bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a Professional Identity Scale for Information Professionals
Authors: Oguz Faith
Published: October 2024

Professional identity is generally defined as one’s interpretation of self as a professional in connection with the personal and professional experiences, attitudes, and aspirations. The research used the framework developed by Pierson et al. (2019), value statements from major professional associations, library and information science (LIS) literature to revise a professional identity scale for counseling profession developed by Woo and Henfield (2015). The developed instrument will be reviewed by small number of experts (N≈20) for content validation. The instrument will be sent out to LIS professionals via mailing lists for construct validation. LIS professionals who have just transitioned from school to work (graduated from LIS programs in the last 5 years) will be invited to participate in the study. The final instrument will include demographic questions (e.g., age, gender), highest degree achieved, employment status, and LIS job experience. Exploratory factor analysis will be carried out to identify the factor structure of the scale and relevant tests (e.g., Kaiser-Meyer-Olkin, Bartlett's test of sphericity) will be performed to investigate and assess the professional identity constructs that will emerge from the data. Confirmatory factor analysis will be conducted to obtain additional measures of fit and possibly explore additional changes. As the profession goes through a transformation and recalibrates itself to stay relevant and better address the needs and expectations of users, having a validated and reliable instrument to assess the professional identity of the professionals in the field will help address this gap.
Power and Controversy: Controversy surrounding Material Challenges at a Public Library
Authors: Yeon Jieun
Published: October 2024

This case study investigates material challenges in a public library system, a growing concern in the United States due to the politicization of topics like gender, sexuality, and race. Material challenges involve requests to remove or restrict library materials, with reported cases skyrocketing to 1,247 in 2023. These challenges not only create public controversy but also highlight disagreements within public library governance. In most cases, governance involves librarians, a board of trustees, and community members, but little research has explored disagreements among these actors.
This study examines a specific public library system experiencing controversy around material challenges, focusing on the distribution and exercise of power among different actors. Data was collected through interviews, recordings, and documents, and analyzed using thematic coding, a meta-network framework, and a chronology of disagreement events. The study identifies legal authority, rights, and networks as the main resources mobilized in the controversy. Legal authority shapes the issues of disagreement, while rights and networks are used to counter this authority and influence the controversy's continuation.
A model of resource mobilization in public governance controversy is proposed, highlighting the unequal distribution of legal authority due to a governance schema based on majoritarianism. Actors without legal authority use other resources to challenge this, which eventually continues the controversy. The study suggests that leveling legal authority could mitigate public controversy and contributes to understanding public library governance during disputes. It offers insights for library practitioners and community members on resolving such controversies effectively.
For Every Book Their Reader: Book Challenges and Library Trauma
Authors: Dudak Leah , Yeon Jieun
Published: October 2024

Since 2021, public and school libraries have become the frontlines of a cultural war. Regardless of the political tendency of the local area, material challenges have been submitted against libraries nationwide. When library workers handle material challenges, under the principle of intellectual freedom, they have often faced retaliatory actions from political groups, such as online attacks on them organized by political groups and budget cuts targeting the libraries. These challenges may create stress and trauma for library workers, both in the action of the banning, and the anticipation of it. For librarians experiencing trauma or at higher risk of exposure to traumatic events, this poster aims to illustrate a library trauma cycle within the context of material challenges. It highlights how library workers face an increased likelihood of trauma when material challenges are prevailing in the nation and how the internalization of trauma occurs within the context of the library and its community. The poster then suggests possible interventions to halt the library trauma cycle, calling for action from library administrators and board members.
READCON: A Curriculum for Library Readiness, Advocacy, and Community Empowerment During Challenging Conditions
Authors: Santos Green Lucy , Dawkins April , Byrd-Fort Valerie
Published: October 2024

This panel introduces the  READCON curriculum: Library Readiness, Advocacy, and Community Empowerment During Challenging Conditions The curriculum equips library workers with soft skills to develop relationships with their communities, partnering more effectively for advocacy. Building on the highly successful Get Ready Stay Ready Community Action Toolkit (GRSR), this curriculum builds foundational skills for library workers to engage in constructive dialogue on potentially divisive aspects of library programming, service, and material challenges. READCON takes Get Ready Stay Ready a step further by providing library workers with the soft skills needed to encourage community members to use the action steps included in the GRSR toolkit. Both resources are highly adaptable, multi-lingual, open-source learning tools developed by experts in academic, public, and school librarianship, education and family law, crisis communications, community advocacy and relations, and youth leadership.
Examining the Role of School Librarians in Teaching Young Children to Detect and Avoid Misinformation
Authors: Zimmerman Tara , Rose Anthony
Published: October 2024

This study investigates the imperative for implementing an informational literacy curriculum in K-5 school libraries to equip students with essential skills for detecting and avoiding misinformation. Using a mixed-methods approach, data were collected from 141 school librarians across the United States. Quantitative analysis revealed significant gaps in information literacy instruction frequency and resource availability. Qualitative analysis identified four overarching themes: Awareness, Identification, Resources, and Risks/Harm. Together these results highlight the pressing need for curriculum development in this area, emphasizing critical thinking skills through age-appropriate resources. The findings underscore the importance of advocating for dedicated instructional time and the creation of tailored teaching materials to empower students as discerning consumers and responsible citizens. This research contributes valuable insights to the fields of school libraries and information literacy, informing future initiatives aimed at enhancing students' ability to navigate the complexities of the digital age.
ENHANCED LION SWARM OPTIMIZATION ALGORITHM WITH CENTRALIZED AUTHENTICATION APPROACH FOR SECURED DATA TRANSMISSION OVER WSN
Authors:   Periyar University, India, S Silambarasan , Devi M Savitha ,   Periyar University Constituent College of Arts and Science, India
Published: October 2024

Securing data accuracy in WSNs (Wireless Sensor Networks) is a major problem. Aggregation techniques for improving accuracy in data processing have been gaining attention of scholars, recently. Existing security systems using singular paths for transmission of data have delays in transmissions while being open to intrusions. Moreover, increased computational overheads and processing time increases the delay of data transmission in the given networks. To overcome these issues, this work proposes ELSOA-CA (Enhanced Lion Swarm Optimization Algorithm and Centralized Authentication) method. This method focuses on an optimal, faster and energy efficient data transmissions while ensuring accurate decisions on tomato crops. Multipath routing introduced in the proposed method ensures faster data transmissions by selecting optimal forwarder nodes which satisfy the constraints of delay and energy. Optimal forwarder node selection is done using ELOSA algorithm. Data transmissions are secured by centralized authentication involving third party nodes. Each and every node in a region gets registered with the authentication node where a node’s genuineness is checked the node is allowed into the forwarder node list, used for data routing. CA (Centralized Authentication) enhances the security level of data transmissions over WSN multi path routing. ELSOA-CA framework’s simulation results provide higher throughputs, reduced energy consumptions, improved network lifetimes PDRs (Packet Drop Ratios) and lesser delay times.
A META HEURISTIC HYBRID MOTH SEARCH ALGORITHM FOR OPTIMIZING LINK QUALITY AND SHORTEST PATH ROUTING IN WIRELESS SENSOR NETWORKS
Authors:   IK Gujral Punjab Technical University, India, Singh Navdeep ,   Amritsar College of Engineering and Technology, India, Bindra Harminder Singh ,   Malout Institute of Management and Information Technology, India
Published: October 2024

The Internet of Things tends to attract deep interest in areas such as electronic, environmental management and enhance the effectiveness from researchers, the industry, citizens and government. IoT provides internet connectivity between connected phones in any context, anytime or anywhere. Wireless sensor networks (WSNs) consequently play an important role in developing a robust, affordable and convenient network of smart devices. Even then, sensor networks are restricted in scope of power, processing, and memory. In this framework, authors proposed a routing protocol of hybrid meta-heuristic moth search algorithm based differential evolution (HMSA-DE). By choosing routes based on the quality of the link, residual energy and recommended measuring mechanisms, the HMSA enhances reliability and energy efficiency. In addition, HMSA offers an event-based load balancing system that further prevents premature node / network power consumption. The findings suggest that HMSA improves the life cycle and availability of the network as well as the performance of IoT application services. It distributes limited network resources evenly and reduces the packet loss rate compared with the results of network protocols.
ABC ALGORITHM BASED MINIMIZATION OF THE DETACTION ERROR IN COOPERATIVE SENSING
Authors:   Government Engineering College, Rajkot, India, Divyesh R Keraliya , R P Sandhani ,   Government Engineering College, Rajkot, India, N V Langhnoja ,   Government Engineering College, Rajkot, India
Published: October 2024

In the recent wireless communication trends, the radio frequency spectrum is the prime concern for effective utilization as there are many radio frequency channels simultaneously used by many users. Cognitive radio (CR) can be the most useful new technique to utilize the radio frequency spectrum effectively and efficiently. Multiple users of the cognitive radio can be detected by sensing the spectrum in cooperative mode and vacant spectrum space is detected from these cognitive radio networks (CRN) for new users. Information of these CR users jointly utilized and combined at the common receiver level either by conventional or soft combining technique. Hence most attention is required in sensing the used cooperative spectrum with a minimum of error. This paper focuses on the optimization technique called Artificial Bees Colony (ABC) under the MINI-MAX criterion to minimize the probability of the error of spectrum energy level weighting coefficient. ABC algorithm generates the weighting coefficients vector which in turn minimizes the probability of error during sensing. Comparative analysis of the performance of this proposed algorithm and traditional soft decision fusion (SDF) methods like Equal Gain Combining (EGC) and hard decision fusion (HDF) methods like Majority, AND, OR etc. is done in this paper and simulation results shows that proposed technique have a minimum of error in detection.
HOME NETWORK SECURITY INCORPORATING MACHINE LEARNING ALGORITHMS IN INTERNET OF MEDICAL THINGS
Authors:   I.K. Gujral Punjab Technical University, India, Arora Pallavi , Kaur Baljeet ,   Guru Nanak Dev Engineering College, India, Teixeira Marcio Andrey ,   Federal Institute of Education, Science, and Technology of Sao Paulo, Brazil
Published: October 2024

The proliferation of chronic disorders such as COVID-19 has recognized the importance of people all over the world having immediate access to healthcare. The recent pandemic has shown deficiencies in the traditional healthcare infrastructure, namely that hospitals and clinics alone are inadequate for grappling with such a disaster. One of the key technologies that favours new healthcare solutions is smart and interconnected wearables. Thanks to developments in the Internet of Things (IoT), these wearables will now collect data on an unprecedented scale. However, as a result of their extensive use, security in these critical systems has become a major concern. This paper presents an intrusion detection mechanism based on Machine Learning Algorithms for healthcare applications used in home network environments. Experiments are carried out on a home network to detect attacks against a health care application. Experiments using the proposed mechanism based on Machine Learning algorithms to detect attacks against a healthcare application are carried out on a home network, and the results show a good performance of the used algorithms.
ENSEMBLE MACHINE LEARNING METHOD FOR DETECTING DEEP FAKES IN SOCIAL PLATFORM
Authors:   National Institute of Electronics and Information Technology, India, Wagh Kavita , Hindka Mayank ,   Texas A&M University, United States of America, Gopi Telagamalla ,   Annamacharya Institute of Technology and Sciences, India, Ahmed Syed Arfath ,   Maulana Azad National Urdu University, India
Published: October 2024

With the rise of deep fake technology, the detection of manipulated media has become crucial in maintaining the integrity of social platforms. In this study, we propose an ensemble machine learning approach combining Support Vector Machines (SVM), Artificial Neural Networks (ANN), k-Nearest Neighbors (KNN), and Decision Trees (DT) for deep fake detection. Our contribution lies in the development of a robust ensemble method that leverages the strengths of multiple algorithms to enhance detection accuracy and resilience against evolving deep fake techniques. Through experimentation on a diverse dataset, our ensemble model demonstrated superior performance compared to individual models, achieving high accuracy and robustness in detecting deep fakes on social platforms. Keywords: Deep fakes, Ensemble learning, Machine learning, Social platforms, Detection.
IMAGE PROCESSING AND CNN BASED MANUFACTURING DEFECT DETECTION AND CLASSIFICATION OF FAULTS IN PHOTOVOLTAIC CELLS
Authors:   PSG College of Technology, India, S Kanthalakshmi , S Maalathy ,   PSG College of Technology, India, Kumar P. Satheesh ,   Nachimuthu Polytechnic College, India
Published: October 2024

Renewable energy resources such as solar energy, biomass, tidal, geothermal, and hydroelectric energy are becoming increasingly important due to their potential to mitigate the negative impacts of climate change and reduce our dependence on finite and polluting fossil fuels. Solar power can provide a clean, sustainable, and reliable source of renewable energy. Important component of solar power generation is the silicon panel and its surface quality is highly related to its robustness and power generation efficiency. Cell breakages resulting from micro-cracks, degradation and shunted areas on cells are proven to cause major issues and these affect the photovoltaic module efficiency and performance. Solar cell defect identification is important because defects in solar cells significantly reduce their efficiency, which in turn affects their power output and lifespan. By identifying and classifying defects during the production of these cells, engineers and researchers can improve the quality control of solar cells, leading to more reliable and efficient solar energy systems. The proposed method in this research paper, utilizes image processing operations such as adaptive Gaussian thresholding, horizontal and vertical line extraction morphological operations, Canny edge detection, K- Means clustering and VGG16 convolutional neural network to identify the defects in solar cells and classify them as defective or non-defective during the manufacturing process itself. Once the defects are classified, the classification data is exported to Excel file and the results are visually represented as labelled images. OpenCV and Keras modules in Python are used to perform the image processing operations which contributes to cost-effective, reduced computation and high-precision solution.
ENHANCED DETECTION OF CANCER LESIONS USING CONVOLUTIONAL NEURAL NETWORKS AND FEATURE FUSION
Authors:   R.M.K. Engineering College, India, S.D. Lalitha , P Kavitha ,   R.M.K. Engineering College, India
Published: October 2024

Breast cancer remains a significant global health concern, with early detection crucial for effective treatment and improved patient outcomes. Traditional methods of detecting breast cancer lesions, such as mammography and ultrasound, often rely on subjective interpretation and may lack sensitivity. Convolutional Neural Networks (CNNs) have shown promise in medical imaging analysis due to their ability to automatically extract features from images and classify abnormalities. However, improving the detection accuracy of breast cancer lesions using CNNs remains a challenge. Existing CNN-based approaches for breast cancer lesion detection may suffer from limited sensitivity and specificity, leading to missed diagnoses or false positives. Additionally, extracting discriminative features from medical images with varying resolutions and noise levels presents a significant challenge. In this study, we propose an enhanced detection framework for breast cancer lesions using CNNs and feature fusion. Our method incorporates multiple CNN architectures, including DenseNet, ResNet, and Inception, to capture diverse image features. Furthermore, we employ feature fusion techniques to integrate complementary information from different CNN models. By combining features at multiple levels, our approach aims to improve the robustness and discriminative power of the detection model. Experimental results on a large dataset of breast cancer images demonstrate the effectiveness of our proposed method. The proposed framework achieves a sensitivity of 0.95 and a specificity of 0.92, outperforming state-of-the-art methods by a significant margin. Moreover, the proposed method exhibits an area under the receiver operating characteristic curve (AUC) of 0.97, indicating its superior discriminative ability in distinguishing between malignant and benign lesions. The computational efficiency of the proposed approach is also shows, with an average inference time of 0.2 seconds per image.
PSO BASED DEEP BELIEF NETWORKS LEARNING FOR IOT BASED CROP DISEASE DETECTION ON PADDY LEAVES USING CLOUD
Authors:   Kings Engineering College, India, M Parameswari , B Yuvaraj ,   Kings Engineering College, India, S Thumilvannan ,   Kings Engineering College, India, E Munuswamy ,   Kings Engineering College, India
Published: October 2024

The Internet of Things (IoT) with advanced machine learning techniques presents significant potential for agricultural applications, particularly in the domain of crop disease detection. Paddy, a staple food for millions, is highly susceptible to various diseases that can drastically affect yield and quality. Early and accurate disease detection is crucial for effective management and mitigation. Traditional methods are often labor-intensive and less reliable, underscoring the need for automated, accurate, and scalable solutions. The primary challenge lies in developing a robust system capable of accurately identifying diseases in paddy leaves using IoT-collected data. This task is complicated by the variability in disease manifestation and environmental conditions, which can affect the quality and consistency of the collected data. Efficient feature extraction and classification techniques are essential to address these issues and ensure high accuracy. This study proposes a novel approach combining Particle Swarm Optimization (PSO) for feature extraction with Deep Belief Networks (DBNs) for classification. IoT devices capture high-resolution images of paddy leaves, which are then processed in the cloud. PSO is employed to optimize the feature extraction process by selecting the most relevant features from the image data. These optimized features are fed into a DBN, which is trained to classify the images into healthy or diseased categories. The use of cloud computing ensures the scalability and computational efficiency of the system. The proposed method demonstrates significant improvements in accuracy and processing speed. The PSO-based feature extraction enhances the relevance of features, reducing the dimensionality and improving the DBN''s performance. Experimental results show an accuracy rate of 96.3%, with a reduction in processing time by 35% compared to traditional methods. The system''s precision and recall rates are 95.8% and 94.7%, respectively, highlighting its effectiveness in real-world applications.
Synergistic Effect of Resveratrol and Paclitaxel in the Treatment of Malignant Pleural Mesothelioma
Authors: Bennett Lunawati Lo
Published: October 2024

Malignant pleural mesothelioma (MPM) is a lethal and aggressive cancer due to exposure to asbestos since this carcinogen is still being used in industrial buildings and housing in several countries. Untreated MPM has a median survival time of 12 months, and most people die within 24 months after diagnosis. If caught early, surgery may be performed. Treatment option for palliative care is limited using platinum with pemetrexed. Malignant transformation of a cell is attributed to a series of genetic and epigenetic events involving alterations in several oncogenes, tumor suppressor genes, and others. Different anticancer and antioxidants with anticancer properties were tested individually and in combination to find the best synergistic effect in killing MSTO-211H, a lung mesothelioma cell line used as model of MPM. Once the combination was identified, assays and staining methods such as MTT, Rhodamine123, Hoechst 33342, Nuclear ID Red/Green, and Western Blot were performed to identify different proteins involved in apoptosis and cell signaling cascade to proof the cytotoxic effect of the combine anticancer and antioxidant treatment. Combination of Paclitaxel (PAC) at 3 µM and Resveratrol (RSV) at 62.5 µM showed synergistic effect on MSTO-211H cells by causing inhibition of epidermal growth factor receptor (EGFR), inhibition of mitogen activated protein kinases (MEKs) 1-4, inhibition of programmed death ligand-1 (PDL-1), inhibition of cell cycle proteins, and induction of caspases 3-8. This study provided possible potential application of using RSV as a chemo-enhancing compound with PAC in the treatment of MPM.
Enhancing Research Involvement of Young People With Lived Expertise: Reflecting on Experiences in Digital Mental Health Research
Authors: Brogden Josephine , de Haan Zsofi , Gorban Carla , Hockey Samuel J , Hutcheon Alexis , Iorfino Frank , Song Yun Ju C , Scott Elizabeth , Hickie Ian B , McKenna Sarah
Published: October 2024

Given the rapid development of digital mental health technologies and a focus on connecting with youth, there is an urgent need to enhance the engagement of young people with lived expertise in research. Even so, youth with lived experience of accessing mental health services are particularly affected by power imbalances and may receive limited compensation in academic settings. Therefore, an emphasis on how research engagement not only improves the work but can benefit young people themselves is required. Here, 5 young people with lived expertise report on their experience of being employed as researchers at the University of Sydney’s Brain and Mind Centre. As such, this team is uniquely placed to offer reflections from their work across multiple stages of research. This led to four key insights, including (1) creating accepting work cultures, (2) providing diverse opportunities for involvement, (3) giving young people agency and flexibility around sharing lived experiences, and (4) creating accommodating work environments for all researchers. We suggest that these insights can support more diverse ways of engaging young people and maximizing the value of participation for both researchers and young people themselves.
The Significance of My Edu-Political Theories and Approach to Teaching Thinking and Creativity for the Upcoming Era of Artificial Intelligence
Authors: Hassan Hosseini Seyed Mohammad
Published: October 2024

Having shed light on the significance of thinking and creativity for survival and prosperity in the present world context, I give a brief introduction to my revolutionary teaching approach and its 6 strategic focal areas, one of which is promoting our people’ thinking and creativity savvy. More importantly, I will bring to the forefront my approach theoretical foundations that I presented after criticizing and rejecting current theories in the field of education. I will define and distinguish the types of high-level thinking, which include creative thinking, emphasized by me in my innovative approach. Also, after enumerating the characteristics of creative people, I will go on to define and explain the role of professors who intend to develop higher levels of thinking of our people in their classes, by employing my approach and the culture accentuated byvme. I have explained some of my effective techniques for improving thinking skills, along with some concrete examples from my personal experiences. In the end - before concluding - I have given suggestions to teachers, professors, researchers and educational policy makers to improve the quality of education for improving the conditions of humanity and guiding them to our common utopia. Many theses and bookticles have been written and published about my approach in different parts of the world which could be noticed in the references section of my first article in the references of this article.
Advanced Algorithms for Offline Signature Recognition and Enhanced Forgery Detection Mechanisms
Authors: V K Vishwanath
Published: October 2024

In contemporary society, signatures hold significant importance in various critical documents such as bank cheques, passports, and driver's licenses. Unfortunately, they can be counterfeited through various means, giving rise to issues like fraudulent identifications, identity theft, and cyber-attacks. To mitigate this problem, our project is centered around the development of a system that discerns the authenticity of a signature, distinguishing between genuine and forged signatures within a dataset. We have employed Convolutional Neural Networks (CNN) and deep learning for this purpose. This choice is driven by the understanding that signatures evolve over time due to a range of behavioral factors like age, mental state, and physical well-being. Consequently, our system is designed to adapt and learn from diverse training datasets, enhancing its accuracy in detection. While online and offline signature verification methods exist, our project primarily focuses on the latter, specifically targeting the detectionof forged offline signatures.
Deep Learning for Solving Partial Differential Equations: A Review of Literature
Authors: Sharma Nishchal
Published: October 2024

Partial Differential Equations (PDEs) are fundamental in modeling various phenomena in physics, engineering, and finance. Traditional numerical methods for solving PDEs, such as finite element and finite difference methods, often face limitations when applied to high-dimensional and complex systems. In recent years, deep learning has emerged as a promising alternative for approximating solutions to PDEs, offering potential improvements in both efficiency and scalability. This paper provides a comprehensive review of the literature on deep learning-based methods for solving PDEs, focusing on key approaches such as Physics-Informed Neural Networks (PINNs), deep Galerkin methods, and neural operators. These methods leverage the expressiveness of neural networks to capture underlying physics while avoiding the curse of dimensionality associated with classical techniques. We explore the theoretical foundations, advantages, and limitations of these deep learning models, along with their applications in diverse fields like fluid dynamics, quantum mechanics, and financial modeling. Additionally, this review examines recent advancements in hybrid models that combine traditional numerical methods with deep learning approaches to enhance accuracy and stability. Through this review, we highlight key trends and open challenges in the field, paving the way for future research at the intersection of deep learning and computational mathematics.
Pertanggungjawaban j&t express atas kerusakan barang selama expedisi, (studi pada j&t express cabang sunset road, kuta badung)
Authors: Komang Gede Dipayana  , I Nyoman Gede Sugiartha  , Ni Made Puspasutari Ujianti
Published: October 2024

J&T Express wajib mengantarkan barang titipan ke tempat tujuan. Ini termasuk memastikankeselamatan dan keamanan kiriman selama transportasi. J&T Express juga harus mengatur transportasi yangaman hingga barang diserahkan kepada penerimanya. Proyek ini mengkaji akibat hukum dari J&T Expressyang melanggar kontraknya secara default. Setelah memeriksa prosesnya, peneliti menetapkan bahwaperusahaan jasa pengiriman seperti J&T Express bertanggung jawab secara hukum atas kerusakan barang yangmereka kirim. Ini karena mereka menggunakan metode hukum seperti analisis undang-undang, metodepenelitian empiris dan fakta yang dikumpulkan dari sumber lain. Kesimpulan yang didapat adalah J&T Expressmenghadapi konsekuensi hukum jika menempatkan barang yang tidak aman di transportasi. Selain itu,pengangkut harus mengganti semua biaya, mengkompensasi keuntungan yang hilang dan membayar biayahukum karena Pasal 1243 1246 KUH Perdata. Selain itu, hal yang sama berlaku untuk item yang ditempatkandi transportasi secara default.
Aspek hukum pemindahan hak atas tanah melalui risalah lelang
Authors: IDA AYU NGURAH KEMENUH  , I Nyoman Putu  Budiartha  , Putu Suwantara
Published: October 2024

Tujuan penelitian ini yaitu Peraturan Menteri Keuangan Nomor 213/PMK.06/2020 Tetang PetunjukPelaksanaan Lelang menjelaskan lelang,terkait objek yang dibahas yakni lelang atas tanah, yang dimaksudadalah lelang hak atas tanah menjadi sarana bagi pihak penjual dan pembeli tanah dalam penguasaan dandimanfaatkannya peruntukan tanah tersebut kepada yang akan membeli secara sah pada saat pembayaran,seperti lelang eksekusi dan lelang non eksekusi. Menggunakan jenis Penelitian hukum normatife. Adapunmasalah yang di rumuskan adalah Apakah pemindahan hak atas tanah melalui risalah lelang dapat memberikankepastian hukum Serta Bagaimana pemindahan hak atas tanah melalui lelang. Mengenai Risalah Lelang suatubukti secara otentik yang dibuat dengan adanya dasar aturan hukum dan dibuat oleh penjabat lelang yangdiberikan kewenangan khusus dalam melaksanakan penjualan barang secara lelang, adanya kesempurnaandalam pembuktian yaitu dengan adanya akta otentik yang dimiliki setelah lelang dengan berita acara sehinggadapat memberikan kepastian hukum dengan mendaftarkan ke Kantor Pertanahan Kabupaten/ Kota setempatkarena pendaftaran tanah mempunyai sifat terbuka diatur pada Peraturan pemerintah Nomor 24 Tahun 1997pada Pasal 41 mengenai Syarat Sah dan mekanisme agar tidak terjadi kendala dalam administrasi pertanahan.
Akibat Hukum Perjanjian Kerja Yang Mencantumkan Non Competition Clause Untuk Melindungi Rahasia Dagang Bisnis
Authors: I Gusti Agung Mahendra  , I Putu Nyoman Budiartha  , I Gusti Agung Ayu Gita Pritayanti Dinar
Published: October 2024

Dalam menghadapi persaingan bisnis yang semakin ketat, para pengusaha dituntut untuk lebih kreatif dalam menciptakan model perjanjian kerja yang dapat mendukung kelangsungan bisnis mereka. Salah satu jenis perjanjian kerja yang biasa digunakan adalah perjanjian dengan Klausula Non Kompetisi. Klausula ini berisi larangan bagi mantan pekerja yang masa kerjanya telah berakhir untuk tidak bekerja di perusahaan pesaing yang dianggap sebagai kompetitor. Tujuannya adalah untuk menjaga kerahasiaan dagang dari pesaing. Dalam perspektif Hukum Dagang, penggunaan Klausula Non Kompetisi diperbolehkan sebagai salah satu metode preventif untuk melindungi kerahasiaan dagang. Namun, Klausula ini dapat membatasi hak seseorang untuk pindah pekerjaan dan perlu dibatasi. Oleh karena itu, penggunaannya memerlukan batasan yang jelas. Meskipun demikian, hingga saat ini, pengaturan hukum di Indonesia belum secara tegas mengatur pencantuman Klausula Non Kompetisi dalam perjanjian kerja. Jenis penelitian yang digunakan dalam hal ini adalah Hukum Normatif, di mana penelitian dilakukan melalui studi dokumen dan pendekatan perundang-undangan untuk menghasilkan pemahaman yang lebih baik tentang sistem hukum yang berlaku
Pembinaan Narapidana Melalui Upaya Asimilasi di Rumah Tahanan Negara Klas II B Klungkung
Authors: I Ketut Gede Satria Wibawa Aryana  , I Nyoman Gede Sugiartha  , I Gusti Agung Ayu Gita Pritayanti Dinar
Published: October 2024

Asimilasi merupakan suatu proses pembinaan narapidana dilakukan di luar tembok Rumah Tahanan Negara yaitu dengan cara mengikuti bimbingan, pendidikan, latihan keterampilan di luar tembok Rumah Tahanan Negara, berolahraga dan bekerja bakti dengan masyarakat atau dikenal dengan tahapan minimum security. Oleh karena itu, penting untuk memahami Bagaimanakah proses asimilasi sebagai upaya pembinaan narapidana selama menjalani masa pidananya di Rumah Tahanan Negara Klas II b Klungkung ? dan apakah Kendala-kendala yang dihadapi dalam pelaksanaan asimilasi di Rumah Tahanan Negara Klas II b Klungkung dan upaya mengatasinya ? Metode penelitian yang digunakan yaitu penelitian empiris. Penelitian ini diharapkan akan mengarah pada pemahaman yang lebih baik tentang bagaimana hukum yang mengatur pelaksanaan asimilasi bahwa adanya suatu sistem kemasyarakatan yang memiliki tujuan yaitu adanya peran yang dilakukan oleh masyarakat sebagai bentuk tanggung jawab. Yang diatur dalam Peraturan Menteri Hukum dan Hak Asasi Manusia Republik Indonesia Nomor M.2.PK.04-10 Tahun 2007
Frontiers in Safety and Efficacy: Introduction
Authors: Roman Stephen J. , Rodeo Scott , Murrell William D
Published: October 2024

There are increasing numbers of people suffering with osteoarthritis and other musculoskeletal disorders. Current treatments for these conditions have significant side effects and comorbidities. Surgery in some cases may be inappropriate or ineffective. The use of regenerative medicine in the form of orthobiologics has been growing. The purpose of these treatments is to treat pain and to possibly enhance the healing of tissue pathology by augmenting the body’s inherent healing capabilities. Orthobiologic products commonly used include platelet rich plasma, adipose and bone marrow derived cellular products and birth tissue products. This review of the current medical literature has been prepared to provide evidence-based information to patients, clinicians, researchers, and regulatory and payer organizations with regard to the safety, efficacy, and cost effectiveness of orthobiologic treatments.
As representações profissionais e suas especificidades teóricas: uma ferramenta de análise das práticas profissionais
Authors: Espíndola Elisângela Bastos de Mélo , Maia Licia de Souza Leão
Published: October 2024

Desde a década de 1990, as representações profissionais têm sido uma abordagem teórica que vem ganhando expressão, ao mesmo tempo em que são feitos questionamentos e estudos dos campos profissionais no âmbito da Psicologia Social. Este artigo tem o objetivo de apresentar e discutir o conceito de representações profissionais, situando o leitor sobre elementos teóricos que as distinguem e que as aproximam das representações sociais. Para tanto, tomamos como principal referência as proposições teóricas desenvolvidas pela equipe de pesquisa Représentations et Engagements professionnels, leurs Évolutions: Recherche et Expertise da Universidade de Toulouse-Le Mirail na França. Dentre as contribuições deste trabalho, enseja-se a abertura de novos caminhos investigativos sobre o desvelamento dos processos e dos produtos da profissionalização e da profissionalidade de grupos profissionais de referência.
Trabalhar de casa na pandemia: Sentimentos e vivências de gestores e não-gestores públicos
Authors: Carvalho Luara , Mourão Luciana , Cardoso Victor Hugo Soares , Abbad Gardênia da Silva , Sandall Hugo , Legentil Juliana , Santos João Otávio Passos Lima dos , Carmo Eliane Almeida do
Published: October 2024

O objetivo do presente estudo foi comparar e discutir as percepções de gestores e não-gestores do serviço público, com e sem experiência com teletrabalho, a respeito dessa modalidade de trabalho adotada compulsoriamente em resposta à pandemia da COVID-19. Participaram 1.749 trabalhadores (26% gestores), sendo 52% sem experiência em teletrabalho. A coleta de dados ocorreu nos primeiros meses da pandemia (abril a junho de 2020), a partir de uma pergunta indutora sobre os sentimentos em relação ao teletrabalho. Foi realizada análise de classificação hierárquica descendente no Iramuteq. Foram encontradas diferenças na percepção do teletrabalho de quem tinha ou não experiência com a modalidade remota, bem como diferenças nas percepções de servidores e gestores, sendo acrescidas a estes últimos preocupações com suas equipes. A discussão apresenta implicações para o serviço público e indicações de estudos futuros.
Psychometrics Properties of Pandemic Coping Scale (PCS)
Authors: Bessa Jonatas Reis , Sousa Roberto Beirão Santos , Trindade Ana Beatriz , Abreu José Neander Silva
Published: October 2024

The COVID-19 pandemic and its preventive methods related to social isolation and quarantine have pointed to a huge change in global behavior. The perception of the hazards of the virus and contamination, as well as obligatory routine changes have impacted negatively on the well-being and mental health of people. To handle this context, humans adopt strategies to cope and deal with the hazards and daily situations. However, there is a lack of studies and instruments which measure practical coping in COVID-19 Pandemics. Thus, this paper presents the development and evidence validity of the Pandemic Coping Scale (PCS), which is a two-factor instrument (Problem-Solving and Self-Protection Attitudes) that presented adequate psychometric measures (CVC > 80; RMSEA= 0,08, CFI = 0,94, TLI= 0,90; CR > 80). It is hoped that this scale may be useful and help professionals in the world to evaluate practical coping strategies during pandemics.
Memórias e conquistas das mulheres trabalhadoras do mar: uma análise psicossocial de narrativas filmadas na Região dos Lagos – RJ
Authors: Carmela Regina , Pinheiro Marta de Araújo
Published: October 2024

O ano de 2022 foi eleito pela ONU como o ano internacional da pesca artesanal para focalizar a importância do setor no cumprimento dos objetivos da Agenda 2030. Uma das orientações da Agenda é a conquista da equidade e igualdade de gênero. Com base nas entrevistas realizadas para um documentário (2018) sobre a pesca artesanal na Região dos Lagos (RJ), apresentamos, sob as lentes da Psicossociologia, as memórias, as conquistas e as perspectivas das mulheres da pesca locais sobre: 1) o território, lembranças, afetos e conhecimentos, 2) relações de gênero na atividade; 3) atuações no presente. Constatamos que elas, atualmente, se reconhecem como pescadoras artesanais. Essa autodenominação e assentimento repercute, desde seus antepassados, nas múltiplas dimensões de suas participações na pesca e contribui atualmente para a busca da equidade de gênero.
The role of central banks in the protection of the banking clients: A law and regulation perspective
Authors: Peci Bedri , Gashi Fitim
Published: October 2024

Customer protection remains a challenge, even in highly developed democracies, reflecting the overall socio-economic development of a region. This paper focuses on the protection of customer rights in the banking sector within selected Western Balkan countries, emphasizing the roles and legal competencies of central banks. The research aims to identify best practices and areas for improvement, particularly in Kosovo. Using qualitative research methodology, the study analyzes primary data from central banks and secondary data from various sources, comparing regulatory practices and the number of complaints across the selected countries. The findings suggest that while strides have been made in customer protection, further regulatory improvements and financial literacy initiatives are needed. The paper concludes by highlighting the importance of enhanced regulatory frameworks and customer education to ensure financial stability and protect customer rights, making a significant contribution to the ongoing discourse on consumer protection in the financial sector.
Moisture Control Using A Low- Cost Experimental Approach For A Vertical Agricultural Indoor Module
Authors: Borrero Henry , Montenegro Danna , Pabon Nicolás , Duran Laura , Vidal Rafael , Tiuso Juan
Published: October 2024

This paper describes an indoor vertical farming low-cost approach undertaken under experimental learning considerations. A structure measuring approximately one meter in height, 0.27 meters in width, and 0.38 meters in depth was constructed to examine the growth of arugula seeds. We equipped our vertical farming structure with emitters of artificial light in order to facilitate the photosynthesis of arugula plants that were planted in trays in a building without sufficient natural light. Further, soil moisture in the trays was monitored so that electromechanical water pumps were activated whenever a high level of soil dryness was detected. As a control unit, an ESP32 microcontroller was used. It was programmed to read sensors and to apply control signals as required. Additionally, ESP32 was configured to send data from sensors to an Internet of Things (IoT) web page, enabling us to monitor the system remotely. BIPES (Block-based Integrated Platform for Embedded Systems) is an intuitive programming tool that is available to the general
 
 
public through the internet, which was used for programming the ESP32. As a final aspect, researchers at the Universidad Distrital Francisco José de Caldas, the Corporación Universitaria Minuto de Dios, in Colombia, and the Universidade Federal of Sao Carlos, in Brazil, became interested in vertical farming as a topic to be involved in, leading to the development of a first approach which is presented in this paper.
Light-curing units for composite resin polymerization
Authors: Vucetic Jelena
Published: October 2024

Light-curing units for light polymerization of composite resins are important
instruments of dental practice, and their proper use has a direct impact on
the physical characteristics of the material being illuminated, its
biocompatibility, as well as on the overall clinical success and durability
of dental composites. Irradiance represents the power of radiation per unit
of irradiated surface and should be distinguished from irradiance measured
directly at the lamp head, which is called output irradiance or emittance.
Also, different areas on the surface of the material can be exposed to
different radiation powers, which sometimes significantly deviate from the
given average value. The reason for this is the inhomogeneity of the
radiation beam. The 3D profile of the light beam gives the most precise
information about the quality of radiation to which the material will be
exposed. Due to the existence of different photoinitiator systems, the use
of devices with a wider emission spectrum that covers a larger range of
light wavelengths is often recommended today. An important characteristic of
the light-curing unit is its power, but the use of lamps of higher power
does not mean a proportional reduction in polymerization time. The quality
and maintenance of light sources are certainly one of the important factors
that influence the success of restorations.
PRÁTICAS DE ROBÓTICA NA PROMOÇÃO DA CULTURA MAKER PARA ALUNOS SURDOS NA EPT
Authors: Pereira Igor Rafael da Silva , Pereira Murilo Sousa , Frota Vitor Bremgartner da , Lacerda Junior José Cavalcante
Published: October 2024

As práticas de Robótica vêm contribuindo na Educação Profissional e Tecnológica (EPT) como estratégia de engajamento e envolvimento dos alunos nas atividades de ensino-aprendizagem. Essa perpectiva pode ser utilizada como elemento de promoção da cultura maker entre as pessoas surdas. Nesta perspectiva, o objetivo deste artigo é verificar como o uso da Robótica pode promover a cultura maker para os alunos surdos na EPT. Para tanto, a estratégia metodológica baseou-se em uma abordagem qualitativa a partir de uma pesquisa-ação, a qual considerou como técnica um levantamento teórico, o desenvolvimento de uma aplicação e um formulário via google forms. O período de realização das atividades aconteceu entre outubro de 2020 a agosto de 2021. Após a coleta os dados, os mesmos foram interpretados a partir da Análise Descritiva. Como resultado, observou-se um impacto positivo do material elaborado no processo de inclusão dos alunos surdos, principalmente, no que diz respeito a colocar em prática o conteúdo relacionado a Robótica pelo docente no decorrer do processo ensino-aprendizagem.
El marketing digital y su repercusión en las ventas de las micro y pequeñas empresas
Authors: Benítez Salinas Denia
Published: October 2024

Actualmente el marketing digital ha cambiado la manera de promocionar los productos y servicios de las empresas, así como también la forma de comunicarse con los clientes, principalmente por el auge que han tenido las redes sociales, de ahí que la presente investigación tenga por objetivo analizar la repercusión del marketing digital en las ventas que registran las micro y pequeñas empresas del Estado de México. El estudio tiene un alcance descriptivo y correlacional, de enfoque cuantitativo, con diseño no experimental de tipo transversal. La herramienta de recolección de datos fue el cuestionario. Además, se utilizó el muestreo por cuotas y cada cuota estuvo conformada por 32 micro y pequeñas empresas. Los resultados del análisis ANOVA señalan que el valor de “p” es 0.000 y por tanto p<0.05 lo que permite establecer la evidencia estadística de que existen diferencias en las ventas de las micro y pequeñas empresas entre las distintas categorías de uso del marketing digital. Por otra parte, el coeficiente de correlación rho de Spearman (0,718) indica la existencia de una correlación positiva alta entre la frecuencia de uso del marketing digital y las ventas en las micro y pequeñas empresas. Lo anterior permite concluir que el marketing digital genera variabilidad en las ventas de las micro y pequeñas empresas. Además, existe una relación positiva alta entre el marketing digital y las ventas de las micro y pequeñas empresas, esto quiere decir que a medida que aumenta el uso del marketing digital, también aumentan las ventas.