bluuebunny/crossref_metadata_2025 huggingface dataset:
Serverless, FaaS and why organizations need them
Authors: Astrova Irina , Koschel Arne , Schaaf Marc , Klassen Samuel , Jdiya Kerim
Published: December 2021

This paper is aimed at helping organizations to understand what they can expect from a serverless architecture in the future and how they can make sound decisions about the choice between microservice and serverless architectures in the present. A serverless architecture is a new approach to offering services in the cloud. It was invented as a solution to the problem that many organizations are facing today – about 85% of their servers have underutilized capacity, which is proved to be costly and wasteful. By employing the serverless architecture, the organizations get a way to eliminate idle, underutilized servers and thus, to reduce their operational costs. Many cloud providers are now jumping to the serverless world because they know it is going to be the future of software architectures. However, being a new approach, the serverless architecture is still relatively immature – it is in the early stages of its support by cloud service platform providers. This paper provides an in-depth study about the serverless architecture and how to apply FaaS in the real world.
Neurules and connectionist expert systems: Unexplored neuro-symbolic reasoning aspects
Authors: Prentzas Jim , Hatzilygeroudis Ioannis
Published: December 2021

Neuro-symbolic approaches combine neural and symbolic methods. This paper explores aspects regarding the reasoning mechanisms of two neuro-symbolic approaches, that is, neurules and connectionist expert systems. Both provide reasoning and explanation facilities. Neurules are a type of neuro-symbolic rules tightly integrating the neural and symbolic components, giving pre-eminence to the symbolic component. Connectionist expert systems give pre-eminence to the connectionist component. This paper explores reasoning aspects about neurules and connectionist expert systems that have not been previously addressed. As far as neurules are concerned, an aspect playing a role in conflict resolution (i.e., order of neurules) is explored. Experimental results show an improvement in reasoning efficiency. As far as connectionist expert systems are concerned, variations of the reasoning mechanism are explored. Experimental results are presented for them as well showing that one of the variations generally performs better than the others.
Addressing the issue of undeclared work – Part I: Applying associative classification per the CRISP-DM methodology
Authors: Alogogianni Eleni , Virvou Maria
Published: December 2021

Addressing undeclared work is a high priority in the labor field for government policymakers since it adversely affects all involved parties and results in significant losses in tax and social security contribution revenues. In the last years, the wide use of ICT in labor inspectorates and the considerable progress in data exchange have resulted in numerous databases dispersed in various units, yet these are not effectively used to increase their functions productivity. This study presents a detailed analysis of a data mining project per the CRISP-DM methodology aiming to assist the labor inspectorates in dealing with undeclared work and other labor law violations. It uses real past inspections data merged with companies characteristics and their employment details and examines the application of two Associative Classification algorithms, the CBA and CBA2, in combination with two types of datasets, a binary and a four-class. The produced models are assessed per the data mining goals and per the initial business objectives, and the research concludes proposing an innovative inspections recommendation tool proved to offer two major benefits: a mechanism for planning targeted inspections of improved efficiency and a knowledge repository for enhancing the inspectors understanding of those features linked with labor law violations.
Chronic Renin-Angiotensin System Activation Induced Neuroinflammation: Common Mechanisms Underlying Hypertension and Dementia?
Authors: Tran Shirley , Kuruppu Sanjaya , Rajapakse Niwanthi W.
Published: December 2021

Hypertension is a major risk factor for the pathogenesis of vascular dementia and Alzheimer’s disease. Chronic activation of the renin-angiotensin system (RAS) contributes substantially to neuroinflammation. We propose that neuroinflammation arising from chronic RAS activation can initiate and potentiate the onset of hypertension and related dementia. Neuroinflammation induced by chronic activation of the RAS plays a key role in the pathogenesis of dementia. Increased levels of pro-inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and transforming growth factor (TGF)-β have been reported in brain tissue of vascular dementia patients and animal models of vascular dementia induced by either angiotensin II infusion or transverse aortic coarctation. It is proposed that neuronal cell death and synaptic dysfunction induced by neuroinflammation lead to cognitive impairment in dementia. The neuroprotective RAS pathway, regulated by angiotensin-converting enzyme 2 (ACE2) which converts angiotensin II into angiotensin-(1–7), can attenuate hypertension and dementia. Furthermore, the use of anti-hypertensive medications in preventing dementia or cognitive decline in hypertensive patients and animal models of dementia have mostly been beneficial. Current evidence suggests a strong link between RAS induced neuroinflammation and the onset of hypertension and dementia, which warrants further investigation. Strategies to counteract an overactive RAS and enhance the neuroprotective arm of the RAS may help prevent or improve cognitive impairment associated with hypertension.
Hybrid approach with Deep Auto-Encoder and optimized LSTM based Deep Learning approach to detect anomaly in cloud logs
Authors: Pankajashan Savaridassan , Maragatham G. , Kirthiga Devi T.
Published: December 2021

Anomaly-based detection is coupled with recognizing the uncommon, to catch the unusual activity, and to find the strange action behind that activity. Anomaly-based detection has a wide scope of critical applications, from bank application security to regular sciences to medical systems to marketing apps. Anomaly-based detection adopted by various Machine Learning techniques is really a type of system that consists of artificial intelligence. With the ever-expanding volume and new sorts of information, for example, sensor information from an incontestably enormous amount of IoT devices and from network flow data from cloud computing, it is implicitly understood without surprise that there is a developing enthusiasm for having the option to deal with more conclusions automatically by means of AI and ML applications. But with respect to anomaly detection, many applications of the scheme are simply the passion for detection. In this paper, Machine Learning (ML) techniques, namely the SVM, Isolation forest classifiers experimented and with reference to Deep Learning (DL) techniques, the proposed DA-LSTM (Deep Auto-Encoder LSTM) model are adopted for preprocessing of log data and anomaly-based detection to get better performance measures of detection. An enhanced LSTM (long-short-term memory) model, optimizing for the suitable parameter using a genetic algorithm (GA), is utilized to recognize better the anomaly from the log data that is filtered, adopting a Deep Auto-Encoder (DA). The Deep Neural network models are utilized to change over unstructured log information to training ready features, which are reasonable for log classification in detecting anomalies. These models are assessed, utilizing two benchmark datasets, the Openstack logs, and CIDDS-001 intrusion detection OpenStack server dataset. The outcomes acquired show that the DA-LSTM model performs better than other notable ML techniques. We further investigated the performance metrics of the ML and DL models through the well-known indicator measurements, specifically, the F-measure, Accuracy, Recall, and Precision. The exploratory conclusion shows that the Isolation Forest, and Support vector machine classifiers perform roughly 81%and 79%accuracy with respect to the performance metrics measurement on the CIDDS-001 OpenStack server dataset while the proposed DA-LSTM classifier performs around 99.1%of improved accuracy than the familiar ML algorithms. Further, the DA-LSTM outcomes on the OpenStack log data-sets show better anomaly detection compared with other notable machine learning models.
NCGAN:A neural adversarial collaborative filtering for recommender system
Authors: Sun Jinyang , Liu Baisong , Ren Hao , Huang Weiming
Published: December 2021

The major challenge of recommendation system (RS) based on implict feedback is to accurately model users’ preferences from their historical feedback. Nowadays, researchers has tried to apply adversarial technique in RS, which had presented successful results in various domains. To a certain extent, the use of adversarial technique improves the modeling of users’ preferences. Nonetheless, there are still many problems to be solved, such as insufficient representation and low-level interaction. In this paper, we propose a recommendation algorithm NCGAN which combines neural collaborative filtering and generative adversarial network (GAN). We use the neural networks to extract users’ non-linear characteristics. At the same time, we integrate the GAN framework to guide the recommendation model training. Among them, the generator aims to make user recommendations and the discriminator is equivalent to a measurement tool which could measure the distance between the generated distribution and users’ ground distribution. Through comparison with other existing recommendation algorithms, our algorithm show better experimental performance in all indicators.
Flexible open-shop problem for minimizing weighted total completion time
Authors: Mashizi Iman Khosravi , Kermani Vahid Momenaei , Shahsavari-Pour Naser
Published: December 2021

In this article, scheduling flexible open shops with identical machines in each station is studied. A new mathematical model is offered to describe the overall performance of the system. Since the problem enjoys an NP-hard complexity structure, we used two distinct metaheuristic methods to achieve acceptable solutions for minimizing weighted total completion time as the objective function. The first method is customary memetic algorithm (MA). The second one, MPA, is a modified version of memetic algorithm in which the new permutating operation is replaced with the mutation. Furthermore, some predefined feasible solutions were imposed in the initial population of both MA and MPA. According to the results, the latter action caused a remarkable improvement in the performance of algorithms.
A novel group decision making method for interval-valued pythagorean fuzzy preference relations
Authors: Yang Ziyu , Zhang Liyuan , Li Tao
Published: December 2021

Interval-valued Pythagorean fuzzy preference relation (IVPFPR) plays an important role in representing the complex and uncertain information. The application of IVPFPRs gives better solutions in group decision making (GDM). In this paper, we investigate a new method to solve GDM problems with IVPFPRs. Firstly, novel multiplicative consistency and consensus measures are proposed. Subsequently, the procedure for improving consistency and consensus levels are put forward to ensure that every individual IVPFPR is of acceptable multiplicative consistency and consensus simultaneously. In the context of minimizing the deviations between the individual and collective IVPFPRs, the objective experts’ weights are decided according to the optimization model and the aggregated IVPFPR is derived. Afterwards, a programming model is built to derive the normalized Pythagorean fuzzy priority weights, then the priority weights of alternatives are identified as well. An algorithm for GDM method with IVPFPRs is completed. Finally, an example is cited and comparative analyses with previous approaches are conducted to illustrate the applicability and effectiveness of the proposed method.
Multi-attribute decision making method based on probabilistic linguistic term sets and its application in the evaluation of emergency logistics capacity
Authors: Yang Yaxu , Guo Zixue , He Zefang
Published: December 2021

The occurrence of public health emergency will cause huge economic losses and casualties, which posed a huge threat to the economic and social development. In response to the emergency, a large amount of emergency relief supplies will be transported to the affected areas. Faced with this public health emergency of international concern, the concept of emergency logistics capacity and the evaluation model based on probabilistic linguistic term sets are proposed. In this paper, the emergency logistics capability evaluation is transformed into user demand evaluation, and the importance of each index of emergency logistics capability is determined by using Quality Function Deployment (QFD) and prospect theory. Under the probabilistic language information environment, a multi-attribute decision making method is established by using TODIM method. Finally, an example is given to verify the feasibility of the proposed method.
A multi-source information fusion method for ship target recognition based on Bayesian inference and evidence theory
Authors: Zhang Yu , Xiao Qunli , Deng Xinyang , Jiang Wen
Published: December 2021

The ship target recognition (STR) is greatly related to the battlefield situation awareness, which has recently gained prominence in the military domains. With the diversification and complexity of military missions, ship targets are mostly performed in the form of formations. Therefore, using the formation information to improve the accuracy of the ship target type recognition is worth studying. To effectively identify ship target type, we in this paper jointly consider the ship dynamic, formation, and feature information to propose a STR method based on Bayesian inference and evidence theory. Specifically, we first calculate the ship position distance matrix and the directional distance matrix with the Dynamic Time Warping (DTW) and the difference-vector algorithm taken into account. Then, we use the two distance matrices to obtain the ship formation information at different distance thresholds by the hierarchical clustering method, based on which we can infer the ship type. Thirdly, formation information and other attribute information are as nodes of the Bayesian Network (BN) to infer the ship type. Afterward, we can convert the recognition results at different thresholds into body of evidences (BOEs) as multiple information sources. Finally, we fuse the BOEs to get the final recognition. The proposed method is verified in simulation battle scenario in this paper. The simulation results demonstrate that the proposed method achieves performance superiority as compared with other ship recognition methods in terms of recognition accuracy.
Real-time unstructured road detection based on CNN and Gibbs energy function
Authors: Liu Mingzhou , Xu Xin , Hu Jing , Jiang Qiannan
Published: December 2021

Road detection algorithms with high robustness as well as timeliness are the basis for developing intelligent assisted driving systems. To improve the robustness as well as the timeliness of unstructured road detection, a new algorithm is proposed in this paper. First, for the first frame in the video, the homography matrix H is estimated based on the improved random sample consensus (RANSAC) algorithm for different regions in the image, and the features of H are automatically extracted using convolutional neural network (CNN), which in turn enables road detection. Secondly, in order to improve the rate of subsequent similar frame detection, the color as well as texture features of the road are extracted from the detection results of the first frame, and the corresponding Gaussian mixture models (GMMs) are constructed based on Orchard-Bouman, and then the Gibbs energy function is used to achieve road detection in subsequent frames. Finally, the above algorithm is verified in a real unstructured road scene, and the experimental results show that the algorithm is 98.4% accurate and can process 58 frames per second with 1024×960 pixels.
Deferred Cesàro summability and statistical convergence for double sequences of sets
Authors: Ulusu Uğur , Gülle Esra
Published: December 2021

The main purpose of this paper is introduced the concept of deferred Cesàro mean in the Wijsman sense for double sequences of sets and then presented the concepts of strongly deferred Cesàro summability and deferred statistical convergence in the Wijsman sense for double sequences of sets. Also, investigate the relationships between these concepts and then to prove some theorems associated with the concepts of deferred statistical convergence in the Wijsman sense for double sequences of sets is purposed.
Integration of Virtual Reality into Transcranial Magnetic Stimulation Improves Cognitive Function in Patients with Parkinson’s Disease with Cognitive Impairment: A Proof-of-Concept Study
Authors: Cheng Tsai-Chin , Huang Shih-Fong , Wu Shang-Yu , Lin Fu-Gong , Lin Wang-Sheng , Tsai Po-Yi
Published: December 2021

Background: Emerging evidence has indicated the positive effects of repetitive transcranial magnetic stimulation (rTMS) on patients with Parkinson’s disease (PD) for the treatment of mild cognitive impairment (MCI). Objective: Investigating whether combining virtual reality (VR) training with rTMS can further enhance cognitive improvement induced by rTMS treatment. Methods: We randomly assigned 40 patients with PD and MCI into three groups, namely the rTMS-VR group (n = 13), rTMS group (n = 11), and sham rTMS group (n = 16). rTMS was administered as 10 consecutive sessions of intermittent theta burst stimulation (iTBS) over the left dorsolateral prefrontal cortex. In the rTMS-VR group, VR training was administered immediately after each rTMS session. Cognitive function was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Montreal Cognitive Assessment (MoCA) at baseline, immediately after intervention, and at 3-month follow-up. Results: Compared with the rTMS group, the rTMS-VR group exhibited significantly more improvements in total and delayed memory scores of the RBANS and the visuospatial/executive function score of the MoCA after intervention (p = 0.000∼0.046) and the delayed memory score of the RBANS at 3-month follow-up (p = 0.028). Conclusion: The integrated rTMS-VR protocol achieved a superior outcome in global cognitive function, more effectively enhancing working memory and visuospatial executive function than did the rTMS protocol alone. The combination of VR and rTMS can be an effective regimen for improving the cognitive function of patients with PD.
BASIC MODEL OF SEPARATE METHODIC OF JUDICIAL PROCEEDINGS: TASKS, CONTENT, STRUCTURE
Authors:   Illichivsk District Court of Mariupol, Donetsk Region, Mariupol, Myroshnychenko Yuriy
Published: December 2021

The article is devoted to the problem of building a basic model of methodic judicial procedure, which in its content should disclose the activities of the court at all stages of the judicial system, give recommendations on the choice of its directions, procedural actions, use of the most appropriate means of influencing specific court situations complexes of procedural actions and tactics of their carrying out at various stages of judicial proceedings. The basic model of judicial methodical criminalistics complex may have the following structure: a) characteristic of the proceedings of a certain type, including the purpose, objectives and directions of judicial investigation; b) typical court situations that correspond to a certain stage of court proceedings; c) typical systems (algorithms) of procedural actions and criminalistics means of influencing judicial situations in order to implement the tactical tasks stipulated by them. The main task of building a basic model methodic of judicial procedure is to study it from a criminalistics standpoint and develop on the basis of knowledge (identified patterns) practical recommendations for decisions and actions of the court in typical situations of the general judicial procedure. Among the tasks of creating a basic judicial methodic can also include: 1) substantiation of the system of judicial proceedings; 2) selection of typical court situations in relation to each of its stages with the disclosure of the main activities of the court to resolve them; 3) development of generalized tactics of procedural actions, characteristic for each stage of court proceedings; 4) identification of the main forms of counteraction to criminal proceedings and development of ways to minimize its negative consequences. Along with the presence of general patterns of legal proceedings, on which the basic model of judicial methodics is based, it is legitimate to assume the presence of a number of features inherent in certain types of legal proceedings and criminal cases classified according to other criteria. Tier сriminalistic support of requires the development of separate scientific-methodical complexes of a lesser degree of generalization.
AN ANALYTICAL SOLUTION OF THE SATURATED AND INCOMPRESSIBLE POROELASTIC MODEL FOR TRANSIENT WAVE PROPAGATION
Authors:   Laboratory of Engineering and Exploration of Petroleum - LENEP,, Silva, Romulo , Priimenko, Viatcheslav
Published: December 2021

A transient wave propagation model is provided as a consequence of a new theory of porous media and wave propagation in saturated poroelastic media. This theory, in the linear case, becomes to be equivalent to the theory proposed by de Boer, R., Ehlers, W. & Liu, Z. in 1993. It leads to a model for the 1-D porous saturated column problem, which after the appropriate establishment of boundary and initial conditions, can be solved analytically with the aid of the Laplace transform concerning time. Numerical experiments are performed to illustrate the behavior of constituents displacement fields. The theory results in having an inertial effect on the motion of solid constituents as commonly expected. However, in contrast to Biot’s theory, is not introduced by the present theory the relative acceleration as an interactive force between solid and fluid constituents to account for the apparent inertial effect.
AN EFFICIENT IDENTIFICATION OF RED BLOOD CELL EQUILIBRIUM SHAPE USING NEURAL NETWORKS
Authors:   LAMAI Laboratory, Cadi Aayad University Marrakesh Morocco, Fahim Houda , Sawadogo Olivier ,   Department of Computer Sciencs, Ouadagoudou University, Burkina Faso, Alaa Nour ,   LAMAI Laboratory, Faculty of science and technology of Cadi Aayad University, Guedda Mohammed ,   LAMFA Laboratory, Picardie Jules Verne University, Amiens France
Published: December 2021

This work of applied mathematics with interfaces in bio-physics focuses on the shape identification and numerical modelisation of a single red blood cell shape. The purpose of this work is to provide a quantitative method for interpreting experimental observations of the red blood cell shape under microscopy. In this paper we give a new formulation based on classical theory of geometric shape minimization which assumes that the curvature energy with additional constraints controls the shape of the red blood cell. To minimize this energy under volume and area constraints, we propose a new hybrid algorithm which combines Particle Swarm Optimization (PSO), Gravitational Search (GSA) and Neural Network Algorithm (NNA). The results obtained using this new algorithm agree well with the experimental results given by Evans et al. (8) especially for sphered and biconcave shapes.
THE HAUSDORFF MOMENT PROBLEM IN THE LIGHT OF ILL-POSEDNESS OF TYPE I
Authors:   Chemnitz University of Technology, Gerth Daniel , Hofmann Bernd ,   Chemnitz University of Technology, Hofmann Christopher , Kindermann Stefan ,   Johannes Kepler University Linz, Industrial Mathematics Institute
Published: December 2021

The Hausdorf moment problem (HMP) over the unit interval in an L 2 -setting is a classical example of an ill-posed inverse problem. Since various applications can be rewritten in terms of the HMP, it has gathered significant attention in the literature. From the point of view of regularization it is of special interest because of the occurrence of a non-compact forward operator with non-closed range. Consequently, HMP constitutes one of few examples of a linear ill-posed problem of type I in the sense of Nashed. In this paper we highlight this property and its consequences, for example, the existence of an infinite-dimensional subspace of stability. On the other hand, we show conditional stability estimates for the HMP in Sobolev spaces that indicate severe ill-posedness for the full recovery of a function from its moments, because H ̈older-type stability can be excluded. However, the associated recovery of the function value at the rightmost point of the unit interval is stable of H ̈older-type in an H1 -setting. We moreover discuss stability estimates for the truncated HMP, where the forward operator becomes compact. Some numerical case studies illustrate the theoretical results and complete the paper.
Glass Production from River Silica of Bangladesh: Converting Waste to Economically Potential Natural Resource
Authors:   Institute of Nuclear Minerals (INM), Atomic Energy Research Establishment (AERE), Bangladesh Atomic Energy Commission (BAEC), Ganakbari, Savar, Dhaka-1349, Bangladesh, Rajib Mohammad , Hossain Md. Fahad ,   Beach Sand Minerals Exploitation Centre (BSMEC), Bangladesh Atomic Energy Commission (BAEC), Kalatoli, GPO Box- 15,  Cox’s Bazar-4700, Bangladesh, Parveen Mahfuza ,   Department of Environmental Science and Disaster Management (ESDM), Daffodil International University (DIU),  Daffodil Smart City, Ashulia, Bangladesh
Published: December 2021

The Ganges-Brahmaputra river system at the Bengal Basin carries large amounts of sediments on the way to finally deposit at the Bay of Bengal. Those river-transported sediments form bar deposits during dry season in many areas of Bangladesh and accumulate economic mineral depositions at suitable geological environments. Dredging is a must for most of those rivers for proper navigation, as well as protecting bank erosion, which generates millions of tons of waste sand. The dredged materials from river beds are mostly composed of silicate minerals, especially quartz and feldspar along with several dark colored heavy minerals. Like the industrial processing of heavy minerals from bulk sands, various physical separation techniques can be utilized for the beneficiation of silica from those river-born silicate minerals in dredged sands. Those silica have been successfully upgraded to near-glass sand grade in the laboratory, however, they have yet to be utilized for any kind of commercial venture. The present study attempts characterization of several river sands through physical separation and laboratory analysis. The upgraded silica was successfully compared with several quality glass sands and laboratory production of glasses. This experimental production of glass from upgraded silica could potentially be economical considering its industrial application with positive environmental consequences through minimizing the dredging cost, increasing the navigability of the river and ecological balance along the flood plain.
Screening for Cervical Cancer
Authors: Agustiansyah Patiyus , Rizal Sanif  , Siti Nurmaini  , Irfannuddin  , Legiran
Published: December 2021

Screening is a public health intervention administered to a target population without symptoms. Screening is not performed to diagnose a disease, but to identify individuals with a higher likelihood of developing the disease itself or a precursor to the disease. Not all diseases are suitable for screening programs. The following criteria help determine whether a disease is suitable for a screening program: (1) The disease is bound to have serious consequences. (2) The disease must have a detectable preclinical and asymptomatic stage. (3) Treatment at the preclinical stage should influence the long-term course and prognosis of the disease being screened. (4) Care must be available and accessible to those who have a positive screening test. History, screening tests and treatment options for cervical pre-cancer meet these criteria.
Clinical Correlations Delirium and other Comorbid in Elderly with COVID-19 Infection
Authors: Putra Khoirun Mukhsinin , Nur Riviati  , Djunaidi AR
Published: December 2021

Background. Delirium is a common condition in geriatric patients. One of the trigger factors for this condition is an infection, such as COVID-19 infection. Elderly with COVID-19 show atypical symptoms such as delirium. Elderly patients with COVID-19 who present with delirium, either as a primary symptom or showing symptoms or signs, have a poor prognosis. This study were aimed to presents covid-19 elderly patient with comorbid delirium.

Case presentation. A 77-year-old woman with disorientation for one day came to Emergency Department with her family. She had no history of headaches, blurred vision, or seizures. However, she had a fever, did not want to eat for three days, and had a purulent decubitus ulcer. The patient was diagnosed with acute delirium syndrome, confirmed COVID-19 with sepsis, malnutrition, hypercoagulation, grade III decubitus ulcer, suspected dementia, immobilization, total dependence. The patient admitted to the isolation ward. The patient had meropenem 500 mg every 12 hours, anticoagulants and favipiravir according to the dose and parenteral nutrition.

Conclusion. Patients with COVID-19 who present with delirium, either as a primary symptom or presenting symptoms or signs, have a worse outcome. Delirium relationship with comorbid factors can increase mortality and morbidity in the elderly with COVID-19.
Dermatoglyphy in Breast Cancer Patients: A Systematic Review
Authors: Inggarsih Rara , Akhyar Dyni Zakyah  , Lusia Hayati  , Joko Marwoto  , Septi Purnamasari  , Arwan Bin Laeto  , Masayu Farah Diba
Published: December 2021

Background. Breast cancer is one of the four types of cancer among women and is the most frequently diagnosed in most countries. Breast cancer occurs due to DNA damage and genetic mutations affected by exposure to estrogen, inheritance of damaged DNA, or pro-cancer genes such as BRCA1 and BRCA2. Therefore, a family history of ovarian cancer or breast cancer increases the risk of developing breast cancer. The embryo of the breast develops around the age of 6 weeks of pregnancy. Similar to breast development, fingerprint patterns also develop during the 6-13 weeks of pregnancy. Thus, the genetic message contained in the genome occurred during that period and was reflected in the dermatoglyphic pattern.Methods. The literature search was systematically used using PubMed, Cochran, Google scholar, and other Gray literature between 2010-2020. Of the 69 publications identified, 21 met the criteria and were included in the review. The review is carried out following the provisions of PRISMA (Preferred Reporting Items for Systematic Review).Results. This systematic review showed fairly consistent findings in breast cancer patients who tended to have more whorl fingerprint patterns and larger ATD angles. For radial loops, ulnar loops and arches were minor compared to the control group potential as an initial screening tool in at-risk groups.Conclusion. Long-term and follow-up studies with larger sample sizes in various ethnicities are needed to validate dermatoglyphics in anthropometric measurements as a promising marker of breast cancer.
Correlation Between Candidiasis And Mortality In Gastric Ulcer Perforation Patients
Authors: Sulistiyani Faradina , Vicky Sumarki Budipramana  , Pepy Dwi Endraswari
Published: December 2021

Background: Gastric ulcer disease remains the most common gastrointestinal disease. This affects about 4 million people every year worldwide with an incidence of 1.5%-3% and 2-14% of these will progress to perforation. Mortality is reported in 30% of cases and caused morbidity in 50% of patients. Some studies have suggested that mortality in patients with peritonitis accompanied by candidiasis ranges from 20%-75%, whereas others have argued that the presence of fungal isolates in patients with perforated peptic ulcer does not affect the outcome. A recent study reported an incidence of 45% of patients peptic ulcer perforation cases accompanied by candidiasis in Dr. Soetomo General Hospital Surabaya in 2019.Methods: This was a cross sectional study based on medical record data of patients with gastric ulcer perforation accompanied by candidiasis who underwent laparotomy and gastric repair surgery at Dr. Soetomo General Hospital Surabaya from January 2019 to December 2020.Results: There was no significant correlation between candidiasis and mortality in gastric ulcer perforation patients (p=0.989).Conclusion: Candidiasis does not increase mortality in patients with gastric ulcer perforation.
Granuloma Inguinale
Authors: Anantawijaya D Adi Agung , Muhammad Izazi Hari Purwoko  , Mutia Devi  , Suroso Adi Nugroho
Published: December 2021

Granuloma ingunale (GI) or donovanosis is a genital ulcer disease caused by theCalymmatobacterium granulomatis. It is a Gram-negative, facultative, obligateintracellular and pleomorphic bacterium. This bacterium has phylogeneticallyclosed to and placed within the Klebsiella genus. Clinically, the disease is com-monly characterized as painless, slowly progressive ulcerative lesions on thegenitals or perineum without regional lymphadenopathy. The lesions are highlyvascular and bleed easily on contact Extragenital lesions may occur but are rareand more common in newborns from mothers with GI genital lesions. Thisdisease is often neglected, therefore it is often misdiagnosed and inaccuratetherapy. Treatment time is 3 weeks or until clinical cure has been achieved forall proposed regimens. It often occurs both in men and women of reproductiveage (20-40 years). This article consists of several theoretical references that havebeen viewed to have a better understanding of GI.
Genital Herpes in Human Immunodeficiency Virus Infected Patients
Authors: Sunur Stella , Izazi Hari Purwoko  , Yulia Farida Yahya  , Raden Pamudji
Published: December 2021

Genital herpes is a recurrent, lifelong sexual transmitted infection caused by HSV, especially type 2. Genital herpes is the most common infection in HIV patient. HSV-2 can increase the risk of HIV acquisition 2 to 3 times. Clinical manifestations of genital herpes can be different between HIV- infected and non-HIV patients. HIV-infected patients have a high risk of developing chronic and severe genital ulcers with atypical manifestation, prolonged healing, and resistant to treatment, depends on CD4 count. Genital herpes can be diagnosed based on history, clinical manifestation, laboratory and histopathologic examination. Management of genital herpes includes education and counseling patients and sexual partners, systemic antiviral, and symptomatic treatment.
Efficacy of Aloe Vera Hydrogel in Inhibition The Growth of Campylobacter rectus and Provetella intermedia Bacteria
Authors: Susanto Chandra , Member Reni Purba  , Ridha Mahrani  , Ramayani Efendi
Published: December 2021

Introduction: Campylobacter rectus and Provetella intermedia bacteria as the main etiology causes of periodontal disease. One of the locally synthesized antimicrobials that is widely used for the treatment of periodontitis is Chlorhexidine, however this drug has side effects when used continuously. To overcome this, an alternative periodontitis therapy with medicinal plants is needed. This study aims to determine the effectiveness of hydrogel Aloe vera antibacterial concentrations of 2.5%, 5%, 10% and 20% in the bacteria Campylobacter rectus and Provetella intermedia.

Methods: This study was a laboratory experimental study with posttest only control group design in vitro. The samples were Campylobacter rectus and Provetella intermedia. The number of groups in this study was six. The sample size was determined by Federer's formula and obtained four replications for each group. Data collection by measuring the inhibition diameter using a slide caliper. Data were analyzed using oneway ANOVA and posthoc LSD.

Results: The results showed that there was a difference in the diameter of the hydrogel Aloe vera inhibition with a concentration of 2.5%, 5%, 10%, 20% and a positive control for Campylobacter rectus and Provetella intermedia bacteria.

Conclusion: This study concluded that there is an antibacterial effectiveness of hydrogel Aloe vera in concentrations of 2.5%, 5%, 10% and 20% on Campylobacter rectus and Provetella intermedia bacteria.
Histopathological Features of Cutaneous Tuberculoid Granuloma Disorders
Authors: Jusuf Fantoni Odelia Jovita , Inda Astri Aryani  , Yuli Kurniawati  , Raden Pamudji
Published: December 2021

Tuberculoid granulomas consist of epithelioid histiocytes, Langhans giant cells and rarely foreign bodies with lymphocytes, plasma cells and caseous necrosis. The granulomatous reaction pattern is defined as a typical inflammatory pattern that is characterized by granulomas. Various etiologies can lead to granulomatous reactions. The histopathological features of cutaneous disorders with tuberculoid granuloma include cutaneous tuberculosis, tuberculids, Morbus Hansen, syphilis and rosacea. There are various clinical manifestations of tuberculoid granuloma with similar appearances which makes it difficult to establish a definitive diagnosis. The histopathological features of cutaneous tuberculoid granuloma disorders can support the diagnosis. Therefore, the clinician can determine the appropriate treatment with the right diagnosis.
Correlation of Serum IL-6 Levels with Muscle Mass, Muscle Strength, and Physical Performance in Elderly Gymnastics Community in Mohammad Hoesin General Hospital Palembang
Authors: Erfin Muhammad , Nur Riviati  , Nova Kurniati  , Erial Bahar  , Erwin Sukandi  , Sudarto
Published: December 2021

Introduction. Old age is related to geriatric syndrome where there are several health problems that often occur related to a decrease in body function and an increase in the inflammatory process. Decrease in muscle mass, muscle strength and physical performance will cause a condition of sarcopenia and frailty syndrome in the elderly. The importance of prevention so that sarcopenia does not occur in the elderly by evaluating the factors that can cause it, one of which is controlling interleukin 6 (IL-6) as proinflammatory. The purpose of this study was to determine the correlation between serum IL-6 levels with muscle mass, muscle strength and physical performance in the elderly gymnastics-community in Mohammad Hoesin General Hospital, Palembang.

Methods. This research is an observational analytic study with a cross-sectional approach which was conducted at the Integrated Geriatric Clinic Internal Medicine RSMH Palembang from November 2019 to November 2020. A sample of 31 people aged > 60 years was examined for muscle mass, muscle strength, physical performance and IL-levels. 6 serum. All data processing and analysis in this study used the SPSS version 25 for Windows program.

Results. of the 31 subjects, 27 were female (87.1%) and 4 male (12.9%). The mean value of muscle mass is37.9 kg/m2, muscle strength 23 kg, and physical performance 6.1 m/sec.There were 28 (90.3%) samples with elevated serum IL-6 levels, while 3 (9.7%) samples had normal levels. There was a significant negative correlation (p = 0.000) with a strong correlation strength (r = -0.722) between serum IL-6 levels and muscle mass and a significant negative correlation (p = 0.050) with a weak correlation strength (r = -0.354) between IL levels -6 serums with physical performance.

Conclusions. There was a significant negative correlation between serum IL-6 levels and muscle mass and physical performance. So, it is very important to prevent an increase in serum IL-6 levels so that the elderly do not fall into a state of sarcopenia.
Effects of Oral Administration of Monosodium Glutamate (MSG) on Obesity in Male Wistar Rats (Rattus Norvegicus)
Authors: Rahayu Mulyati Sri , Sri Wahyuni  , Yuziani
Published: December 2021

Introduction: Monosodium glutamate (MSG) is one of the most widely employed food enhancers. Although the umami compound, controversy persists regarding the effects of MSG intake on body weight. Chronic MSG intake may result in excessive body weight gain and obesity. Consumption of MSG result in organ damage, cardiovascular disease, oxidative stress, and also risk factors for obesity. This study aims to determine the effect of oral MSG on obesity in adult male Wistar rats (Rattus norvegicus).Methods: This true experimental study used the post-test control group design. Twenty-four adult male Wistar rats were randomly divided into four groups: control (received distilled water), Group 1 (MSG 0.378 mg/gr BW), Group 2 (0.756 mg/gr BW) and Group 3 (1.512 mg/gr BW). The obesity parameter was obtained by the Lee index. Kruskal-Wallis test follows by Mann-Whitney test were used to compare the Lee index between groups.Results: Lee’s index mean for each group was 358.4%, 314.1%, 287.8%, and 320.9%, respectively. The Kruskal Wallis test showed a significant difference in the Lee index between groups (p = 0.043). A follow-up test using Mann-Whitney found a significant difference between group 2 and the control group (p = 0.043, p <0.05). The mean of Lee index of group 2 was 70.51% lower than the control group.Conclusion: This study concluded that Lee index was not increased in MSG-treated rats than in the control group after oral MSG intervention for 21 days.
Recurrence Prediction Score of the Localy Advance Breast Cancer in West Sumatera Province, Indonesia
Authors: Qorina Shinta , Wirsma Arif Harahap  , Ricvan Dana Nindrea
Published: December 2021

Introduction: Breast cancer is the most common malignancy that occurs in women in the world, which is about 18% of cancer cases that occur in women. Every year there are 1 million new cases of breast cancer worldwide and nearly 60,000 patients die from this disease. Therefore, the authors want to find out more about the prognosis factors that play a role in influencing the survival of patients with locally advanced breast cancer in Padang city, West Sumatera Province Indonesia.

Methods: This study is a retrospective case-control study of locally advanced breast cancer for patients in Padang city. The study was conducted at the Surgical Oncology Division of Dr. M Djamil Padang Hospital, Ropana Suri Hospital, Ibnu Sina Hospital and Siti Rahmah Padang Hospital from September 2018 to December 2018. The total number of samples for the two groups was 242 people. The sampling technique used was convenience sampling.

Results: In this study 4 prognostic factors were found that had a significant effect on predicting breast cancer recurrence, namely histopathological type, stage, regional lymph and lymphovascular invasion with p <0.05.

Conclusion: Prognosis factors that influence breast cancer recurrence are histopathological type, stage, regional lymph node status and lymphovascular invasion. A scoring system is obtained that is good enough to predict the possibility of breast cancer recurrence.
THE EFFECTIVENESS OF THE DEMONSTRATION METHOD AND AUDIO-VISUAL METHOD ON ADOLESCENT KNOWLEDGE ABOUT BREAST SELF-EXAMINATION
Authors: Hindriati Titik , Nurmisih Nurmisih , Diniyati Diniyati , Rosmaria Rosmaria
Published: December 2021

Introduction: Breast cancer is the most frequent type of cancer in women, and it is one of the major causes of mortality. Efforts should be made to prevent breast cancer by using the breast self-examination (BSE) method of early diagnosis. This study aims to determine the effectiveness of the demonstration and audio visual methods on adolescent knowledge about breast self-examination at SMA Pertiwi 1 Jambi City, Indonesia. Methods. This study is a quasi-experimental study using a two-group pretest-posttest design at the private high school Pertiwi 1 Jambi City, involving 122 participants divided into two groups. Group 1 consisted of 61 participants given BSE material by demonstration, while group 2 consisted of 61 participants given material using audio-visual media. Data processing in this study used univariate and bivariate analysis, and the statistical test used was the Wilcoxon test. Results. The results showed that there was an increase in students’ knowledge about BSE after the demonstration with p-value < 0.0001, and displayed audio-visually with p-value < 0.0001. Conslusion: demonstration and audiovisual methods proved effective in increasing adolescent knowledge about breast self-examination at at SMA Pertiwi 1 Jambi City, Indonesia.
Diagnóstico Histopatológico e Imuno-histoquímico de Linfoma de Baço com Apresentação Clínica Atípica: Relato de Caso
Authors: Fragoso Gabrielle Ruthes , Santos Eduardo Pires dos , Marques Camila Morais , Lima Renata Bernardini de
Published: December 2021

Introdução: Tanto o angiossarcoma esplênico quanto o linfoma não Hodgkin (LNH) de células B não só são raros como apresentam desafios diagnósticos. Relato do caso: Paciente do sexo masculino, 45 anos, obeso, sudorese noturna há um ano, e dor abdominal cíclica há dois, com clínica inicial de angiossarcoma, contudo, sob o exame histopatológico e imuno-histoquímico, mostrou tratar-se de LNH de células B com apresentação atípica. A ultrassonografia (US) de abdome total realizada ao início do sintoma de sudorese noturna não teve alterações. Após um ano, a US apresentou massa esplênica. Na ressonância magnética da região abdominal, constatou-se tumoração esplênica expansiva heterogênea no aspecto anterior, suspeita de angiossarcoma esplênico. Após esplenectomia total, pancreatectomia caudal e linfadenectomia retroperitoneal, o exame histopatológico mostrou neoplasia maligna pouco diferenciada extensamente necrótica substituindo o parênquima esplênico. O estudo imuno-histoquímico foi positivo para os marcadores CD20 em diversos focos, para o BCL2 e para o KI67 (em 95% dos núcleos das células neoplásicas). A histopatologia e a imuno-histoquímica foram compatíveis com o diagnóstico de LNH difuso de alto grau, com imunofenótipo B do baço, sem sinal de infiltração de tecidos adjacentes. Após a esplenectomia total e quatro ciclos de quimioterapia, o paciente estava livre do linfoma e sem sintomas. Conclusão: É de suma importância o reconhecimento do diagnóstico correto de neoplasias raras como a relatada. Tanto a clínica quanto os exames de imagem, mesmo que fundamentais, podem ser imprecisos, reiterando a importância dos exames histológico e imuno-histoquímico complementares.
Rasio Keuangan Kinerja Bank Konvesional yang Terdaftar di Bursa Efek Indonesia
Authors: Hidayat Gustina
Published: December 2021

Kinerja bank dapat memberikan gambaran presentasi yang dicapai bank dalam operasionalnya, yang mana menggambarkan kondisi kesehatan keuangan perusahaan dengan indikator kecukupan modal, likuiditas dan profitabilitas. Dampak pandemi Covid-19 terhadap kinerja sektor perbankan, sungguh besar, nasabah yang akan bertansaksi di alihkan melalui m-banking­, nasabah yang menerima kucuran kredit dari bank, tidak mampu membayar cicilan pokok dan bunganya, dalam arti menjadi kredit macet. Analisis kinerja keuangan Bank yang mengalami penuruan paling besar, sehingga analisi kesehatan bank menjadi factor utama bagi para investor, nasabah. Setelah melakukan uji kriteria awal, dalam penelitian ini akan menggunakan empat objek penelitian pada PT. Bank Negara Indonesia, Tbk PT Bank Mandiri, Tbk PT Bank CIMB Niaga, Tbk dan PT Bank BCA, Tbk untuk menganalisis rasio keuangan bank pada periode 2015- 2020. Secara keseluruhan analisis kinerja keuangan menggunakan model RGEC dengan nilai rerata setiap rasionya dinyatakan dalam keadaan sehat, membuktikan bahwa Bank BNI, Bank Mandiri, Bank CIMB Niaga dan Bank BCA pada periode 2015-2019 berada pada predikat keadaan baik.