The Prevalence, Management and Impact of Dysmenorrhea on Medical Students’ Lives—A Multicenter Study

Introduction: Dysmenorrhea is defined as the presence of painful menstruation, and it affects daily activities in different ways. The aims of this study were to assess the prevalence and management of dysmenorrhea and to determine the impact of dysmenorrhea on the quality of life of medical students. Material and methods: The study conducted was prospective, analytical and observational and was performed between 7 November 2019 and 30 January 2020 in five university centers from Romania. The data was collected using an original questionnaire regarding menstrual cycles and dysmenorrhea. The information about relationships with family or friends, couples’ relationships and university activity helped to assess the effects of dysmenorrhea on quality of life. The level of significance was set at p < 0.05. Results: The study comprised 1720 students in total. The prevalence of dysmenorrhea was 78.4%. During their menstrual period, most female students felt more agitated or nervous (72.7%), more tired (66.9%), as if they had less energy for daily activities (75.9%) and highly stressed (57.9%), with a normal diet being difficult to achieve (30.0%). University courses (49.4%), social life (34.5%), couples’ relationships (29.6%), as well as relationships with family (21.4%) and friends (15.4%) were also affected, depending on the duration and intensity of the pain. Conclusion: Dysmenorrhea has a high prevalence among medical students and could affect the quality of life of students in several ways. During their menstrual period, most female students feel as if they have less energy for daily activities and exhibit a higher level of stress. The intensity of the symptoms varies considerably and, with it, the degree of discomfort it creates. Most student use both pharmacological and non-pharmacological methods to reduce pain (75.7%). University courses, social life, couples’ relationships, as well as relationships with family and friends are affected, depending on the duration and intensity of the pain.

Sử dụng mạng máy tính phân tán trong xây dựng giải pháp thám mã khối

Tóm tắt—Bài báo trình bày một giải pháp sử dụng năng lực của mạng máy tính phân tán cho thám mã khối. Hệ thống có cấu trúc dựa trên 3 phần mềm. Phần mềm quản trị sử dụng cho nhập dữ liệu đầu vào, phân tích và chia khoảng không gian khóa và phân tích kết quả. Phần mềm thám mã trên CPU và GPU được cài đặt tương ứng cho các máy tính trong mạng phân tán có nhiệm vụ thám mã đối với dữ liệu phần mềm quản trị cung cấp. Kết quả được gửi về phần mềm quản trị để phân tích và giải mã. Quá trình thám mã được thực hiện cùng lúc trên toàn bộ máy tính trong mạng vào thời gian máy tính nhàn rỗi, không ảnh hưởng tới hoạt động hàng ngày của người dùng. Hệ thống bao gồm cả các máy tính có sử card GPU giúp tăng hiệu suất thám mã lên gấp 11 lần. Giải pháp đã được ứng dụng trong thám mật khẩu Windows qua mã băm LAN Manager. Abstract—This paper presents a method to use the capabilities of distributed computer networks in cryptanalysis of block ciphers. The system is structured based on 3 software. Management software for input data entry, analysis, and keyspace division. Cryptanalysis software on CPU and GPU is installed respectively for client computers in the distributed network is responsible for cryptanalysis of data provided by the management software. The results are sent to the administrative software for analysis and decoding. The encryption process is performed on all computers in the network at the same time in their spare time, without affecting the user's daily activities. The system includes GPU computers that increase the performance of the cryptanalysis by 11 times. This solution has been applied in Windows password detection via LAN Manager hash code.

From Intricacy to Conciseness: A Progressive Transfer Strategy for EEG-Based Cross-Subject Emotion Recognition

Emotion plays a significant role in human daily activities, and it can be effectively recognized from EEG signals. However, individual variability limits the generalization of emotion classifiers across subjects. Domain adaptation (DA) is a reliable method to solve the issue. Due to the nonstationarity of EEG, the inferior-quality source domain data bring negative transfer in DA procedures. To solve this problem, an auto-augmentation joint distribution adaptation (AA-JDA) method and a burden-lightened and source-preferred JDA (BLSP-JDA) approach are proposed in this paper. The methods are based on a novel transfer idea, learning the specific knowledge of the target domain from the samples that are appropriate for transfer, which reduces the difficulty of transfer between two domains. On multiple emotion databases, our model shows state-of-the-art performance.

Generative design of 3D printed hands-free door handles for reduction of contagion risk in public buildings

During the emergency caused by COVID 19 evidence has been provided about the risk of easily getting the virus by touching contaminated surfaces and then by touching eyes, mouth, or nose with infected hands. In view of the restarting of daily activities in presence, it is paramount to put in place any strategy that, in addition to social distancing, is capable to positively impact on the safety levels in public buildings by reducing such risk. The main aim of this paper is to conceive a design methodology, based on a digital, flawless, and sustainable procedure, for producing human-building interfacing solutions that allow anybody to interact in a safer and more comfortable way. Such solutions are focused on the adaptation of existing buildings features and are thought to be an alternative to sensor based touchless technology when this is not applicable due to economic or time constraints. The process is based on the integration of digital technologies such as 3D Scanning, Generative Design and Additive Manufacturing and is optimised to be intuitive and to be adaptive, hence, to be replicable on different kinds of surfaces. The design concept is finalised to generate automatically different products that meet geometry fitting requirements and therefore adapt to the specific geometries of existing handles. A specific case on Hands Free Door Handles is presented and the results of manufacturing and preliminary validation process are provided and discussed.

Impacts of COVID-19 on the Education, Life and Mental Health of Students in Bangladesh

COVID-19’s unanticipated consequences have resulted in the extended closure of various educational institutions, causing significant hardship to students. Even though many institutions rapidly transitioned to online education programs, various issues have emerged that are impacting many aspects of students’ lives. An online survey was conducted with students of Bangladesh to understand how COVID-19 impacted their study, social and daily activities, plans, and mental health. A total of 409 Bangladeshi students took part in a survey. As a result of the COVID-19 pandemic, 13.7% of all participants are unable to focus on their studies, up from 1.2% previously. More than half of the participants (54%) have spent more time on social media than previously. We found that 45% of the participants have severe to moderate level depression. In addition, 48.6% of the students are experiencing severe to moderate level anxiety. According to our findings, students’ inability to concentrate on their studies, their increased use of social media and electronic communications, changing sleep hours during the pandemic, increased personal care time, and changes in plans are all correlated with their mental health.

The duration of daily activities has no impact on measures of overall wellbeing

It is widely assumed that the longer we spend in happier activities the happier we will be. In an intensive study of momentary happiness, we show that, in fact, longer time spent in happier activities does not lead to higher levels of reported happiness overall. This finding is replicated with different samples (student and diverse, multi-national panel), measures and methods of analysis. We explore different explanations for this seemingly paradoxical finding, providing fresh insight into the factors that do and do not affect the relationship between how happy we report feeling as a function of how long it lasts. This work calls into question the assumption that spending more time doing what we like will show up in making us happier, presenting a fundamental challenge to the validity of current tools used to measure happiness.

TYPOLOGY OF PRIVATE CAR USERS DURING COVID-19 PANDEMIC IN KAYURINGIN JAYA

<p>The Covid-19 Pandemic was indicated in March 2020, which has changed people's daily activities patterns. Implementing the restricting regulation imposed by the government made some of the people's daily activities diverted to an online system. As a result, community mobility has decreased, especially on private car usage. However, there is a shift in vehicle usage which many people are starting to switch their mode to the private car in daily travel. This condition was predicted would continue even after the Pandemic ends. The increase in private car usage will worsen the congestion than before the Covid-19 Pandemic appropriate steps and handling are needed to prevent the increase in congestion. One of them is by knowing the characteristics and journeys of private car users during the Covid-19 Pandemic. This research is a typology of private car users during the Covid-19 Pandemic to identify the similarities and differences in the characteristics possessed by each private car user through the typological groups formed. Through this research, it can be seen the movement patterns and characteristics of the people who use private cars. This study uses the Hierarchical Cluster Analysis method. The analysis is based on several variables such as private car usage frequency variables, socioeconomic characteristics variables, demographic variables, household variables, and household travel patterns object of this research is 107 households which are owners and use of private cars for further analysis and form clusters of private car users that have the same characteristics of each cluster. The typology of private car users is compiled based on the unique characteristics possessed by each cluster that is formed. The results of this study are 8 typologies of private car users, which are divided from intensive users to irregular users. Typology 1 has the largest number of respondents and dominates the frequency of trips by private car users. The benefit of this research for the government is as input in the formulation of policies to regulate the use of private cars so that the policies taken by the government can be right on target</p>

Analisis followers to likes ratio pada 5 akun termahal TikTok

ABSTRACTTikTok is a social media application launched by a Chinese company. TikTok allows users to create 15-second videos accompanied by music, filters, and several other creative features. In Indonesia, there are 30.7 million active users, making Indonesia the country with the largest TikTok users in the world. The large number of active TikTok users in Indonesia can certainly provide opportunities for content creators, influencers, reviewers and public figures to make the TikTok platform a social media marketing platform. The 5 Most Expensive TikTok Accounts that use TikTok as a platform to share their daily activities as well as their activities are reviewing products that are distributed to be promoted, namely: Zachking, Ryaz Aly, BabyAriel, LorenGray and Kristen Hancher. The purpose of this study is to calculate the credibility of the performance of 5 TikTok Termhal Accounts as the account with the most expensive endorsement fee. The method used for this research is quantitative exploratory method. The results of this study indicate that a content creator named Zachking gets the first rank and has good account performance credibility.