THE ROLE AND IMPORTANCE OF A COMPLIANCE OFFICER IN THE ACTIVITIES OF A FINANCIAL INSTITUTION IN ORDER TO PREVENT THE LEGALIZATION (LAUNDERING) OF CRIMINALLY ACQUIRED FUNDS AND THE FINANCING OF TERRORISM

The relevance of the topic is confirmed by the changes taking place in the financial monitoring system: the complication of procedures aimed at countering money laundering and financing of terrorism, the creation of specialized international and European requirements and the changes of requirements for compliance specialists. Financial institutions more often face the incompetence the incompetence of these employees and their negligence. The author analysed anti money laundering and counter financing of terrorism legal acts, as well as revealed the main recommendations to financial institutions for preventing money laundering and terrorism financing. Based on scientific research, the main risk factors for using financial institutions for money laundering were identified. Based on these risks factors, the author identified the role and importance of a compliance officer in order to prevent the legalization (laundering) of criminally acquired funds and the financing of terrorism.

Risk-Assessment and Victim-Support Recommendations During the COVID-19-Related Lockdowns

This chapter covers the effects of the COVID-19 crisis on the incidence and severity of domestic abuse cases in Europe. First, the manifestation of the COVID-19 lockdown and its adverse effects on private life are described. Building upon this description, co-occurring risks factors with a high potential to initiate or intensify domestic abuse (e.g., cramped living conditions) are discussed. Responding to various calls on investigating the impact of COVID-19 on domestic abuse incidents, IMPRODOVA research on the first lockdown shows that the related concerns for various reasons are inconsistently reflected in domestic abuse-related statistics. In some IMPRODOVA partner countries, however, victimisation numbers went up, after the lockdown ended. Consequently, the complexity of detecting domestic abuse cases during lockdowns are discussed. In line with the strong concern about intensified victimisation, innovative responses by front-line professionals to detect and manage domestic violence and abuse cases are presented. Building on the beforehand presented assumptions, findings and explanations, the chapter closes by highlighting eighteen recommendations regarding risk assessment and victim support during pandemics.

Carriage of mutations R462Q (rs 486907) and D541E (rs 627928) of the RNASEL gene and risk factors in patients with prostate cancer in Burkina Faso.

Background Prostate cancer (Pca) is a public health problem that affects men, usually of middle age or older. It is the second most common cancer diagnosed in men and the fifth leading cause of death. The RNASEL gene located in 1q25 and identified as a susceptibility gene to hereditary prostate cancer, has never been studied in relation to prostate cancer in Burkina Faso. The aim of this study was to analyze the carriage of RNASEL R462Q and D541E mutations and risks factors in patients with prostate cancer in the Burkina Faso. Methods This case-control study included of 38 histologically diagnosed prostate cancer cases and 53 controls (cases without prostate abnormalities). Real-time PCR genotyping of R462Q and D541E variants using the TaqMan® allelic discrimination technique was used. Correlations between different genotypes and combined genotypes were investigated. Results The R462Q variant was present in 5.3% of cases and 7.5% of controls. The D541E variant was present in 50.0% of cases and 35% of controls. There is no association between R462Q variants (OR= 0.60; 95%IC, 0.10 - 3.51; p= 0.686) and D541E variants (OR=2.46; 95%IC, 0.78 - 7.80; p= 0.121) and genotypes combined with prostate cancer. However, there is a statistically significant difference in the distribution of cases according to the PSA rate at diagnosis (p ˂ 0.001). For the Gleason score distribution, only 13.2% of cases have a Gleason score greater than 7. There is a statistically significant difference in the Gleason score distribution of cases (p ˂ 0.001) Conclusions These variants, considered in isolation or in combination, are not associated with the risk of prostate cancer.

Abstract 1122‐000011: Risk Factors Associated with Various Subtypes of Ischemic Stroke: A Prospective Study

Introduction : Stroke is the main cause of adult disability and the second most leading cause of death worldwide. The number of deaths due to stroke is 5·54 million worldwide. Stroke is also a major cause of long‐term disability. Globally, 70% of strokes and 87% of both stroke‐related deaths and disability‐adjusted life years occur in low and middle‐income countries. The incidence of stroke varies among various countries. Over the last four decades, the stroke incidence in low and middle‐income countries has become more than doubled. . However, there are limited data and very few studies on various subtypes of ischemic stroke and their risks factors in our country. So, we purposively designed this study. The aim of this study was to investigate the risks factors associated with the various subtypes of ischemic stroke according to TOAST criteria. Methods : This was a prospective observational cross sectional study conducted during June‐2019 to May‐2020. A total of 220 ischemic stroke patients aged above 30 years confirmed by CT Scan/MRI of brain were included in this study. A complete history was taken regarding hypertension, diabetes, dyslipidemia, ischemic heart disease, current smoking history of previous stroke, positive familial history, coronary artery diseases, alcohol consumption and demographic characteristics were noted in the questionnaire. Hypertension was defined as systolic blood pressure (SBP) > 140 mmHg, diastolic blood pressure > 90 mmHg or both on two separate occasions, or the use of anti‐hypertensive medication at any time before the onset of stroke. Diabetes was defined if fasting plasma glucose levels are 126 mg/dl or higher after an overnight fast on more than one occasion or as random blood glucose level 200 mg/dl or higher on more than one occasion. Ischemic stroke was classified according to TOAST criteria. Data were collected with a pre structured questionnaire from the patients’ investigations reports and face to face interview with the researcher (an expert neurologist). Results : Among the 220 stroke patients, Large‐artery atherosclerosis (LAA), Cardio‐embolism (CE), Small‐vessel occlusion (SVO, Stroke of other determined etiology (SODE) and Stroke of undetermined etiology (SUDE) were being observed 84(38.18%), 14(6.36%), 63(28.64%), 12(5.45%) and 47(18.18%). The highest prevalence of subtypes 70(31.82%) was found in the age group (51‐60). The prevalence of subtypes was found 150(68.18%) in male and 70(31.82%) in female. 86(39.09%) prevalence of subtypes was found who were from rural areas whereas 134(60.91%) was observed in urban areas. The significant risk factors associated with the prevalence of various subtypes of ischemic stroke were observed Hypertension, Diabetes Mellitus, Smoking history, Dyslipidemia, Heart disease, H/O Previous Stroke, Positive Familial History, Coronary Artery Disease and Alcohol Consumption (p <0.05). Conclusions : The higher prevalence of Large‐artery atherosclerosis (LAA) was found in this study. It suggests the influence of uncontrolled hypertension, diabetes mellitus, smoking habit and dyslipidemia. So, importance should be given on various subtypes of ischemic stroke and collective preventive measures and strategies are to be taken to control the associated risk factors especially hypertension, diabetes mellitus, smoking habit and dyslipidemia to decrease the stroke mortality rate.

Identifying the Main Risk Factors for Cardiovascular Diseases Prediction Using Machine Learning Algorithms

Cardiovascular Diseases (CVDs) are a leading cause of death globally. In CVDs, the heart is unable to deliver enough blood to other body regions. As an effective and accurate diagnosis of CVDs is essential for CVD prevention and treatment, machine learning (ML) techniques can be effectively and reliably used to discern patients suffering from a CVD from those who do not suffer from any heart condition. Namely, machine learning algorithms (MLAs) play a key role in the diagnosis of CVDs through predictive models that allow us to identify the main risks factors influencing CVD development. In this study, we analyze the performance of ten MLAs on two datasets for CVD prediction and two for CVD diagnosis. Algorithm performance is analyzed on top-two and top-four dataset attributes/features with respect to five performance metrics –accuracy, precision, recall, f1-score, and roc-auc—using the train-test split technique and k-fold cross-validation. Our study identifies the top-two and top-four attributes from CVD datasets analyzing the performance of the accuracy metrics to determine that they are the best for predicting and diagnosing CVD. As our main findings, the ten ML classifiers exhibited appropriate diagnosis in classification and predictive performance with accuracy metric with top-two attributes, identifying three main attributes for diagnosis and prediction of a CVD such as arrhythmia and tachycardia; hence, they can be successfully implemented for improving current CVD diagnosis efforts and help patients around the world, especially in regions where medical staff is lacking.

Tracking brucellosis–a re-emerging disease

Brucellosis caused by members of the genus Brucella is of major concern for animal and public health and is recognized as a re-emerging zoonotic disease. Brucellosis causes flu-like symptoms like fever, sweats, weakness, pain in muscles, joint and back, with some symptoms persisting for longer time periods. Infections occur through consumption of unpasteurized dairy products or undercooked meat, inhalation, and contact with animals. Human-to-human transmission is rare. Surveillance of this disease in animals and humans and prevention of infection risks factors are the most effective strategies to prevent brucellosis. With the progress in sequencing technologies, whole genome sequencing (WGS) has become an effective tool in surveillance, tracking of pathogens and in outbreak investigation. WGS allows identification of the source of infection and to elucidation of transmission chains, which enables authorities to implement timely and appropriate interventions.

An Assessment of Prominent Risks Factors Behind the Development of COVID-19 Pandemic Digital Eye Strain in context with the Online Class Room

The COVID-19 outbreak has destructively affected the education system over the world and brought about prominent alterations in the traditional systems of teaching and learning. In order to flatten the curve of disease transmission, several countries have resorted to online classes for students. Apart from the benefits of this strategy, there exists a chance of developing ocular complications in students those are continuously viewed the digital screen without any break. T-test and frequency analysis was used to find out the link between the digital electronic gadgets and eye strains. SPSS version 24.0.0 was used for all the statistical analyses. Here we assessed the various prominent factors behind the development of complications in eyes instigated by the electronic gadgets with special inference on the type of electronic gadgets, time spend, distance, type of usage, kind of posture, light condition, stress, and kind of symptoms towards digital eye strains. One of the major fact that has been emerged in this investigation is that the usage of electronic gadgets for online classes purposes have greatly increased than the other usage. The use of electronic gadgets for work and educational purposes has been recognized as a normal activity among individuals. With the extensive prevalence of developing digital eye strain in the students, it is paramount that the results of this investigation can be used for research purposes as strong research evidence to prevent the complications allied with eyes.

Childhood Antisocial Behavior: A Neurodevelopmental Problem

Early-onset disruptive, aggressive, and antisocial behavior is persistent, can become increasingly serious as children grow older, and is difficult to change. In 2007, our group proposed a theoretical model highlighting the interplay between neurobiological deficits and cognitive and emotional functioning as mediators of the link between genetic influences and early social adversity, on the one hand, and antisocial behavioral problems in childhood, on the other. In this article, we review the post-2007 evidence relevant to this model. We discuss research on genetics/epigenetics, stress/arousal regulation, and emotion and executive functioning in support of the argument that antisocial children, especially those who persist in engaging in antisocial behavior as they grow older, have a range of neuropsychological characteristics that are important in explaining individual differences in the severity and persistence of antisocial behavior. Current clinical practice tends not to acknowledge these individual neuropsychological risks factors or to target them for intervention. We argue that aggressive and disruptive behavior in childhood should be regarded as a neurodevelopmental problem and that intervening at the level of mediating neuropsychological processes represents a promising way forward in tackling these serious behavioral problems. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.