bluuebunny/crossref_metadata_2025 huggingface dataset:
Statistical Learning for Accurate and Interpretable Battery Lifetime Prediction
Authors: Attia Peter M. , Severson Kristen A. , Witmer Jeremy D.
Published: September 2021

Data-driven methods for battery lifetime prediction are attracting increasing attention for applications in which the degradation mechanisms are poorly understood and suitable training sets are available. However, while advanced machine learning and deep learning methods promise high performance with minimal data preprocessing, simpler linear models with engineered features often achieve comparable performance, especially for small training sets, while also providing physical and statistical interpretability. In this work, we use a previously published dataset to develop simple, accurate, and interpretable data-driven models for battery lifetime prediction. We first present the “capacity matrix” concept as a compact representation of battery electrochemical cycling data, along with a series of feature representations. We then create a number of univariate and multivariate models, many of which achieve comparable performance to the highest-performing models previously published for this dataset; thus, our work can serve as a comprehensive benchmarking study for this dataset. These models also provide insights into the degradation of these cells. Our approaches can be used both to quickly train models for a new battery cycling dataset and to benchmark the performance of more advanced machine learning methods.
Research on Impact Stress Transfer Characteristics of Lunar Rock Coring Drill
Authors: Li Peng , Wang Yizhuo , Xu Bo , Liu Junwei , Zhang Weiwei
Published: September 2021

In the whole lunar surface drilling and sampling task, it is critical to make the operation of the drilling and sampling impact system efficient and reliable. This paper focuses on how to improve the impact stress obtained at the cutting edge of the drill bit. Firstly, with the objective of maximizing the output impact energy, the design parameters of the percussive mechanism are optimally selected; based on the one‐dimensional stress wave transfer theory, the collision input model and transfer models of impact stress in the drilling tool are established. Secondly, in order to verify the above design parameters and theoretical models, the percussive drive characteristics’ test and the transfer characteristics’ tests of impact stress in the drill stem and drilling tool joints are carried out in turn. The experimental results are consistent with the theoretical analysis, which clarifies the transfer characteristics of the impact stress at the various stages of generation, incidence, and transfer to the cutting edge. It was finally found that increasing the percussive frequency and impact energy of the percussive mechanism as well as the contact stiffness of the collision surface can increase the incident impact stress of the drilling tool, while reducing the length of the screw connection between the drill bit and the drill stem can reduce the impact stress loss. This provides a theoretical reference for the design of the percussive mechanism and drilling tools in lunar surface drilling and sampling tasks.
Diagnostic Performance and Appropriate Cut‐Offs of Different Anthropometric Indicators for Detecting Children with Overweight and Obesity
Authors: Asif Muhammad , Aslam Muhammad , Ullah Kalim , Qasim Muhammad , Afzal Khurram , Abbas Asad , Ali Manzar , Younis Muhammad , Ullah Sami , Asad Muhammad Hassham Hassan Bin , Wyszyńska Justyna
Published: September 2021

In the clinical settings, different anthropometric indicators like neck circumference (NC), waist circumference (WC), midupper arm circumference (MUAC), waist‐to‐height ratio (WHtR), and arm‐to‐height ratio (AHtR) have been suggested for evaluating overweight and obesity in children. The comparative ability of these indicators in Pakistan is yet unknown. This study is aimed at examining the validity of different anthropometric indicators of overweight and obesity simultaneously and at determining their superlative cut‐off values that would correctly detect overweight and obesity in children. For this purpose, the dataset of anthropometric measurements height, weight, WC, MUAC, and NC of 5,964 Pakistani children, aged 5‐12 years collected in a cross‐sectional multiethnic anthropometric survey (MEAS), was used. Receiver operating characteristic (ROC) curve analysis was performed to assess the validity of different anthropometric indicators. The most sensitive and specific cut‐off points, positive and negative predictive values of each indicator were also calculated. The results of the ROC curve indicated that all the studied indicators had a good performance but the indicators AHtR and WHtR had the highest value of the area under the curve (AUC) for the screening of children with overweight and obesity (AUC > 0.80). In the overall sample, AHtR, WHtR, MUAC, WC, and NC cut‐off points indicative of overweight, in both boys and girls, were 0.14, 0.46, 18.41 cm, 62.86 cm, and 26.36 cm and 0.14, 0.47, 18.16 cm, 64.39 cm, and 26.54 cm, respectively; the corresponding values for obesity were 0.14, 0.47, 18.67 cm, 62.10 cm, and 26.36 cm and 0.14, 0.48, 20.19 cm, 64.39 cm, and 25.27 cm. We concluded that the sex‐specific cut‐off points for AHtR, WHtR, MUAC, WC, and NC can be used to diagnose overweight and obesity in Pakistani children.
Intelligent Algorithm-Based Magnetic Resonance Imaging in Radical Gastrectomy under Laparoscope
Authors: Mo Wenkui , Zhao Cansong
Published: September 2021

The study focused on the influence of intelligent algorithm-based magnetic resonance imaging (MRI) on short-term curative effects of laparoscopic radical gastrectomy for gastric cancer. A convolutional neural network- (CNN-) based algorithm was used to segment MRI images of patients with gastric cancer, and 158 subjects admitted at hospital were selected as research subjects and randomly divided into the 3D laparoscopy group and 2D laparoscopy group, with 79 cases in each group. The two groups were compared for operation time, intraoperative blood loss, number of dissected lymph nodes, exhaust time, time to get out of bed, postoperative hospital stay, and postoperative complications. The results showed that the CNN-based algorithm had high accuracy with clear contours. The similarity coefficient (DSC) was 0.89, the sensitivity was 0.93, and the average time to process an image was 1.1 min. The 3D laparoscopic group had shorter operation time (86.3 ± 21.0 min vs. 98 ± 23.3 min) and less intraoperative blood loss (200 ± 27.6 mL vs. 209 ± 29.8 mL) than the 2D laparoscopic group, and the difference was statistically significant (

P
<
0.05

). The number of dissected lymph nodes was 38.4 ± 8.5 in the 3D group and 36.1 ± 6.0 in the 2D group, showing no statistically significant difference (

P
>
0.05

). At the same time, no statistically significant difference was noted in postoperative exhaust time, time to get out of bed, postoperative hospital stay, and the incidence of complications (

P
>
0.05

). It was concluded that the algorithm in this study can accurately segment the target area, providing a basis for the preoperative examination of gastric cancer, and that 3D laparoscopic surgery can shorten the operation time and reduce intraoperative bleeding, while achieving similar short-term curative effects to 2D laparoscopy.
Some Summation Formulas for the Generalized Kampé de Fériet Function
Authors: Verma Ashish , Younis Jihad , Pandey Vikash Kumar , Aydi Hassen
Published: September 2021

The aim of this manuscript is to establish several finite summation formulas (FSFs) for the generalized Kampé de Fériet series (GKDFS). Moreover, the particular result for confluent forms of Lauricella series in

n

variables and four generalized Lauricella functions are obtained from the finite summation formulas for the GKDFS.
Stochastic Damage Constitutive Relationship of Steel‐Reinforced Concrete Bond‐Slip
Authors: Xie Ming , Liu Jiahao , Wang Peng , Wang Zi , Zhou Jingjing
Published: September 2021

The bond‐slip damage of the interface between profile steel and concrete is the key point of steel‐reinforced concrete structure. This paper is based on the statistical analysis of a large amount of experimental data and the distribution characteristics of bonding stress on the bonding surface of the profile steel and concrete, and the conversion rules between the three parts (chemical bonding force, frictional resistance, and mechanical interaction) of the bond force are obtained. According to the mutual conversion rules of the three parts of the bonding force on the steel‐reinforced concrete bonding surface, a mesomechanical model based on the spring‐friction block element is established. Taking into account the discreteness of concrete performance on the bonding surface and the randomness of defects, using the stochastic damage theory, a constitutive model of stochastic bonding damage on the steel‐reinforced concrete bonding surface is established. The comparative analysis with the results of a large number of steel‐reinforced concrete pull‐out tests shows that the model can reasonably reflect the damage characteristics of the steel‐reinforced concrete bonding surface.
Multiposition Rotation Interference Absolute Measurement Method for High-Precision Optical Component Surfaces
Authors: Zhu Xueliang , Nie Fengming , Liu Bingcai , Liu Ruikun , Tian Ailing
Published: September 2021

Modern optical engineering requires increasingly sophisticated interferometry methods capable of conducting subnanometer scale measurements of the large aperture, high-precision optical component surfaces. However, the accuracy of interferometry measurement is limited to the accuracy with which the surface of the reference mirror employed in the interferometer system is known, and the influence of gravity-induced deformation cannot be ignored. This is addressed in the present work by proposing a three-flat testing method based on multiposition rotation interference absolute surface measurement technology that combines the basic theory of N-position rotation with the separability of surface wavefront functions into sums of even and odd functions. These functions provide the rotational symmetric components of the wavefront, which then enables the absolute surface to be reconstructed based on the N-position rotation measurements. In addition, we propose a mechanical clamping combined with computational method to compensate for the gravity-induced deformations of the flats in the multiposition rotation absolute measurements. The high precision of the proposed absolute surface measurement method is demonstrated via simulations. The results of laboratory experiments indicate that the combination compensation method provides the high-precision surface reconstruction outcomes. The present work provides an important contribution for supporting the interferometry measurement of large aperture, high-precision optical component surfaces.
Complex Neutrosophic Soft Matrices Framework: An Application in Signal Processing
Authors: Khan Madad , Anis Saima , Bibi Kainat , Iqbal Sohail , Smarandache Florentin
Published: September 2021

In this paper, we introduce the concept of complex neutrosophic soft matrices. We define some basic operations including complement, union, and intersection on these matrices. We extend the concept of complex neutrosophic soft sets to complex neutrosophic soft matrices and prove related properties. Moreover, we develop an algorithm using complex neutrosophic soft matrices and apply it in signal processing.
Fuzzy C-Means Algorithm-Based Adoption of Obturator Nerve Block under Adaptive Ultrasound Imaging for Bladder Tumor
Authors: Hu Jianyun , He Pinglin , Zhang Bixin , Su Bin , Chen Jing , Hu Haifeng
Published: September 2021

This work aimed to study the adoption of obturator nerve block (ONB) based on adaptive medical ultrasound imaging under C-means algorithm in transurethral resection of bladder tumor (TURBT). 120 patients with bladder tumors were diagnosed by C-means algorithm-based ultrasound imaging and were enrolled into group A (epidural anesthesia + resection), group B (general anesthesia), and group C (epidural anesthesia + ONB), each with 40 cases. The accuracy of the detection method, noise level, and complications before and after the operation were compared. All patients received TURBT for treatment. There was no significant difference in the general information of patients in each group (

P
>
0.05

). As a result, the correct segmentation rate of the tumor region segmented by ultrasound imaging by C-means algorithm reached 95.6%. The incidence of obturator nerve reflex (ONR) in group A (7.5%) was greatly inferior to groups B and C (

P
<
0.05

). The length of hospital stay in group A was (4.01 ± 1.43) days, which was notably different from groups B and C, with considerable difference among the three (

P
<
0.05

). In short, the adaptive medical ultrasound imaging under C-means algorithm was more accurate in the diagnosis of bladder tumors. Moreover, ONB can effectively reduce the ONR and the incidence of complications in patients.
Burden of Renal Cysts Imaging: A Survey of Patients among the Greater Plains Collaborative
Authors: Kalot Mohamad A. , Dahm Philipp , Cowell Lindsay G. , Noureddine Lama , Mustafa Reem A.
Published: September 2021

Purpose: Renal cysts are a frequent incidental finding on cross-sectional radiographic imaging. While most cysts are indolent, individuals with such cysts are frequently monitored for interval growth and potential malignant transformation, which is ultimately rare. In this study, we aimed to assess patients’ values and preferences (believes and attitudes) about renal cysts. Methods: We deployed a cross-sectional survey to a random sample of patients with a diagnosis of renal cysts who were identified by billing code and self-identification. We collected data about demographics, insurance status, family history and overall health, and characteristics of patients with renal cysts. We performed a binary regression analysis (adjusted for age, gender, family history of cancer and kidney disease, and treatment plan for renal cysts) to determine anxiety predictors in patients with renal cysts. Results: We included 301 respondents in whom billing code and self-identification corresponded; of these, 138 had renal cysts and 163 did not. In an adjusted regression analysis, there was a suggestion that a clear management plan (OR = 0.49, 95% CI [0.22–1.11]) (p value 0.08) may be associated with less anxiety and a family history of renal disease may be associated with more anxiety (OR = 1.94 [0.76–4.94]) (p value 0.17). Family history of cancer also did not significantly predict anxiety (OR = 0.54 [0.24–1.19]) (p value 0.13). All these results were not statistically significant and had wide confidence intervals of the effect estimates make the results imprecise. Conclusion: Findings of this pilot study suggest a clear management plan for the renal cyst(s) management may be associated with a lower level of anxiety, thereby by emphasizing the importance of good communication, patient engagement and evidence-based guidance. More definitive, adequately powered studies are needed to evaluate this finding further. In addition, further studies exploring differences in imaging practices, patient symptomatology and patient engagement by different provider types would be insightful. Ultimately, tools to improve shared decision-making are needed to provide more patient-centered care.
Spontaneous Spinal Epidural Hematoma Mimicking Stroke and Its Outcome post Intravenous Thrombolysis
Authors: Szeto Cheuk Ling Charing , Hui Kwok Fai
Published: September 2021

Background and Purpose: Spontaneous spinal epidural hematoma (SSEH) is a rare neurological emergency. Its presentation, depending on location of hematoma, could mimic stroke. While intravenous thrombolysis (IVT) is recommended to commence as early as possible in case of acute ischemic stroke, it is likely that it could be given to SSEH patients. We aimed to examine the prevalence, outcome, and prognosis of such patients. Methods: We have retrospectively screened all patients given IVT from January 2008 to March 2021 admitted to United Christian Hospital, a tertiary hospital in Hong Kong. We reviewed the final diagnosis of all patients and included cases diagnosed with SSEH. Their clinical and radiological features, treatment, and outcome were analyzed. We further performed a literature review to search for all cases with SSEH given IVT and review their clinical features and outcome. Results: Out of a total of 940 patients over the 12-year span, 2 patients were diagnosed with SSEH, accounting for 0.21% of cases. From our literature search, to date, there are only 10 cases that had been reported from 5 case reports where IVT was given to SSEH patients. Of the 12 cases, all presented with hemiparesis and 9 with pain. Of those with neck pain, 3 with initial computed tomography angiogram done showed SSEH which was missed initially. Eight were treated surgically and 4 conservatively. All recovered with no major disability. Conclusions: Though a rare disease, awareness toward SSEH presenting as stroke mimic should be raised.
IL-6 Is Associated with Progression of Coronary Artery Calcification and Mortality in Incident Dialysis Patients
Authors: Roy Neil , Rosas Sylvia E.
Published: September 2021

Introduction: Inflammation is important in the pathogenesis of atherosclerosis. Elevated interleukin-6 (IL-6) is associated with cardiovascular events and also predicts mortality in individuals with CKD. Our goal was to determine the association between IL-6, FGF23, and high-sensitivity C-reactive protein (hsCRP) on coronary artery calcification (CAC) progression and mortality in incident dialysis patients without prior coronary events. Methods: A prospective cohort of incident adult dialysis participants had CAC measured by ECG-triggered multislice CT scans at baseline and at least 12 months later. Lipids, mineral metabolism markers, FGF23, and inflammatory markers, such as IL-6 and hsCRP, were measured at the baseline visit. Results: Participants in the high IL-6 tertile had the highest baseline CAC score (133.25 [10.35–466.15]) compared to the low (0.25 [0–212.2]) and intermediate (29.55 [0–182.85]) tertiles. Almost half of the participants with high IL-6 (15 of 32 [46.9%]) experienced progression of CAC compared to participants with low (8 of 32 [25%]) and intermediate (9 of 32 [28.1%]) (p = 0.05) IL-6 levels. Each log increase in IL-6 was associated with increase in death (hazard ratio 2.2, 95% CI: 1.2–3.8; p = 0.01). After adjusting for smoking, age, gender, race, diabetes, phosphate, and baseline calcium score, IL-6 (log) was associated with 2.2 times (95% CI: 1.1–4.6; p = 0.03) increase in death. Conclusion: IL-6 is associated with progression of CAC and mortality in incident dialysis patients.
Total power deficiency estimation of isolated power system network using full-state observer method
Authors: Jamri M. Saifuzam , Kamarudin Muhammad Nizam , Mohd Jamil Mohd Luqman
Published: September 2021

An isolated electrical network with an independent local distributed generator is very sensitive towards the contingencies between load demand and supply. Although the network system has less complexity in term of structure, its stability condition is crucial due to its stand-alone operating condition. The total power deficit in the network gives the important information related to the dynamical frequency responses which may directly affect the system’s stability level. In this paper, the approach to estimate the total power deficiency for the isolated electrical network was presented by utilized the Luenberger observer method. Although the power deficit is not the state variable in the network mathematical model, the solution of estimation problem was feasible by introducing the new variable using additional dummy system. The simulation was carried out by using MATLAB/Simulink environment and the designed estimator was verified using multifarious load demand changes. The results show that the estimated signal was successfully tracked the expected actual signal with minimum error.
An investigation of inertia constant in single generator on transient analysis for an isolated electrical network system
Authors: Jamri M. Saifuzam , Kamarudin Muhammad Nizam , Mohd Jamil Mohd Luqma
Published: September 2021

An isolated electrical network which fed by an independent generator for a low voltage system is considerable in remote and islandic areas. Although the network system has less complexity in term of system structure, its stability level is crucial due to frequency dynamical responses. An influence of initial stability margin on frequency stability study during contingency situation is a thing rather than being ignored. Here the initial transient response inherently delivers important info such as system inertia and momentarily power deficit. In this paper, an investigation of transient stability responses under different inertia values is carried out. The investigation is carried out by modelling the isolated system in MATLAB/Simulink environment which consists of state-space mathematical equations. It is confirmed that the generator system inertia shapes the initial slope, speed droop and oscillation. For a verification purpose, the influence of system inertia is also analyzed using bode diagram in which system gain and frequency margin are evaluated.

 
Modeling of high frequency high voltage of waveforms on life of enamel insulation
Authors: Rao S. Narasimha , Kasinathan Elanseralathan
Published: September 2021

In recent years it has been observed that insulation failure in electrical motors is caused by adjustable speed drives fed by power electronic converters. These converters produce impulse waveforms having a high slew rate generated by the high switching frequency of IGBTs. This paper focuses on high switching frequency stress in low voltage electrical motors for adjustable speeds. To examine the motor winding insulation under such stress twisted-pair samples were developed from enameled wires. A single-coated polyester of enamel with a thickness of 40 microns is used for this work. High-frequencies, high voltages of Square, and Square-rising, Square-spike waveforms of 10-30 kHz are used here. The test results show that the insulation fails earlier for the Square waveform compared to the Square-spike and Square-rising waveforms. In a nutshell, there is an analysis of PD formation in the insulation system at a higher switching frequency is analyzed. Electric field distributions between twisted pairs with various air gaps of the insulation system stressed by the Square and Square-rising waveforms up to 30 kHz are modeled using COMSOL software.
An analysis of manual and autoanalysis for submicrosecond parameters in the typical first lightning return stroke
Authors: Bahari Muhammad Akmal , Baharudin Zikri Abadi , Sutikno Tole , Rahman Ahmad Idil Abdul , Hanafiah Mohd Ariff Mat , Ibrahim Mazree
Published: September 2021

The mechanism on how lightning detection system (LDS) operated never been exposed by manufacturer since it was confidential. This scenario motivated the authors to explore the issue above by using MATLAB to develop autoanalysis software based on the feature extraction. This extraction is intended for recognizing the parameters in the first return stroke, and compare the measurement between the autoanalysis software and the manual analysis. This paper is a modification based on a previous work regarding autoanalysis of zero-crossing time and initial peak of return stroke using features extraction programming technique. Further, the parameter on rising time of initial peak is added in this autoanalysis programming technique. Finally, the manual analysis using WaveStudio (LeCroy product) of those two lightning parameters is compared with autoanalysis software. This study found that the autoanalysis produce similar result with the manual analysis, hence proved the reliability of this software.
Enhancement of medical images using fuzzy logic
Authors: Fadil Yousra Ahmed , Al-Bander Baidaa , Radhi Hussein Y.
Published: September 2021

Image enhancement is one of the most critical subjects in computer vision and image processing fields. It can be considered as means to enrich the perception of images for human viewers. All kinds of images typically suffer from different problems such as weak contrast and noise. The primary purpose of image enhancement is to change an image's visual appearance. Many algorithms have recently been proposed for enhancing medical images. Image enhancement is still deemed a challenging task. In this paper, the fuzzy c-means clustering (FCM) technique is utilized to enhance the medical images. The method of enhancement consists of two stages. The proposed algorithm conducts a cluster test on the image pixels. It then increases the difference of gray level between the diverse objects to accomplish the enhancement purpose of the medical images. The experimental results have been tested using various images. The algorithm enhanced the small target of the image to a reasonable limit and revealed favorable performance. The results of image enhancement techniques were evaluated by using terms of different criteria such as peak signal to noise ratio (PSNR), mean square error (MSE) and average information contents (AIC), showing promising performance.
Designated path routing algorithm for dense wireless sensor network
Authors: Subramaniam Siva Kumar , Azman Amierul Syazrul , Lee Mohamad Yusry , Feroz Farah Shahnaz
Published: September 2021

Due to extensive pipeline dissemination in the oil and gas refinery, the nodes need to be placed in a grid formation. As such, since most oil and gas industry applications require continuous data gathering, a heavy data stream will be introduced in the network traffic, mainly when the network density is high. As a result, performance degradation and poor energy consumption will occur. Ad hoc on-demand distance vector and optimized link state routing protocol have been simulated to investigate these issues further. Due to packet congestion, the network experiences a domino effect on the performance, such as packet loss, throughput degradation, and poor energy consumption. Thus, a tailored solution is required since oil and gas industry relies heavily on sensor data to keep track of pipelines condition to prevent anomalous events from happening. The proposed algorithm has been developed to optimize the network performance by dividing the traffic into two and by reducing the flooding during route discovery. The results have shown better network performance and energy consumption can be achieved using the proposed algorithm when compared to the others.
Machine learning deployment for arms dynamics pattern recognition in Southeast Asia region
Authors: Indra Zul , Setiawan Azhari , Jusman Yessi , Adnan Arisman
Published: September 2021

Finding the most significant determinant variable of arms dynamic is highly required due to strategic policies formulations and power mapping for academics and policy makers. Machine learning is still new or underdiscussed among the study of politics and international relations. Existing literature have much focus on using advanced quantitative methods by applying various types of regression analysis. This study analyzed the arms dynamic in Southeast Asia countries along with its some strategic partners such as United States, China, Russia, South Korea, and Japan by using ‘Decision Tree’ of machine learning algorithm. This study conducted a machine learning analysis on 55 variable items which is classified into 8 classes of variables videlicet defense budget, arms trade exports, arms trade imports, political posture, economic posture, security posture and defense priority, national capability, and direct contact,. The results suggest three findings: (1) state who perceives maritime as strategic drivers and forces will seek more power for its maritime defense posture which is translated to defense budget, (2) big size countries tend to be an arms exporter country, and (3) state’s energy dependence often leads to a higher volume of arms transfers between countries.
An effective face recognition method using guided image filter and convolutional neural network
Authors: S. Yallamandaiah , N. Purnachand
Published: September 2021

In the area of computer vision, face recognition is a challenging task because of the pose, facial expression, and illumination variations. The performance of face recognition systems reduces in an unconstrained environment. In this work, a new face recognition approach is proposed using a guided image filter, and a convolutional neural network (CNN). The guided image filter is a smoothing operator and performs well near the edges. Initially, the ViolaJones algorithm is used to detect the face region and then smoothened by a guided image filter. Later the proposed CNN is used to extract the features and recognize the faces. The experiments were performed on face databases like ORL, JAFFE, and YALE and attained a recognition rate of 98.33%, 99.53%, and 98.65% respectively. The experimental results show that the suggested face recognition method attains good results than some of the state-of-the-art techniques.
A comparative and comprehensive study of prediction of Parkinson’s disease
Authors: Prasath N. , Pandi Vigneshwaran , Manickavasagam Sindhuja , Ramadoss Prabu
Published: September 2021

Objectives: Parkinson's Disease (PD) is a form of neurodegenerative disease that is caused the progressive weakening of dopaminergic nerve cells that affects a large number of people around the world.  The event of recent treatment methods principally depends upon the experimental data resulting from assessment balances and patients’ journals that take varied boundaries with reference to legitimacy, inter-rater inconsistency, and incessant monitoring. Methods: Nowadays various techniques and algorithms are utilized in predicting the accuracy in PD. A range of those techniques, including SVM, Artificial Neural Network, Naive Bayes, Kernel based extreme learning through subtractive clustering landscapes, Random Forest, The Multi-Layer Perceptron with Back-Propagation Learning Algorithm are widely applied to form the acceptable decision accurately. During this work, and in-depth review was administered on various techniques proposed by numerous researchers. a replacement system must be proposed which uses DL techniques and considers other attributes of paralysis agitans which can improve the prediction and be an advancement within the medical field. Result: It has been observed that many researches have been done in identifying the PD yet there is a need of suitable method or algorithm to improve the prediction of PD which will help in the clinical management. Conclusion and Future work: Most of the methods have used speech as a major attribute for their research and have produced substantial accuracy. In order to increase the precision approaches involving movements, facial expression and other attributes also be considered for evaluation
Content-based image retrieval for fabric images: A survey
Authors: Tena Silvester , Hartanto Rudy , Ardiyanto Igi
Published: September 2021

In recent years, a great deal of research has been conducted in the area of fabric image retrieval, especially the identification and classification of visual features. One of the challenges associated with the domain of content-based image retrieval (CBIR) is the semantic gap between low-level visual features and high-level human perceptions. Generally, CBIR includes two main components, namely feature extraction and similarity measurement. Therefore, this research aims to determine the content-based image retrieval for fabric using feature extraction techniques grouped into traditional methods and convolutional neural networks (CNN). Traditional descriptors deal with low-level features, while CNN addresses the high-level, called semantic features. Traditional descriptors have the advantage of shorter computation time and reduced system requirements. Meanwhile, CNN descriptors, which handle high-level features tailored to human perceptions, deal with large amounts of data and require a great deal of computation time. In general, the features of a CNN's fully connected layers are used for matching query and database images. In several studies, the extracted features of the CNN's convolutional layer were used for image retrieval. At the end of the CNN layer, hash codes are added to reduce  search time.
Ensino e aprendizagem no contexto do Ensino Remoto e da Educação a Distância: caminhos e possibilidades
Authors: Elias Júnior Jorge , Carmona Fábio , Cesaretti Mário Luís Ribeiro , Bollela Valdes Roberto
Published: September 2021

Todo o conhecimento acumulado sobre o processo de ensino e aprendizagem, considerando as melhores práticas docentes e os conceitos sobre aprendizado de adultos, aprendizagem significativa e aprendizado centrado no estudante devem ser continuamente exercitados e revisitados, independente do formato: presencial, ensino remoto (ER) ou ensino a distância (EaD). A necessidade de ampliação da utilização do ER emergencial, determinada pela crise pandêmica de 2020, trouxe novos desafios para professores e estudantes em todo o mundo. Dentre os desafios se apresenta areinterpretação dos conceitos presentes no processo de ensino e aprendizagem sob a lente do mundo digital. Esta revisão busca apresentar as melhores práticas sob o prisma do novo contexto da vida digital no ensino para as profissões da saúde, incluindo aqui as oportunidades oferecidas pela pandemia
Avaliação do Estudante na Educação remota (ER) e à Distância (EAD): como desenvolver de modo efetivo, enfatizando a devolutiva
Authors: Volpe Fábio Antônio Perecim , Quintana Silvana Maria , Borges Marcos de Carvalho , Troncon Luiz Ernesto de Almeida
Published: September 2021

A avaliação do estudante, que constitui parte essencial da sua educação, sobretudo nas profissões da saúde, vem sofrendo grandes avanços nos seus conceitos fundamentais e, sobretudo, na sua prática cotidiana. Boa parte dessas mudanças relaciona-se à crescente utilização de estratégias de ensino e aprendizagem mediadas pela tecnologia da informação e comunicação (educação à distância ou ensino remoto), que foi, mais recentemente, acelerada pela pandemia do COVID-19. Deve ser também destacado que parte dessas mudanças implicou em maior reconhecimento da grande efetividade da avaliação formativa, desenvolvida, sobretudo, por meio da prática da devolutiva (feedback) frequente e de boa qualidade, seguindo recomendações técnicas adequadas. Neste artigo, apresentam-se alguns conceitos básicos de avaliação educacional e da avaliação do estudante, discute-se o papel estratégico da avaliação formativa e o poder da devolutiva (feedback), descrevem-se algumas das características da devolutiva efetiva e as correspondentes recomendações para a sua prática e descreve-se brevemente um conjunto de sugestões sobre possíveis maneiras efetivas de praticar a avaliação do estudante na educação remota e à distância, com ênfase na finalidade formativa, mas sem desconsiderar a somativa, que implica na tomada de decisões como aprovação ou reprovação.
FMRP unida por um semestre melhor: narrativas de um pacto que celebra valores humanos e compromissos coletivos durante a pandemia da Covid-19
Authors: Panúncio-Pinto Maria Paula , Flauzino Rodrigo Humberto , Ferraz Victor Evangelista de Faria , Bollela Valdes Roberto
Published: September 2021

A pandemia da COVID-19 impactou a educação superior de diversas formas, demandando criatividade e resiliência no seu enfrentamento. Além dos novos desafios, o cenário induzido pela crise sanitária também agudizou problemas pré-existentes, principalmente no que se refere às relações humanas dentro da universidade, à equidade no acesso a recursos educacionais e à capacitação para o desenvolvimento profissional, qualidade de vida e o cuidado com as pessoas, entre tantos outros desafios. Nesse contexto, em busca de respostas para os problemas apresentados, diferentes centros e comissões da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP) se uniram e propuseram a celebração do Pacto “FMRP: UNIDA POR UM SEMESTRE MELHOR”. O Pacto foi proposto para reafirmar os valores da instituição, fortalecer as relações e a rede de suporte às pessoas e aos processos, minimizar o estresse e o impacto na saúde e bem-estar de estudantes, funcionários e professores. O objetivo deste relato é apresentar os termos e condições que tornaram o Pacto possível, como estratégias utilizadas para sua execução, ações integradas de diferentes setores, comunicação qualificada visando responder às necessidades da comunidade acadêmica. O pacto promoveu ações para garantir acesso a recursos para ensino e aprendizagem, capacitação profissional e cuidado nas relações interpessoais e entre os diferentes setores da instituição. O Pacto nasceu no contexto da pandemia e chamou atenção para a necessidade constante de aprimorarmos nossas relações, de investir no diálogo e na integração. Já não se trata de ações para “um semestre melhor”, mas de compromissos e valores que reafirmamos e devem seguir conosco seja qual for o contexto e situação.
T. F. Torrance in the light of Stephen Holmes’s critique of contemporary Trinitarian thought
Authors: Radcliff Jason
Published: September 2021

This article examines T. F. Torrance’s doctrine of the Trinity in the light of Stephen Holmes’s recent critiques of the so-called 20th-century Trinitarian ‘revival’. This article (1) analyzes Torrance’s reading of the Fathers in light of Holmes, (2) explores areas where Holmes’s critique has potential to apply to Torrance, and (3) offers suggestions concerning where Torrance is relevant and complementary to Holmes. This article argues that Torrance ‘reconstructs’ the patristic doctrine of the Trinity from a Reformed, evangelical, and Christocentric perspective and, as such, his project is different from but complementary to Holmes. Yet Torrance’s reconstruction is relevant and under-utilized by the current scholarly conversation. Building upon the ground cleared by Holmes, this article offers new insight into (1) Torrance’s reading of the Fathers, (2) Torrance’s version of the patristic doctrine of the Trinity, and (3) Torrance’s relevance in the current scholarly conversation on the doctrine of the Trinity in the Fathers.
Back to the Future: The Millennium and the Exodus in Revelation 20
Authors: Guy Laurie
Published: September 2021

Revelation 20 has the puzzling story-line of a menacing Satan being released from a God-imposed imprisonment of one thousand years. Why would God let Satan out? There are strong intratextual connections between Revelation 20 and Revelation 12, that chapter also pointing to a two-stage overthrow of Satan. Revelation 20 has exodus linkage in its ‘dragon’ and ‘abyss’ language. In addition, Revelation 20 and the exodus tradition in the earlier Book of Jubilees both involve a two-stage overthrow of Satan (‘Mastema’). Exodus thus seems to be a template for the Revelation 20 storyline, bringing a message of hope to a trapped people. As God came through a second time at the Sea of Reeds, so God will again bring about a final deliverance and overthrow of Satan for John’s audience. Revelation 20 is thus not primarily about a distant millennial future but more about hope for a first-century embattled people.
Review of Gibberifera Obraztsov (Lepidoptera: Tortricidae) from China, with description of a new species
Authors: ZHANG AIHUAN
Published: September 2021

Chinese species of the genus Gibberifera Obraztsov are reviewed. G. tetracornata sp. nov. is described as new to science with illustrations of adult and genitalia. Other species are summarized with detailed references cited and information about host-plants and distribution. A key to Chinese species of Gibberifera based on characters of male genitalia is given.
Two new Peruvian species of Tichocoelidia Kramer (Hemiptera: Cicadellidae: Neocoelidiinae) with a key to males
Authors: GONÇALVES CLAYTON CORRÊA , BARBOSA JULIANNA FREIRES
Published: September 2021

Two new species of Tichocoelidia Kramer, 1962 are described and illustrated, T. marceloi sp. nov. and T. vanessae sp. nov., both from Cusco, Peru. A key to males of the four known species of Tichocoelidia is provided.
Rhamphothrips genus-group in China, with description of two new species and two new records (Thysanoptera: Thripidae)
Authors: LI YAJIN , LIU ZHUOCHENG , ZHANG HONGRUI
Published: September 2021

Amalothrips bifurcus sp.n. is described from Southwestern China as the third species of Amalothrips, characterized by the forked sense cone on antennal segments III–IV. Rhamphothrips yunnanensis sp.n. is described as the second known species of Rhamphothrips in which the male has laterally on the mesosternum one thorn-like seta and one stout shaded seta. Two species, Amalothrips noorazlani Ng and Parexothrips palumai Mound, are newly recorded from China.
Pulmonary function after segmentectomy versus lobectomy in patients with early-stage non-small-cell lung cancer: a meta-analysis
Authors: Wang Xinxin , Guo Haixie , Hu Quanteng , Ying Yongquan , Chen Baofu
Published: September 2021

Objective

Segmentectomy is widely performed for early-stage lung cancer. However, the effects of segmentectomy versus lobectomy on pulmonary function remain unclear. We performed a meta-analysis with the aim of comparing segmentectomy and lobectomy in terms of preservation of pulmonary function in patients with early-stage non-small-cell lung cancer (NSCLC).

Methods

We conducted a literature search of PubMed using the terms ‘pulmonary function’ AND ‘segmentectomy’ AND ‘lobectomy’. The primary outcomes of interest were the forced expiratory volume in 1 second (FEV1), FEV1 as percent of predicted (%FEV1), change in FEV1 (Δ%FEV1), and the ratio of postoperative to preoperative FEV1.

Results

Thirteen studies comprising 2027 patients met the inclusion and exclusion criteria and were included for analysis, including 787 patients in the segmentectomy group and 1240 patients in the lobectomy group. Patients in the segmentectomy group showed significantly better preservation of FEV1 and %FEV1 compared with the lobectomy group. The reduction in FEV1 after surgery was significantly less in the segmentectomy group compared with the lobectomy group, and Δ%FEV1 was significantly higher in the segmentectomy group than in the lobectomy group.

Conclusion

Segmentectomy results in better preservation of pulmonary function compared with lobectomy in patients with early-stage NSCLC.
Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review
Authors: Zuraw Aleksandra , Aeffner Famke
Published: September 2021

Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. While some aspects, such as whole-slide imaging for archiving, consulting, and teaching, have gained broader acceptance, other facets such as quantitative tissue image analysis and artificial intelligence–based assessments are still met with some reservations. While most vendors in this space have focused on diagnostic applications, that is, viewing one or few slides at a time, some are developing solutions tailored more specifically to the various aspects of veterinary pathology including updated diagnostic, discovery, and research applications. This has especially advanced the use of digital pathology in toxicologic pathology and drug development, for primary reads as well as peer reviews. It is crucial that pathologists gain a deeper understanding of digital pathology and tissue image analysis technology and their applications in order to fully use these tools in a way that enhances and improves the pathologist’s assessment as well as work environment. This review focuses on an updated introduction to the basics of digital pathology and image analysis and introduces emerging topics around artificial intelligence and machine learning.
Anti-swing radial basis neuro-fuzzy linear quadratic regulator control of double link rotary pendulum
Authors: Hazem Zied Ben , Fotuhi Mohammad Javad , Bingül Zafer
Published: September 2021

In this article, a radial basis neuro-fuzzy linear quadratic regulator controller is developed for the anti-swing control of a double link rotary pendulum system. The objective of this work is to study the radial basis neuro-fuzzy linear quadratic regulator controller and to compare it with a fuzzy linear quadratic regulator and the linear quadratic regulator controllers. In the proposed radial basis neuro-fuzzy linear quadratic regulator controllers, the positions and velocities of state variables multiplied by their linear quadratic regulator gains are trained using two radial basis neural networks architecture. The output of the two radial basis neural networks is used as the input variables of the fuzzy controller. The novel architecture of the radial basis neuro-fuzzy controller is developed in order to obtain better control performance than the classical adaptive neuro-fuzzy controller. To determine the control performance of the anti-swing controllers, different control parameters are computed. According to the comparative results, the anti-swing radial basis neuro-fuzzy linear quadratic regulator controller yields improved results than fuzzy linear quadratic regulator and linear quadratic regulator. Furthermore, the performance of the three controllers developed was compared based on robustness analysis under external force disturbance. The results obtained here indicate that the anti-swing radial basis neuro-fuzzy linear quadratic regulator controller product has better performance than other controllers in terms of vibration suppression ability.
Assessment of Productivity and Crop Diversification Pattern in Punjab Agriculture
Authors: Rani Poonam , Sahoo Ajeet Kumar
Published: September 2021

This study examines the structure of agriculture productivity and crop diversification across different zones in Punjab, India during 1966–1967 to 2017–2018. The composite entropy index shows that almost all zones are specialised in few crops but some of them are relatively less or some are more. Hence, we found zones are experiencing a lateral movement toward crop specialisation and crop diversification is not happening. Further, results reveals that accessibility of market and roadhave a positive influenced the level of crop diversification are accessibility of market, roads have found a positive influenced on crop diversification. Whereas more use of fertiliser, intensity of irrigation and rainfall have leads to concentration rather than crop diversification. Similarly, study also analysed the factors that are responsible of variation in productivity by regional factors such as better road, fertiliser, urbanisation, literacy and cropping intensity. As the analysis indicates that there is need to emphasise on agro-climatic regional preparation by clearly identifying the existing resource endowments and constraints of the agro-climatically homogeneous regions.

JEL: C23,Q10, Q19