangbingdu liquid group and 1(0.2%) participants in the placebo group (

P
>
0.05

) had treatment-related AEs, which mainly include diarrhea and dyspepsia in the Kangbingdu liquid group and constipation in the placebo group. Conclusion. The study’s conclusion in this paper was based on the placebo, Kangbingdu oral liquid two groups which clinically diagnosed the common cold and flu. (1) Kangbingdu oral liquid can effectively improve the comprehensive clinical symptoms of common adult cold, also improved main symptoms, including sore throat, muscle aches, headache, and so on. (2) Kangbingdu oral liquid effectively shortens the time of body temperature to return to normal.
Facts and Hopes in Cancer Antigens Recognized by T Cells
Authors: Brochier Walther , Bricard Orian , Coulie Pierre G.
Published: August 2022

T cells are key effectors of our immune response against tumors and exert their antitumor effects upon recognizing a variety of tumor-specific peptides presented by HLA molecules on the surface of tumor cells. The identification of the tumor-specific antigens of a given tumor is not required for immune checkpoint therapy (ICT), which mainly reactivates existing tumor-specific T cells together with T cells of unknown specificities. To decrease the activation of non–tumor-specific T cells, active or passive immunizations against tumor-specific antigens are considered. These immunizations require the identification of at least some of the tumor-specific antigens displayed on the tumor cells of a patient. While this has become an easy task for tumors with a large number of mutations generating neoantigens, it remains difficult for the remainder. Here, we review some facts about human tumor-specific or tumor-associated antigens, as well as some hopes for their future use in cancer immunotherapy.