bluuebunny/crossref_metadata_2025 huggingface dataset:
What I wish I’d known: How experienced physician managers diagnose, treat and prevent disruptive behaviour
Authors: Goodwin Christian , Haas Susan , Berry William
Published: August 2022

As health systems continue to consolidate at a rapid pace, many physicians are stepping into roles that involve managing other physicians. While more physicians are thrust into these positions each year, the managerial training they receive is highly variable and often insufficient for dealing with the challenges they will face, notably disruptive behaviour. Broadly defined, disruptive behaviour includes any actions that affect a team’s ability to effectively care for patients, and can even threaten patient and provider health. New physician managers--who typically have little prior experience in management roles--need specific supports to address this uniquely daunting challenge.

Over our management careers, we have spoken with dozens of new and experienced physician managers to understand how they manage disruptive behaviour in the workplace and to collect their advice for future physician managers. In this paper, we reflect on those conversations and distill them into a three-part approach for diagnosing, treating and preventing disruptive behaviour in the workplace. We describe how the right management approach depends on a thorough assessment of the most likely drivers of the disruptive behaviour. Second, we present strategies for treating the behaviour focusing on the physician leader’s communication skills and available institutional resources. Finally, we advocate for system-level changes that institutions or departments can implement both to prevent disruptive behaviour and to better prepare new managers to address it.
Pilot study of jadomycin B pharmacokinetics and anti-tumoral effects in zebrafish larvae and mouse breast cancer xenograft models
Authors: McKeown Brendan T. , Relja Nicholas J. , Hall Steven R. , Gebremeskel Simon , MacLeod Jeanna M. , Veinotte Chansey J. , Bennett Leah G. , Ohlund Leanne B. , Sleno Lekha , Jakeman David L. , Berman Jason N. , Johnston Brent , Goralski Kerry B.
Published: August 2022

Despite numerous therapeutic options, multidrug resistance (MDR) remains an obstacle to successful breast cancer therapy. Jadomycin B, a natural product derived from Streptomyces venezuelae ISP5230, maintains cytotoxicity in MDR human breast cancer cells. Our objectives were to evaluate the pharmacokinetics, toxicity, anti-tumoral, and anti-metastatic effects of jadomycin B in zebrafish larvae and mice. In a zebrafish larval xenograft model, jadomycin B significantly reduced the proliferation of human MDA-MB-231 cells at or below its maximum tolerated dose (40 µm). In female Balb/C mice, a single intraperitoneal dose (6 mg/kg) was rapidly absorbed with a maximum serum concentration of 3.4 ± 0.27 µm. Jadomycin B concentrations declined biphasically with an elimination half-life of 1.7 ± 0.058 h. In the 4T1 mouse mammary carcinoma model, jadomycin B (12 mg/kg every 12 h from day 6 to 15 after tumor cell injection) decreased primary tumor volume compared to vehicle control. Jadomycin B-treated mice did not exhibit weight loss, nor significant increases in biomarkers of impaired hepatic (alanine aminotransferase) and renal (creatinine) function. In conclusion, jadomycin B demonstrated a good safety profile and provided partial anti-tumoral effects, warranting further dose-escalation safety and efficacy studies in MDR breast cancer models.
The interactive effect of vitamin D3 supplementation and vitamin D receptor polymorphisms on weight and body composition in overweight women with hypovitaminosis D: a randomized, double-blind, placebo-controlled clinical trial
Authors: Ebrahimof Samira , Angoorani Pooneh , Shab-Bidar Sakineh , Abedidni Somayeh , Jahangir Farzaneh , Hedayati Mehdi
Published: August 2022

Different responses to vitamin D supplementation may be due to genes involved in vitamin D metabolism, including the vitamin D receptor ( VDR) gene. The present study aimed to determine the interactive effect of vitamin D supplementation and VDR polymorphisms, including FokI (rs2228570) and BsmI (1544410) on weight and body composition in overweight women with hypovitaminosis D. This study comprised two phases: a double-blind, randomized and a before-after clinical trial. In the first phase, 50 healthy overweight women aged 20–45 years with hypovitaminosis D were randomly categorized into intervention and control groups and were given 50 000 IU/w vitamin D3 or placebo for 12 weeks. In the second phase, 75 women received 50 000 IU/w of vitamin D3 for 12 weeks. All variables were measured at baseline and after 12 weeks. Circulating 25(OH)D was measured using an ELISA kit. Anthropometric indices were calculated according to standard protocol (WHO-TRH-854). Body composition was determined using the body impedance analysis method. The VDR polymorphisms were detected using the PCR sequence. Supplementation resulted in a significant increase in the level of 25(OH)D in the intervention group but did not affect the anthropometric profile of the subjects. When considering FokI genotypes, carriers of the FF genotype had higher fat mass reduction than carriers of Ff +  ff genotypes.
News sharing on Twitter reveals emergent fragmentation of media agenda and persistent polarization
Authors: Cicchini Tomas , del Pozo Sofia Morena , Tagliazucchi Enzo , Balenzuela Pablo
Published: August 2022

News sharing on social networks reveals how information disseminates among users. This process, constrained by user preferences and social ties, plays a key role in the formation of public opinion. In this work, we used bipartite news-user networks to study the news sharing behavior of main Argentinian media outlets in Twitter. Our objective was to understand the role of political polarization in the emergence of high affinity groups with respect to news sharing. We compared results between years with and without presidential elections, and between groups of politically active and inactive users, the latter serving as a control group. The behavior of users resulted in well-differentiated communities of news articles identified by a unique distribution of media outlets. In particular, the structure of these communities revealed the dominant ideological polarization in Argentina. We also found that users formed two groups identified by their consumption of media outlets, which also displayed a bias towards the two main parties that dominate the political life in Argentina. Overall, our results consistently identified ideological polarization as a main driving force underlying Argentinian news sharing behavior in Twitter.
Constructing viable quark mass matrices in the flavor basis using S3 × Z3 symmetry
Authors: Garg Mahak , Channey Kanwaljeet S. , Vashisht Aseem , Ahuja Gulsheen , Gupta Manmohan
Published: August 2022

Non-Abelian discrete symmetry group [Formula: see text] has been used to construct quark mass matrices in the flavor basis. Interestingly, the case when [Formula: see text] is nondiagonal and [Formula: see text] is diagonal, is very much compatible with the presently refined data regarding the quark masses and mixing. However, the other case, when [Formula: see text] is nondiagonal and [Formula: see text] is diagonal, looks to be incompatible with the data.
Research on Fast Recognition of Vulnerable Traffic Participants in Intelligent Connected Vehicles on Edge Computing
Authors: Gu Musong , Lyu Jingjing , Li Zhongwen , Yan Zihan , Fan Wenjie
Published: August 2022

Real-time and fast recognition of all kinds of traffic participants in intelligent driving has always been a major difficulty in the research of internet of vehicles. With the advent of edge computing, we try to deploy an image recognition algorithm directly to the intelligent vehicles. However, the original image recognition algorithm is difficult to be directly deployed on the vehicles due to limited edge device resources. Based on this, a fast recognition model of vulnerable traffic participants based on depthwise separable convolutional neural network (DSCYOLO) is proposed in this paper. The algorithm can significantly reduce the convolutional parameter quantity and computing load, making it suitable for deployment on the vehicle-mounted edge embedded devices. In order to validate the effectiveness of the proposed method, its simulation results are compared with the main target detection models Faster R-CNN, SSD and YOLOv3. The results show that the recognition time of the proposed model is reduced by 80.28%, 66.80% and 86.74%, respectively, on the basis of a relatively high recognition precision. The model can realize real-time detection and fast recognition of vulnerable traffic participants, so as to avoid a large number of traffic accidents. It has significant social and economic benefits.
MACHINE LEARNING-BASED MODELING AND OPTIMIZATION IN HARD TURNING OF AISI D6 STEEL WITH ADVANCED AlTiSiN-COATED CARBIDE INSERTS TO PREDICT SURFACE ROUGHNESS AND OTHER MACHINING CHARACTERISTICS
Authors: DAS ANSHUMAN , DAS SUDHANSU RANJAN , PANDA JYOTI PRAKASH , DEY ABHIJIT , GAJRANI KISHOR KUMAR , SOMANI NALIN , GUPTA NITIN KUMAR
Published: August 2022

In recent times, mechanical and production industries are facing increasing challenges related to the shift towards sustainable manufacturing. In this work, the machining was performed in dry cutting condition with the newly developed AlTiSiN-coated carbide inserts coated through scalable pulsed power plasma technique, and a dataset was generated for different machining parameters and output responses. The machining parameters are speed, feed and depth of cut, while the output responses are surface roughness, cutting force, crater wear length, crater wear width and flank wear. Abrasion and adhesion were found to be the two dominant wear mechanisms. With speed, the tool wear was found to increase. Cutting force was found to increase rapidly for higher speed ranges (70, 80 and 90[Formula: see text]m/min). But reduction of cutting force was observed in both low and medium ranges of cutting speed (40, 50, 55 and 60[Formula: see text]m/min). With higher values of feed and depth of cut, higher cutting force was also noticed. With the variation of depth of cut, the machined surface morphology and machined surface roughness were found to deteriorate. With higher feed and depth of cut values, more surface damages were observed compared to low values of feed and depth of cut. Both the feed rate and tool–chip contact length contributed significantly to the formation of crater on the tool rake surface. At high speed, continuous chips were observed. Both chip sliding and sticking were observed on the tool rake face. The data collected from the machining operation was used for the development of machine learning (ML)-based surrogate models to test, evaluate and optimize various input machining parameters. Different ML approaches such as polynomial regression (PR), random forests (RF) regression, gradient boosted (GB) trees and adaptive boosting (AB)-based regression were used to model different output responses in the hard machining of AISI D6 steel. Out of the four ML methodologies, RF and PR performed better in comparison to the other two algorithms in terms of the [Formula: see text] values of predictions. The surrogate models for different output responses were used to prepare a complex objective function for the germinal center algorithm-based optimization of the machining parameters of the hard turning operation.
Coupled and uncoupled sign-changing spikes of singularly perturbed elliptic systems
Authors: Clapp Mónica , Soares Mayra
Published: August 2022

We study the existence and asymptotic behavior of solutions having positive and sign-changing components to the singularly perturbed system of elliptic equations [Formula: see text] in a bounded domain [Formula: see text] in [Formula: see text], with [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]. If [Formula: see text] is the unit ball we obtain solutions with a prescribed combination of positive and nonradial sign-changing components exhibiting two different types of asymptotic behavior as [Formula: see text]: solutions whose limit profile is a rescaling of a solution with positive and nonradial sign-changing components of the limit system [Formula: see text] and solutions whose limit profile is a solution of the uncoupled system, i.e. after rescaling and translation, the limit profile of the [Formula: see text]th component is a positive or a nonradial sign-changing solution to the equation [Formula: see text]
Multiple positive and sign-changing solutions for a class of Kirchhoff equations
Authors: Li Benniao , Long Wei , Xia Aliang
Published: August 2022

This paper is concerned with the existence of multiple non-radial positive and sign-changing solutions for the following Kirchhoff equation: [Formula: see text] where [Formula: see text] are constants, [Formula: see text], [Formula: see text] is a parameter, and [Formula: see text] is a potential function. Under the assumption on [Formula: see text] with exponential decay at infinity, we construct multi-peak positive and sign-changing solutions for problem (0.1) as [Formula: see text] (or [Formula: see text]), where the peaks concentrate at infinity.
INVESTIGATION OF FRACTURE-RESISTANCE OF HUMAN TEETH AT THE DENTIN–ENAMEL JUNCTION USING THE J-INTEGRAL CALCULATION OF FINITE ELEMENT ANALYSIS
Authors: ZHU XINYAO , WANG SHAOWEI , YE JING , GUO HONGLEI , WANG RONG
Published: August 2022

Most human teeth have an exposed surface layer of calcified enamel, which is harder than the inner layer of dentin. The interface between the enamel and dentin is called the dentin–enamel junction (DEJ), which ensures that teeth do not collapse and fall off. The purpose of this study was to use finite element analysis software through the [Formula: see text]-integral method and the extended finite element method (XFEM) to simulate three models of DEJ structures: (i) wavy DEJ with no thickness, (ii) rectangle DEJ with a thickness of 0.3[Formula: see text]mm, and (iii) wavy DEJ with a thickness of 0.3[Formula: see text]mm. This paper demonstrates that the layered structure of human teeth plays a positive role in enhancing the fracture strength and preventing the crack from spreading to the depths of teeth. At the same time, we also justify of the scalloped structure and concave orientation of the DEJ interface. The residual stresses in DEJ and its adjacent dentin region are also an important factor of tooth resistance to crack propagation. In addition, the configuration of the DEJ interface and residual stresses in DEJ and dentin areas are further justified by means of XFEM method. The findings in this study provide potential inspiration for the biomimetic design toward strengthening the dentin and dentin-like materials.
Stabilization of Stochastic Exchange Rate Dynamics Under Central Bank Intervention Using Neuronets
Authors: Mourtas Spyridon D. , Katsikis Vasilios N. , Drakonakis Emmanouil , Kotsios Stelios
Published: August 2022

The exchange rate dynamics affect national economies because fluctuations in currency prices distort their economic activity. To maintain an optimal exchange rate policy, these dynamics are crucial for countries with a trade economy. Due to the difficulty in predicting the participants behavior in some complex economic systems, which might throw the system into chaos, a novel stochastic exchange rate dynamics (SERD) model is introduced and investigated in this paper. Furthermore, a neural network approach is proposed and examined as a control chaos method to address the problem of stabilizing SERD through central bank interventions. Derived from power activation feed-forward neuronets, a 2-input weights-and-structure-determination-based neuronet (2I-WASDBN) model for controlling chaos in SERD under central bank intervention is presented in this paper. Six simulation experiments on stabilizing the chaotic behavior of the SERD model show that the 2I-WASDBN model outperforms other well-performing neural network models and that it is more effective than traditional methods for controlling chaos. By examining the volume of necessary intervention predicted by the 2I-WASDBN model, central banks can better comprehend exchange rate fluctuations and, in conjunction with their monetary policies, can make more precise decisions regarding the strategy of their interventions.
Parallel Scheduling of Machines, Tool Transporter and Tools in a Multi Machine FMS with Alternative Routing Using Flower Pollination Algorithm
Authors: Reddy N. Sivarami , Lalitha M. Padma , Ramamurthy D. V. , Rao K. Prahlada
Published: August 2022

Scheduling jobs and tools is a significant problem for manufacturing systems. Inefficient job scheduling and tool loading planning may result in the underutilization of capital-intensive machines and a high machine idle time. Tools are transferred by a tool transporter (TT) between machines. Therefore, efficient scheduling of jobs, TT, and the tools with alternate machines enables a manufacturing system to increase machines’ utilization and decrease their idle times. This paper addresses machines, TT, and tools concurrent scheduling with alternate machines and only one copy of every tool variety is made available where the tools are costly, in a multi-machine flexible manufacturing system, taking into account tool transfer times for makespan (MS) minimization. The tools are placed in a central tool magazine, which shares and serves them to many machines to cut down the price of duplicating the tools in each machine. The problem is to assign machines from alternate machines, tools, and corresponding TT trips, including the deadheading trip and loaded trip, to job operations for MS minimization. This paper uses a nonlinear mixed-integer programming framework to present the problem, and a flower pollination algorithm (FPA) is employed to solve it. The results show that FPA outperforms the Jaya algorithm, and the usage of alternate machines for the operations reduces the MS. Reduction in MS indicates an improvement in utilization of resources.
Concurrent Scheduling of Machines and AGVS in Multi-Machine FMS with Alternative Routing Using Symbiotic Organisms Search Algorithm
Authors: Reddy N. Sivarami , Lalitha M. Padma , Ramamurthy D. V. , Rao K. Prahlada
Published: August 2022

This paper addresses machines and automated guided vehicles (AGVs) simultaneous scheduling with alternative machines in a multi-machine flexible manufacturing system (FMS) to produce the best optimal sequences for the minimization of makespan (MKSN). This problem is highly complex to solve because it involves the selection of machines for job operations (jb-ons), the sequencing of jb-ons on the machines, the assignment of AGVs, and associated trips such as AGVs’ deadheaded trip and loaded trip times to jb-ons. This paper offers a nonlinear mixed integer programming (MIP) formulation for modeling the problem and the symbiotic organisms search algorithm (SOSA) for solving the problem. For verification, a manufacturing company’s industrial problem is employed. The results show that SOSA outperforms the existing methods and the Jaya algorithm, and using alternate machines for the operations can reduce the MKSN.
Elastoplastic Solutions for Deep Tunnel Excavation in Weak Rocks with High Geostress Considering Different Stress Release Measures
Authors: Xu Chen , Xia Caichu , Han Changling
Published: August 2022

The Deformation Reserved (DR) method and the Pilot Heading (PH) method are two commonly used stress release methods in the construction of weak rock tunnel under high geostress. The ground pressure exerted on the support would be reduced to a certain extent with the stress release measures according to the Convergence–Confinement principle. The elastoplastic solutions of tunneling with DR method and PH method are derived, respectively, considering the support delay. By introducing the concept of stress release ratio, the equivalent relationship between two methods is studied. The effects of these two methods on reducing the contact pressure between surrounding rock and support are compared. Furthermore, the stress release effects of DR method and PH method under different conditions are explored. The results show that DR method is much more suitable when the geostress is not very high and surrounding rock is intact with high strength. Contrarily, if the geostress is quite high and the surrounding rock is very weak, PH method is suggested. For DR method, the stress release effect abates gradually with the increase of initial geostress, but the effect of stress release by PH method is much better under high geostress. Though both DR method and PH method are effective in reducing the contact pressure between surrounding rock and lining, the reserved deformation and the radius of the pilot tunnel are not suggested to be as large as possible.
A Novel Unit Cell for Low-Frequency Vibration Suppression Through Meta-Plates: Modeling, Optimization and Testing
Authors: Khansanami Mohammad Farid , Younesian Davood
Published: August 2022

Exceptional properties of emerging of unconventional metamaterials including phononic/sonic crystals such as bandgap frequency have made them pertinent in various applications. In this paper, a novel single-phase optimized unit cell is proposed via genetic algorithm interfaced with the FE method. The unit cell parameters are fine-tuned according to two different objective functions over the low-frequency range of 2[Formula: see text]kHz to achieve the widest and maximum bandgaps summation for the in-plane and out-of-plane modes. For the in-plane propagation, almost 1681[Formula: see text]Hz bandgaps summation and a wide 635[Formula: see text]Hz frequency bandgap are obtained. Besides, there have been 1311[Formula: see text]Hz and 368[Formula: see text]Hz bandgap for the other case. Then, the meta-plates acquired through the investigations with finite arrangements are computed numerically and experimentally to mitigate longitudinal and bending wave propagation. It is found that the structures have high-performance capability to suppress the low-frequency vibrations inside the specified area and can substantially attenuate the propagation of elastic waves.
Green Synthesis of Gd(OH)3 and Eu:Gd(OH)3 Nanorods: Effect of Reaction Parameters on Morphology, Crystallinity and Thermal Conversion to Photoluminescent Oxide Nanorods
Authors: Khan Abdul Hanan , Masood Saima , Majeed Aasiya , Nazir Sadaf , Jaiswal Piyush , Shivashankar S. A. , Majeed Shafquat
Published: August 2022

Through a green approach using water as a solvent, nanorods of Gd(OH)3 in the diameter range of 15–50 nm and lengths varying from 40 nm to 290 nm were synthesized at low temperatures with high crystallinity. The as-prepared Gd(OH)3 nanorods were characterized by various methods like XRD, TGA, TEM, etc. The effect of reaction time, base and surface directing agent on the crystallinity and morphology of Gd(OH)3 powders were also investigated. Further, through a similar route Eu doped Gd(OH)3 nanorods were also prepared (showing a similar morphology as undoped powders) that were annealed at modest temperatures to obtain Eu:Gd2O3 powders and their photoluminescence properties were analyzed.
Global stability of bistable traveling wavefronts for a three-species Lotka–Volterra competition system with nonlocal dispersal
Authors: Hao Yu-Cai , Zhang Guo-Bao
Published: August 2022

This paper is devoted to the study of traveling wavefronts for a three-component Lotka–Volterra system with nonlocal dispersal. This system arises in the study of three-species competition model in which there is no competition between two of these three species. It has been shown that this system admits a bistable traveling wavefront. In this paper, we further investigate the stability of bistable traveling wavefronts. By constructing suitable super- and sub-solutions and using a dynamical system approach, we obtain the globally asymptotic stability of the bistable traveling wavefronts.
Dynamic Green’s Functions for an Infinite Acoustic Field with Multiple Spheres Subjected to the Robin Boundary Conditions
Authors: Lee Wei-Ming , Chen Jeng-Tzong
Published: August 2022

A semi-analytical approach is presented to solve three-dimensional dynamic Green’s function for an infinitely extended acoustic field with multiple spheres subjected to the Robin boundary conditions. The multipole expansions of the acoustic field induced by a time-harmonic point source are expanded with spherical wave functions. As an alternative to the complex addition theorem, the multipole expansion is computed in a straightforward way. By taking the finite number of terms, an algebraic system is constructed and is used to obtain Green’s function. This result of one sphere agrees with the available analytical solution. For the case of more than one sphere, the proposed results are verified by the numerical method such as the boundary element method (BEM). It indicates that the present solution is more accurate than that of the BEM and shows a fast convergence. Finally, the parameter study is performed to explore the influences of the exciting frequency of the point source, the surface admittance, the number and the separation of spheres on the dynamic Green’s functions. The proposed results can be applied to solve the acoustic scattering problems and to increase the application of boundary integral equation method in the way of numerical Green’s functions.
Middleware 101
Authors: Gazis Alexandros , Katsiri Eleftheria
Published: August 2022

What to know now and for the future.
Surface Planarization of CdZnTe Wafers: Effect of Slurry Formulation and CMP Processing Parameters on Surface Planarity
Authors: Qasim Mohd , Parthiban P. , Das D.
Published: August 2022

This study investigates the effect of chemical mechanical planarization (CMP) processing parameters such as platen velocity, the concentration of the oxidizer and abrasive nanoparticle, slurry pH and surfactant types on the surface roughness of cadmium zinc telluride (CdZnTe) substrate. It was found that these parameters have a significant effect on the quality of the polished surfaces. It was found that lower platen velocity, lesser concentration of abrasive particles, basic slurry pH, and addition of anionic surfactant (SDS) into the CMP slurry solution showed improved surface planarity. Optical Surface Profiler and atomic force microscopy (AFM) techniques were used to monitor the surface topography before and after polishing. A notable root-mean-square surface roughness, (Rq), ∼0.9 nm, has been obtained on the polished CdZnTe (CZT) surface over a scan area of 481 × 361 μm2 under the optimized conditions of 60 rpm relative velocity, slurry pH of 9, 3.75 vol% of oxidizer (H2O2) and 1.25 wt% of abrasive (SiO2 nanoparticle). A probable mechanism of the present CMP surface planarization of CZT substrate has been proposed. Unlike the conventional surface planarization processes, which involve two-step lapping followed by CMP for the CZT surfaces, we have developed a single step CMP process to obtain good surface planarity.
Gut Microbiota and Inflammatory Cytokine Changes in Patients with Ankylosing Spondylitis
Authors: Liu Bin , Ding Zhenghua , Xiong Junhui , Heng Xing , Wang Huafu , Chu Weihua
Published: August 2022

Ankylosing spondylitis (AS) is a chronic inflammatory disease characterized by sacroiliac joint lesions and spinal ascending involvement. The aim of this work was at investigating the gut microbiota profile and proinflammatory cytokines in AS patients. Gut microbiota of AS patients was clearly different from that of healthy human controls. 16S rRNA sequencing analysis demonstrated a changed microbial diversity in the AS patients, and there was a significant increase in the abundance of Cyanobacteria, Deinococcota, Patescibacteria, Actinobacteriota, and Synergistota at a phyla level increased in AS, while the relative abundance of Acidobacteriota, Bdellovibrionota, Campylobacterota, Chloroflexi, Gemmatimonadota, Myxococcota, Nitrospirota, Proteobacteria, and Verrucomicrobiota declined in AS patients. ELISA results for the markers of inflammation in the AS patients revealed increased concentrations of proinflammatory cytokines such as IL‐23, IL‐17, and IFN‐γ. Our findings support the fact that the intestinal microbiota are altered in AS with an inflammatory status, which indicates that gut microbiota should be a potential target for ankylosing spondylitis therapy.
Ventricular Tachycardia or Fibrillation Storm in Coronavirus Disease
Authors: Khan Muhammad H. , Aqtash Obadah , Harris David M. , Costea Alexandru I. , Gerson Myron C.
Published: August 2022

Ventricular tachycardia (VT) or ventricular fibrillation (VF) storm associated with severe acute respiratory syndrome coronavirus 2 infection is a potentially fatal complication; the correlation of these 2 disorders, however, has not been well studied. This retrospective case series examined outcomes of 2 patients who were admitted for repeated implantable cardioverter-defibrillator shocks with or without syncope and observed to have VT/VF storms with COVID-19. Mechanisms of VT/VF storms in COVID-19 are multifactorial including myocarditis, systemic inflammation, hyperadrenergic state, hemodynamic instability, hypoxia, acidosis, and proarrhythmic drugs. A higher incidence of VT/VF storm is observed in patients with comorbidities and those requiring critical care, with some studies reporting increased mortality. In our cohort, 1 of the 2 patients succumbed to the complications from COVID-19, and the other patient was discharged to home in stable condition. Monitoring of life-threatening arrhythmias in the setting of COVID-19 may need to be adopted to prevent morbidity and mortality.
New Statistical Approaches for Modeling the COVID‐19 Data Set: A Case Study in the Medical Sector
Authors: Almazah Mohammed M. A. , Ullah Kalim , Hussam Eslam , Hossain Md. Moyazzem , Aldallal Ramy , Riad Fathy H.
Published: August 2022

Statistical distributions have great applicability for modeling data in almost every applied sector. Among the available classical distributions, the inverse Weibull distribution has received considerable attention. In the practice of distribution theory, numerous methods have been studied and suggested/introduced to increase the flexibility level of the traditional probability distributions. In this paper, we implement different distribution methods to obtain five new different versions of the inverse Weibull model. The new modifications of the inverse Weibull model are called the logarithm transformed‐inverse Weibull, a flexible reduced logarithmic‐inverse Weibull, the weighted TX‐inverse Weibull, a new generalized‐inverse Weibull, and the alpha power transformed extended‐inverse Weibull distributions. To illustrate the flexibility and applicability of the new modifications of the inverse Weibull model, a biomedical data set is analyzed. The data set consists of 108 observations and represents the mortality rate of the COVID‐19‐infected patients. The practical application shows that the new generalized‐inverse Weibull is the best modification of the inverse Weibull distribution.
Primary Cerebral Venous Thrombosis in a Patient with Immune Thrombocytopenic Purpura
Authors: Farfouti M. Taher , Masri Christina , Ghabally Mike , Roumieh George
Published: August 2022

Introduction. Immune thrombocytopenic purpura is an autoimmune hematological disorder characterized by low platelet level due to its destruction through autoimmune antibodies. Cerebral venous thrombosis is a serious condition defined by a thrombosis in the cerebral venous sinuses that occurs mostly in the presence of a hypercoagulable state. Hemorrhage and thrombosis are processes with a paradoxical etiology; thus, the association between these two conditions seems to be extremely rare. Case Presentation. We herein report a case of a 19-year-old female with a chief compliant of generalized tonic-clonic episode, severe headache, and blurred vision. Physical examination was significant for a bilateral Babinski’s sign and severe bilateral papilledema. Laboratory workup, computed tomography, and magnetic resonance imaging were normal except for severe thrombocytopenia. Magnetic resonance venography was diagnostic for cerebral venous thrombosis. Her past medical history was significant for immune thrombocytopenic purpura that was treated with prednisolone 40 mg per day which posed a therapeutic challenge. High-dose prednisolone and platelet transfusion were initiated; enoxaparin was administrated and switched to warfarin after stabilization of platelet count. The patient was neurologically intact after 14 days of appropriate treatment and was on follow-up. Many hypotheses were suggested to explain the unexpected thrombotic events in a patient with immune thrombocytopenic purpura which were related to the disease etiology or treatment, taking into account common risk factors (such as age, obesity, smoking, hypertension, diabetes mellitus, dyslipidemia, splenectomy, and oral contraceptive agents). Conclusion. The association between immune thrombocytopenic purpura (which is a major risk factor for bleeding) and cerebral venous thrombosis ( which is caused by a thromboembolic event )has carried a major challenge to the management plan. We believe that immune thrombocytopenic purpura and its treatment methods should be taken into consideration as risk factors for thromboembolic phenomenon.
Sensor Action Recognition, Tracking, and Optimization Analysis in Training Process Based on Virtual Reality Technology
Authors: Wan Huizhen
Published: August 2022

In order to solve the problem of improving the training efficiency and competition performance of athletes, a system of sensor action recognition, tracking, and optimization analysis based on virtual reality technology is proposed. After using the perceptual interaction subsystem to build a three-dimensional training scene through the virtual environment producer, the picture in the three-dimensional scene is rendered through the view module in the model operator system. At the same time, the logic module calculates the physical attenuation of athletes and sends the calculation results back to the perceptual interaction subsystem effect generator through the interface to present the interactive effect of athletes’ training. The experimental results show that the maximum improvement of the performance of five randomly selected athletes in the 100-meter, 200-meter, and 400-meter dash competitions after using the system can reach 5 s, 4.5 s, and 6 s, respectively. Conclusion. The system can effectively complete the calculation of athletes’ physical fitness attenuation and has good carrying capacity. It can improve athletes’ physical fitness training effect and competition simulation efficiency and can improve athletes’ competition performance after application.
The Role of Digital Information Technology for Social Welfare Computing in the Context of the Internet of Things
Authors: Lu Yuqing
Published: August 2022

The paper measures the income distribution effects and welfare effects of VAT itself based on Chip2013 household income and expenditure microdata using the Gini coefficient, Suits index, and Theil index from the perspective of annual income and lifetime income, respectively, and the effective VAT rate. Taking provinces as the basic research unit, we use the first-right method, LISA time path, and Spatiotemporal leap to evaluate China’s well-being level from 2010 to 2020 and analyze its Spatiotemporal dynamic characteristics. At present, most countries adopt a tax rate model with 1∼3 bands. The current VAT rate structure is “13% + 9% + 6%,” which is in line with the international development trend. In the data preprocessing module, the HTTP(S) responses of non-IoT devices are first filtered out and then the text that may contain device information is extracted from the remaining HTTP(S) responses by integrating multidimensional features, and finally, the irrelevant strings in the text are filtered out. At the end of the paper, simulation experiments are designed to verify the function and performance of the identification information extraction system for this heritage connected device, and the results verify that the model identification method in this paper can achieve better identification results compared with existing methods. The results verify that the model recognition method in this paper can achieve better recognition results compared with existing methods.
The Impact of Rural Labor Force Feminizing Fluctuation on Grain Production and its Regional Differences: Evidence from China
Authors: Wang Haifeng , Li Guangsi , Hu Yunzhi
Published: August 2022

Based on panel data from 2002 to 2018, this study establishes a variable coefficient model of the interaction term between the proportion of rural female labor force and the ratio of mechanization. The influence of the increase in the rural female labor force ratio on grain production is discussed. The results show that the feminization of the rural labor force has a significant negative impact on grain-planting area and proportion, leading to an adverse impact on grain planting. Conversely, in the plain, which is relatively easy to mechanize with massive production, the adverse effects of feminization of labor on grain production will be weakened. The regional analysis found that feminization of the workforce reduces the area and proportion of food acreage planted in the eastern region, machinery use completely counteracts the negative impact of labor feminization in the eastern and western regions, with a positive effect, whereas in the central region, the impact of machinery use is not significant. Therefore, in the process of increasing the proportion of rural women, we should pay attention to its adverse effects on food cultivation and regional differences and take targeted measures to stabilize the food supply.
Continuous Theta-Burst Stimulation Promotes Paravascular CSF-Interstitial Fluid Exchange through Regulation of Aquaporin-4 Polarization in APP/PS1 Mice
Authors: Wu Cheng , Lin Tuo , Ding Qian , Zhang Ni , Ou Zi-tong , Cai Gui-yuan , Chen Hong-ying , Xu Jia-yue , Li Ge , Pei Zhong , Xu Guang-qing , Lan Yue
Published: August 2022

Amyloid-β (Aβ) deposition plays a crucial role in the occurrence and development of Alzheimer’s disease (AD), and impaired Aβ clearance is the leading cause of Aβ deposition. Recently, studies have found that the glymphatic system performs similar functions to the peripheral lymphatic system. Glymphatic fluid transport mainly consists of cerebrospinal fluid (CSF) entering the brain from the paravascular space (PVS) by penetrating arteries and CSF and interstitial fluid exchanging mediated by aquaporin-4 (AQP4). This system promotes the drainage of interstitial fluid (ISF) in the parenchyma and removes metabolic waste, including Aβ, in the brain. Glymphatic system dysfunction plays an essential role in the occurrence and progression of AD. Regulation of glymphatic fluid transport may be a critical target for AD therapy. This study explored the regulatory effects of continuous theta-burst stimulation (CTBS) on the glymphatic system in APPswe/PS1dE9 (APP/PS1) mice with two-photon imaging. The results demonstrated that CTBS could increase glymphatic fluid transport, especially CSF and ISF exchange, mediated by improved AQP4 polarization. In addition, the accelerated glymphatic pathway reduced Aβ deposition and enhanced spatial memory cognition. It provided new insight into the clinical prevention and treatment of Aβ deposition-related diseases.
Identification of an Epigenetic Signature for Coronary Heart Disease in Postmenopausal Women’s PBMC DNA
Authors: Zhong Xiao , Song Ziguang , Gao Pingping , Li Mingyang , Ning Zhongping , Song Xiang
Published: August 2022

Menopause is accompanied with an increased risk of cardiovascular disease. DNA methylation may have a significant impact on postmenopausal women’s development of coronary heart disease. DNA methylation alterations in peripheral blood mononuclear cells (PBMCs) from women with coronary heart disease and healthy controls were detected using the Illumina Infinium MethylationEPIC BeadChip platform in this work. We employed Sangerbox technology and the GO and KEGG databases to further study the pathogenesis of coronary heart disease in postmenopausal women. After that, we used functional epigenetic module analysis and Cytoscape to remove the hub genes from the protein–protein interaction networks. Five genes (FOXA2, PTRD, CREB1, CTNAP2, and FBN2) were the hub genes. Lipid accumulation, endothelial cell failure, inflammatory responses, monocyte recruitment and aggregation, and other critical biological processes were all influenced by these genes. Finally, we employed methylation-specific PCR to demonstrate that FOXA2 was methylated at a high level in postmenopausal women with coronary heart disease. To better understand coronary heart disease in postmenopausal women’s molecular mechanisms, our study examine the major factors contributing to the state of DNA methylation modification, which will help discover novel diagnostic tools and treatment options.
The Effects of 6 Common Antidiabetic Drugs on Anti-PD1 Immune Checkpoint Inhibitor in Tumor Treatment
Authors: Zhan Ze-Tao , Liu Lu , Cheng Ming-Zhen , Gao Yi , Zhou Wei-Jie
Published: August 2022

Diabetes and cancer are common diseases and are frequently diagnosed in the same individual. These patients need to take antidiabetic drugs while receiving antitumor drugs therapy. Recently, immunotherapy offers significant advances for cancer treatment. However, it is unclear whether antidiabetic drugs affect immunotherapy. Here, by employing syngeneic mouse colon cancer model and melanoma model, we studied the effects of 6 common antidiabetic drugs on anti-PD1 immune checkpoint inhibitor in tumor treatment, including acarbose, sitagliptin, metformin, glimepiride, pioglitazone, and insulin. We found that acarbose and sitagliptin enhanced the tumor inhibition of anti-PD1, and metformin had no effect on the tumor inhibition of anti-PD1, whereas glimepiride, pioglitazone, and insulin weakened the tumor inhibition of anti-PD1. Our study suggests that cancer patients receiving anti-PD1 antibody therapy need serious consideration when choosing antidiabetic drugs. In particular, acarbose significantly inhibited tumor growth and further enhanced the therapeutic effect of anti-PD1, which can be widely used in tumor therapy. Based on this study, further clinical trials are expected.
[Retracted] Research on Organization Design of College Chinese Teaching under Big Data Environment
Authors: Shi Jiayu , Wu You
Published: August 2022

The pivotal and most important technology point of the application of big data in modern network teaching is the establishment of teaching platform. Based on Hadoop big data technology, this paper establishes a big data platform designed by Chinese teaching institutions in colleges and universities. The teaching system not only realizes the diversified development of network teaching but also realizes the discovery of teaching platform users’ needs and the push of resources. In addition, it is found that a small number of people do not have a high understanding of the teaching mode of big data through extensive studies, which also shows that traditional teaching is still lagging behind in big data education. However, on the whole, the Chinese teaching model in universities based on the big data environment deserves further promotion and application in universities.
Rapamycin Alleviates 2,4,6-Trinitrobenzene Sulfonic Acid-Induced Colitis through Autophagy Induction and NF-κB Pathway Inhibition in Mice
Authors: Ni Zhen , Li Hao , Mu Dong , Hou Juanni , Liu Xiaoyan , Tang Shanhong , Zheng Shumei
Published: August 2022

Background. Recent genetic studies indicated that variants of autophagy genes were associated with the predisposition of Crohn’s disease (CD). The autophagy deficiency may affect the innate and adaptive immunity, which is related to persistent and excessive inflammation of the bowel. However, it remains unclear how autophagy modulates the expression of immune response regulator NF-κB and proinflammatory cytokine TNF-α in CD. Aim. We aimed to investigate the role of rapamycin on the expression of NF-κB p65 and TNF-α in 2, 4, 6-trinitrobenzene sulfonic acid (TNBS)-induced mouse colitis and lipopolysaccharide (LPS)-induced HT-29 cells. Methods. TNBS-induced colitis mice were treated with saline or rapamycin, and the disease activity index (DAI) and histological scores of colonic mucosa were evaluated. The expressions of p65, ATG16L1 and LC3 were detected by western blot and immunohistochemistry staining. The monodansylcadaverine (MDC) staining and transmission electron microscopy were developed to study the autophagy in LPS-induced HT-29 cells. Expression of TNF-α from colon tissue and HT-29 cells were detected by ELISA. The expressions of p65, ATG16L1 and LC3 in active CD patients were also investigated. Results. Significantly more autophagosomes were observed in rapamycin-treated cells than in controls. Rapamycin remarkably upregulated the expression of ATG16L1 and LC3II, inhibited p65 nucleus translocation and secretion of TNF-α both in vivo and in vitro. The expression of both ATG16L1 and LC3II increased in mild to moderate CD specimens, while no significant difference was noted between severe CD and normal controls. The expression of p65 increased notably in severe CD compared to those in mild to moderate patients. Conclusions. In LPS-treated HT-29 cells and TNBS-induced colitis, p65 is overexpressed, which results in exaggerated secretion of TNF-α and induce or worsen the inflammation in the bowel. Rapamycin protects against colitis through induction of autophagy, thus inhibiting the activation of NF-κB pathway and secretion of TNF-α.
[Retracted] Metaheuristic Optimization‐Driven Novel Deep Learning Approach for Brain Tumor Segmentation
Authors: Kalpana R. , Bennet M. Anto , Rahmani Abdul Wahab
Published: August 2022

Brain tumor has the foremost distinguished etiology of high morality. Neoplasm, a categorization of brain tumors, is very operative in distinguishing and determining the tumor’s exact location in the brain. Magnetic resonance imaging (MRI) is an efficient noninvasive technique for the anatomical examination of brain tumors. Growth tissues have a distinguishable look in MRI pictures in order that they are unit‐wide used for brain tumor feature extraction. The existing research algorithms for brain tumors have some limitations such as different qualities, low sensitivity, and diagnosing the tumor at its stages. In this particular piece of research, an innovative method of optimization known as the procedure for lightning attachment algorithm (PLA) is used, and for the purpose of classification, a CNN model known as DenseNet‐169 is applied. PLA was used in order to optimize the growth, and a network model known as the DenseNet‐169 model was utilized in order to extract the various growth‐optimization choices. First, the MR images of the brain were preprocessed to remove any outliers. Next, the Dense Net‐169 CNN model was used to extract network choices from the MR images. In addition, it is used to execute the function of a classifier in order to identify the growth as either an aberrant growth or a traditional growth. In addition, the publicly benchmarked datasets that are widely utilized have validated the algorithmic rule that was granted. The planned system demonstrates the satisfactory accuracy in getting ready to on the dataset and outperforms many of the notable current techniques.