bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality of attachment, trauma, psychopathology, and frequency of non-suicidal self-injury in Mexican adolescents suffering from psychosocial vulnerability: Description of a risk profile
Authors: Marín-Tejeda Miguel , Martínez-Martínez Kalina Isela , Santillán Torres-Torija Carolina
Published: April 2021

Introduction. Suffering from psychosocial vulnerability, particularly during adolescence, increases the likelihood of experiencing adverse life circumstances, psychiatric conditions, and non-suicidal self-injury (NSSI). Objective. We studied: 1. record-based demographic and clinical characteristics, as well as the frequency of NSSI in adolescents, beneficiaries of services for vulnerable population of one of six Non-Governmental Organizations (NGO’s), we compared by beneficiary type: internal (IB) versus external (EB); 2. predictive relationship of NSSI with depression, difficulties in emotion regulation (DER) and suicidal ideation (administered measures); 3. Comparison of average scores on measures by: quality of attachment (QOA) and presence/absence of NSSI. Method. A convenience sample of 255 adolescents (45.5% women, ages 11-15) answered instruments in institutional facilities (Mexico City and Puebla), where 181 (71%) resided as IB and 74 (29%) resided in family home (EB). The mental health staff of each NGO specified according to the record: demographics, psychiatric diagnoses, history of trauma, and QOA between the minor and his attachment figure. Results. 42% denied NSSI episodes, 16.9% indicated a non-significant pattern, and 35.6% reported a significant and recent pattern. IB presented higher scores in all measurements, higher report of interpersonal trauma, depressive, anxiety, and behavior disorders. Minors with positive QOA obtained significantly lower scores. Discussion and conclusion. Compared to EB’s, adolescents residing in NGOs have a higher risk profile, particularly those without a positive QOA, a fact that is associated with a greater presence of psychopathology and significant and recent NSSI.
Emotional distress and its care in empowered indigenous women exposed to domestic violence and the demands of child rearing
Authors: Vega Leticia , Gutiérrez Rafael , Fuentes de Iturbe Patricia , Rodríguez Eva Ma.
Published: April 2021

Introduction. Indigenous girls and women in Mexico suffer emotional distress due to marital violence and adherence to gender roles. They are unlikely to denounce violence or treat their health in a timely manner. Women can cope with their distress by participating in empowerment processes. Objective. Describe in indigenous empowered women the emotional distress caused by domestic violence in their childhood and the current demands of raising their children and the actions they take to cope with them. Method. Qualitative and phenomenological qualitative research, in-depth interviews, and participant observation were conducted with nine migrant indigenous women to explore experiences during their upbringing, emotional reactions, and current mental health problems. Results. The software Atlas. ti V 7 was used to undertake a theoretical categorization of the data. Findings included exposure to violence, the influence of a good mother, and past and present emotional distress overcome through empowerment and professional care. Discussion and conclusion. Participating in urban empowerment activities enables participants to reflect on the violence experienced and the attendant distress, identify them as gender violence, and use them in their favor. They are strategic when coping with current distress due to the conflictive upbringing of their children, using psychological services and the urban upbringing prescriptions of children’s rights, and incorporating indigenous parenting practices, which encourage community commitment, responsibility, and early self-sufficiency in children. Empowerment is suggested as an effective means of improving the health of indigenous women in Mexico.
Self-reported executive function, and not performance-based measures, strongly associates with symptoms of premenstrual syndrome/premenstrual dysphoric disorder
Authors: Meza-Moreno Frida Itzel , Pimienta-Alcaraz María José , Vázquez-Valdez María Fernanda , Balderas-Sánchez Cynthia Patricia , Toledo-Fernández Aldebarán
Published: April 2021

Introduction. Premenstrual syndrome/premenstrual dysphoric disorder (PMS/PMDD) may be neuropsychologically understood as impairments of executive functions (EF), since these are related to the regulation of complex behavior and cognition. Objective. To test the utility of self-report of EF versus performance-based measures, for the understanding of PMS/PMDD, and to analyze interactive effects between symptoms of these pathologies and EF on daily-life functionality. Method. Mexican women were recruited through non-probabilistic procedures. The Premenstrual Symptoms Screening Tool (PSST) was used to determine severity of symptoms and functional impairment in daily-life activities, and the Behavioral Rating Inventory of Executive Functions-Adults (BRIEF-A) (short Spanish-translated version) adapted to collect information on EF during luteal versus follicular phases. Performance was evaluated with Stroop, Trail Making Test and Letter-Number Sequencing. Results. A total of 157 were analyzed. Three groups were formed: No diagnosis (n = 78); PMS (n = 67) and PMDD (n = 12). Between-group differences were observed for both BRIEF-A-Luteal and BRIEF-A-Follicular. Bivariate correlations between these measures and the PSST were found, with double the magnitude relative to BRIEF-A-Luteal. Only two indicators of performance-based measures were weakly associated to the PSST. The regression model showed high multicollinearity between self-reported EF and PMS/PMDD symptoms, and no interaction was found. Discussion and conclusion. Self-report probed a better association than based-performance tests for the assessment of EF in PMS/PMDD. EF deficits and PMS/PMDD symptoms, particularly during luteal phase, may be as closely link as to allow for the consideration of these diagnoses as partial forms of dysexecutive syndrome.
MODELING SIMULATION AND ANALYSIS OF ROBOT GRASPING POSE FOR NOVEL OBJECTS
Authors: Sengottuvel. P Dhanasekar.J,
Published: April 2021

Modern day robotics aims at bringing precision and motor dexterity of humans to machines. Many scientists are working on mimicking the attributes of a human in order to grasp different object. Initially, the robots were preprogrammed to hold different object but this method is not as effective against a novel object because the image of a novel object does not match with the pre-stored program data. Hence end effector will not be able to pick up the object or it may get damaged. In this paper, a new method is discussed on the dimension and the center of mass. The robot automatically calculates the grasping point and finds the suitable pose of the gripper to grasp the desired object. This proposed work of robot simulation is achieved using MATLAB 8.2 and Creo parametric 2.0. The robot model designed using Creo is fed as input into the MATLAB to generate control signals for the robot to grasp novel objects. By this the robot will automatically grasp a new unknown object by comparing the database already created and be able to handle the object dynamically.
Simulation and dSPACE Hardware Implementation of Carrier based SVPWM for Open-end Induction motor
Authors: Et. al. A Sriharibabu,
Published: April 2021

This paper deals with the implementation of carrier based Space vector pulse width modulated methods (SVPWM) in conjunction with a three phase open end induction motor(OEIM). Among various PWM methods, now a day’s carrier based PWM methods draws more attention due to their easier digital implementation. The main focus of this paper is effortless digital implementation of PWM methods to drive the open end induction motor which is supplied using two dc to ac converters (VSI), using various carrier-based Space vector PWM schemes. MATLAB Simulink platform is used to simulate different carrier based PWM methods for the VSI fed Induction motor. In the present work dSPACE 1104 is used for the digital implementation. The simulation and hardware results which are obtained from various modulation techniques for the proposed model are secure produced by using voltage and current waveforms, FFT analysis, and the most predominantly the THD is slighter. Theoretical and realistic values are corroborating by simulation and experimentation.
PRIVACY-PRESERVING IN MULTI-PARTY DATA RELEASE ON CLOUD FOR BIG DATA USING FUSION LEARNING
Authors: Et. al. Divya Dangi,
Published: April 2021

The data volume increases every day and the next wave of apps cannot be envisaged without the created and executed data-driven algorithms. In this post, we undertook an extensive survey on privacy issues in the context of big data. At every point of the Big Data life cycle, we explored privacy challenges and discussed some of the advantages and disadvantages of the Big Data application of new privacy conservation schemes. Much progress has been made in protecting the protection of consumers from data production to data storage, but many transparent questions and hurdles exist.
AN INVESTIGATION AND ANALYSIS OF CYBER SECURITY INFORMATION SYSTEMS: LATEST TRENDS AND FUTURE SUGGESTION
Authors: Et. al. Tarun Dhar Diwan,
Published: April 2021

Network protection includes of the strategies and procedures implemented in this paper to avoid and monitor intrusion attempts, infringement, manipulation or violation of a computer system and services accessed by the network. Network protection applies to the different countermeasures put in place to secure or flow through the network and data collected on or through it. Protection for web applications is the method of securing websites and internet resources from multiple security attacks that target weaknesses in an application. Security for web apps is a data management division that primarily deals with the security of websites, web applications and web services. Risks to cyber security include a broad range of allegedly criminal practices on the web. For years, computer security risks against utility assets were identified, cyber-attacks arising from the exploitation of data device weaknesses by unauthorized access users This study is a cyber infrastructure assault, vulnerability and vulnerabilities, including hardware and software devices, networks, business networks, intranets, and cyber intrusion usage. Only big organisations are at risk of cyber-attacks, a widespread misunderstanding. Even then, the targeting of small and medium sized enterprises has seen a large improvement. This is since less-sophisticated cyber defence mechanisms appear to be used by these smaller organisations. As many as 50% of all cyber-attacks hit small companies, wasting $200,000 on average, sufficient to get out of business for less-established entities. an enterprise-grade protection device and awareness of the various forms of cyber threats facing corporations in 2025 to safeguard company from hacking attacks. fight cyber threats successfully and decrease the exposure of enterprise.
Investigation on Optimization of Mechanical Properties of Bagasse Reinforced Epoxy Composite Using Grey Relational Analysis
Authors: Et. al. D K Mohan Kumar,
Published: April 2021

In this present study, the fabrication of polymer composite matrix has been designed using the epoxy matrix and bagasse fibre. The most crucial operating parameters such as chemical treatment, volume fraction of fibre content, concentration of chemical, and soaking hours of fibre in the chemical were evaluated. Based on these parameters, the outcomes such as tensile strength, flexural strength, impact strength, hardness, inter laminar shear strength, and coefficient of friction were measured and evaluated. The optimisation of all the operating parameters against the various outcome parameters has been performed by Grey relational analysis. The analysis assist in making decisionto select the best optimum parameters by assigning the rank for the combined mechanical properties with respect to different operating input variables. The optimum combination of operating parameters determined was (i) chemical treatment – KMnO4 (ii) Volume fraction of fibre content – 30 wt % (iii) Concentration of chemical – 7% and (iv) soaking hours of fibre – 6 hours.
Survey of Triangle Security in Cloud
Authors: Et. al. Judy Flava B,
Published: April 2021

Cloud computing remains the world's most demanded development trend. It is one of the most important topic whose application is currently being explored. The distributed storage has been one of the apparent administrations in distributed computing. Instead of providing the engaged worker for conventionally organizated storage, the distributed storage sets various outsider individuals with the knowledge. The customer does not care about any details on various external employees and no one knows exactly where information is spared. The distributed storage supplier asserts that the information can be secured, but no one trusts in it. Security risk is information placed in the plain content configuration over cloud and across the organization. This document offers a method that allows customers to securely store and access data from the distributed storage. It also ensures that neither the distributed storage provider, apart from the verified customer, can get details. This technique ensures the safety and confidentiality of cloud-related information. Another favorite position is that if the cloud provider breaks down, the information of the client remains safe as all information is encoded. Customers must also not stress that cloud providers have illegal access to their data.
Analysis of Key Generation Methods for Enable Secured Communication in the IoTs System
Authors: Et. al. Nikhil Subhash Patankar,
Published: April 2021

The open stack communication protocol of the internet of things always in security threats. The vulnerability of protocol faces a problem of man in middle attacks and loss of integrity of communication. Cryptography plays a vital role in security authentication on IoT based enable communication system.  IoT devices' limited resource constraints cannot offer any security mechanism on the physical level and network level. The key generation methods uplift the security provision in IoT enables communication model. The process of key generation applied three types of cryptography algorithm, symmetric, asymmetric and hybrid algorithm. The complexity of key generation methods needs more computational time and memory; this is the limitation of IoT devices. So various authors proposed a lightweight key generation algorithm for security and authentication. This paper analyzed the performance of key generation methods based on different cryptography approaches and measured their security strength. For the analysis process, use MATLAB software and sample text data file for the communication of two parties. Some ADHOC methods apply to measure protocol weakness during the communication network compromised with a man in the middle attack.  The variable key size also reflects the security strength of IoTs enable devices.
The Diagnosis of Chronic Liver Disease using Machine Learning Techniques
Authors: Harshpreet Kaur Golmei Shaheamlung,
Published: April 2021

In the 21st-century, the issue of liver disease has been increasing all over the world. As per the latest survey report, liver disease death toll has been rise approximately 2 million per year worldwide. The overall percentage of death by liver disease is 3.5% worldwide. Chronic Liver disease is also considered to be one of the deadly diseases, so early detection and treatment can recover the disease easily. Due to rapid advancement in Artificial intelligence (AI), like various machine learning algorithms SVM, K-mean clustering, KNN, Random forest, Logistic regression, etc., This will improve the life span of a patient suffering from Chronic Liver Disease (CLD) in early stages. The data can be obtained in a large volume due to the broad exploitation of bar codes for supreme marketable products, the mechanization of various business and government dealings, and the development in the data collection tools. This research work is based on liver disease prediction using machine learning algorithms. Liver disease prediction has various levels of steps involved, pre-processing, feature extraction, and classification. In this s research work, a hybrid classification method is proposed for liver disease prediction. And Datasets are collected from the Kaggle database of Indian liver patient records. The proposed model achieved an accuracy of 77.58%. The proposed technique is implemented in Python with the Spyder tool and results are analyzed in terms of accuracy, precision, and recall.
INTELLIGENT AQUAPONICS USING IoT
Authors: Et al. Sujatha Anand
Published: April 2021

Conventional agriculture and aquaculture present the unwelcome situation of great extents of consumption in both land  and  water  resources.  The  threat  of pollution of water bodies also need  to  be  taken  into account. The urbanization policies and population explosion with rapid migration from rural areas makes the concept of aquaponics reuse of ecological crop rising and reusing methods  essential. This   technology   coalesces   recirculation of water used in aquaculture and hydroponics for crop supplement and water recycle; reduction of pollution and enhancement of efficiency and yield. Hydroponics and aquaculture is proposed in this paper on a combinatory  solution  for  better  agriculture  practice.  Intelligent monitoring of water quality and nutrient circulation can be abstracted, tabulated and summarized. This paper popularizes the implementation of IoT in aquaponics.
DEVELOPMENT OF VEHICLE TRACKING USING SENSOR FUSION
Authors: Et. al. M Hyndhavi,
Published: April 2021

The development of vehicle tracking using sensor fusion is presented in this paper. Advanced driver assistance systems (ADAS) are becoming more popular in recent years. These systems use sensor information for real-time control. To improve the standard and robustness, especially in the presence of environmental noises like varying lighting, weather conditions, and fusion of sensors has been the center of attention in recent studies. Faced with complex traffic conditions, the single sensor has been unable to meet the security requirements of ADAS and autonomous driving. The common environment perception sensors consist of radar, camera, and lidar which have both pros and cons. The sensor fusion is a necessary technology for autonomous driving which provides a better vision and understanding of vehicles surrounding. We mainly focus on highway scenarios that enable an autonomous car to comfortably follow other cars at various speeds while keeping a secure distance and mix the advantages of both sensors with a sensor fusion approach. The radar and vision sensor information are fused to produce robust and accurate measurements. And the experimental results indicate that the comparison of using only radar sensors and sensor fusion of both camera and radar sensors is presented in this paper. The algorithm is described along with simulation results by using MATLAB.
Design and Analysis of a Non-Uniform Meander RF MEMS Switch
Authors: Et. al. C Leela Mohan,
Published: April 2021

This paper aimed to design and analysis of non-uniform meander capacitive shunt RF MEMS switch. The less pull in voltage is obtained in flexure type membrane by proposed RF MEMS Switch. The selection of materials for the beam and dielectric layer is expressed in this paper and also shown the performance depends on materials utilized for the design. The high isolation of -31.15dB actuating at the pull-in voltage of 7.69V with a spring constant of 3.28N/m produced the switch and is obtained by the optimization process. Capacitive contact switches have capability of power handling. The actuated switch state provides an excellent isolation. It shorts the ground by RF signal. MEMS technology is the integration of electrical and mechanical components on single platform i.e. substrate [10]. From the literature, various researchers have proposed different RF MEMS Switch, but still there few challenges on optimization of the Switch for best performance. The electromechanical analysis such as Upstate, Downstate capacitances and stress analysis have been carried out. The performance of the switch is analyzed by taking appropriate materials selected by Ashby’s approach. These optimized dimensions are feasible to fabricate. The substrate height, material for the substrate and coplanar waveguides are used for the impendence matching. For obtaining the less pull in voltage overlapping area is to be increased.
Area and Power Efficient Fused Floating-point Dot Product Unit based on Radix-2r Multiplier & Pipeline Feedforward-Cutset-Free Carry-Lookahead Adder
Authors: K. Rama Naidu M. Madhu Babu,
Published: April 2021

Fused floating point operations play a major role in many DSP applications to reduce operational area & power consumption. Radix-2r multiplier (using 7-bit encoder technique) & pipeline feedforward-cutset-free carry-lookahead  adder(PFCF-CLA) are used to enhance the traditional FDP unit. Pipeline concept is also infused into system to get the desired pipeline fused floating-point dot product (PFFDP) operations. Synthesis results are obtained using 60nm standard library with 1GHz clock. Power consumption of single & double precision operations are 2.24mW & 3.67mW respectively. The die areas are 27.48 mm2 , 46.72mm2 with an execution time of 1.91 ns , 2.07 ns for a single & double precision operations respectively. Comparison with previous data has also been performed. The area-delay product(ADP) & power-delay product(PDP) of our proposed architecture are 18%,22% & 27%,18% for single and double precision operations respectively.
Use of ICT in Teaching Vocational Subjects
Authors: Dr. Mahima Gupta, Prof. Banhi Jha Deepak Chakravarty,
Published: April 2021

In today’s modern world, globalization has completely changed the way of working. The way we live, learn, work, and even define work has changed due to new information and communication technologies—Hence, it can stated that human capital fuel up the modern economy. In reality, the information and communication technology revolution has turned intelligence into a valuable commodity. In today's economy, economic growth is based on mental intelligence rather than physical strength, and its worth is generated by recruiting knowledgeable workers and continuing to learn. Incorporating information and communication technology (ICT) into vocational and technical education and the educational system in general has a vast range of consequences on teaching and learning.
Low Power and Area Efficient Borrow Save Adder for MAC Unit in VLSI Application
Authors: V. Kumaravel, M. Pooja S. Gayathri Priya, J. Jagan Babu,
Published: April 2021

In hypercompetitive embedded system environment, to develop the unique characteristic of machine learning computation for more efficient MAC design for reduced both the area and power. In this paper, Multiply–accumulate (MAC) computations account for a large part of machine learning accelerator operations use in pipelined structure is usually adopted to improve the performance by reducing the number of adder circuits. The proposed a pipelining method that eliminates some of the flip-flops in carry look adder in selectively. Here, introduce the applying the Feed forward-Cutset-Free (FCF) pipelining method in borrow save adder (BSA) to the accumulator by reducing the design, optimized the power dissipation and undesired data transition in (MFCF-PA). From the FPGA Xilinx simulation output result shows that, the MAC unit reached between 15% and 25% energy saving and area reduction of 15% over the existing carry look ahead adder (CLA) conformist pipelined MAC units.
CONTEXT STORAGE USING CLOUD-BASED MONGODB WITH RULE-BASED RETE ALGORITHM
Authors: Et. al. Shivakumar. C,
Published: April 2021

In this Context-aware computing era, everything is being automated and because of this, smart system’s count been incrementing day by day.  The smart system is all about context awareness, which is a synergy with the objects in the system. The result of the interaction between the users and the sensors is nothing but the repository of the vast amount of context data. Now the challenging task is to represent, store, and retrieve context data. So, in this research work, we have provided solutions to context storage. Since the data generated from the sensor network is dynamic, we have represented data using Context dimension tree, stored the data in cloud-based ‘MongoDB’, which is a NoSQL. It provides dynamic schema and reasoning data using If-Then rules with RETE algorithm. The Novel research work is the integration of NoSQL cloud-based MongoDB, rule-based RETE algorithm and CLIPS tool architecture. This integration helps us to represent, store, retrieve and derive inferences from the context data efficiently..
PREDICTIVE ANALYTICS USING DEEP NEURAL NETWORKS
Authors: Et. al. Ranjana Durai,
Published: April 2021

Several studies indicate that teaching methods have a significant impact on the academic performance of the students. Similarly, they also connote a substantial dependance of a student’s performance on the methods and techniques they employ in their study schedule. In this project, a model based on Deep Neural Network (DNN) has been deployed for the Predictive Analysis of a student’s performance was tested for results. Furthermore, this model also aims at recommending study methodologies to students based upon the psychometric features derived from a self-analysis questionnaire that was prepared for the same.

Various factors that influence the performance of a student were identified and corresponding data was collected. This includes internal assessment scores, scores in the 10th grade and 12th grade   board exams, attendance percentage for the particular semester and travel duration, availability internet connection facility, number of arrears among the others. This model was implemented on data of the student batches graduating in years in the duration of 2016-22. Test data evaluation presents an accuracy of 96.3% in the prediction of the   student performance.
MARITIME SURVEILLANCE USING SAR OCEANIC IMAGES
Authors: Et. al. DR.J.Chenni Kumaran,
Published: April 2021

Marine things to do play a necessary position in the improvement of a nation. There is, however, a possible threat to the protection of a country via marine routes. This paper provides the most effective and easy-to-use method that enables the defense and marine protection authority staff to track the middle sections of the ocean for unusual marine activities by collecting an oceanic image from a SAR satellite. It helps the user by extracting information such as number of ships at particular region, distance between each, length and breadth of ships and the velocity at which the ship is moving. It includes various modules such as initial tiling and pre-processing, vessel or ship detection and wake detection for estimating velocity of ship. The interface of this framework is very user-friendly and fully implemented with a MATLAB.
USE OF MACHINE LEARNING ALGORITHMS IN CYBER SECURITY
Authors: Et. al. Sheha kothari,
Published: April 2021

Artificial intelligence (AI) has made incredible progress, resulting in the most sophisticated software and standalone software. Meanwhile, the cyber domain has become a battleground for access, influence, security and control. This paper will discuss key AI technologies including machine learning in an effort to help understand their role in cyber security and the implications of this new technology. This paper discusses and highlights the different uses of machine learning in cyber security.
Fleet maintenance using IOT technology
Authors: Dr. Ramkrishna Manatkar Surabhi Hatagale,
Published: April 2021

In fleet management, fleet maintenance is an important exposure to increase availability. Periodic and preventive maintenance is one such crucial aspect which is considered regardless of the practical faults which in sets of the need for repair and replacement cost as well time attached with it. With development in technology IOT and big data have been in talks. With all the data that is being produced predictive maintenance can be performed using this technology. IOT based predictive maintenance can increase fleet availability, stability and efficiency, reduced cost through effective maintenance  planning and eliminate unnecessary maintenance tasks.
PREDICTIVE MACHINE LEARNING (ML) ALGORITHM USING IOT FRAMEWORK FOR NOVEL CORONA VIRUS (COVID-19)
Authors: Mylavarapu Kalyan Ram G. S. N. Murthy, M. V. Sangameswar, Venubabu Rachapudi,
Published: April 2021

During earlier months of the pandemic COVID-19 with no recommended cure or vaccine available only solution to destroy the chain is self-isolation which can be maintained by physical distancing. This is now understood that the world require much faster solution to accommodate and deal with the future COVID-19 spread over the world by non-clinical methods namely data mining, augmented intelligence and several Artificial Intelligence (AI) techniques. It has become a huge hindrance to mitigate for the healthcare industry to provide more potential involved for patient's diagnosis and also for effective prognosis of 2019-CoV pandemic. Therefore, the proposed framework is implemented with the Internet of Things (IoTs) in healthcare industry for collecting the symptom data of real-time that is beneficial in predicting whether the person gets infected with COVID-19 virus or not. This can be done through various signs namely body temperature, blood oxygen level, headache, coughing patterns, etc. Thus, the research work focused on faster identification of COVID-19 virus infection cases potentially using Machine Learning (ML) algorithm from the real-time symptom data. Moreover, the obtained results have illustrated that K-Nearest Neighbour (KNN) algorithm is highly efficient while compared with other ML algorithms such as Naive Bayes and Logistic Regression (LR) in predicting the possible recovery of the infected patients from pandemic COVID-19 with the accuracy of 96.85%.
Role of Government to boost exports of Gems & Jewellery from India
Authors: Dr. Vani Kamath Hemant Kumar Tantia,
Published: April 2021

India’s present foreign exchange earnings from Gems and jewellery sector is in the range of US$ 36 to 43 billion per annum during last five year from 2015 to 2020. Being huge potential of its growth, the government has set an annual target of USD 75 billion in jewellery exports by the year 2025. (Source – GJEPC India, Ministry of Commerce & Industry). In order to achieve this daunting goal, the government has declared Gems and Jewellery sectors a focus area for export promotion and  under taken various measures to boost its exports by way of liberalisation in export policy, extending financial support, technology up gradation and skill development .This research paper attempts to analyse the various strategies adopted by the government to achieve the set target. For this research, primary and secondary data have been collected and analysed. The findings of the study would be very useful for the growth of exports.
Laboratory Safety System using IOT
Authors: Et. al. S V Priya,
Published: April 2021

Internet of Things (IoT) conceptualizes the idea of remotely connecting and monitoring real world objects (things) through the Internet. This concept can be aptly incorporated to make laboratories smarter, safer and automated. This IoT project focuses on building a smart lab safety system which sends alerts to the owner by using Internet in case of any danger and raises an alarm optionally.A safety system needs to be designed to ensure at most safety in the laboratories.
IMPACT OF COVID-19 ON SUPPLY CHAIN AND LOGISTICS
Authors: Et. al. Mrs. Aparna Lalitkumar Patil
Published: April 2021

In early January 2020, coronavirus outbreak started to build up as a pandemic in the city of Wuhan in China, leading to social, human as well as economic disturbance, leaving no life untouched. COVID-19, the coronavirus pandemic impacted the production, logistics as well as the supply chain system in the entire world.  As companies, around the globe are trying to repair their shattered value chains in the short-term and reduce their supply chain risks in the long-term, India also has an exclusive chance to emerge as a business terminus during and after the COVID-19 pandemic.
Género, belleza y pretensiones artísticas en el campo de las peluquerías
Authors: Arango Gaviria Luz Gabriela
Published: April 2021

Con base en los resultados de una investigación cualitativa (2010), abordo los salones de belleza y peluquerías de Bogotá, Colombia, como campo de producción de una oferta de posibilidades estilísticas. En diálogo con la crítica feminista a la belleza, analizo los modos en que el género interviene en los discursos y las prácticas de mujeres y hombres estilistas que acuden a una idea de arte para significar su trabajo, construir su identidad y defender el valor simbólico de su profesión u oficio. Distingo tres tipos de experiencias y estrategias: varones artistas del diseño de imagen en la alta peluquería; barberos y peinadoras afrocolombianos; mujeres artistas y peluqueras transgresoras. Las luchas simbólicas en las que participan estilistas y peluqueros muestran la variedad de usos posibles de valores compartidos como el arte, la belleza o lo moderno, y cómo estos usos son configurados por relaciones de género, clase, etnicidad y raza.
Analysis of healthcare for patients with cardiovascular diseases in Russian Federation in comparison with the practice of Europe and USA
Authors: Medvedeva E. A. , Zvartau N. E. , Villevalde S. V. , Yakovlev A. N. , Solovieva A. E. , Fedorenko A. A. , Karlina V. A. , Zaitsev V. V. , Endubaeva G. V. , Panarina S. A. , Erastov A. M.
Published: April 2021

The medical community, researchers and healthcare organizers are constantly challenged by comparing key indexes reflecting the effectiveness of cardiovascular care, primarily for the dynamic assessment and implementation of the world's best practices to reduce cardiovascular mortality. The analysis of health care for patients with cardiovascular diseases (CVD) is a complex, multicomponent process, the structure and key tools of which differ from country to country. Using different data sources, methodological and analytical approaches creates certain limitations and barriers to the assessment. In order to update the ideas about the modern coordinate system and tools for assessing cardiovascular care, the authors presented practices for analyzing major indexes in Russia, European countries, and the United States. The review presents sources of statistical data, principles for assessing risk factors, cardiovascular morbidity and mortality, and specific features of monitoring the availability and quality of cardiovascular care.
Psychological Continuum of Elderly Patients Suffering from Arterial Hypertension with Metabolic Syndrome, Against the Background of Chronotherapy with a Fixed Combination of Amlodipine, Lisinopril and Rosuvastatin
Authors: Agarkov N. M. , Okhotnikov O. I. , Korneeva S. I. , Moskaleva E. O. , Moskalev A. A. , Kolomiets V. I. , Markelova A. M. , Markelova E. A.
Published: April 2021

Aim        To study the psychological continuum in elderly patients with arterial hypertension associated with metabolic syndrome during the chronotherapy with a fixed combination (FC) of amlodipine, lisinopril, and rosuvastatin.

Material and methods        In the inpatient conditions, 63 patients aged 60–74 years with arterial hypertension associated with metabolic syndrome were treated with chronotherapy with a FC of amlodipine, lisinopril, and rosuvastatin (5 / 10 / 10 mg/day in the evening). These patients composed the main group. The control group (58 patients aged 60–74 years with arterial hypertension associated with metabolic syndrome) was treated with the FC of amlodipine, lisinopril, and rosuvastatin at the same dose of 5 / 10 / 10 mg/day in the morning.

Results   At one year, the disorders of psychological continuum were significantly decreased with the chronotherapy (evening dosing) with the antihypertensive FC of amlodipine, lisinopril, and rosuvastatin compared to the traditional treatment (morning dosing) at the same dose of 5 / 10 / 10 mg/day in both groups. With the chronotherapeutic approach, the dynamic of cognitive disorders in patients aged 60–74 years with arterial hypertension associated with metabolic syndrome was characterized by a significant increase in the Mini-Mental-State-Examination scale score from 17.8±0.3 at baseline to 23.5±0.4 with the evening dosing (р<0.001) vs. the increase from 16.9±0.3 to 20.4±0.4 (р<0.001) with the morning dosing. The situational anxiety score decreased from 40.0±2.2 to 30.6±1.8 (р<0.05) and from 40.8±2.5 to 33.5±1.9  (р<0.05), and the trait anxiety score decreased from 48.8±2.0 to 26.4±1.9 (р<0.001) and from 44.9±1.9 to 30.7±1.7  (р<0.01) with the evening and morning dosing, respectively. Depressive disorders slightly decreased with the chronotherapy by 14.1 % vs. 7.7 % with the traditional regimen; nevertheless, they were consistent with depressive spectrum disorders in both groups.

Conclusion            The study results showed a higher effectiveness of the chronotherapeutic treatment compared to the traditional treatment with FC of amlodipine, lisinopril, and rosuvastatin in arterial hypertension with metabolic syndrome.
Socio-economic assessment of patient blood management practical implementation in surgical treatment of coronary heart disease (I20–I25)
Authors: Golukhova E. Z. , Kupryashov A. A. , Khicheva G. A. , Kuksina E. V. , Volkova O. I. , Kurilovich E. O. , Popovich L. D.
Published: April 2021

Aim    To evaluate possible social and economic benefits of correcting preoperative iron deficiency /iron deficiency anemia as a comorbidity in a model population in the process of transition from the routine practice to the optimized preparation of patients to elective surgery (as exemplified by several circulatory diseases: I20 – I25, class IX ICD 10).Material and methods    By building imitation models depending on the patient blood management (PBM) practice, changes in years of life lost/saved adjusted for disability were evaluated, including in monetary terms, in relation to the annual number of operations performed for ischemic heart disease (IHD) (I20 – I25) in the age group of 17 years and older, as well as a potential effect of PBM on the applied health economics.Results    With implementation of the PBM systemic measures in cardiac surgery, the potentially prevented annual social and economic damage will amount to more than 38 thousand years of life saved and more than 20.2 billion rubles in monetary terms. Furthermore, it will be possible to exclude 9435 hemotransfusion from the cardiosurgical practice, which will annually save more than 2.3 thousand liters of blood with a total cost of 77.7 million rubles in favor of clinical situations that have no alternative.Conclusion    The implementation of PBM in cardiac surgery, the discipline with the highest levels of preoperative iron deficiency/anemia and the use of blood components, will not only improve the clinical outcomes and cost-effectiveness of surgical interventions, but will also prevent social and economic damage to the country.
Trends in female sterilization in north central Nigeria
Authors: Thosmas Sambo T. , Adewole Nathaniel D. , Muhammad Rafat B. , Adebayo Francis O. , Offiong Richard A. , Agida Teddy E.
Published: April 2021

Background: Contraception is key to the reduction of maternal mortality. Tubal ligation is a good option for women seeking out a safe, effective, permanent and convenient form of contraceptive. However, due to variety of reasons, there is aversion to it especially in developing world. The objective of this study was to determine the trends, uptake, socio-demographic characteristics of acceptors, indications and complications of bilateral tubal ligation (BTL) in our environment.Methods: A retrospective study of BTL at UATH was conducted over a five year period, from 1 January 2015 to 31 December 2019. The records of women who had BTL were retrieved from the medical records department, family planning clinic, and the theatre. The data was analyzed using SPSS 21.Results: The mean age and parity were 36.0±4.0 and 5.0±2.0 respectively. The incidence of BTL was 1.3%. Majority of those that had BTL had at least secondary level of education 100 (83.4%) and 58 (48.3%) were grand multiparous. Majority of cases 87 (72.5%) were done during caesarean section/laparotomy. Postpartum BTL accounted for 15.0%, while interval BTL accounted for 12.5%. Completed family size was the commonest indication 48.3%. No client came back with regrets. There was one case of failed BTL.Conclusions: BTL is a safe and effective method of sterilization. There is an increasing trend in utilization of BTL however the rate is still low.
Pragmatic abilities of children with severe to profound hearing loss
Authors: Vaidya Hemangi , Waknis Aarti P. , Deshpande Shweta
Published: April 2021

Background: Western studies indicate that children with hearing impairment (CHI) are at risk of pragmatic delay due to their delayed language development. Pragmatics is influenced by culture. Hence the objective of the study was to compare the pragmatic skills of Marathi speaking CHI using hearing devices and typically developing children (TDC) matched according to their expressive language age, chronological age, and hearing age.

Methods: Group I included 40 CHI using a hearing device having a chronological age range of 24 to 68 months, with an expressive language age of 6 to 48 months on receptive-expressive emergent language scale (REELS) and with a hearing age in the range of 12 to 36 months. Group II consisted of 40 TDC in the age range of 6 to 48 months. Checklist for assessment of pragmatics of pre-schoolerswas administered for assessment of pragmatics to children in both the groups.

Results: Statistical analysis using unpaired t test indicated that there was a significant difference in pragmatic skills of the two groups when they were matched on the basis of their chronological and expressive language age (p<0.01), but there was no significant difference between the two groups when they were matched on the basis of their hearing age (p>0.01).

Conclusions: Pragmatic ability is delayed in CHI and is more a function of hearing age than chronological age or expressive language age. Thus, pragmatic abilities should be assessed and intervention provided if required for CHI even if they have good expressive ability.
Health Advocacy and Health Communication for Elderly Health Care Consumers: Rationale, Demand, and Policy Implications
Authors: Kreps Gary L.
Published: April 2021

Health advocacy is an important set of communication activities to promote the best health outcomes for individuals confronting health threats, especially for elderly health care consumers, who utilize high levels of health care services for both chronic and acute health problems. However, many elderly health care consumers do not receive adequate advocacy support and have difficulty shaping health care policies and practices due to problems with ageism and power imbalances within health care systems, which accord far more authority to health care providers and administrators than to consumers in the delivery of care. This limits elders' participation and influence in health care, despite research showing that active consumer involvement usually improves health outcomes. Strategic health advocacy can rebalance power within health care, developing and refining health policies and practices. The best advocacy actively represents the voices, concerns, and needs of consumers within health care systems to help make programs responsive to consumer needs. Health advocates must effectively communicate patients' perspectives and needs to key audiences using strategic message strategies and channels to influence health policies and practices. Yet effective advocacy does not happen naturally and needs to be nurtured by relevant programs and policies to represent consumer needs for enhancing health outcomes for elderly health care consumers.
Przymusowe ubezpieczenia budowli kościelnych w międzywojennej Polsce
Authors: Bednaruk Waldemar
Published: April 2021

W pierwszych latach istnienia niepodległego państwa polskiego utrzymano, a następnie rozszerzono na nowe tereny, obowiązek ubezpieczania nieruchomości kościelnych od ognia. Ta kategoria budynków została w toku prac nad nowym systemem wyodrębniona. Stworzono dla niej nową taryfę i pobierano niższą składkę z tytułu podpisanych umów. Te preferencyjne warunki naliczania składek wynikały z największej odporności budowli kościelnych na ryzyko pożaru. Materiał, z którego budowano nieruchomości kościelne, ich umiejscowienie oraz odporność na pozostałe czynniki zwiększające niebezpieczeństwo wybuchu pożaru sprawiały, iż budynki kościelne ulegały zniszczeniu bardzo rzadko. Dzięki dobrym wynikom finansowym w tym dziale branża ubezpieczeń mogła oferować lepsze warunki klientom mniej zamożnym, co przyczyniło się do poprawy sytuacji osób najbiedniejszych.
Clergy Formation in the Provisions of Zamość and Lviv Synods
Authors: Levytskyy Oleksandr
Published: April 2021

Formacja duchowieństwa w postanowieniach Synodów Zamojskiego i Lwowskiego

Artykuł analizuje etapy formacji duchowieństwa w postanowieniach Synodów Zamojskiego i Lwowskiego. Badania mają na celu wyjaśnienie i ustrukturyzowanie głównych podejść i zasad procesu formacji duchowieństwa w postanowieniach Synodu Zamojskiego z 1720 r. i Synodu Lwowskiego z 1891 r. W szczególności autor przeanalizował dokumenty normatywne tych synodów, które dotyczą regulacji formacji duchowieństwa w Kościele. Rozważane są etapy i metody przygotowania kandydatów do kapłaństwa. Nacisk kładzie się na stopniowe logiczne uporządkowanie dokumentów normatywnych dotyczących formacji kapłańskiej w Kościele ukraińskim.
Considerações sobre Anonimato, Pseudoanonimato e Criptomoedas
Authors: Oliveira Jordan Vinícius , Lopes Marília Carneiro da Cunha
Published: April 2021

O presente artigo avalia a temática do anonimato e do pseudoanonimato para as criptomoedas. A pergunta de pesquisa avalia se existe, no ordenamento jurídico nacional, algum elemento restritivo para a transação de criptomoedas com o intuito de anonimato. Sob o prisma jurídico, a Lei Geral de Proteção de Dados Pessoais e as normativas da do Banco Central e da Receita Federal integram o quadro de avaliação. Sob o prisma tecnológico, o modo de funcionamento e a relação com anonimato ou pseudoanonimato do Bitcoin, do Monero, do Zcash e do Dash compõem a análise. A conclusão é a de que, até o momento, a transação de criptomoedas verdadeiramente anônimas não encontra vedações expressas na legislação nacional.
A maldição da grandeza: uma resenha crítica da obra “The curse of bigness: antitrust in the new Gilded Age”, de Tim Wu
Authors: Faleiros Júnior José Luiz De Moura
Published: April 2021

A ascensão de poucas grandes empresas que exploram atividades empresariais na Internet ao patamar de “impérios da comunicação” foi apontada, com pioneirismo, por Tim Wu, renomado Professor da Universidade de Columbia, que, em “The Curse of Bigness”, defende que os governos devem fazer cessar a autorregulação e intervir, por legislações antitruste, para cindir gigantes da tecnologia como Google, Facebook e Amazon, a fim de restaurar o dinamismo e promover a inovação. O objetivo primordial desta resenha é apresentar a mais recente obra de Tim Wu, sob viés crítico, a partir do contraste que permeia o direito econômico à luz da inexorável presença da tecnologia e da ponderação de valores concernentes ao intervencionismo regulatório estatal quanto à invocação de leis antitruste – especialmente, no caso da obra em análise, o Sherman Act norte-americano. Na análise crítica propugnada em sintonia com a metodologia empregada por Wu no curso de seu texto, apontar-se-á, por derradeiro, a necessidade de observância estrita da garantia de direitos fundamentais nos meandros do porvir.