bluuebunny/crossref_metadata_2025 huggingface dataset:
THE VALUE OF SUCCESS CHARACTERS IN THE PREVENTION OF PSYCHOLOGICAL DISORDERS IN THE PANDEMIC TIME COVID-19 (Overview of the Al-Qur'an Surat Al-'Ashr)
Authors: Al Halik  , Sukma Sari Dewi Chan
Published: September 2021

Penyebaran virus corona yang semakin meningkat membuat virus baru ini menjadi perhatian utama masyarakat dunia, maka tidak heran di linimasa hingga dipemberitaan topik corona selalu ditemukan. Penerimaan informasi yang berlebihan mampu mempengaruhi kesehatan psikis dan fisik seseorang. Masyarakat yang tidak mampu memfilter informasi yang masuk bisa menjadi penyebab munculnya pikiran stress, kecemasan, ketakutan, serta kekhawatiran  yang  berlebihan, sehingga membawa perubahan psikologis pada kesehatan mental. Tujuan dari penelitian sebagai langkah pemikiran untuk mencegah terjadinya gangguan psikologis di masa pandemi dengan mengikuti nilai-nilai karakter sukses yang ada di QS. Al-Ashr. Penilitian dilakukan dengan pendekatan library research, mengikuti langkah yang sistematis mulai dari mengumpulkan, mengolah dan menyimpulkan data temuan. Nilai-nilai karakter sukses yang bisa ambil sebagai langkah pencegahaan gangguan psikologis dalam masa pandemi Covid-19 dari QS. Al-Ashr yaitu: meningkatkan keimanan, memperbanyak amal shaleh, nasehat menasehati pada kebenaran dan menasehati supaya sabar dengan kesabaran. Menginternalisasikan empat karakter ini, seseorang akan mendapatkan keuntungan besar dan terselamatkan dari kerugian seperti stress, kecemasan dan kekhawatiran yang tidak berkesudahan.
KONSEP LABORATORIUM BIMBINGAN DAN KONSELING SEBAGAI UPAYA MENYIAPKAN CALON KONSELOR PROFESIONAL
Authors: Alawiyah Desi , Mulkiyan
Published: September 2021

Artikel ini ini bertujuan untuk menawarkan konsep laboratorium bimbingan dan konseling sebagai salah satu gambaran terancangangnya laboratorium dalam mendukung dan mengembangkan potensi mahasiswa. Mahasiswa seharusnya tidak hanya memiliki ilmu konsep dan teoritis semata, melainkan mahasiswa juga harus mendapatkan soft skill. Pengembangan ilmu konsep dan teoritis bisa didapatkan melalui pembelajaran kelas, tetapi pengembangan soft skill mahasiswa didapatkan pada pembelajaran di laboratorium. Mahasiswa butuh mengembangankan soft sikll sebagai bentuk pencapaian pembelajaran dan pengembangan untuk membangun sikap professional. Dikarenakan keberadaan laboratorium sangat urgensi dalam mendidik dan memberikan skill bagi mahasiswa sebagai calon konselor. Sehingga dibutuhkan sebuah konsep laboratorium yang mendukung kebutuhan tersebut. Konsep Laboratorium yang ditawarkan berupa sistem layanan, ruangan laboratorium bimbingan dan konseling, instrumentasi, dan dokumentasi. Sehingga dengan adanya konsep laboratorium bimbingan dan konseling disetiap prodi BKI diharapkan kedepannya mahasiswa bisa mengenal kondisi di sekolah maupun masyarakat secara komprehensif. Tidak menghasilkan lulusan yang cenderung teoritis tetapi minim praktik dan tidak mampu berbuat banyak terhadap lingkungan sekitarnya.
Integration of IoT and Blockchain
Authors: Brohi Muhammad Nawaz
Published: September 2021

present, we are in the world of digital revolution. Use of smartphones and internet accelerated due to the impact of the novel Covid-19 virus. The whole world started to turn digital. The industrialization of Internet of Things (IoT) enables more devices to connect and communicate which leads to many data transfer transactions. The architecture of IoT is centralized. The distributed and decentralized architecture of Blockchain can be used to provide secure and scalable transactions of IoT devices. Blockchain is a distributed ledger technology, which provides secure data transactions that cannot be tampered and altered. In this paper, we provide advantages and challenges of integrating IoT and Blockchain. We also provide different architectures and algorithms proposed by researchers to provide secure data transactions.  We shall also shed light on the future research directions of integrating Blockchain and IoT.
Performance Evaluation of China Internet Monetary Fund Based on Super-efficient DEA
Authors: Huang Lingling , Zeng Qianling , Lin Fan , Deng Wenyan , Pan Wenchao
Published: September 2021

Since 2013, China’s Internet money fund market has entered a new era. On June 17, 2013, Yu’e Bao, jointly launched by Alipay and Tianhong Fund Company, was the first to go public. In just a few short years, the Internet money fund market has developed in full swing, and Tencent, Baidu, and JD have also participated in the development of related change wealth management businesses. This article uses super-efficiency DEA to evaluate fund performance. Through the validity test of 16 sample fund products in 2019, 7 sample funds are valid according to the DEA; and 16 sample fund products in 2020 are tested for validity, 9 sample funds are valid according to the DEA. The research found that most of the Internet financial products have not yet reached their effectiveness, which is mainly reflected in the fund’s custody and management fees. There is still a lot of room for development in China’s Internet fund market.
Effects of Resistance Training and Whole-Body Electromyostimulation on Muscular Strength in Female Collegiate Softball Players
Authors: Raja Hussain Raja Nurul Jannat , Shari Maisarah
Published: September 2021

Strength and conditioning coaches frequently use traditional resistance training (TRT) to build strength. However, in recent years, whole-body electromyostimulation (WB-EMS) was used in elite athletes to increase muscle strength. This study aimed to assess the effect of two different types of training on muscular strength. Sixty female collegiate players (Age = 23.52±1.89 years, Height = 156.20±1.71cm; Mass = 53.21±3.17kg) participated in this study and were randomly assigned to three training groups. All groups trained as usual for eight weeks, except for the first group, which received additional TRT. The second group received additional electrical stimulation training, and the third group did not receive any additional training following the regular softball bat swing training. Muscular strength (upper and lower body) was assessed by a 3RM bench press and a 3RM squat test before and after the eight-week programme. The primary findings indicate that after eight weeks of training, upper body and lower body strength increased significantly in both the TRT and WB-EMS groups (p = 0.000 and p = 0.000, respectively) in comparison to the control group. However, the t value indicated that the TRT group improved both upper body strength (20.18) and lower body strength (29.18) more than the WB-EMS group (upper body = 6.18; lower body = 6.47). The findings demonstrate the efficacy of both training modalities for increasing muscular strength and suggest that TRT be prioritised over whole-body electrical stimulation training for increasing muscular strength in collegiate softball players.
Bibliometric Analysis of Research on Peer Feedback in Teaching and Learning
Authors: Lam Catherine Nguoi Chui , Habil Hadina
Published: September 2021

A growing body of literature has highlighted the pivotal role of peer feedback in teaching and learning. However, a paucity of studies explore the trend of literature in this research area, particularly using a bibliometric approach. Therefore, this study was conducted to reveal the major trends in the research area and construct an intellectual landscape of the relevant studies in the field. Bibliometric details of a total of 276 research articles, published from 1985 to 2020 (August), were retrieved from the Scopus database for further analysis. In particular, the publication trend, the most productive countries, the most productive authors, the top ten source titles, and keyword used in the research area, were explored using bibliometric indicators. The rapid growth of publications on peer feedback was observed since 2010, with a sharp peak noted in 2019. Furthermore, writing context was found as the central focus of peer feedback research. Among others, three key themes that surfaced out of term-occurrence analysis included: impacts/effects of using peer feedback approach, sub-themes concerning peer feedback implementation, and peer feedback in writing context. Additionally, from the review of 30 top-cited publications, 3 prominent themes: effects of using peer feedback approach, effective or ineffective peer feedback, and potential challenges or issues in peer feedback implementation emerged. Based on the findings, this paper concludes with some recommended avenues for future research.
PENINGKATAN PENGGUNAAN TEKNOLOGI INFORMASI DALAM EDUKASI PEMASARAN DIGITAL PELAKU USAHA RUMAHAN
Authors: Muhammmad Abulwafa , Saputra Dhio
Published: September 2021

Pelaku usaha rumahan merupakan salah satu  bidang bisnis yang banyak berperan dalam menopang perekonomian di Indonesia. Pelaku usaha rumahan merupakan bagian dari  UMKM ( Usaha Mikro Kecil  Menegah) yang harus selalu mengikuti perubahan dan perkembangan yang ada. Salah satu perubahan dan perkembangan yang memiliki pengaruh besar dalam bidang pemasaran usaha rumamhan adalah Teknologi Informasi. Hal ini menjadi tantangan  bagi pelaku usaha rumahan untuk selalu belajar meningkatkan penggunaan teknologi informasi dengan pemasaran digital – media social ( wa, instagram, facebook), serta memahami konsep bisnis digital secara baik. Pemasaran digital menuntut pelaku usaha rumahan untuk memiliki skill foto produk  dan branding produk  yang baik. Adanya kegiatan pengabdian masayrakat yang memberikan pembelajaran tentang pemasaran digital dan pengingkatan penggunaan teknologi informasi mampu meningkatkan skill dan wawasan pelaku usaha rumahan untuk mantap berjuang dalam pemasaran digital.
SOME ASPECTS OF ANTI-CORRUPTION EDUCATION OF STUDENTS IN THE EDUCATIONAL PROCESS
Authors: Кириллов С.И. , Кривошеев С.В.
Published: September 2021

В настоящей статье рассматриваются вопросы антикоррупционного воспитания обучающихся в высших учебных заведениях. Определяются основные методы, направления антикоррупционного воспитания, предлагаются способы повышения эффективности обучения студентов правилам предупреждения и противодействия коррупции. Авторы доказывают, что результативность антикоррупционного воспитания будущих специалистов неразрывно связано с профессиональными компетенциями сотрудников соответствующих ведомств и зависит от множества факторов.

This article examines the issues of anti-corruption education of students in higher educational institutions. The main methods, directions of anticorruption education are determined, methods of increasing the effectiveness of teaching students the rules of preventing and combating corruption are proposed. The authors argue that the effectiveness of anti-corruption education of future specialists is inextricably linked with the professional competencies of employees of the relevant departments and depends on many factors.
OCORRÊNCIAS DE INUNDAÇÕES NO ESTADO DO PARANÁ E OS SISTEMAS DE MONITORAMENTO E ALERTA DE DESASTRES PARA O COMBATE DE EVENTOS EXREMOS / FLOOD OCCURRENCES IN THE STATE OF PARANÁ AND DISASTERS MONITORING AND ALERT SYSTEMS TO COMBAT EXTREME EVENTS
Authors: Ferentz Larissa Maria da Silva
Published: September 2021

O objetivo do presente artigo é analisar a incidência de inundações no estado do Paraná nos últimos 10 anos. Além disso, também se procura apresentar os sistemas de monitoramento e alerta de desastres brasileiros, utilizados no combate aos eventos extremos. Os dados das ocorrências foram coletados nos Sistemas da Coordenadoria Estadual de Proteção e Defesa Civil do Paraná, enquanto que a identificação dos alertas foi realizada por meio de pesquisa bibliográfica. Como principais resultados, foi possível observar que existem 98 registros de inundações no período em análise, sendo mais frequentes nos municípios de Querência do Norte, União da Vitória e Rio Negro. Nos últimos 10 anos, quase 200 mil pessoas já foram afetadas, e os prejuízos econômicos no estado já passam de 260 milhões de reais. Para auxiliar no monitoramento desses eventos, o Brasil possui alguns sistemas importantes, tais como o Sistema de Alerta de Cheias e os Sistema de Monitoramento de Movimentos de Massa e Processos Hidrológicos. Conclui-se que é necessário maiores investimentos para monitoramento e alerta das comunidades, a fim de minimizar os prejuízos econômicos, e principalmente, os danos materiais e humanos.
ANÁLISE FÍSICO-QUIMICO DO SOLO DA ÁREA DE CONTAMINAÇÃO DO ARROIO DOURADO, EM FOZ DO IGUAÇU
Authors: Oliveira Robson , Ramirez Kleber Gomes , Lauro Macarius Di
Published: September 2021

O estudo foi conduzido com o objetivo de analisar a qualidade do solo que se encontra na área do antigo lixão já desativado, conhecido como “Arroio Dourado”, localizado na região oeste do Paraná em Foz do Iguaçu. Com a desativação do lixão na década de 90, sem a devida recuperação da área degradada, e consequentemente com a expansão urbana na cidade, diversas famílias carentes estabeleceram residência nessa região, seja por falta de emprego ou moradia adequada. As condições da área do antigo lixão é motivo de diversas disputas judiciais entre moradores e poder público, sendo este estudo essencial para o esclarecimento das condições quanto à qualidade do solo na região. A pesquisa tomou como partida a problemática socioambiental e dos riscos a saúde humana, relacionados ao contato com metais pesados proveniente dos resíduos que estão depositados na área. O estudo concluiu que a análise de solo no antigo lixão apresentou concentrações de 10,83 mg.kg-1 de chumbo, 107 mg.kg-1 de cromo e 6,14 mg.kg-1 de níquel em amostra de solo composta, estes valores encontram-se acima da recomendação nacional conforme Resolução Conama nº 420/2009 e de outros parâmetros internacionais, definindo o local como um ambiente insalubre, que pode gerar consequências negativas a saúde humana e ao meio ambiente.
ASPECTOS SOCIOAMBIENTAIS EM BASE DE DADOS GEOGRÁFICOS PARA A GESTÃO PÚBLICA E AMBIENTAL NO ESTADO DO PARÁ
Authors: Aguiar Ponciana Freire de
Published: September 2021

A presente pesquisa é uma análise da Gestão Pública e Ambiental do estado do Pará por meio de tratamento de dados geográficos em meio geotecnológico, tendo como objetivo geral analisar os aspectos relacionados a atual gestão pública e ambiental do estado, bem como suas lacunas, avaliando a viabilidade da análise de indicadores, como os de dados secundários socioambientais do IBGE e do INPE, por meio de mapeamentos temáticos e análise qualitativa, comprovando a utilidade do uso de ferramentas e técnicas do geoprocessamento para apoio a tomada de decisões. A metodologia configurou-se na coleta e tratamento bibliográficos, cartográficos e documentais, tendo sido realizada a geração de mapas temáticos utilizando dados secundários destes órgãos em software SIG. A pesquisa apresenta resultados com uma análise apontando para a necessidade de atualização do uso de dados secundários em geotecnologias sobre aspectos socioambientais do estado do Pará, sendo fundamentais a atualização do diagnóstico e o macrozoneamento ecológico-econômico, como instrumento de gestão desatualizado desde 2012, para contribuir com uma gestão pública e ambiental apropriadas para o desenvolvimento sustentável do estado.
Superior Mesenteric Artery Thrombosis for Emergency Laparotomy in Covid-19 Patient: A Case Report
Authors: Hassan Asif , Desai Pushkar , Al Abady Ali , Baawain Saleh
Published: September 2021

The novel coronavirus disease 2019 (COVID-19) pandemic has caused significant morbidity and mortality worldwide. The most common symptoms include fever, cough, and shortness of breath (predominantly involving pulmonary function). However, there are lesser-known presentations that affect other systems too. Vascular complications have been reported in the literature focusing on venous thrombosis, which appears to be more common than arterial thrombosis. Among arterial thrombosis, mainly lower limb involvement is reported so far. Here, we report an unusual presentation in COVID-19, which presented with acute abdomen due to superior mesenteric artery thrombosis without respiratory symptoms. We report this case as a varied form of coronavirus complication presentation and highlight the need for eternal vigilance and a reactive approach for early diagnosis.
The effect of destructive leadership on self-efficacy and counterproductive work behaviors: A research on service sector employees in Mersin, Turkey
Authors: Aydinay Murat , Cakici Aysehan , Cakici A. Celil
Published: September 2021

The aim of this study was to find out the effect of destructive leadership on employees’ self-efficacy and counterproductive work behaviors. The data was collected from a convenience sample of 486 service sector employees in Mersin, Turkey. Descriptive statistics, explanatory factor analysis, and regression analysis were conducted to analyze the data. The results showed that lack of competence in leadership, excessive authoritarianism, and favoritism dimensions increased the organization-oriented counterproductive work behaviors while resistance to technology and change dimension decreased these behaviors. In contrast, insensitivity to subordinates had no effect on counterproductive work behaviors. Furthermore, destructive leadership had no effect on employees’ self-efficacy, but self-efficacy affected counterproductive work behaviors. This study provides theoretical and practical implications for understanding the effect of destructive leadership behaviors on the employees’ self-efficacy and counterproductive work behaviors in the context of the service sector.
EDUCAÇÃO E TECNOLOGIA: ELEMENTOS CRUCIAIS PARA O DESENVOLVIMENTO SUSTENTÁVEL NO SÉCULO XXI
Authors: Filho Isac Sales Pinheiro
Published: September 2021

Introdução: A sustentabilidade é um vocábulo utilizado para designar assuntos pertinentes aos recursos naturais, assim como a exploração e preservação dos espaços ambientais de maneira consciente. Vale ressaltar também nesse caso, que o desenvolvimento sustentável é um conceito incontestável e indissociável ao proposto na discussão e que somente através da educação e do apoio dado pelos inúmeros aparatos tecnológicos disponíveis na atualidade é que o ser humano alcançará melhores posicionamentos frente aos desafios socioambientais contemporâneos. Objetivo: Conscientizar os indivíduos na mudança de pensamento e comportamento através da educação e dos arranjos tecnológicos disponíveis, alcançando profundas reflexões de maneira criativa, autônoma e inovadora, adquirindo assim, resultados significantes em prol de um ambiente ecologicamente sustentável. Material e Métodos: O trabalho foi elaborado através de pesquisa bibliográfica, elencando profissionais da área em questão, otimizando os argumentos em benefício coletivo de todos os interessados nessa temática , tais autores podem ser citados: Azevedo (2018), Freitas (2016), Loures (2009), Nascimento(2007) e Setubal(2015), perfazendo-se assim como essenciais para a concretude do trabalho. Resultados: Diante dos argumentos apresentados nesse resumo, comprovou-se que a abordagem é significante acerca das perspectivas ambiental, econômica e social, reconhecendo o papel preponderante da educação e da tecnologia como mediadores da relação homem e natureza, visando resgatar valores intrínsecos na busca por soluções eficientes. Com isso, esse documento acadêmico torna-se um veículo promotor de novas discussões ambientais. Conclusão: A relação entre o meio ambiente, educação e tecnologia, assumem um papel cada vez mais desafiador, cabendo nesse sentido a cada indivíduo manter o compromisso real e interdependente entre os fatores de maior relevância já destacados, impulsionando para a construção de uma sociedade ambientalmente sustentável.
The Struggle Of Women Against Oppression – A Study Of Nadia Hashimi’s The Pearl That Broke Its Shell
Authors: Monish V Jibin , Kannadhasan Dr M.
Published: September 2021

Feminism is a liberation ideology for women since it is premised on the idea that women are treated unfairly because of their sexual identity. Feminism examines the factors that contribute to female oppression. Women’s oppression in Afghanistan is described in this report. The system of masculine oppression of women is termed as patriarchy. Patriarchy is the oppressive structure, according to this understanding. Patriarchy is a phrase that refers to a societal structure and practises in which men dominate, oppress, and exploit women. As a political framework, patriarchy tries to dominate and oppress women, limiting their ability to make decisions about their sexuality, childrearing, mothering, loving, and labouring. This research examines the subjugation of women in Afghanistan during the Taliban regime. Through this study, we can sense the struggle of women in facing the society and to live the day today life.
Internet of Things: A Review of Functionality, Applications, Architectures and Challenges
Authors:   Post Graduate Department of Computer Science, University of Kashmir, Hazratbal., Zahoor Saniya , A.Sofi Shabir ,   Department of Information Technology, National Institute of Technology Srinagar.
Published: September 2021

The Internet of Things (IoT) is an emerging paradigm that embodies the vision of merging smart objects while utilizing the internet as the backbone of the communication system to establish a smart interaction among physical entities in pervasive environments. In IoT, data is generated in realtime and stored in permanent repositories. Additional data in the form of meta-data that describes things adds to the data volume and to manage this data, architecture is required. IoT finds its applicability in a plethora of applications such as transportation, smart city, smart health, smart environment, home entertainment, sports, etc. but there is no universal architecture for all IoT implementations. We have layered architectures and domain-specific architectures for different IoT applications. Besides a large number of architectures for IoT, it faces several potential challenges such as scalability, reliability, heterogeneity, etc. This paper presents an understanding of the Internet of Things in terms of its functionality, layered and domain-specific architectures, and its potential challenges.
A Deep Learning based Approach to Argument Recommendation
Authors: Li Guangjie , Tang Yi , Yi Biyi , Zhang Xiang , He Yan
Published: September 2021

Code completion is one of the most useful features provided by advanced IDEs and is widely used by software developers. However, as a kind of code completion, recommending arguments for method calls is less used. Most of existing argument recommendation approaches provide a long list of syntactically correct candidate arguments, which is difficult for software engineers to select the correct arguments from the long list. To this end, we propose a deep learning based approach to recommending arguments instantly when programmers type in method names they intend to invoke. First, we extract context information from a large corpus of opensource applications. Second, we preprocess the extracted dataset, which involves natural language processing and data embedding. Third, we feed the preprocessed dataset to a specially designed convolutional neural network to rank and recommend actual arguments. With the resulting CNN model trained with sample applications, we can sort the candidate arguments in a reasonable order and recommend the first one as the correct argument. We evaluate the proposed approach on 100 open-source Java applications. Results suggest that the proposed approach outperforms the state-of-theart approaches in recommending arguments.
Sentiment Analysis of Covid-19 Vaccine Responses in Mexico
Authors: Salinas Jessica , Flores Carlos , Ceballos Hector , Cantu Francisco
Published: September 2021

The amount of information that social networks can shed on a certain topic is exponential compared to conventional methods. As new COVID-19 vaccines are approved by COFEPRIS in Mexico, society is acting differently by showing approval or rejection of some of these vaccines on social networks. Data analytics has opened the possibility to process, explore, and analyze a large amount of information that comes from social networks and evaluate people's sentiments towards a specific topic. In this analysis, we present a Sentiment Analysis of tweets related to COVID-19 vaccines in Mexico. The study involves the exploration of Twitter data to evaluate if there are preferences between the different vaccines available in Mexico and what patterns and behaviors can be observed in the community based on their reactions and opinions. This research will help to provide a first understanding of people's opinions about the available vaccines and how these opinions are built to identify and avoid possible misinformation sources.
A Multi-Input Multi-Output Transformer-Based Hybrid Neural Network for Multi-Class Privacy Disclosure Detection
Authors: Mehdy A K M Nuhil , Mehrpouyan Hoda
Published: September 2021

The concern regarding users’ data privacy has risen to its highest level due to the massive increase in communication platforms, social networking sites, and greater users’ participation in online public discourse. An increasing number of people exchange private information via emails, text messages, and social media without being aware of the risks and implications. Researchers in the field of Natural Language Processing (NLP) have concentrated on creating tools and strategies to identify, categorize, and sanitize private information in text data since a substantial amount of data is exchanged in textual form. However, most of the detection methods solely rely on the existence of pre-identified keywords in the text and disregard the inference of underlying meaning of the utterance in a specific context. Hence, in some situations these tools and algorithms fail to detect disclosure, or the produced results are miss classified. In this paper, we propose a multi-input, multi-output hybrid neural network which utilizes transfer-learning, linguistics, and metadata to learn the hidden patterns. Our goal is to better classify disclosure/non-disclosure content in terms of the context of situation. We trained and evaluated our model on a human-annotated ground truth dataset, containing a total of 5,400 tweets. The results show that the proposed model was able to identify privacy disclosure through tweets with an accuracy of 77.4% while classifying the information type of those tweets with an impressive accuracy of 99%, by jointly learning for two separate tasks.
A Self-Supervised Tibetan-Chinese Vocabulary Alignment Method based on Adversarial Learning
Authors: Hou Enshuai , zhu Jie
Published: September 2021

Tibetan is a low-resource language. In order to alleviate the shortage of parallel corpus between Tibetan and Chinese, this paper uses two monolingual corpora and a small number of seed dictionaries to learn the semi-supervised method with seed dictionaries and self-supervised adversarial training method through the similarity calculation of word clusters in different embedded spaces and puts forward an improved self-supervised adversarial learning method of Tibetan and Chinese monolingual data alignment only. The experimental results are as follows. First, the experimental results of Tibetan syllables Chinese characters are not good, which reflects the weak semantic correlation between Tibetan syllables and Chinese characters; second, the seed dictionary of semi-supervised method made before 10 predicted word accuracy of 66.5 (Tibetan - Chinese) and 74.8 (Chinese - Tibetan) results, to improve the self-supervision methods in both language directions have reached 53.5 accuracy.
Artificial Intelligence & Machine Learning Role in Financial Services
Authors: Parne Prudhvi
Published: September 2021

Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector.
Open Lorawan Sensor Node Architecture for Agriculture Applications
Authors: Bolte Philipp , Witkowski Ulf , Morgenstern Rolf
Published: September 2021

In agriculture, it becomes more and more important to have detailed data, e.g. about weather and soil quality, not only in large scale classic crop farming applications but also for urban agriculture. This paper proposes a modular wireless sensor node that can be used in a centralized data acquisition scenario. A centralized approach, in this case multiple sensor nodes and a single gateway or a set of gateways, can be easily installed even without local infrastructure as mains supply. The sensor node integrates a LoRaWAN radio module that allows long-range wireless data transmission and low-power battery operation for several months at reasonable module costs. The developed wireless sensor node is an open system with focus on easy adaption to new sensors and applications. The proposed system is evaluated in terms of transmission range, battery runtime and sensor data accuracy.
Minimization of the delay time and its spread in a compact vacuum breaker
Authors: Davydov Sergei , Dolgov Alexander , Kozlov Alexander , Yakubov Rustam
Published: September 2021

The similarity of the switching mechanisms of compact vacuum spark breakers and spark breakers with laser ignition is established at a comparable level of energy flux density in the ignition node–ionization of the residual gas by a stream of short-wave radiation and fast electrons from the cathode spot plasma or laser plasma. This mechanism allows you to effectively

reduce the delay in triggering the spark gap by increasing the ignition energy. An experimental study of the advantages of using an ignition circuit with increased energy for controlling

small-sized vacuum spark breakers is carried out. There is a steady decrease in the delay time of the spark gap and an increase in the level of delay stability. From the point of view of minimization and stability of the delay time of the spark gap, the energy investment in the formation of the initiating plasma occurs most effectively at the spark stage of the auxiliary discharge along the surface of the dielectric in the ignition node.
The concept of a grid-based instrument for measuring micrometeoroid parameters
Authors: Voronov Konstantin , Telegin Alekcey , Ryazanov Dmitriy
Published: September 2021

The article describes the design of a grid-based device for measuring the parameters of charged microparticles (micrometeoroids). The main attention is paid to the issues of calculating the errors in measuring the charge, mass and velocity of such microparticles. A 3D model of the device was developed and calculated ratios were carried out to calculate the arameters of charged microparticles.
Investigating the application of Static Synchronous Compensator (STATCOM) for mitigating power transmission line losses
Authors:   , Aduragba Adebiyi Abayomi
Published: September 2021

Voltage instability and increased power loss on transmission lines are major challenges in power transmission due to ever increasing load growth. This work investigates the effect of Static Synchronous Compensator (STATCOM) to mitigate power losses and enhance the voltage stability of a transmission system. STATCOM, a shunt-connected power electronic device, operate as a Voltage Source Converter (VSC) to improve power transfer capacity of transmission lines by injecting a set of three-phase balanced sinusoidal current with controllable magnitude and phase angle into the transmission lines to regulate the line voltage and compensate for reactive power at the Point of Common Coupling (PCC). To validate the capacity of STATCOM in this light, a modified model of IEEE 14 bus test system was simulated using DIgSILENT PowerFactory v15. Four different load profiles were included by increasing the base load in a step of 10%. In each case, power flow was run with and without STATCOM incorporated in the network with a view to determine the impact of STATCOM on bus voltage and transmission line losses. The simulation results are obtained were recorded and analyzed. It is noted that there was sufficient improvement in the new voltage profile obtained for the weak buses of the system, the active and reactive power losses were mitigated by 17.73% and 24.80% respectively when STATCOM was incorporated at normal load. The results showed that STATCOM could give quick voltage support to reduce the likelihood of voltage collapse and mitigate power losses along the transmission lines. Reduction of reactive power losses along the lines is higher than the active power losses resulting in the improvement of the voltage profile as the device is connected to the system.
Optimization of irrigation water in South Africa for sustainable and beneficial use
Authors:   , Ikudayisi Akinola Mayowa
Published: September 2021

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.
Ground-based Investigation of HOx and Ozone Chemistry in Biomass Burning Plumes in Rural Idaho
Authors: Lindsay Andrew J. , Anderson Daniel C. , Wernis Rebecca A. , Liang Yutong , Goldstein Allen H. , Herndon Scott C. , Roscioli Joseph R. , Dyroff Christoph , Fortner Ed C. , Croteau Philip L. , Majluf Francesca , Krechmer Jordan E. , Yacovitch Tara I. , Knighton Walter B. , Wood Ezra C.
Published: September 2021

Abstract. Ozone (O3), a potent greenhouse gas that is detrimental to human health, is typically found in elevated concentrations within biomass burning (BB) smoke plumes. The radical species OH, HO2, and RO2 (known collectively as ROx) have central roles in the formation of secondary pollutants including O3 but are poorly characterized for BB plumes. We present measurements of total peroxy radical concentrations ([XO2] ≡ [HO2] + [RO2]) and additional trace-gas and particulate matter measurements from McCall, Idaho during August 2018. There were five distinct periods in which BB smoke impacted this site. During BB events, O3 concentrations were enhanced as evidenced by ozone enhancement ratios (ΔO3/ ΔCO) that ranged up to 0.25 ppbv ppbv−1. [XO2] was similarly elevated during some BB events. Overall, quantified instantaneous ozone production rates (P(O3)) were only slightly impacted by the presence of smoke as NOx enhancements were minimal. Measured XO2 concentrations were compared to zero-dimensional box modeling results to evaluate the effectiveness of the Master Chemical Mechanism (MCM) and GEOS-Chem mechanisms during periods of BB influence and overall agreed within 31 %. One period of BB influence had distinct measured enhancements of 15 pptv XO2 that were not reflected in the model output, likely due to the presence of an unmeasured HOx source, quite likely nitrous acid (HONO). To our knowledge, this is the first BB study featuring peroxy radical measurements.
The outflow of Asian biomass burning carbonaceous aerosol into the upper troposphere and lower stratosphere in spring: radiative effects seen in a global model
Authors: Chavan Prashant , Fadnavis Suvarna , Chakroborty Tanusri , Sioris Christopher E. , Griessbach Sabine , Müller Rolf
Published: September 2021

Abstract. Biomass burning (BB) over Asia is a strong source of carbonaceous aerosols during spring. From ECHAM6–HAMMOZ model simulations and satellite
observations, we show that there is an outflow of Asian BB carbonaceous
aerosols into the upper troposphere and lower stratosphere (UTLS) (black carbon: 0.1 to 6 ng m−3 and organic carbon: 0.2 to 10 ng m−3)
during the spring season. The model simulations show that the greatest
transport of BB carbonaceous aerosols into the UTLS occurs from the
Indochina and East Asia region by deep convection over the Malay Peninsula and Indonesia. The increase in BB carbonaceous aerosols enhances atmospheric
heating by 0.001 to 0.02 K d−1 in the UTLS. The aerosol-induced heating
and circulation changes increase the water vapor mixing ratios in the upper troposphere (by 20–80 ppmv) and in the lowermost stratosphere (by 0.02–0.3 ppmv) over the tropics. Once in the lower stratosphere, water vapor is
further transported to the South Pole by the lowermost branch of the
Brewer–Dobson circulation. These aerosols enhance the in-atmosphere radiative forcing (0.68±0.25 to 5.30±0.37 W m−2), exacerbating atmospheric warming, but produce a cooling effect on climate (top of the
atmosphere – TOA: -2.38±0.12 to -7.08±0.72 W m−2). The model simulations also show that Asian carbonaceous aerosols are
transported to the Arctic in the troposphere. The maximum enhancement in
aerosol extinction is seen at 400 hPa (by 0.0093 km−1) and associated
heating rates at 300 hPa (by 0.032 K d−1) in the Arctic.
Evaluating consistency between total column CO2 retrievals from OCO-2 and the in situ network over North America: implications for carbon flux estimation
Authors: Rastogi Bharat , Miller John B. , Trudeau Micheal , Andrews Arlyn E. , Hu Lei , Mountain Marikate , Nehrkorn Thomas , Baier Bianca , McKain Kathryn , Mund John , Guan Kaiyu , Alden Caroline B.
Published: September 2021

Abstract. Feedbacks between the climate system and the carbon cycle represent a key source of uncertainty in model projections of Earth's climate, in part due to our inability to directly measure large-scale biosphere–atmosphere carbon fluxes. In situ measurements of the CO2 mole fraction from surface flasks, towers, and aircraft are used in inverse models to infer fluxes, but measurement networks remain sparse, with limited or no coverage over large parts of the planet. Satellite retrievals of total column CO2 (XCO2), such as those from NASA's Orbiting Carbon Observatory-2 (OCO-2), can potentially provide unprecedented global information about CO2 spatiotemporal variability. However, for use in inverse modeling, data need to be extremely stable, highly precise, and unbiased to distinguish abundance changes emanating from surface fluxes from those associated with variability in weather. Systematic errors in XCO2 have been identified and, while bias correction algorithms are applied globally, inconsistencies persist at regional and smaller scales that may complicate or confound flux estimation. To evaluate XCO2 retrievals and assess potential biases, we compare OCO-2 v10 retrievals with in situ data-constrained XCO2 simulations over North America estimated using surface fluxes and boundary conditions optimized with observations that are rigorously calibrated relative to the World Meteorological Organization X2007 CO2 scale. Systematic errors in simulated atmospheric transport are independently evaluated using unassimilated aircraft and AirCore profiles. We find that the global OCO-2 v10 bias correction shifts the distribution of retrievals closer to the simulated XCO2, as intended. Comparisons between bias-corrected and simulated XCO2 reveal differences that vary seasonally. Importantly, the difference between simulations and retrievals is of the same magnitude as the imprint of recent surface flux in the total column. This work demonstrates that systematic errors in OCO-2 v10 retrievals of XCO2 over land can be large enough to confound reliable surface flux estimation and that further improvements in retrieval and bias correction techniques are essential. Finally, we show that independent observations, especially vertical profile data, such as those from the National Oceanic and Atmospheric Administration aircraft and AirCore programs are critical for evaluating errors in both satellite retrievals and carbon cycle models.
ALADIN laser frequency stability and its impact on the Aeolus wind error
Authors: Lux Oliver , Lemmerz Christian , Weiler Fabian , Kanitz Thomas , Wernham Denny , Rodrigues Gonçalo , Hyslop Andrew , Lecrenier Olivier , McGoldrick Phil , Fabre Frédéric , Bravetti Paolo , Parrinello Tommaso , Reitebuch Oliver
Published: September 2021

Abstract. The acquisition of atmospheric wind profiles on a global
scale was realized by the launch of the Aeolus satellite, carrying the
unique Atmospheric LAser Doppler INstrument (ALADIN), the first Doppler wind lidar in space. One major component of ALADIN is its high-power, ultraviolet
(UV) laser transmitter, which is based on an injection-seeded,
frequency-tripled Nd:YAG laser and fulfills a set of demanding requirements
in terms of pulse energy, pulse length, repetition rate, and spatial
and spectral beam properties. In particular, the frequency stability of the
laser emission is an essential parameter which determines the performance of
the lidar instrument as the Doppler frequency shifts to be detected are on
the order of 108 smaller than the frequency of the emitted UV light.
This article reports the assessment of the ALADIN laser frequency stability
and its influence on the quality of the Aeolus wind data. Excellent
frequency stability with pulse-to-pulse variations of about 10 MHz (root
mean square) is evident for over more than 2 years of operations in space
despite the permanent occurrence of short periods with significantly
enhanced frequency noise (> 30 MHz). The latter were found to
coincide with specific rotation speeds of the satellite's reaction wheels,
suggesting that the root cause are micro-vibrations that deteriorate the
laser stability on timescales of a few tens of seconds. Analysis of the
Aeolus wind error with respect to European
Centre for Medium-Range Weather Forecasts (ECMWF) model winds shows that the
temporally degraded frequency stability of the ALADIN laser transmitter has
only a minor influence on the wind data quality on a global scale, which is
primarily due to the small percentage of wind measurements for which the
frequency fluctuations are considerably enhanced. Hence, although the Mie
wind bias is increased by 0.3 m s−1 at times when the
frequency stability is worse than 20 MHz, the small contribution of 4 %
from all Mie wind results renders this effect insignificant
(< 0.1 m s−1) when all winds are considered. The impact on the
Rayleigh wind bias is negligible even at high frequency noise. Similar
results are demonstrated for the apparent speed of the ground returns that
are measured with the Mie and Rayleigh channel of the ALADIN receiver. Here, the application of a frequency stability threshold that filters out wind observations with variations larger than 20 or 10 MHz improves the accuracy of the Mie and Rayleigh ground velocities by only 0.05
and 0.10 m s−1, respectively, however at the expense of
useful ground data.
Toward hyper-resolution global hydrological models including human activities: application to Kyushu Island, Japan
Authors: Hanasaki Naota , Matsuda Hikari , Fujiwara Masashi , Hirabayashi Yukiko , Seto Shinta , Kanae Shinjiro , Oki Taikan
Published: September 2021

Abstract. Global hydrological models that include human activities are powerful tools for assessing water availability and use at global and continental scales. Such models are typically applied at a spatial resolution of 30 arcminutes (approximately 50 km). In recent years, some 5-arcminute (9-km) applications have been reported, but with numerous technical challenges, including the validation of calculations for more than a million grid cells and the conversion of simulation results into meaningful information relevant to water resource management. Here, the H08 global water resources model was applied in two ways to Kyushu Island in Japan at resolution of 1 arcminute (2 km), and the detailed results were compared. One method involved feeding interpolated global meteorological and geographic data into the default global model (GLB; in accordance with previous high-resolution applications). For the other method, locally derived boundary conditions were input to the localized model (LOC; this method can be easily extended and applied to other regions, at least across Japan). The results showed that GLB cannot easily reproduce the historical record, especially for variables related to human activities (e.g., dam operation and water withdrawal). LOC is capable of estimating natural and human water balance components at daily time scales and providing reliable information for regional water resource assessment. The results highlight the importance of improving data preparation and modeling methods to represent water management and use in hyper-resolution global hydrology simulations.