bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Impact of Noise on Hyperbolic-Type Traveling Wave Solutions of Some Stochastic Evolution Equations
Authors: Taskesen Hatice , Alaloush Mohanad
Published: July 2022

In this paper, traveling wave solutions of some nonlinear stochastic evolution equations emerging in miscellaneous fields such as modeling of flame propagation, magneto-acoustic waves in plasma and small-amplitude water waves with surface tension are investigated. By means of Galilean transformation and tanh method, we obtain some exact solutions such as kink wave solution, solitary wave solution and periodic solution. To illustrate the impact of noise on the solutions, we assigned different noise functions for the external noise. The results showed that the waveform deforms as the noise intensity increases.
A Random-Matrix-Theory-Based Analysis of the Brazilian Stock Market During the 2008 Financial Crisis and Asian Crisis and Temporal Neighborhoods
Authors: Aires Debora Barbosa , Crepaldi Antonio Fernando
Published: July 2022

Several approaches and concepts of physics, such as Random Matrix Theory, have been used to investigate the complexity of financial time series. This study aims to analyze the spectrum of stock correlation in the Brazilian stock market by applying Random Matrix Theory to the subprime and Asian financial crisis periods and their temporal neighborhoods. Results show evident synchronized market behavior during both crises. The results also show that the period preceding a crisis presents symptoms which may predict future crises. Thereby, the methodology presented here could be used by the market as a tool that helps to anticipate possible market fluctuations.
BIO-MAGNETIC FLOW OF HEAT TRANSFER OVER MOVING HORIZONTAL PLATE BY THE PRESENCE OF VARIABLE VISCOSITY AND TEMPERATURE
Authors: JUMANA SADIA ANJUM , FERDOWS M. , TZIRTZILAKIS E. E.
Published: July 2022

This work aims at the investigation of 2D, steady, laminar, viscous, incompressible boundary layer and heat transfer flow of a biomagnetic fluid over a convectively heated moving horizontal plate in the presence of a magnetic dipole. It is assumed that the fluid viscosity is the inverse linear function of temperature and the temperature at the wall varies as power law function. The governing equations involve a system of coupled PDEs (momentum and energy equations) which are converted into a system of nonlinear ODEs by utilizing similarity transformations. The transformed ODEs along with the boundary conditions are then solved numerically by adopting a finite difference algorithm. The physical effects of the governing parameters (i.e., ferrohydrodynamic interaction parameter, buoyancy force parameter, viscosity-temperature parameter, wall parameter) on the flow fields along with the skin friction and heat transfer rate are presented. Verification of this work has been done by comparing former published results and acceptable agreement is found. It has been analyzed theoretically by using suitable transformations, that the ferrohydrodynamic interaction parameter, has a great enhancement effect on biomagnetic fluid rather than that on a regular fluid. It has been discovered that the inclusion of certain intensity of magnetic field along with the consideration of the variable viscosity and temperature, has significant effects on the flow and heat transfer mechanism. These outcomes could be of interest in medical as well as bioengineering implementations, like magnetic drug delivering in blood cells, separating RBCs (Red Blood Cells), controlling the flow of blood during surgeries and treating cancer by producing magnetic hyperthermia.
Accurate image segmentation based on adaptive distance regularization level set method
Authors: Xiao Hanguang , Zhang Bolong , Liu Ruihua , Zou Yangyang , Xie Ting
Published: July 2022

Level set method has been widely applied in the field of image segmentation. However, the level set formulation is inevitably affected by the regularization function, in-homogeneity and weak edge in the process of evolution, which often leads to the instability and inaccuracy of image segmentation results. To solve these problems, a new distance regularization term defined by a double-well potential function is proposed to satisfy more ideal characteristics of signed distance property. In addition, a novel edge indicator function is introduced to segment images with uneven intensity or weak edge. Finally, the adaptive adjustment formulas of distance regularization and area parameters are derived to alleviate the difficulty of parameter adjustment. Experimental results show that the proposed model provides better accuracy and versatility, quantitative experiment on Weizmann segmentation evaluation database achieves mean Dice score (96.87%), IoU (94.38%), Hausdorff distance (3.20[Formula: see text]mm), Recall (97.68%) and Precision (96.32%), respectively.
Approximation of point interactions by geometric perturbations in two-dimensional domains
Authors: Borisov D. I. , Exner P.
Published: July 2022

In this paper, we present a new type of approximation of a second-order elliptic operator in a planar domain with a point interaction. It is of a geometric nature that the approximating family consists of operators with the same symbol and regular coefficients on the domain with a small hole. At the boundary of it, Robin condition is imposed with the coefficient which depends on the linear size of a hole. We show that as the hole shrinks to a point and the parameter in the boundary condition is scaled in a suitable way, nonlinear and singular, the indicated family converges in the norm-resolvent sense to the operator with the point interaction. This resolvent convergence is established with respect to several operator norms and order-sharp estimates of the convergence rates are provided.
More on the outer connected geodetic number of a graph
Authors: Ganesamoorthy K. , Jayanthi D.
Published: July 2022

For a connected graph [Formula: see text] of order at least two, a total outer connected geodetic set [Formula: see text] of a graph [Formula: see text] is an outer connected geodetic set such that the subgraph induced by [Formula: see text] has no isolated vertices. The minimum cardinality of a total outer connected geodetic set of [Formula: see text] is the total outer connected geodetic number of [Formula: see text] and is denoted by [Formula: see text]. We determine bounds for it and also find the total outer connected geodetic number for some special classes of graphs. It is shown that for positive integers [Formula: see text] and [Formula: see text] with [Formula: see text] there exists a connected graph [Formula: see text] with [Formula: see text] [Formula: see text] and [Formula: see text]. It is proved that for each triple [Formula: see text] and [Formula: see text] of positive integers with [Formula: see text], [Formula: see text] and [Formula: see text], there exists a connected graph [Formula: see text] of order [Formula: see text] such that [Formula: see text] and [Formula: see text]. It is also shown that for positive integers [Formula: see text] such that [Formula: see text] with [Formula: see text], there exists a connected graph [Formula: see text] such that [Formula: see text] and [Formula: see text], where [Formula: see text] is the outer connected geodetic number of a graph [Formula: see text].
Advancing in the technical hierarchy
Authors: Meil Doug
Published: July 2022

The
Communications
website, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.

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Follow us on Twitter at http://twitter.com/blogCACM

http://cacm.acm.org/blogs/blog-cacm

Doug Meil considers the steps to becoming a technical leader.
Sampling near neighbors in search for fairness
Authors: Aumüller Martin , Har-Peled Sariel , Mahabadi Sepideh , Pagh Rasmus , Silvestri Francesco
Published: July 2022

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points
S
and a radius parameter
r
> 0, the
r
-near neighbor (
r
-NN) problem asks for a data structure that, given any query point
q
, returns a point
p
within distance at most
r
from
q.
In this paper, we study the
r
-NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance
r
from the query should have the same probability to be returned. The problem is of special interest in high dimensions, where
Locality Sensitive Hashing
(LSH), the theoretically leading approach to similarity search, does not provide any fairness guarantee. In this work, we show that LSH-based algorithms can be made fair, without a significant loss in efficiency. We propose several efficient data structures for the exact and approximate variants of the fair NN problem. Our approach works more generally for sampling uniformly from a sub-collection of sets of a given collection and can be used in a few other applications. We also carried out an experimental evaluation that highlights the inherent unfairness of existing NN data structures.
FPGAs in client compute hardware
Authors: Mattioli Michael
Published: July 2022

Despite certain challenges, FPGAs provide security and performance benefits over ASICs.
On the Analysis and Evaluation of Proximity-based Load-balancing Policies
Authors: Panigrahy Nitish K. , Vasantam Thirupathaiah , Basu Prithwish , Towsley Don , Swami Ananthram , Leung Kin K.
Published: July 2022

Distributed load balancing is the act of allocating jobs among a set of servers as evenly as possible. The static interpretation of distributed load balancing leads to formulating the load-balancing problem as a classical balls-and-bins problem with jobs (balls) never leaving the system and accumulating at the servers (bins). While most of the previous work in the static setting focus on studying the maximum number of jobs allocated to a server or
maximum load
, little importance has been given to the
implementation cost
, or the cost of moving a job/data to/from its allocated server, for such policies.

This article designs and evaluates server proximity aware static load-balancing policies with a goal to reduce the
implementation cost
. We consider a class of proximity aware Power of Two (POT) choice-based assignment policies for allocating jobs to servers, where both jobs and servers are located on a two-dimensional Euclidean plane. In this framework, we investigate the tradeoff between the implementation cost and load-balancing performance of different allocation policies. To this end, we first design and evaluate a
Spatial Power of two
(sPOT) policy in which each job is allocated to the least loaded server among its two geographically nearest servers. We provide expressions for the lower bound on the asymptotic expected maximum load on the servers and prove that sPOT does not achieve classical POT load-balancing benefits. However, experimental results suggest the efficacy of sPOT with respect to expected implementation cost. We also propose two non-uniform server sampling-based POT policies that achieve the best of both implementation cost and load-balancing performance.

We then extend our analysis to the case where servers are interconnected as an
n
-vertex graph
G(S, E)
. We assume each job arrives at one of the servers,
u,
chosen uniformly at random from the vertex set
S.
We then assign each job to the server with minimum load among servers
u
and
v
where
v
is chosen according to one of the following two policies: (i) Unif-POT(
k
): Sample a server
v
uniformly at random from
k
-hop neighborhood of
u;
(ii) InvSq-POT(
k
): Sample a server
v
from
k
-hop neighborhood of
u
with probability proportional to the inverse square of the distance between
u
and
v
. An extensive simulation over a wide range of topologies validates the efficacy of both the policies. Our simulation results show that both policies consistently produce a load distribution that is much similar to that of a classical POT. Depending on topology, we observe the total variation distance to be of the order of 0.002–0.08 for both the policies while achieving a 8%–99% decrease in implementation cost as compared to the classical POT.
Implementation Challenges: Universal R-Dump Converter for Switched Reluctance Motor
Authors: Vijayaragavan C. M. , Vanaja Ranjan P. , Velraj R.
Published: July 2022

This study presents the challenges faced while implementing a new converter topology for switched reluctance motor (SRM) drives. A novel converter configuration that can excite the motor directly from the grid supply, i.e., alternating current supply, was proposed in earlier research. The proposed converter topology is designed to draw power directly from an AC grid. This converter is a modified version of the R-dump converter. There are many converter topologies available for excitation of SRM. The uniqueness of the converter topology developed in this research shows that it can use 4 switches per phase, which in turn increases the redundancy of the whole system. Moreover, this topology is well suitable for SRM excitation since the machine coil structure is constructed with 4 coils and 5 terminals. Since this novel converter is having the advantages of operating in AC input voltage, it improves the usefulness of SRM in household applications such as washing machines, hair dryers, and vacuum cleaners. An analysis of real-time implementation challenges faced while realizing the universal R-dump (URD) converter is presented with discussion to overcome the challenges. An experimental setup is made to verify the converter working.
Analysis of the Deep Development Mechanism of College Education under the Field Theory
Authors: Zhao Qianqian , Li Yan
Published: July 2022

Nowadays, the development of online college education is in full swing, and various online college education platforms have also sprung up. The development of technology has made these online platforms more and more powerful, escorting the continuous development of online education. Colleges and universities, as the main front for the cultivation of high-quality talents in my country, have already introduced large-scale online courses into education and teaching, enriching the teaching content, and expanding the teaching form. In the face of new technical means and abundant online education resources, the teaching quality of online classrooms in colleges and universities is so low, which deserves our further reflection. For a long time, the effect of online classroom teaching in colleges and universities has been closely concerned by the academic community, but most of them start from external factors, ignoring the internal relationship of online classrooms. Clarifying the complex relationships in the online classroom field of colleges and universities and clarifying the rules of habitus and capital operation in the online classroom field of colleges and universities are the intrinsic motivation and important source to stimulate the vitality of the online classroom field of colleges and universities and improve the quality of teaching. By grasping the essence of classroom teaching and analyzing the inherent characteristics of the online classroom field, this research intends to clarify the proper state of the online classroom field, and to explore the reasons why the current online classroom field function has not been fully realized, so as to find the depth of college education.
Comparison of the Effect of Ketamine and Dexmedetomidine Combined with Total Intravenous Anesthesia in Laparoscopic Cholecystectomy Procedures: A Prospective Randomized Controlled Study
Authors: Efe Mercanoglu E. , Girgin Kelebek N. , Turker G. , Aksu H. , Ozgur M. , Karakuzu Z. , Turkcan S. , Ozcan B.
Published: July 2022

This randomized prospective clinical study aimed to investigate the effects of dexmedetomidine or ketamine administration to total intravenous anesthesia (TIVA) on postoperative analgesia in subjects undergoing elective laparoscopic cholecystectomy procedures. 90 adults, American Society of Anesthesiologists (ASA) physical status 1 and II patients, who underwent elective laparoscopic cholecystectomy procedures were included in the study and randomized into three groups equally. Remifentanil, propofol, and rocuronium infusions were used for TIVA guided by the bispectral index. In group KETA, 10 μg/kg/min ketamine was added to TIVA before surgery, and in group DEX, 0.5 μg/kg/h dexmedetomidine was added to TIVA before surgery. Normal saline infusions were infused in the control group. Postoperative analgesia was provided with intravenous patient-controlled analgesia (PCA) morphine (1 mg bolus morphine, 5 min lockout time). Hemodynamic parameters, scores of visual analogue scale (VAS) for pain, rescue morphine requirements, and side effects such as sedation, nausea, and vomiting were recorded for 48 hours after surgery. Postoperative first analgesic requirement time was longer in group KETA (

P
<
0.001

), and it was longer in group DEX than in the control group (

P
<
0.001

). Pain scores were lower in group KETA and group DEX than in the control group at all corresponding times throughout the 48 h period of observation. Intravenous PCA morphine consumptions were higher in the control group than in group KETA (

P
<
0.001

for all followed-up times), and they were higher in group DEX than in group KETA (

P
<
0.001

for all followed-up times). It is concluded that the use of dexmedetomidine or ketamine infusions can be suitable as an additive for TIVA in the intraoperative period. Furthermore, the addition of both drugs to the TIVA protocol may improve postoperative pain relief and decrease opioid consumption.
Uplink Multiple Access for Reconfigurable Intelligent Surface-Aided Wireless Systems
Authors: Nguyen Nhan Duc , Le Chi-Bao , Munochiveyi Munyaradzi
Published: July 2022

The integration of reconfigurable intelligent surface- (RIS-) aided wireless communication and multiple access is an attractive and promising scheme for next-generation wireless networks. In this research work, separate uplink RIS-aided nonorthogonal multiple access (NOMA) and uplink relay-assisted NOMA schemes are studied, where the RIS and relay devices are deployed to enhance the coverage of an obstructed single-antenna far user by assisting it to communicate with a single-antenna base station. In each scenario, both perfect successive interference cancellation (pSIC) and imperfect successive interference cancellation (ipSIC) operations are considered in the proposed multiple access network. To characterize the system performance, the associated residual interference caused by ipSIC and relay loop self-interference is characterized using the Rayleigh fading model; subsequently, new channel statistics are derived based on the Gauss-Laguerre polynomial. Consequently, the closed-form approximate outage probability expressions are derived for each scenario in the high signal-to-noise ratio (SNR) regime. To gain further insight, the system throughput in the delay-limited transmission is also obtained for each scenario. The formulated expressions are validated via Monte-Carlo simulations. Finally, the obtained simulation results demonstrate and validate the superiority of the RIS system over the relay device under several system parameters of interest despite the limitation of ipSIC.
A Theoretical Scientific Programming Framework for Application of Linear Matrix Transformation in Plane Computer Graphics
Authors: Chen Mingcan
Published: July 2022

Plane computer graphics are basic information carriers in many industrial scenarios, such as engineering simulation, automatic control, and software design. Plane computer graphics are generally a kind of digital signals guided by mathematical symbols, and each vertex of a plane computer graph forms a graph matrix. Therefore, linear matrix transformation serves as the most common algorithmic unit to realize various information processing operations. To improve ease of graph matrix computing in practical engineering scenarios, this paper proposes a theoretical scientific programming framework for application of linear matrix transformation in plane computer graphics. Firstly, theoretical basis of linear matrix transformation in homogeneous plane coordinates is displayed and analyzed. Then, the universal theorem about linear transformation of graph matrices is deduced, and corresponding proofs are also given. Finally, a case study is set up to demonstrate the main workflow of the proposed theoretical scientific programming framework. The simulative results reveal feasibility of the proposal.
Internet of Things Information Network Security Situational Awareness Based on Machine Learning Algorithms
Authors: Meng Lei
Published: July 2022

In order to accurately predict the security situation of Internet of Things information network, a research method based on machine learning algorithm for security situational awareness of Internet of Things information network is proposed. The perception result is represented by the perception model, the sample data are preprocessed based on the linear discriminant analysis method, the sample data are optimized to obtain the combined features, and then the processed data are used as the training input of the RBF neural network to find out the mapping relationship with the network situation value, so as to quantify the security posture of the system. The results show that automatic discovery and classification of seven violations is achieved. Since the platform was launched in China Mobile, more than 65,000 suspected illegal IoT cards have been discovered, effectively monitoring and controlling the operation and behavior of IoT cards. The processing efficiency of IoT card violations has been increased by more than 20 times. After the system is put into use, the discovery of suspected illegal users and behaviors can be realized through full automation, and the process of analysis, confirmation, and disposal can be shortened to 2 hours, which effectively reduce the false alarm rate and reduce operator costs. In previous monitoring of IoT cards, the false-positive rate of illegal IoT cards was about 83%, while the false-positive rate of existing algorithms dropped to 20%.Monitoring shows that business abuse monitoring detects the highest proportion of illegal IoT  cards, 59%; infractions of Internet of Things cards detected through Internet abuse monitoring accounted for 20%; the proportion of Internet of Things card with machine card separation is 8%; in the information security risk monitoring (including spam text messages and harassing phone calls), the number of illegal Internet of Things cards found is small, only 3% and 2%, respectively; other infractions, including unauthorized use in locations and user complaints, accounted for 8%. It can effectively improve the ability to discover illegal IoT cards, greatly improve the accuracy of judgment, and improve the efficiency of disposal. The comparison verifies that the method is reliable and effective in the security situation awareness of the Internet of Things information network. Using the Internet of Things information security management system software based on the machine learning algorithm, the system software suitable for anomaly data detection is trained by adjusting the main parameters of the algorithm, which improves the automation and intelligence degree of the system software.
Ticagrelor-Induced Torsades de Pointes following Myocardial Infarction
Authors: Bu Seong Hyeon , Kim Sung-Hwan
Published: July 2022

We report a case of excessive QT prolongation and subsequent torsades de pointes (TdP) following the administration of ticagrelor in a 58-year-old male patient. The patient had no suspected cause of QT prolongation. After cessation of ticagrelor, QT interval was normalized and no further TdP was observed.
Diagnostic Values of Blood Urea Nitrogen (BUN), Creatinine (Cr), and the Ratio of BUN to Cr for Distinguishing Heart Failure from Asthma and Chronic Obstructive Pulmonary Disease
Authors: Zhang Jingjing , Zhou Ling , Zhang Yuezhan
Published: July 2022

Background. In clinical practise, it can be challenging to tell the difference between asthma and chronic obstructive pulmonary disease (COPD) and heart failure (HF), which share comparable dyspnea symptoms. We aimed to examine whether renal function indexes blood urea nitrogen (BUN), creatinine (Cr), and the ratio of BUN to Cr (BUN/Cr) can be used to distinguish HF from asthma and COPD. Methods. A total of 170 patients were admitted for dyspnea symptoms in this retrospective study. There are 69 patients with HF (HF group), 50 patients with asthma (asthma group), and 51 patients diagnosed with COPD (COPD group). The levels of BUN, Cr, and the ratio of BUN/Cr in the three groups were compared. Student’s

t

-test or the one-way analysis of variance (ANOVA) test was used to compare means. Using the area under the receiver operating characteristic curve, model differentiation was evaluated (AUC).

Z

-test comparisons of AUC were carried out. Results. Compared with the asthma/COPD group (asthma group + COPD group) or the COPD group, the levels of BUN and Cr were raised in the HF group, while there was no significant difference of the BUN/Cr ratio. Compared with those in the asthma group, the levels of BUN, Cr, and BUN/Cr ratio were significantly increased in the HF group (all

p
<
0.05

), whereas no significant differences of BUN, Cr, and BUN/Cr ratio were found between asthma and COPD. The AUC in distinguishing HF from asthma/COPD were 0.736 and 0.751 for BUN and Cr, respectively, and no significant difference was observed between BUN and Cr. The cutoff values (specificity, sensitivity, and Youden index) in distinguishing between HF and asthma/COPD were 20.45 mg/dL (79.21%, 56.52%, and 0.357) for BUN and 0.782 mg/dL (72.28%, 68.12%, and 0.404) for Cr, respectively. Conclusions. BUN and Cr showed accurate and reliable diagnostic values which could be potential biomarkers for differentiating HF from asthma and/or COPD.
Delayed Interval Delivery in Preterm Premature Rupture of Membranes in Dichorionic Triamniotic Triplets: Ethical Considerations for Maternal Health Case Report
Authors: Hosiani Ali , Brown James , Alahakoon Indika T.
Published: July 2022

Background. Although there are numerous studies on delayed interval delivery in twins, this study is one of few reporting on preterm premature rupture of membranes in triplets and even fewer on dichorionic triamniotic triplet twins. The case presented here highlights the important interplay between informed consent and patient autonomy. Case Presentation. A 37-year-old woman gravida 1, para 0 with a dichorionic triamniotic triplet pregnancy experienced preterm premature rupture of membranes of the singleton triplet at 15 weeks and six days of gestation. Delayed interval delivery was offered to the parents, who chose to continue the pregnancy while acknowledging the risks for maternal and foetal health. The patient was treated with prophylactic intravenous antibiotics and discharged on oral antibiotics after an eight-day admission. Two days after being discharged, she was readmitted with clinical signs of chorioamnionitis. Within six hours, the preterm premature rupture of membranes singleton was delivered. Three days later, she again presented to the hospital with preterm premature rupture of membranes of one of the dichorionic twins. After discussion with the maternal foetal medicine team, the parents chose to terminate the pregnancy. Delayed interval delivery was not successful in this patient, and it is unclear at which gestational age it is too early to offer expectant management. Conclusions. The case affirmed the very poor foetal survival rate when the first delivery occurs at under 20 weeks’ gestation. A standardised management of delayed interval delivery should be established to assist with consistent parental counselling.
A Novel Fault Diagnosis Method for Denoising Autoencoder Assisted by Digital Twin
Authors: Cai Wenan , Zhang Qianqian , Cui Jie
Published: July 2022

Digital twin (DT) is an important method to realize intelligent manufacturing. Traditional data-based fault diagnosis methods such as fractional-order fault feature extraction methods require sufficient data to train a diagnosis model, which is unrealistic in a dynamically changing production process. The ultrahigh-fidelity DT model can generate fault state data similar to the actual system, providing a new paradigm for fault diagnosis. This paper proposes a novel digital twin-assisted fault diagnosis method for denoising autoencoder. First, in order to solve the problem of limited or unavailable fault state data for machines in dynamically variable production scenarios, a DT model of the machine is established. The model can simulate a dynamically changing production process, thereby generating data for different failure states. Second, a novel denoising autoencoder (NDAE) with Mish as the activation function is proposed and trained using the source domain data generated by DT. Finally, in order to verify the effectiveness and feasibility of the proposed method, the method is applied to a fault diagnosis example of a triplex pump, and the results show that the method can realize intelligent fault diagnosis when the fault state data are limited or unavailable.
Dynamical Features of Isolated Two- and Three-Level Atoms Interacting with a Cavity Field
Authors: Abd-Rabbou M. Y. , Khalil E. M. , Almalki Fadhel
Published: July 2022

Some dynamical features of two- and three-level atoms interacting locally with an ideal cavity field are investigated. These dynamical features are introduced by employing the statistical atomic inversion, entropy squeezing, and tomographic entropy. Our results show that the initial setting states play an essential role in the temporal evolution of the three quantities. The sensitivity of the two-level atomic state is less than that depicted by the three-level atom. The initial state has a small impact on the two types of entropies for the two-level atom. However, it has an appreciable effect in the case of the three-level atom for different regulations of the initial atomic state.
Routing Path Selection and Data Transmission in Industry-Based Mobile Communications Using Optimization Technique
Authors: Bharti Rajendra Kumar , Bhoopathy V. , Bhanarkar Parul , Ambashtha Kanahaiya Lal , Priya K. , Durai C. Anand Deva , Krishna Manam Vamsi , Josephson P. Joel , Sahile Kibebe
Published: July 2022

In a mobile network, nodes are share data packets; sometimes, that packets are totally flooding. The packet dropping node does not easily detect for routing time instance. The node trust level is minimum causing the packet loss; it affects the entire network performance, and it reduces throughput and increases communication overhead. Proposed exhaustive routing path allocation (ERP) technique is applied to select the legitimate node for broadcasting the data packets completely. The attacker nodes of that flooding packets are detected by using the legitimate detector which are present in network environment. The node credence level evaluation algorithm is planned to estimating each and every node authority range, whether the nodes have higher credence level basis efficient packet transmission in wireless nodes; otherwise, nodes have lesser credence level basis in effective packet broadcasting. These higher credence level nodes are assigned for communication process in movable network. It improves the throughput and minimizes the communication overhead. The performance metrics of the parameters are delay, communication overhead, throughput, network lifetime, energy consumption, and packet loss.
Integral Fire Protection Analysis of Complex Spatial Steel Structure Based on Optimized Gaussian Transformation Model
Authors: Wang Zhiyi
Published: July 2022

The rapid development of complex space steel structure buildings has brought new challenges to structural fire protection analysis and design. On the basis of analyzing the deficiencies of structural fire protection design in existing normative and performance-based design methods and based on the knowledge and research results of fire science, structural engineering, computer simulation, and other disciplines, this paper proposes an improved Gaussian transformation model and applied it to the overall fire performance analysis of this complex space steel structure. The proposed model is based on theoretical research and practical application of the simulation and analysis of the overall fire performance of complex spatial buildings. The coupled analysis model and system integration method of spatial overall structure fire and structure are established. The improved Gaussian transformation model is used to propose the integrity of complex spatial structures. It is a system analysis model for fire analysis. The experimental results show that the designed algorithm model can effectively realize the overall fire performance analysis of complex spatial steel structures and can provide a useful reference for China’s building fire protection research, building fire protection design, fire rescue, emergency plan formulation, and other engineering practical applications.
THEM6: A Novel Molecular Biomarker Predicts Tumor Microenvironment, Molecular Subtype, and Prognosis in Bladder Cancer
Authors: Zhao Xu , Hu Jiao , Li Jiuyi , Gu Lan , Chen Jinbo , Othmane Belaydi , Gong Guanghui , Yuan Junbin , Deng Huiyin
Published: July 2022

Background. Thioesterase superfamily member 6 (THEM6) has been implicated in the development and progression of various cancers. However, prior research emphasized on its regulatory role merely, we aim to investigate the effect of THEM6 gene on the immunological role and its relationship with molecular subtype in bladder cancer (BLCA). Methods. Through pan-cancer analysis, we explored the THEM6 expression pattern and immunological role using The Cancer Genome Atlas (TCGA) database. In addition, we performed a correlation of THEM6 and its immunological functions, including immunomodulators, immune checkpoints, cancer immunity cycles, T cell inflamed score, and tumor-infiltrating immune cells in the BLCA tumor microenvironment (TME) based on TCGA and BLCA microarray cohort from Xiangya Hospital. We also assessed the accuracy of THEM6 in predicting the molecular subtype and its response to different interventions in BLCA. Finally, we computed and validated a prediction model established by THEM6-related different expressed immune-related genes that might help in BLCA prognosis. Results. THEM6 led to immunosuppression in BLCA TME. Furthermore, there was a downregulation in the immunological functions. Besides, THEM6 could effectively distinguish BLCA molecular subtypes, and THEM6 low expression implied basal subtype that was more effective to several interventions, such as immune checkpoint blockade (ICB) therapies, neoadjuvant chemotherapy, and radiotherapy. While THEM6 high expression indicated luminal subtype, hyperprogression and better response to targeted therapies, such as blocking THEM6 and several immune-inhibited oncogenic pathways. Conclusions. THEM6 may be with potential immune-modulating properties and may become a potential new immunotherapy target for BLCA. THEM6 could accurately predict the molecular subtype of BLCA, which was helpful for guiding the treatment. Simultaneously, the prediction model may exhibit an excellent predictive value in patients with BLCA.
Recurrence of LV Thrombus in a Patient with Severe Ischaemic Cardiomyopathy Anticoagulated with Apixaban
Authors: Farooqui Azhar , Lwin Tin , Costa Daniel , Hetherington Simon , Mattu Raj
Published: July 2022

Background. Anticoagulation with warfarin remains the mainstay treatment for left ventricular thrombi. Although successful thrombus resolution has been reported with direct oral anticoagulants’ (DOACs’) recurrence/progression while resuming Apixaban therapy is yet to be reported. Case Presentation. This case report describes left ventricular thrombus progression/recurrence in a patient anticoagulated with Apixaban undergoing implantable cardioverter defibrillator to cardiac resynchronisation therapy with defibrillator upgrade procedure. He was thereafter changed to warfarin. Contrast echocardiogram at 6 months follow-up did not identify the previously demonstrated mural thrombus. Conclusion. Prospective randomised control trials should be conducted in patients with left ventricular thrombus to compare anticoagulants, assess the efficacy and safety of DOACs, and evaluate uninterrupted DOAC versus transient withdrawal for cardiac device procedures.
Seroprevalence of COVID-19 in Blood Donors: A Systematic Review and Meta-Analysis
Authors: Nourmohammadi Hassan , Dehkordi Ali Hasanpour , Adibi Amir , Amin Hashemipour Seyed Mohammad , Abdan Mohsen , Fakhri Moloud , Abdan Zahra , Sarokhani Diana
Published: July 2022

Introduction. Determining the prevalence of SARS-CoV-2 in blood donors makes the control of virus circulation possible in healthy people and helps implement strategies to reduce virus transmission. The purpose of the study was to examine the seroprevalence of COVID-19 in blood donors using systematic review and meta-analysis. Materials and Methods. The electronic databases PubMed, Scopus, Web of Science, and the Google Scholar search engine were searched using standard keywords up to 2022-04-26. The variance of each study was calculated according to the binomial distribution. Studies were combined according to the sample size and variance. Q Cochrane test and I2 index were used to examine the heterogeneity of the studies. Data analysis was performed in STATA 14 software, and the significance level of the tests was

P
<
0.05

. Results. In the 28 papers examined with 227894 samples, the seroprevalence of COVID-19 in blood donors was 10% (95% CI: 9%, 11%), estimated 5% (95% CI: 4%, 7%) among men and 6% (95% CI: 4%, 7%) among women. This rate in different blood groups was as follows: A 12% (95% CI: 10%–14%), B 12% (95% CI: 10%–15%), AB 9% (95% CI: 7%–12%), and O 13% (95% CI: 11%–16%). The seroprevalence of COVID-19 in blood donors in North America 10%, Europe 7%, Asia 23%, South America 5%, and Africa was 4%; Moreover, the seroprevalence of IgG antibodies was estimated to be 23% (95% CI: 18%–29%) and IgM 29% (95% CI: 9%–49%). Conclusion. The highest prevalence of COVID-19 serum in women blood donors was among blood group O and Asia. The seroprevalence of IgG and IgM antibodies was high too.
IgG4-assoziierte Erkrankung mit gastrointestinaler Beteiligung: Fallberichte und Literaturübersicht
Authors: Zhang Xinhe , Jin Xing , Guan Lin , Lin Xuyong , Li Xuedan , Li Yiling
Published: July 2022

Die IgG4-assoziierte Erkrankung ist eine immunvermittelte chronische, systemische und autoinflammatorische Erkrankung, die verschiedene Organe im gesamten Körper betreffen kann. Am häufigsten sind die Bauchspeicheldrüse und die Gallenwege betroffen. Aufgrund der vielfältigen klinischen Erscheinungsformen der Krankheit sind viele Organe betroffen. Daher kann es leicht zu Fehldiagnosen kommen oder sie kann übersehen werden. Der Verdauungstrakt ist ein selten betroffenes System, und die meisten IgG4-assoziierten Magenerkrankungen werden mittels Endoskopie als Tumoren diagnostiziert. In diesem Artikel wird über zwei spezielle Fälle von IgG4-assoziierten Erkrankungen mit atrophischer Gastritis und Darmpolypen berichtet, um eine empirischere und theoretische Grundlage für die klinische Diagnose und Therapie zu schaffen.
Reliability of Automatic Computer Vision-Based Assessment of Orofacial Kinematics for Telehealth Applications
Authors: Simmatis Leif , Barnett Carolina , Marzouqah Reeman , Taati Babak , Boulos Mark , Yunusova Yana
Published: July 2022

Introduction: Telehealth/remote assessment using readily available 2D mobile cameras and deep learning-based analyses is rapidly becoming a viable option for detecting orofacial and speech impairments associated with neurological and neurodegenerative disease during telehealth practice. However, the psychometric properties (e.g., internal consistency and reliability) of kinematics obtained from these systems have not been established, which is a crucial next step before their clinical usability is established. Methods: Participants were assessed in lab using a 3 dimensional (3D)-capable camera and at home using a readily-available 2D camera in a tablet. Orofacial kinematics was estimated from videos using a deep facial landmark tracking model. Kinematic features quantified the clinically relevant constructs of velocity, range of motion, and lateralization. In lab, all participants performed the same oromotor task. At home, participants were split into two groups that each performed a variant of the in-lab task. We quantified within-assessment consistency (Cronbach’s α), reliability (intraclass correlation coefficient [ICC]), and fitted linear mixed-effects models to at-home data to capture individual-/task-dependent longitudinal trajectories. Results: Both in lab and at home, Cronbach’s α was typically high (>0.80) and ICCs were often good (>0.70). The linear mixed-effect models that best fit the longitudinal data were those that accounted for individual- or task-dependent effects. Discussion: Remotely gathered orofacial kinematics were as internally consistent and reliable as those gathered in a controlled laboratory setting using a high-performance 3D-capable camera and could additionally capture individual- or task-dependent changes over time. These results highlight the potential of remote assessment tools as digital biomarkers of disease status and progression and demonstrate their suitability for novel telehealth applications.
A persuasive agent architecture for behavior change intervention
Authors: Ojeniyi Adegoke , Khalid Adam , Kehinde Obafunmiso Christiana
Published: July 2022

A persuasive agent makes use of persuasion attributions to ensure that its predefined objective(s) is achieved within its immediate environment. This is made possible based on the five unique features namely sociable, persuasive, autonomy, reactive, and proactive natures. However, there are limited successes recorded within the behavioural intervention and psychological reactance is responsible for these failures. Psychological reactance is the stage where rejection, negative response and frustration are felt by the users of the persuasive system. Thus, this study proposes a persuasive agent (PAT) architecture that limits the experience of psychological reactance to achieve an improved behavioural intervention. PAT architecture adopted the combination of the reactance model for behavior change and the persuasive design principle. The architecture is evaluated by conducting an experimental study using a user-centred approach. The evaluation reflected that there is a reduction in the number of users who experienced psychological reactance from 70 per cent to 3 per cent. The result is a better improvement compared with previous outcomes. The contribution made in this study would provide a design model and a steplike approach to software designers on how to limit the effect of psychological reactance on persuasive system applications and interventions.
Prediction analysis on the pre and post COVID outbreak assessment using machine learning and deep learning
Authors: Walecha Ishaan , Jain Divya
Published: July 2022

In this time of a global urgency where people are losing lives each day in a large number, people are trying to develop ways/technology to solve the challenges of COVID-19. Machine learning (ML) and artificial intelligence (AI) tools have been employed previously as well to the times of pandemic where they have proven their worth by providing reliable results in varied fields this is why ML tools are being used extensively to fight this pandemic as well. This review describes the applications of ML in the post and pre COVID-19 conditions for contact tracing, vaccine development, prediction and diagnosis, risk management, and outbreak predictions to help the healthcare system to work efficiently. This review discusses the ongoing research on the pandemic virus where various ML models have been employed to a certain data set to produce outputs that can be used for risk or outbreak prediction of virus in the population, vaccine development, and contact tracing. Thus, the significance and the contribution of ML against COVID-19 are self-explanatory but what should not be compromised is the quality and accuracy based on which solutions/methods/policies adopted or produced from this analysis which will be implied in the real world to real people.
Meliorating usable document density for online event detection
Authors: Samanta Manisha , Meena Yogesh Kumar , Mazumdar Arka Prokash , Singh Girdhari , Gopalani Dinesh
Published: July 2022

Online event detection (OED) has seen a rise in the research community as it can provide quick identification of possible events happening at times in the world. Through these systems, potential events can be indicated well before they are reported by the news media, by grouping similar documents shared over social media by users. Most OED systems use textual similarities for this purpose. Similar documents, that may indicate a potential event, are further strengthened by the replies made by other users, thereby improving the potentiality of the group. However, these documents are at times unusable as independent documents, as they may replace previously appeared noun phrases with pronouns, leading OED systems to fail while grouping these replies to their suitable clusters. In this paper, a pronoun resolution system that tries to replace pronouns with relevant nouns over social media data is proposed. Results show significant improvement in performance using the proposed system.
Design and implementation of DC linear actuator and stepper motor for remote control of the driverless tractor robot
Authors: Sukontanakarn Viroch , Chalardsakul Tanawat , Saengchandr Banjerd
Published: July 2022

This research was to propose the DC linear actuators and a stepper motor as mechanical drive systems such as brake pedal, clutch pedal, forward-reverse gearshift, gear position selection, tail-lifting system to lift the chemical tank, and the speed selection system of power take-off (PTO). The DC linear actuators were used instead of the muscles, arms, and legs of the human being. The stepper motor was used to control the steering direction of a driverless tractor robot. The control was based on the programmable logic controller and radio remote control for the driverless tractor robots. Both MATLAB/Simulink simulation and experimental results were the validation and satisfactorily achieved. The test results of the driverless tractor robot in spraying water on a football field were satisfactory steering response and rapid braking.
Optimized speed control with torque ripple reductions of BLDC motor based on SMC approach using LFD algorithm
Authors: Kadhim Quasy Shabib , Abbas Abbas H. , Ali Mohammed Moanes Ezzaldean
Published: July 2022

Brushless DC motors (BLDCM) are utilized in various applications, including electric cars, medical and industrial equipment, where highefficiency speed control is necessary to meet load and tracking reference fluctuations. In this study, the optimal parameters of proportional-integral (PI) and sliding mode controller (SMC) for BLDC motor speed control are determined using Lévy flight distribution (LFD) technique. The integral time absolute error (ITAE) is used as a fitness function with the LFD algorithm for tuning the PI and SMC parameters. The optimization algorithms' performance is presented statistically and graphically. The simulation results show the SMC based on the LFD technique has superiority over SMC without optimization and PI controller in fast-tracking to the desired value with zero overshoot with rising time (6 ms) and low-speed ripple up to (± 9 RPM) under non-uniform conditions.