bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of job satisfaction among clinical research coordinators
Authors: Qi Linyan , Fu Qibo , Li Wenchang , Wu Jiheng , Li Ji , Ni Shaoqing
Published: June 2024

BACKGROUND: While CRCs play a crucial role in clinical trials, their job satisfaction has not received enough attention. OBJECTIVE: To assess the job satisfaction of CRCs and to explore the relevant factors. METHODS: The survey was programmed into an online questionnaire platform and distributed to CRCs in China for self-evaluation. The Minnesota Satisfaction Questionnaire (MSQ) was used to assess job satisfaction, and data on demographic characteristics, working situations, burnout and social support also were collected to identify factors associated with job satisfaction. Data analysis was performed using the R software program. Factors associated with job satisfaction were explored using ordinal logistic regression models. RESULTS: 2,840 participants were included in this survey, and the mean value of overall job satisfaction was characterized as “moderate to not fully satisfied”. Additionally, both burnout and overall social support were reported at moderate levels. Ordinal logistic regression analysis revealed that age, monthly income, sleep duration per day, weekly working time, a fixed workplace, subjective support, utilization of support, emotional exhaustion, depersonalization and reduced personal accomplishment were significantly associated with all types of job satisfaction (p <  0.05). Among all the factors, a fixed workplace was more strongly associated with job satisfaction than the other factors (OR = 0.596, p <  0.001). CONCLUSIONS: Implementing the fixed-point CRC mode to promote the provision of a fixed workplace, improving the CRC career development path, increasing income, subjective support and utilization of support, reducing weekly working time, job burnout will help to predict job satisfaction in CRCs.
Writing Errors: A Study of Students Linguistic Errors in Insya Muwajjah Learning
Authors: Aflisia Noza , Kasmantoni  , Yanti Yunika Febri
Published: June 2024

This research aims to analyze students' linguistic errors when learning insya muwajjah. This research is a case study of students from the Arabic Education Study Program at IAIN Curup using a qualitative approach. The primary data source comes from 11 fourth-semester students and Insya Muwajjah, the subject lecturer. Meanwhile, secondary data comes from student essays in the Insya Muwajjah subject. Apart from that, it also uses books and articles from scientific journals. Data collection instruments are interviews, surveys, and documentation. Data analysis methods include condensation, display, and conclusion drawing/verification. The research results show that students' linguistic errors in Insya Muwajjah learning include four errors. First, phonetics, namely, students cannot differentiate between letters that have similar sounds. Second, morphological, namely, students do not understand word changes. Third, syntax, namely, students' lack of grammar understanding, so there are still many errors in the final lines of words. Fourth, semantics: many students still use inappropriate words in sentences.
Функціональний стан плавців високої кваліфікації за умов диференційованої спортивної підготовки
Authors: Михалюк Євген , Гороховський Єгор
Published: June 2024

Резюме. Вивчено питання пошуку нових шляхів оптимізації тренувального процесу плавців високої кваліфікації. Мета. Аналіз впливу тренувальних навантажень на функціональний стан висококваліфікованих плавців залежно від методики тренувань. Методи. Для оцінки вегетативної регуляції серцевої діяльності використовували часовий та спектральний методи аналізу варіабельності серцевого ритму (ВСР), центральну гемодинаміку (ЦГ) вивчали методом автоматизованої тетраполярної реографії за В. Кубічеком у модифікації Ю. Т. Пушкаря, фізичну роботоздатність вимірювали за загальноприйнятою методикою на стаціонарному велоергометрі (Corival, Lode, Нідерланди) з використанням субмаксимального тесту PWC170 з подальшим розрахунком відносного значення фізичної роботоздатності (PWC170/кг). Результати. Виявлено достовірне зниження PWC170/кг у сучасних плавців-спринтерів кваліфікації КМС (як жінок, так і чоловіків), та чоловіків-плавців рівня МС-МСМК. Різниця в показниках ВСР та центральної гемодинаміки була статистично незначущою. Встановлено достовірне зниження функціонального стану сучасних плавців-спринтерів обох статей на фоні більш раннього досягнення нормативів кандидата у майстри спорту, майстра спорту та майстра спорту міжнародного класу, ніж їхні ровесники у 2006 р. Однією з можливих причин зниження функціонального стану плавцівпринтерів високого класу обох статей може бути зміна сучасної методики тренувального процесу, яка орієнтована на зменшення тренувальної роботи в зоні розвитку загальної витривалості (аеробної спрямованості) на користь збільшення роботи швидкісно-силової (анаеробної) спрямованості.
Ключові слова: плавці обох статей, варіабельність серцевого ритму, центральна гемодинаміка, фізична роботоздатність.
PENGEMBANGAN KURIKULUM BERBASIS MUATAN LOKAL DAN IMPLEMENTASINYA DI SMPN 4 DAN MTS MANGKU ALAM KONGBENG
Authors: Utami Auliya
Published: June 2024

Penelitian ini fokus pada pembahasan mengenai pengembangan kurikulum berbasis muatan lokal dan bagaimana perencanaan, pelaksanaan dan evaluasi pengembangan kurikulum berbasis muatan lokal di SMPN 4 Kongbeng dan di MTs Mangku Alam Kongbeng. Penelitian ini menggunakan metode kualitatif dan analisis diskriptif. Hasil penelitian ini menunjukkan bahwa perencanaan pengembangan kurikulum di SMPN 4 dan MTs Mangku Alam Kongbeng diimplementasikan dengan mengidentifikasi kondisi dan kebutuhan daerah, menentukan peran dan komposisi muatan lokal, mengidentifikasi bahan kajian muatan local, menentukan topik atau mata pelajaran muatan lokal, kemudian mengembangkan standar kompetensi, kompetensi dasar serta silabus dan RPP. Adapun pelaksanaan pengembangan kurikulumnya diimplementasikan dengan membuat program muatan lokal BTQ dan praktek agraris. Kemudian, pengembangan kurikulum tersebut dievaluasi dengan model Formative evaluation dan model Summative evaluation.
Avaliação pré-clínica da interferência do chá de Conocarpus erectus L. (Combretaceae) sobre o perfil hematológico e bioquímico de rotina
Authors: Paz Allane Patricia Santos da , Santos Gisely Santiago , Vale Michael Eduardo Melo do , Galvão Izabela Nascimento , Silva Lara Gabriele Silva da , Negrão Tamara Ingrid dos Santos , Hamoy Moises , Mello Vanessa Jóia de , Madeira Lucimar Di Paula dos Santos
Published: June 2024

The Conocarpus erectus L, known as “button mangrove”, is a plant with great ethnopharmacological applicability in diabetes, gastric ulcer, and diarrhea, widely used as a single treatment, or associated with allopathy. Using a preclinical model, the present work evaluated possible alterations in the hematological and biochemical tests of Wistar rats after consumption of lyophilized C. erectus L. tea for 40 days, at the dose traditionally used for digestive disorders. Exposure in repeated doses could not promote significant changes in body mass and routine hematological/biochemical parameters evaluated. Studies with these characteristics promote a greater understanding of the use of traditional medicine, the possible interactions on diagnostic laboratory parameters, and the impact on patient follow-up.
Can Thanksgiving Destinations Predict Climate Migration Patterns?
Authors: Han Chaeyeon , Hwang Uijeong , Guhathakurta Subhrajit
Published: June 2024

This research explores the relationship between climate-induced migration destination choice and social ties in the US, using anonymized smartphone data from SafeGraph. It shows that Thanksgiving travel patterns correlate with relocations following Hurricanes Harvey, Irma, and Maria. Findings reveal a statistically significant positive correlation, suggesting that states with a greater change in visitors during Thanksgiving week compared to regular week are likelier destinations for post-disaster relocation, emphasizing social ties’ crucial role in such decisions. This research highlights the need for urban planning and emergency management to consider the spatial distribution of social networks, which could inform evacuation strategies and disaster recovery policies.
Preserving Eco-processed Films in Canada
Authors: Lee Helen
Published: June 2024

Eco-processing is a method of filmmaking that incorporates organic material into the photochemical filmmaking process. This method is taken up in experimental filmmaking to engage with the materiality of the film and has a history of being used as a means of making an artistic commentary on the degradation of the environment. Eco-processing presents various challenges to preservation due to its unconventional approach to standard photochemical filmmaking. Additionally, in the Canadian context these challenges are exacerbated by there being no evident repository to collect and preserve independent, experimental films. The impetus to address the lack of infrastructure for preserving eco-processed films in Canada lies in these films' artistic and historical documentation of our geological age. By examining the information sharing networks within which experimental processes such as eco-processing flourish and archival models that emphasize living, active approaches to filmmaking, this MRP aims to demonstrate the possibilities of questioning standardization and prioritizing practitioner perspectives in film preservation.
Temporal Climatic Shifts in Henan Province: A 16-decades Perspective Through Regression, SARIMA, and NAR Modeling
Authors: Lin Qing , Ang Ling Weay , Shao Yiyang , Palaniappan Sellappan
Published: June 2024

Global warming is having a significant impact on all aspects of human production and life. This study employs a cross-sectional analysis to investigate the temporal dynamics of average temperature changes in Henan Province, China, from 1851 to 2012. Utilizing the Berkeley Earth Surface Temperature Data and the Daily Meteorological Dataset of China National Surface Weather Station v3.0, we applied regression analysis, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Nonlinear Autoregressive Network (NAR) models to predict temperature trends. Results indicate a significant warming trend over the 160-year period, with the models demonstrating strong predictive performance, albeit with some variability. The study underscores the increasing temperatures' implications for the province's agricultural sustainability and ecological balance. This study highlights the urgency of understanding and mitigating climate change's impacts, particularly in Henan Province, China, for the sake of agricultural sustainability, water resources, and public health. The research findings contribute valuable insights and methodologies to climate data analysis, aiding future predictions and policy-making efforts.
Wix for Web Development and the Application of the Waterfall Model and Project Based Learning for Project Completion: A Case Study
Authors: Madiah Mawar , Ng Kai Xuen , Tan Yew Wen , Tan Zhi Heng , Chong Zhi Tian , Chan Jia Xuan
Published: June 2024

Website development without prior knowledge of HTML or programming experience would be a significant challenge. This study aims to share the students' experiences developing a website using Wix, a user-friendly website builder. The website was assigned as a project-based assessment of one of the courses required to complete a Foundation programme. The course was delivered using a project-based learning (PBL) approach in this context. The students worked as a group to write a project proposal, plan activities, develop the website, write reports, and present the outcome. As for the website development process, the study demonstrates the completion of the project using the Waterfall model, a sequential approach to the software development lifecycle (SDLC). In summary, this study aims to explore the use of Wix for web development, the PBL approach for course delivery, and the Waterfall model for completing the website project. The result shows that the students could complete the website development project in a timely manner by using Wix as their web design platform and adopting the Waterfall model as their project management approach. In addition, the students also benefitted from the PBL approach. The outcomes of this study will be of great benefit to educators, particularly in their role in helping students complete their website development projects.
Knowledge-based Word Tokenization System for Urdu
Authors: Khan Asif , Khan Khairullah , Khan Wahab , Khan Sadiq Nawaz , Haq Rafiul
Published: June 2024

Word tokenization, a foundational step in natural language processing (NLP), is critical for tasks like part-of-speech tagging, named entity recognition, and parsing, as well as various independent NLP applications. In our tech-driven era, the exponential growth of textual data on the World Wide Web demands sophisticated tools for effective processing. Urdu, spoken widely across the globe, is experiencing a surge in, presents unique challenges due to its distinct writing style, the absence of capitalization features, and the prevalence of compound words. This study introduces a novel knowledge-based word tokenization system tailored for Urdu. Central to this system is a maximum matching model with forward and reverse variants, setting it apart from conventional approaches. The novelty of our system lies in its holistic approach, integrating knowledge-based techniques, dual-variant maximum matching, and heightened adaptability to low-resource language speakers, emphasizing the urgent need for advanced Urdu Language Processing (ULP) systems. However, Urdu, labeled as a low-resource language challenges compared to traditional machine learning (ML) approaches. Significantly, our system eliminates the need for a features file and pre-labelled datasets, streamlining the tokenization process. To evaluate the proposed model's efficacy, a comprehensive analysis was conducted on a dataset comprising 100 sentences with 5,000 Urdu words, yielding an impressive accuracy of 97%. This research makes a substantial contribution to Urdu language processing, providing an innovative solution to the complexities posed by the unique linguistic attributes of Urdu tokenization.
اسلوب تدريسي المبرمج وفق طريقة التفريقي وأثره في تعلم مهارتي المناولة والتهديف بكرة القدم لطلاب المرحلة الإعدادية بأعمار 16-17 سنة
Authors: Lec. Dr. Majid Hussein Messier
Published: June 2024

تكمن أهمية البحث لمعرفة أسلوب تدريسي المبرمج وفق طريقة التفريقي وأثره في تعلم مهارتي المناولة والتهديف بكرة القدم لطلاب المرحلة الإعدادية بأعمار 16-17 سنة. ويهدف البحث الى التعرف على اسلوب تدريسي المبرمج وفق طريقة التفريقي وأثره في تعلم مهارتي المناولة والتهديف بكرة القدم لطلاب ومن خلال الملاحظة العلمية لمستوى تعليم مهارة المناولة والتهديف في كرة القدم. ويحتاج إلى تعليم أكثر دقة وتفاعل الطالب مع تعلمه، حيث أن معظم طرق التدريس تحتاج إلى تطوير جديد وحداثة في استخدام الطريقة المناسبة. واستخدم الباحث المنهج التجريبي أشتمل مجتمع البحث على (86) طالب في إعدادية المركزية للبنين، بأعمار (16-17) سنة. في حين تم اختيار عينة البحث (الطريقة العشوائية البسيطة) القرعة مجموعة التجريبية (20) ومجموعة ضابطة بعدد (20) طالب. اما عينة التجربة الاستطلاعية (10) طالب واستبعد الباحث (16) طالب من أفراد مجتمع البحث واستمر البرنامج التعليمي لمدة ثمانية أسابيع وبواقع وحدتين تعليميتين في الأسبوع، في أيام (الاحد، الثلاثاء) وكانت مدة الوحدة (45) دقيقة وتوصل الباحث إلى الاستنتاجات ان اسلوب تدريسي المبرمج وفق طريقة التفريقي وأثره هو اسلوب جيد وفعال تعليم وتطوير مهارتي المناولة والتهديف بكرة القدم ويوصي لباحث الاستفادة من أسلوب تدريسي المبرمج وفق طريقة التفريقي وأثره في تطوير قابلية الطلاب على المقارنة والاستنتاج وتحمل المسؤولية.
ПРОЦЕДУРА ДОБРОВІЛЬНОЇ РЕАЛІЗАЦІЇ ДЛЯ ВЕЛИКИХ ПЛАТНИКІВ ПОДАТКІВ: АНАЛІЗ ТА ПРАКТИЧНІ АСПЕКТИ
Authors: Гуменюк О. І.
Published: June 2024

У сучасному світі ефективне управління податковими платежами стає ключовим аспектом успішної діяльності підприємств та індивідуальних платників податків. Зростаюча складність податкового законодавства та нестабільність економічних умов породжують необхідність пошуку способів оптимізації податкового співробітництва. Одним із ефективних інструментів у цьому процесі є процедура добровільної реалізації. Ця стаття розгляне суть та переваги цього процесу на основі сучасних досліджень та практичного досвіду.
Добровільна реалізація – це процедура, за допомогою якої платник податків може виправити порушення податкового законодавства за допомогою добровільної декларації та виплати податкових зобовʼязань. Основною ідеєю цього механізму є стимулювання платників податків до самостійного визнання помилок та відповідального підходу до виконання податкових обовʼязків.
У світі існують численні приклади успішної реалізації, які підтверджують ефективність цього механізму. Наприклад, компанія X виявила помилки у своїй податковій звітності та вчасно скористалася процедурою добровільної реалізації, що дало змогу уникнути негативних наслідків та зберегти репутацію на ринку.
Добровільна реалізація податкових зобовʼязань є важливим інструментом оптимізації податкового співробітництва, який дає можливість платникам податків зменшити ризики та забезпечити фінансову стабільність. Важливо підтримувати ініціативи та програми, спрямовані на підтримку цього процесу та забезпечення дотримання законодавства у сфері оподаткування.
Метою дослідження є системне опрацювання теоретико-методологічних засад та методичних засобів щодо вирішення наукового завдання – щодо удосконалення правового забезпечення процедури добровільної реалізації великих платників податків.
ПРАВОВЕ РЕГУЛЮВАННЯ ШТУЧНОГО ІНТЕЛЕКТУ У ФІНАНСОВОМУ СЕКТОРІ УКРАЇНИ
Authors: Касьяненко Л. М. , Шаркова В. С. , Петрук В. П.
Published: June 2024

Стаття присвячена характеристиці правового регулювання використання штучного інтелекту у фінансовому секторі України. Проведено систематичний аналіз понять, що стосуються впровадження штучного інтелекту у фінансові процеси, зосереджено увагу на різноманітних сценаріях, де штучний інтелект може значно полегшити функціонування фінансових підрозділів.
Виявлено ризики, пов'язані з впровадженням штучного інтелекту у фінансову сферу, та обґрунтовано напрями їх зниження. Аналізовано ситуації, в яких штучний інтелект може стати ключовим інструментом для оптимізації процесів у фінансових установах, підвищення продуктивності та зменшення ризиків. Зосереджено думку на важливості збалансованого підходу до використання штучного інтелекту, враховуючи його нормативно-правове регулювання в зарубіжних країнах. Звертається увага, що штучний інтелект у фінансовому секторі може бути як шансом на успіх, так і потенційною загрозою для майбутнього. Автором обґрунтовується потреба в пошуку оптимального способу впровадження штучного інтелекту в бізнес-процеси, щоб забезпечити успішне й стабільне майбутнє для фінансового сектору. Додатково, варто врахувати, що впровадження штучного інтелекту у фінансову сферу потребує не тільки технологічних змін, а й формування культури його застосування.
У статті обговорюється важливість правового регулювання використання штучного інтелекту у фінансовому секторі. Зазначається, що нарощування використання штучного інтелекту у фінансових процесах створює потребу у відповідному законодавстві, яке б забезпечувало ефективний контроль за використанням цих технологій і захищало як публічний, так і приватний інтерес. Виявлення й усунення недoлiкiв прaвoвoгo регулювaння штучного інтелекту у фінансовому секторі є неoбхiднoю умoвoю пoдaльшoгo нaйбiльш ефективнoгo, рaцioнaльнoгo й дoцiльнoгo його викoристaння.
ДОСУДОВА ФОРМА ВИРІШЕННЯ ПУБЛІЧНО-ПРАВОГО СПОРУ ЯК ЕФЕКТИВНИЙ ЗАСІБ ЗАХИСТУ ПРАВ, СВОБОД ТА ІНТЕРЕСІВ ОСОБИ І СПОСОБИ ЩОДО ЇЇ ВДОСКОНАЛЕННЯ
Authors: Ситников О. Ф.
Published: June 2024

Реалізація особою гарантованого Конституцією України права на захист можлива насамперед за допомогою створення таких форм захисту, які розкривають процесуальний зміст цього права: самозахист, позасудову, досудову та судову форми захисту.
У статті досліджуються форми захисту субʼєктивних прав учасників публічно- правових відносин, які поділяються на три основних форми: самозахисту, досудова та судова. Судова форма оскарження рішень, дій або бездіяльності субʼєктів владних повноважень є головною, але не єдиною в системі захисту прав і законних інтересів приватних осіб у відносинах з державою. Надано аналіз сучасного стану досудового порядку оскарження рішень, дій чи бездіяльності владних субʼєктів та узагальнено такі види досудового вирішення публічно-правових спорів, як парламентський, адміністративний та громадський. Через використання загальнонаукових та спеціальних методів наукового пізнання вдалось всебічно дослідити обʼєкт дослідження – досудовий порядок вирішення публічно-правового спору. Результати дослідження відобразили недоліки досудового порядку вирішення спорів та знайшли як законодавчі, так і практичні способи щодо вдосконалення адміністративно-правових суперечок у позасудовому порядку.
Класифікація форм захисту прав особи дала змогу всебічно дослідити процесуальні можливості захисту своїх прав у складних умовах реформування адміністративної та судової систем держави. Доведено, що досудовий порядок врегулювання адміністративно-правових спорів є не тільки альтернативою судовій формі захисту, але і самостійною, дієвою формою захисту прав, свобод та інтересів особи в публічно- правових відносинах. Аналіз вирішення публічно-правового спору в досудовому порядку розкрив усі можливості та переваги процедури досудового вирішення спору, а дослідження кожного із засобів захисту за відповідними критеріями класифікації надала нам можливість більш повно розкрити досудову форму вирішення різноманіття адміністративно-правових спорів.
Innovation in the management of the breast cancer patient pathway: from correct identification to target therapies. Perspectives, opportunities and insights
Authors: Adamo Vincenzo , Airoldi Mario , Amunni Gianni
Published: June 2024

Considering the current and future therapeutic options that are or will be available in the adjuvant treatment of breast cancer, this document reports on the insights from two multi-regional expert meetings aimed at investigating possible problems of access to the treatment pathway involving the BRCA (BReast CAncer) test.
The experts stated that the update of the AIOM guidelines (diagnostic and therapeutic innovations) will require a correction of clinicians’ behaviors and a partial reorganization of the current Integrated Care Pathways (ICPs).
From this point of view, the update of the AIOM GLs could supply to Regions and, above all, to all cancer networks a valid rationale for starting a process of harmonization of ICPs aimed at guaranteeing the rapid access to treatments by improving the quality of the service provided by the National Health Service (SSN).
To ensure to breast cancer patients a rapid access to the latest approved treatments, experts believe that it will be necessary to update the access pathway to genetic tests. This could lead to an increase in the use of genetic tests, creating one of the main organizational and economic challenge that regions and cancer networks will have to face.
Indicadores de bem-estar de novilhas Jersey criadas em sistema de semiconfinamento e confinamento com e sem fornecimento de homeopático
Authors: Nascimento Aline Luiza do , Nora Luisa , Vitt Maksuel Gatto de , Piaia Arthur Mocelin , Giacomelli Charles Marcon , Torteli Mario Augusto , Silva Aleksandro Schafer da
Published: June 2024

Os ruminantes quando criados em sistemas intensivos e submetidos à presença de variáveis que potencializam o estresse, podem desenvolver estereotipias comportamentais. Além disso, dietas fornecidas em confinamento apresentam menos volumoso em comparação a dietas forrageiras que os bovinos consomem enquanto estão ao pasto. Essas alterações da dieta afetam o tempo de ingestão e quando submetidos a sistemas confinados, os animais utilizam menos tempo engajados em comportamentos alimentares, fatores esses que podem contribuir para aparecimento de comportamentos anormais. Ainda, é escasso o número de informações sobre essas situações, sendo assim o objetivo desse estudo foi avaliar se a inclusão de um produto homeopático poderia minimizar os comportamentos anormais, considerando dois sistemas de criação (confinamento e semiconfinamento) e análises pré e pós-alimentação. Diante disso, foram utilizadas 14 novilhas da raça Jersey com 12 meses de idade, divididas em dois grupos de sete animais cada. O estudo teve duração de 60 dias, sendo que os primeiros 30 dias em sistema de semiconfinamento (acesso à pastagem) e os últimos 30 dias em confinamento. Por um observador, três vezes na semana (segundas, quartas e sextas-feiras) foram feitas coletas de dados comportamentais antes e após alimentação vespertina. Ao final de cada etapa (dias 28, 29 e 30; e dias 58, 59 e 60) foi observado o comportamento das novilhas, três vezes ao dia, com duração de 50min cada, por até três avaliadores. Dentre os resultados obtidos, a vocalização apresentou 66% menos chance de ocorrência para grupo tratamento. O tipo de sistema de criação afetou o perfil comportamental das novilhas, principalmente quando observado a estereotipia oral de enrolar a língua nos animais alojados em sistemas confinados. O sistema de criação também teve influência sob a ruminação, apresentando 77% menos chance de ocorrência para animais confinados. Outros comportamentos (em repouso e lambendo outros animais) também foram influenciados pelo sistema de criação. Com exceção do enrolar a língua, todos os outros comportamentos animais tiveram efeito do momento de observação, antes ou depois da alimentação. A partir desses resultados constata-se influência do sistema semiconfinado sobre a maior ocorrência de comportamentos naturais como a ruminação e repouso, sugerindo que nesse sistema os animais estão submetidos a maiores condições de conforto, e por consequência, apresentam menos estereotipias.
Efeitos da mobilização precoce em pacientes em uso de ventilação mecânica invasiva internados na Unidade de Terapia Intensiva adulto: Revisão integrativa
Authors: Silva Amanda Paula Couto , Oliveira Maria Clara Leandro , Rodrigues Suzane de Faria , Andrade Cleyton Oliveira de , Costa Kelly Aline Rodrigues
Published: June 2024

A mobilização precoce em pacientes sob ventilação mecânica na Unidade de Terapia Intensiva (UTI) é essencial para prevenir complicações, promover uma recuperação mais rápida e reduzir o tempo de ventilação mecânica. Este estudo teve como objetivo analisar os efeitos dessa prática em pacientes adultos na UTI. Foram realizadas buscas nas bases de dados PEDro, PubMed e SciELO, utilizando descritores específicos. Os critérios de inclusão consideraram textos completos gratuitos, ensaios clínicos e artigos publicados nos últimos 10 anos. Excluíram-se estudos que não respondiam à pergunta de pesquisa. A busca resultou em 25 artigos, dos quais 05 foram incluídos na análise. Os resultados mostraram que a mobilização precoce oferece benefícios significativos, como melhoria na mobilidade dos pacientes, melhor recuperação funcional a curto e longo prazo, redução de complicações e diminuição do tempo de ventilação mecânica. A intervenção de reabilitação aprimorada foi associada a benefícios específicos em termos de mobilização precoce, níveis de atividade física e saúde mental, em comparação com o cuidado padrão na UTI. A comparação entre os grupos enfatizou a importância de implementar estratégias específicas para melhorar os desfechos dos pacientes críticos em ventilação mecânica. Em resumo, os estudos revisados evidenciam a eficácia da mobilização precoce na melhoria dos resultados e do cuidado aos pacientes na UTI sob ventilação mecânica. A prática promove melhores desfechos clínicos e funcionais, destacando a necessidade de sua ampliação para beneficiar um maior número de pacientes críticos.
Harbor seal predation on migrating steelhead smolts entering marine waters
Authors: Moore ME , Malick MJ , Thomas AC , Klungle MM , Berejikian BA
Published: June 2024

After decades of historic exploitation, harbor seal Phoca vitulina populations in many marine ecosystems are increasing, and in some cases causing alarm over predation impacts on prey species of conservation concern. To gauge the magnitude of harbor seal predation impact on juvenile Puget Sound steelhead Oncorhynchus mykiss, a threatened population under the US Endangered Species Act, we quantified harbor seal predation rates in the Nisqually River estuary and nearshore marine environment of south Puget Sound in Washington State, USA, using 2 independent assessments. First, we developed a prey consumption model for the years 2016-2018 using the proportion of steelhead in seal scat (assessed using DNA metabarcoding, bioinformatics, and hard parts), seal daily energetic requirements, steelhead smolt size and abundance information, and seal abundance estimates. Second, we used acoustic telemetry data from individually tagged steelhead smolts (2014-2019 and 2021) to quantify predation events in the Nisqually River estuary based on spatial and temporal behavioral patterns of both predator and prey. The consumption model estimated that 9.0% (2017) to 32.8% (2018) of steelhead outmigrants (i.e. ‘smolts’) were eaten by harbor seals, accounting for most of the total mortality incurred in the Nisqually estuary and South Puget Sound (23 km) in 2 out of 3 years. Predation mortality rates through the estuary (5 km), assessed using acoustic telemetry analysis, ranged from 11.0% (2014) to 24.8% (2016). Our results demonstrate that a large proportion of a threatened salmonid population can be lost to harbor seal predation over a small segment of their migration route, even in a relatively natural delta estuary.
Private Sensitive Content on Social Media: An Analysis and Automated Detection for Norwegian
Authors: Borgen Haldis , Zachariassen Oline , Mise Pelin , Yildiz Ahmet , Özgöbek Özlem
Published: June 2024

This study addresses the notable gap in research on detecting private-sensitive content within Norwegian social media by creating and annotating a dataset, tailored specifically to capture the linguistic and cultural nuances of Norwegian social media discourse. Utilizing Reddit as a primary data source, entries were compiled and cleaned, resulting in a comprehensive dataset of 4482 rows. Our research methodology encompassed evaluating a variety of computational models—including machine learning, deep learning, and transformers—to assess their effectiveness in identifying sensitive content. Among these, the NB BERT-based classifier emerged as the proficient, showcasing accuracy and F-1 score. This classifier demonstrated remarkable effectiveness, achieving an accuracy of 82.75% and an F1-score of 82.39%, underscoring its adeptness at navigating the complexities of privacy-sensitive content detection in Norwegian social media. This endeavor not only paves the way for enhanced privacy-sensitive content detection in Norwegian social media but also sets a precedent for future research in the domain, emphasizing the critical role of tailored datasets in advancing the field.
Poisoning Attacks on Federated Learning for Autonomous Driving
Authors: Garg Sonakshi , Jönsson Hugo , Kalander Gustav , Nilsson Axel , Pirange Bhhaanu , Valadi Viktor , Östman Johan
Published: June 2024

Federated Learning (FL) is a decentralized learning paradigm, enabling parties to collaboratively train models while keeping their data confidential. Within autonomous driving, it brings the potential of reducing data storage costs, reducing bandwidth requirements, and to accelerate the learning. FL is, however, susceptible to poisoning attacks. In this paper, we introduce two novel poisoning attacks on FL tailored to regression tasks within autonomous driving: FLStealth and Off-Track Attack (OTA). FLStealth, an untargeted attack, aims at providing model updates that deteriorate the global model performance while appearing benign. OTA, on the other hand, is a targeted attack with the objective to change the global model's behavior when exposed to a certain trigger. We demonstrate the effectiveness of our attacks by conducting comprehensive experiments pertaining to the task of vehicle trajectory prediction. In particular, we show that, among five different untargeted attacks, FLStealth is the most successful at bypassing the considered defenses employed by the server.For OTA, we demonstrate the inability of common defense strategies to mitigate the attack, highlighting the critical need for new defensive mechanisms against targeted attacks within FL for autonomous driving.
Green Urban Mobility with Autonomous Electric Ferries: Studies of Simulated Maritime Collisions using Adaptive Stress Testing
Authors: Vatle Jan-Marius , Eriksen Bjørn-Olav Holtung , Mengshoel Ole J
Published: June 2024

With 90% of the world's goods transported by sea vessels, it is crucial to investigate their safety. This is increasingly important as autonomy is being introduced into sea vessels, which transport goods and people. To study the safety of an autonomous ferry's collision avoidance system, we consider the Adaptive Stress Testing (AST) method in this work. AST uses machine learning, specifically reinforcement learning, along with a simulation of a system under test---in our case, an autonomous and electric ferry---and its environment. Whether that simulation is fully or partially observable has implications for the integration into existing engineering workflows. The reason is that the fully observable simulation induces a more complex interface than the partially observable simulation, meaning that the engineers designing and implementing AST need to acquire and comprehend more potentially complex domain knowledge. This paper presents maritime adaptive stress testing (MAST) methods, using the world's first autonomous, electric ferry used to transport people as a case study. Using MAST in multiple scenarios, we demonstrate that AST can be productively utilized in the maritime domain. The demonstration scenarios stress test a maritime collision avoidance system known as Single Path Velocity Planner (SP-VP). Additionally, we consider how MAST can be implemented to test using both fully observable (gray box) and partially observable (black box) simulators. Consequently, we introduce the Gray-Box MAST (G-MAST) and Black-Box MAST (B-MAST) architectures, respectively. In simulation experiments, both architectures successfully identify an almost equal number of failure events. We discuss lessons learned about MAST including the experiences with both the Gray-Box and Black-Box approaches.
Weight Rescaling: Applying Initialization Strategies During Training
Authors: Niehaus Lukas , Krumnack Ulf , Heidemann Gunther
Published: June 2024

The training success of deep learning is known to depend on the initial statistics of neural network parameters. Various strategies have been developed to determine suitable mean and standard deviation for weight distributions based on network architecture. However, during training, weights often diverge from their initial scale. This paper introduces the novel concept of weight rescaling, which enforces weights to remain within their initial regime throughout the training process. It is demonstrated that weight rescaling serves as an effective regularization method, reducing overfitting and stabilizing training while improving neural network performance. The approach rescales weight vector magnitudes to match the initialization methods’ conditions without altering their direction. It exhibits minimal memory usage, is lightweight on computational resources and demonstrates comparable results to weight decay, but without introducing additional hyperparameters as it leverages architectural information. Empirical testing shows improved performance across various architectures, even when combined with additional regularization methods like dropout in AlexNet and batch normalization in ResNet-50. The effectiveness of weight rescaling is further supported by a thorough statistical evaluation.
A Clearer View on Fairness: Visual and Formal Representations for Comparative Analysis
Authors: Mendez Julian Alfredo , Kampik Timotheus , Tubella Andrea Aler , Dignum Virginia
Published: June 2024

The opaque nature of machine learning systems has raised concerns about whether these systems can guarantee fairness. Furthermore, ensuring fair decision making requires the consideration of multiple perspectives on fairness.At the moment, there is no agreement on the definitions of fairness, achieving shared interpretations is difficult, and there is no unified formal language to describe them. Current definitions are implicit in the operationalization of systems, making their comparison difficult.In this paper, we propose a framework for specifying formal representations of fairness that allows instantiating, visualizing, and comparing different interpretations of fairness. Our framework provides a meta-model for comparative analysis. We present several examples that consider different definitions of fairness, as well as an open-source implementation that uses the object-oriented functional language Soda.
Should You Trust Your Voice Assistant? It’s Complicated, but No
Authors: Stamatiou Filippos , Karakonstantis Xenofon
Published: June 2024

The widespread use of voice-assisted applications using artificial intelligence raises questions about the dynamics of trust and reliance on these systems. While users often rely on these applications for help, instances where users face unforeseen risks and heightened challenges have sparked conversations about the importance of fostering trustworthy artificial intelligence. In this paper, we argue that the prevailing narrative of trust and trustworthiness in relation to artificial intelligence, particularly voice assistants, is misconstrued and fundamentally misplaced. Drawing on insights from philosophy and artificial intelligence literature, we contend that artificial intelligence systems do not meet the criteria for participating in a relationship of trust with human users. Instead, a narrative of reliance is more appropriate. However, we investigate the matter further to explore why the trust/trustworthiness narrative persists, focusing on the unique social dynamics of interactions with voice assistants. We identify factors such as diverse modalities and complexity, social aspects of voice assistants, and issues of uncertainty, assertiveness, and transparency as contributors to the trust narrative. By disentangling these factors, we shed light on the complexities of human-computer interactions and offer insights into the implications for our relationship with artificial intelligence. We advocate for a nuanced understanding of trust and reliance in artificial intelligence systems and provide suggestions for addressing the challenges posed by the dominance of the trust/trustworthiness narrative.
Designing Robots to Help Women
Authors: Cooney Martin , Klasén Lena M Widin , Alonso-Fernandez Fernando
Published: June 2024

Robots are being designed to help people in an increasing variety of settings--but seemingly little attention has been given so far to the specific needs of women, who represent roughly half of the world's population but are underrepresented in robotics. Here we used a speculative prototyping approach to explore this expansive design space: First, we identified some challenges that disproportionately affect women in relation to crime, health, and daily activities, as well as opportunities for designers, which were visualized in five sketches. Then, one of the sketched scenarios was further explored by developing a prototype, of a drone equipped with computer vision to detect hidden cameras that could be used to spy on women. While object detection introduced some errors, hidden cameras were identified with a reasonable accuracy of 80% (Intersection over Union (IoU) score: 0.40). Our aim is that these results could help spark discussion and inspire designers, toward realizing a safer, more inclusive future through responsible use of technology.
STATUS E APRENDIZAGEM COLETIVA EM REDES INTERORGANIZACIONAIS
Authors: Souza da Costa Rodrigo , Vinícius Pereira Correa Marcos
Published: June 2024

O propósito geral deste trabalho é examinar de que forma o status das organizações influencia o aprendizado entre os atores de um Arranjo Produtivo Local (APL) APL sob a perspectiva dos Sistemas Adaptativos Complexos (SAC). Os APL) têm se tornado espaço relevante para o desenvolvimento de comunidades de aprendizagem, com o objetivo de promover o compartilhamento de conhecimento, sobretudo, entre pequenas e médias organizações. Nesse contexto, a literatura tem apresentado poucos estudos empíricos a respeito das redes organizacionais como referência para a aprendizagem compartilhada em processos de internacionalização (MCNAMARA, 2005). A análise dos dados foi realizada por uma análise de conteúdo que se se trata de um conjunto de técnicas de exame de mensagens de forma sistemática e objetiva, tanto de forma qualitativa, como quantitativa, que possibilitem inferência acerca do conteúdo da mensagem. A análise utilizada neste trabalho foi utilizou-se o tema como forma de unidade de registro para que se possibilite que a análise temática tenha condições de encontrar “núcleos de sentido” na comunicação (BARDIN, 2002). Como resultado, destaca-se que os níveis de status de atores que atuem em Sistemas Adaptativos Complexos (SAC) são elementos que em uma comunidade de aprendizagem tem potencial para auxiliar o processo colaborativo e inter-relação organizacional, que apresentam interesses comuns de atuação e suas exigências adaptativas, por meio do compartilhamento de experiências, conhecimentos e busca de informações, facilitada por agência legitimada, com a finalidade de tornar mais efetivo o desempenho individual e coletivo de seus participantes.
Medir la innovación:
Authors: Carini Gabriel , Frutero Román
Published: June 2024

El agronegocio supuso en Argentina una mutación en las prácticas agropecuarias. Entre las más notorias se contó la incorporación intensiva de conocimiento y de las innovaciones del campo de la ingeniería genética. Estas dimensiones supusieron un radical cambio en la forma de operar dentro del proceso productivo pasando a concebirse cada vez más con una lógica empresarial. Sobre esa base, se propone un análisis del proceso de transformación digital en cooperativas agropecuarias, un actor central en la comercialización de los bienes y servicios de origen agropecuario. En la introducción se avanza en la construcción de un estado de la cuestión con relación a cómo esta problemática fue abordada en Argentina y qué elementos conceptuales estructuran la propuesta. Luego, se presentan las elecciones metodológicas en torno a la escala de análisis y al instrumento de relevamiento. De forma seguida, se propone una presentación de los principales resultados, enfatizando en cuatro aspectos: 1) la cultura organizacional en relación con la predisposición para incorporar tecnologías a la gestión del negocio agropecuario, 2) la percepción de la dirigencia cooperativa sobre los aportes de las tecnologías a la empresa cooperativa, 3) la planificación a corto plazo sobre la inversión en tecnologías y 4) la aplicación efectiva de tecnologías a la administración de los procesos internos. En la discusión y conclusiones se realiza una recapitulación de los principales hallazgos entendiendo que si bien existe una alta valoración de las posibilidades que ofrece el uso de tecnologías para la gestión de los agronegocios, el proceso de transformación digital para las cooperativas agropecuarias es aún fragmentario.
A coal bursting liability evaluation model based on fuzzy set theory and analysis of three influencing factors
Authors: Wang Chao , Jin Zijun , Liu Xiaofei , Wang Tuanhui , Liu Yu , Zhang Shaoyuan , Wang Qiwei
Published: June 2024

The classification of coal bursting liability is of great significance for the prevention and control of rock burst. To address the shortcomings in existing bursting liability classification methods, a comprehensive evaluation model for bursting liability based on a combination of weighted-fuzzy set theory and three influencing factor analyses is proposed. The model selects four evaluation indicators: dynamic failure time (DT), elastic energy index (WET), bursting energy index (KE), and uniaxial compressive strength (RC). Two types of membership functions, trapezoidal fuzzy numbers (TFN) and Gaussian fuzzy numbers (GFN), are used to quantitatively describe the fuzziness between indicator levels. The Delphi method and a random forest feature identification method are combined to obtain a subjective and objective combined weighting, determining the optimal combination weight of the four indicators. Based on Zadeh operator (ZO), maximum-minimum operator (MMO), weighted-average operator (WAO), and all-around restrictive operator (ARO), calculations are carried out for the synthesis of indicator weights and memberships. Maximal membership principle (MMP) and Credible identification principle (CIP) are utilized as evaluation principle to assess the bursting liability level, constructing 16 fuzzy comprehensive evaluation models. The impact of membership functions, fuzzy operators, and evaluation principle on evaluation results are systematically analyzed based on the discrimination results of 127 sample sets. The results show that the optimal fuzzy comprehensive evaluation model is constructed using the trapezoidal fuzzy numbers, weighted average operator, and maximal membership principle (TFN-WAO-MMP), with a classification accuracy of 97.64%. Finally, the optimal model is applied to 10 engineering instances, and the evaluation results are consistent with the actual situation, verifying the reliability and effectiveness of the model. Overall, these findings contribute to the development of a more sophisticated and accurate method for assessing the rock burst tendency of coal specimens. By leveraging the theory of fuzzy sets, this approach provides a more nuanced and nuanced evaluation of rock burst tendency, and thus offers the potential to improve workplace safety and efficiency in the coal mining industry.
Utilizing machine learning for early screening of thyroid nodules: a dual-center cross-sectional study in China
Authors: Weng Shuwei , Ding Chen , Hu Die , Chen Jin , Liu Yang , Liu Wenwu , Chen Yang , Guo Xin , Cao Chenghui , Yi Yuting , Yang Yanyi , Peng Daoquan
Published: June 2024

Background

Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformation. Early screening is crucial for management, yet current models focus mainly on ultrasound features. This study explores machine learning for screening using demographic and biochemical indicators.

Methods

Analyzing data from 6,102 individuals and 61 variables, we identified 17 key variables to construct models using six machine learning classifiers: Logistic Regression, SVM, Multilayer Perceptron, Random Forest, XGBoost, and LightGBM. Performance was evaluated by accuracy, precision, recall, F1 score, specificity, kappa statistic, and AUC, with internal and external validations assessing generalizability. Shapley values determined feature importance, and Decision Curve Analysis evaluated clinical benefits.

Results

Random Forest showed the highest internal validation accuracy (78.3%) and AUC (89.1%). LightGBM demonstrated robust external validation performance. Key factors included age, gender, and urinary iodine levels, with significant clinical benefits at various thresholds. Clinical benefits were observed across various risk thresholds, particularly in ensemble models.

Conclusion

Machine learning, particularly ensemble methods, accurately predicts thyroid nodule presence using demographic and biochemical data. This cost-effective strategy offers valuable insights for thyroid health management, aiding in early detection and potentially improving clinical outcomes. These findings enhance our understanding of the key predictors of thyroid nodules and underscore the potential of machine learning in public health applications for early disease screening and prevention.