Ulama Versus Politisi: Gerakan Politik Baju Koko Melawan Koalisi Partai Politik Pengusung Calon

Abstract: This study aims to look at the contestation between ulama who are members of the Baju Koko and a single candidate pair supported by a coalition of major political parties in Kalibeber Village. The research method used in this research is to use a type of qualitative research with a case study approach. The results of the study show that, firstly, in the context of visible power, the single candidate pair team utilizes the campaign form to offer policy programs that Baju Koko cannot have because it is not regulated in terms of the empty box campaign form. Second, the single candidate pair team took advantage of the public's lack of knowledge regarding empty boxes to gain votes, while Baju Koko practiced black campaigning to undermine the credibility of the single candidate pair. Third, the single candidate team used the charisma of the elderly ulama in Kalibeber to attract people's votes, while Baju Koko used several scholars who were members of the movement. The results of the contest showed that Baju Koko had to suffer defeat in its base of movement by a single candidate pair even though it had been supported by several scholars in Kalibeber.Abstrak: Penelitian ini bertujuan untuk melihat kontestasi antara ulama yang tergabung dalam gerakan politik Baju Koko dan pasangan calon tunggal yang didukung oleh koalisi partai politik besar di Desa Kalibeber. Metode penelitian yang digunakan dalam penelitian ini adalah dengan menggunakan jenis penelitian kualitatif dengan pendekatan studi kasus. Hasil dari penelitian menunjukan pertama, dalam konteks kekuasaan terlihat, timses paslon tunggal memanfaatkan bentuk kampanye untuk menawarkan program-program kebijakan yang tidak bisa dimiliki oleh Baju Koko karena tidak diatur secara regulasi terkait bentuk kampanye kotak kosong. Kedua, timses paslon tunggal memanfaatkan minimnya pengetahuan masyarakat terkait kotak kosong untuk mendulang suara sedangkan Baju Koko melakukan praktik kampanye hitam untuk menjatuhkan kredibilitas paslon tunggal. Ketiga, timses calon tunggal memanfaatkan kekharismatikan ulama sepuh di Kalibeber untuk menggaet suara rakyat, sedangkan Baju Koko memanfaatkan sejumlah ulama yang tergabung dalam pergerakan. Hasil kontestasi menunjukan, Baju Koko harus mengalami kekalahan di basis pergerakannya sendiri oleh paslon tunggal meskipun sudah didukung oleh sejumlah ulama di Kalibeber

Screening for psychological distress among High School Graduates Accepted for Enrollment at Alexandria Faculty of Medicine: Academic year 2016/2017

Background: Mental and psychological health of adolescents in general and prospective medical students in particular is a priority area to investigate as it affects wellbeing of the future doctors.Objectives: The current research was conducted to screen first year medical students accepted for enrollment at Alexandria Faculty of Medicine to identify those with a high probability of having psychological distress before the start of academic courses as well as explore the sources of stress among them.Methods: A cross sectional survey of 779 high school graduates accepted for admission to Alexandria Faculty of medicine was conducted. Participants were approached on the days of obligatory pre-enrollment medical examination. The translated Arabic version of DASS 21 questionnaire was used to screen students for three negative emotional symptoms namely depression, anxiety and stress. Inquiry about age, sex, residency and type of high school was added.Results: More than a tenth of studied medical students (12.6%) suffered from severe or profound stress and 29.1% of them had mild to moderate stress. Moreover, one fifth (20%) of studied students were severely anxious and less than one third (29.3%) had mild to moderate anxiety. Severe and profound depression was diagnosed among 14.3% of students whereas, 18.7% them were moderately depressed. No association was found between any of studied negative emotional symptoms and the students’ educational background or their residency.Conclusion: Nearly half of the prospective medical students might have some sort of psychological distress before starting their study in the Faculty of Medicine. They should be investigated to verify diagnosis and start intervention to minimize its adverse effects on academic performance and advancement at the faculty. Stress management courses should be considered for all medical students.Keywords: Psychological distress, Prospective medical students, Adolescents’ psychological health, Depression, Anxiety, Stres

The CCL2 chemokine is a negative regulator of autophagy and necrosis in liminal B breast cancer cells

Luminal A and B breast cancers are the most prevalent forms of breast cancer diagnosed in women. Compared to luminal A breast cancer patients, patients with luminal B breast cancers experience increased disease recurrence and lower overall survival. The mechanisms that regulate the luminal B subtype remain poorly understood. The chemokine CCL2 is overexpressed in breast cancer, correlating with poor patient prognosis. The purpose of this study was to determine the role of CCL2 expression in luminal B breast cancer cells. Breast tissues, MMTV-PyVmT and MMTV-Neu transgenic mammary tumors forming luminal B-like lesions, were immunostained for CCL2 expression. To determine the role of CCL2 in breast cancer cells, CCL2 gene expression was silenced in mammary tumor tissues and cells using TAT cell-penetrating peptides non-covalently cross linked to siRNAs (Ca-TAT/siRNA). CCL2 expression was examined by ELISA and flow cytometry. Cell growth and survival were analyzed by flow cytometry, immunocytochemistry, and fluorescence microscopy. CCL2 expression was significantly increased in luminal B breast tumors, MMTV-PyVmT and MMTV-Neu mammary tumors, compared or normal breast tissue or luminal A breast tumors. Ca-TAT delivery of CCL2 siRNAs significantly reduced CCL2 expression in PyVmT mammary tumors, and decreased cell proliferation and survival. CCL2 gene silencing in PyVmT carcinoma cells or BT474 luminal B breast cancer cells decreased cell growth and viability associated with increased necrosis and autophagy. CCL2 expression is overexpressed in luminal B breast cancer cells and is important for regulating cell growth and survival by inhibiting necrosis and autophagy

Comparison of Supervised Machine Learning Algorithms for Malware Detection

Due to the prevalence of security issues and cyberattacks, cybersecurity is crucial in today's environment. Malware has also evolved significantly over the past few years. With the advancement of malware analysis, Machine Learning (ML) is increasingly being used to detect malware. This study's major objective is to compare the best-supervised ML algorithms for malware detection based on detection accuracy. This study includes the scripting and development of supervised ML techniques such as Decision Tree (DT), K-Nearest Neighbors (KNN), Naive Bayes, Random Forest, and Neural Networks. This study was solely concerned with the Windows malware dataset. The malware classification was determined by testing and training the supervised ML algorithms using the extracted features from the malware dataset. Then, the percentage of detection accuracy was used to compare the detection performance of all five algorithms. The detection accuracy is calculated using the confusion matrix, which includes the False Positive Rate (FPR), the True Positive Rate (TPR), and the False Negative Rate (FNR). The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. To improve the detection accuracy for future research, it is suggested that the malware dataset be enhanced using several architectures, such as Linux and Android, and use additional supervised and unsupervised machine learning algorithms

Reducing Honeypot Log Storage Capacity Consumption – Cron Job with Perl-Script Approach

Honeypot is a decoy computer system that is used to attract and monitor hackers’ activities in the network. The honeypot aims to collect information from the hackers in order to create a more secure system. However, the log file generated by honeypot can grow very large when heavy traffic occurred in the system, such as Distributed Denial of Services’ (DDoS) attack. The DDoS possesses difficulty when it is being processed and analyzed by the network administrator as it required a lot of time and resources. Therefore, in this paper, we propose an approach to decrease the log size that is by using a Cron job that will run with a Perl-script. This approach parses the collected data into the database periodically to decrease the log size. Three DDoS attack cases were conducted in this study to show the increasing of the log size by sending a different amount of packet per second for 8 hours in each case. The results have shown that by utilizing the Cron job with Perl-script, the log size has been significantly reduced, the disk space used in the system has also decreased. Consequently, this approach capable of speeding up the process of parsing the log file into the database and thus, improving the overall system performance. This study contributes to providing a pathway in reducing honeypot log storage using the Cron job with Perl-Script.

Towards Designing A Hierarchical Fuzzy System for Early Diagnosis of Heart Disease

Heart disease may represent a range of conditions that affect our heart. Disease under heart diseases umbrella include coronary heart disease, heart attack, congestive heart failure, and congenital heart disease, is the leading cause of death. Mor eover, heart disease not only attacks the elderly. In the present day, lots of younger people might be getting affected by the number of heart diseases. In order to decrease the mortality rate caused by heart disease, it is necessary for the disease, to be diagnosed at an early stage. In this paper, we have proposed the use of hierarchical fuzzy systems (HFSs) for early diagnosis of heart disease. However, to design the HFSs is challenging, especially for the complex system. Therefore, in this paper, we foc us on designing a hierarchical fuzzy system to handle the complex medical application. The designed HFS consists of six key main steps implemented on heart disease. The input variables of heart disease includes shortness of breath, discomfort, pressure, he aviness, or pain in the chest, arm, or below the breastbone, fatigue, nausea, difficulties in climbing stairs, swelling in ankles, difficulty to sleep at night, irregular heartbeats, fullness, sweating, take frequent break during the day, dizzy and depress ed. Additionally, the output of heart disease is to classify whether the patient is healthy or suspecting with heart disease. The study contributes to providing insight into a way of designing the HFSs, particularly for the complex medical application

Association of specific ACE2 and TMPRSS2 variants with circulatory cytokines of COVID-19 Emirati patients

IntroductionThe COVID-19 pandemic represented one of the most significant challenges to researchers and healthcare providers. Several factors determine the disease severity, whereas none alone can explain the tremendous variability. The Single nucleotide variants (SNVs) in angiotensin-converting enzyme-2 (ACE2) and transmembrane serine protease type-2 (TMPRSS2) genes affect the virus entry and are considered possible risk factors for COVID-19.MethodsWe compiled a panel of gene variants from both genes and used in-silico analysis to predict their significance. We performed biological validation to assess their capacity to alter the ACE2 interaction with the virus spike protein. Subsequently, we conducted a retrospective comparative genome analysis on those variants in the Emirati patients with different disease severity (total of 96) along with 69 healthy control subjects.ResultsOur results showed that the Emirati population lacks the variants that were previously reported as associated with disease severity, whereas a new variant in ACE2 “Chr X:g.15584534” was associated with disease severity specifically among female patients. In-silico analysis revealed that the new variant can determine the ACE2 gene transcription. Several cytokines (GM-CSF and IL-6) and chemokines (MCP-1/CCL2, IL-8/CXCL8, and IP-10/CXCL10) were markedly increased in COVID-19 patients with a significant correlation with disease severity. The newly reported genetic variant of ACE2 showed a positive correlation with CD40L, IL-1β, IL-2, IL-15, and IL-17A in COVID-19 patients.ConclusionWhereas COVID-19 represents now a past pandemic, our study underscores the importance of genetic factors specific to a population, which can influence both the susceptibility to viral infections and the level of severity; subsequently expected required preparedness in different areas of the world

Characterization of greater middle eastern genetic variation for enhanced disease gene discovery

The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia1-3, has resulted in an elevated burden of recessive disease4. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized ‘genetic purging’. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics