bluuebunny/crossref_metadata_2025_split huggingface dataset:
PerFedNILM: A Practical Personalized Federated Learning-based non-Intrusive Load Monitoring
Authors: Pan Zibin , Wang Haosheng , Li Chi , Wang Haijin , Zhao Junhua 
Published: October 2023

Abstract
Non-Intrusive Load Monitoring (NILM) is a valuable technique for breaking down overall power consumption into the energy usage of individual appliances. Understanding power usage patterns through NILM plays an important role in reducing energy costs and achieving carbon reduction goals. However, privacy concerns often deter consumers from sharing their electricity consumption data. To address these privacy concerns, Federated Learning (FL) has been introduced in NILM, which enables the training of NILM models while keeping power consumers' data locally. However, FL's reliance on a single global model leads to poor performance on clients with unique power consumption patterns. In response to this challenge, we present a Personalized Federated Learning NILM algorithm (PerFedNILM), a practical personalized FL approach for NILM. PerFedNILM limits the local update bias across clients and trains personalized models for individual clients to improve load monitoring performance. Additionally, it mitigates the negative impact of client dropout, which is a common issue in practice. Our experiments on using real-world energy data demonstrate that PerFedNILM outperforms previous FL-based NILM methods, especially in client dropout scenarios.
Identification of 5236-Year Lunar Calendrical Data Cycle Comprising of 2702-year and 2534-year asymmetric Sub-Cycles in respect of Conjunction Based Pure Lunar Calendar
Authors: Mir Ghulam Nabi , Banday Shoaib 
Published: October 2023

Abstract
The United Nations Periodical ’State Of World Population’, authored by United Nations Population Fund, in its April 2023 issue, has declared World Population having crossed eight (8) Billion figure on November 15, 2022. Muslims, who constitute 24.9 percent of the World Population and, who are currently standing on the threshold of breaching the two(2) Billion mark, find themselves in very embarrassing situations every now & then due to the absence of an accurate, internationally accepted and shariah-compliant pure Lunar Calendar. For Muslims, there is a highly stressed religious obligation to celebrate all Islamic events as per the Islamic Lunar Hijri Calendar dates. This Calendar, also referred to simply as ’the Hijri Calendar’, is a pure lunar calendar, bound to the phases of the moon, unlike the Jewish, the Chinese and the Hindu Luni-Solar arrangements, and the start of month is marked by the physical sighting of young waxing crescent through unaided eyes. This dependence of a pure Islamic Lunar Calendar on actual astronomical observation of a young waxing crescent makes the prediction of the length of months difficult. The prediction rules/ criteria for earliest visibility of new moon were formulated as early as 300 B.C. by the Chinese and the Babylonians, followed by some good follow-up work by the Hindus. Later on, the subject attracted the best of Muslim scientific minds throughout the peak of Islamic Sciences and culminated in the formulation of a no. of prediction rules/ generalizations. However, with the fall of the Golden Muslim Era, these evolving prediction rules were pushed to oblivion for centuries together. It is only during the last century or so, that the quest into the crescent challenge has got rejuvenated and upgradation of existing astronomical criteria for better accuracy as well as formulation of new ones is well and truly underway. This work, involving the study of Lunar Calendrical Data for almost 8 Millennia from 2700 B.H. to 5500 A.H. has established that the Conjunction-Based Pure Lunar Calendrical System operates in continuous Data Cycles of 5236 Years, with an average value of 354.36707 days per year and 29.530589 days per month. The revelations are most probably going to shape-up the formulation of an Islamic Lunar Calendar with International Applicability.
A Privacy Providing Context-based Trust Model for OSN and its Relation to GDPR
Authors: Voloch Nadav , Gal-Oz Nurit , Gudes Ehud 
Published: October 2023

Abstract
Users’ privacy has become a key objective inthe operation of Online Social Networks (OSN), whichinvolves major concerns regarding personal data exposure and processing. It became a demand with the raiseof legislative initiatives such as the General Data Protection Regulation (GDPR) in the EU that affects mostof the commercial companies, government institutions,and other sectors that process personal data. While thesubject of ensuring privacy in OSN is widely addressedin current research, we focus on challenges related toseveral principles concerning the right to the protectionof personal data, as defined by the GDPR. In previousresearch we have devised a comprehensive Trust-basedModel for Social Networks, that uses Trust, Access Control and Flow Control, to enhance users’ control overtheir data. Users of social networks share data of various contexts, and for a specific user, some contexts aremore sensitive than others. In this paper we use contextdependent trust to build a refined model for controllingpersonal content that aligns with the users’ preferences.We propose a context-based trust model that involvesuser actions, OSN features and OSN activities. It provides a means for revealing the sources of sensitive datadissemination and prevents them from happening. Wevalidate this model by analyzing trust using sentimentanalysis of posts in a real network. The context-basedmodel we present in this paper, addresses the need toestablish an infrastructure for the enforcement of dataprotection rules, concerning users’ privacy in OSN, suchas data minimization and the right-to-be-forgotten. Wealso propose a solution for Digital Rights Management(DRM) to control and manage access to copyrightedmaterial.
Association of Immune-inflammation-based prognostic index with depression: A cross-sectional analysis of NHANES data
Authors: Li Li , Yin Kailin , Wang Xintong , Zheng Yawei , Wu Minghua , Li Hui , Li Wenlei 
Published: October 2023

Abstract
Background:
Immune-inflammatory mediators might modulate a wide range of immune and inflammatory processes，resulting in an increased risk of depression. The objective of this study was to assess the association between Systemic Immune-inflammation Index (SII) and depression through a population-based retrospective cohort of the National Health and Nutrition Examination Survey from 2005 to 2020.
Methods:
The 2005–2020 data of enrolled participants from the National Health and Nutrition Examination Survey were selected. Among them, non-pregnant adults with complete data of SII and Patient Health Questionnaire-9 (PHQ9) questionnaire were included in the study. The depression was assessed with PHQ9 questionnaire. The restricted cubic spline (RCS) was used to flexibly simulate the association of SII with the incidence of depression. Taking SII as an independent variable and the incidence of depression as a dependent variable, logistic regression analysis was conducted to analyze the correlation between SII and the incidence of depression. We further transformed SII from a continuous variable to a classified variable (tierce) for sensitivity analysis. A series of subgroup analysis were used to explore whether the research results applied to specific people. Where there was evidence of non-linearity, piecewise-linear models with change points were fitted for depression of overall participants and specific populations to quantify associations.
Results:
After screening, a total of 42,133 subjects were finally included in the study. After adjusting for covariates, the RCS analysis indicated that log2-SII was associated with the incidence of depression in a J-shaped curve with a nonlinear relationship, and the inflection point of the curve was log2-SII=8.50 (95%CI: 8.42-8.57). We estimated that log2-SII was in the range of 8.42-8.57, and the incidence of depression was the lowest, with a positive correlation above (P < 0.05) and a negative correlation below (P > 0.05). When log2-SII > 8.50, the incidence of depression increased by 18% (OR=1.18, 95%CI: 1.10-1.27) with one additional unit of log2-SII. The results of subgroup analysis suggested that the correlation between SII and the incidence of depression was not consistent in different subgroups.
Conclusion:
In conclusion, our ﬁndings suggest that SII was significantly associated with depression regardless of the potential confounders in a complicated non-linear manner. Further basic andprospective studies are needed to explore the effect of SII on depression.
Moyamoya Disease Manifesting as Paroxysmal Kinesigenic Dystonia: A Case Report and Literature Review
Authors: Chenxi Yang , Daiquan Gao , Yunzhou Zhang , Junqiu Zhou 
Published: October 2023

Abstract
Background: Moyamoya disease (MMD) is an uncommon intracranial vasculopathy that typically presents with ischemic or hemorrhagic stroke. Dyskinesia is a rare manifestation of MMD.
Case presentation: We report a patient with MMD presenting with paroxysmal kinesigenic dystonia (PKD). Magnetic resonance imaging (MRI) and Digital subtraction angiography (DSA) were performed to confirm the diagnosis. Electroencephalogram and cognition assessment were also applied. A MRI of the brain showed infraction. DSA showed stenosis of the bilateral internal carotid and middle cerebral artery with prominent basal collaterals, which was compatible with MMD. We also review the cases of Moyamoya-induced dyskinesia reported previously.
Conclusions: PKD might be a rare manifestation of MMD. MMD should be considered in the differential diagnosis of PKD.
The Growth, Geography, and Implications of Trade in Digital Products
Authors: Hidalgo César , Stojkoski Viktor , Koch Philipp , Coll Eva 
Published: October 2023

Abstract

Despite global efforts to harmonize international trade statistics, our understanding about trade in digital products and its implications remains elusive. Here, we study five key aspects of trade in digital products by introducing a novel dataset on the exports and imports of digital products. First, we show that compared to trade in physical goods, the origin of digital products exports is more spatially concentrated. Second, we show that between 2016 and 2021 trade in digital products grew faster than physical trade, at an annualized growth rate of 20% compared to 6% for physical trade. Third, we show that trade in digital products is large enough to partly offset some important trade balance estimates, like the physical trade deficit of the United States. Fourth, we show that countries that have decoupled economic growth from greenhouse gas emissions have larger and faster growing exports in digital product sectors. Finally, we add digital products to measures of economic complexity, showing that digital products tend to rank high in terms of sophistication contributing positively to the complexity of digital exporters. These findings provide a novel lens to understand the impact of the digital sector in the evolving geography of global trade.
The impact of perceived social support and nursing care satisfaction on the level of hope enhancement among cancer patients
Authors: Cal Ayse , Nalbant Guler 
Published: October 2023

Abstract
Objectives This study was carried out to examine the impact of perceived levels of social support and nursing care satisfaction on the level of hope among cancer patients.
Methods The study was carried out using a descriptive research design. The research sample consisted of 250 cancer patients receiving treatment at the radiation oncology clinic of an education and research hospital in the Black Sea region. The data collection instruments included the Demographic Information Form, the Cancer Patient Social Support Scale, the NEWCASTLE Satisfaction with Nursing Care Scale, and the Herth Hope Index. Data were reported based on descriptive statistics, Pearson correlation analysis, and multiple regression analysis results.
Results It was observed that perceived social support, satisfaction with nursing care, and age explained 23% of the variation in hope levels among cancer patients. The relationship between age and hope was found to be weak and negative. The relationship between hope and social support is moderate, while the relationship between nursing care satisfaction and hope is weak but positive.
Conclusions It can be concluded that hope for the future tends to increase among cancer patients who are relatively younger, have higher levels of social support, and report higher levels of satisfaction with nursing care.
Longitudinal Subcortical Volumes and Neurodevelopment in Extremely Preterm Children Treated Early with Katona Neurohabilitation
Authors: Castro-Chavira Susana A. , Gutiérrez-Hernández Claudia C. , Carrillo-Prado Cristina , Harmony Thalía 
Published: October 2023

Abstract
Preterm birth incidence has increased in recent years and is associated with a rise in long-term neurological and developmental sequelae in children. Because the morbidity and prevalence of developmental deficits increase as the number of weeks of gestation decreases, extremely preterm infants are at greater risk of developing cerebral palsy, severe cognitive impairment, epilepsy, attention/hyperactivity disorders, learning disorders, and autism spectrum disorders. In this study, 15 participants born extremely preterm were followed up from two months until past three years of age. During the first months of postnatal life, the participants received Katona neurohabilitation, which provides vestibular and proprioceptive stimulation through the intensive practice of genetically determined, human-specific elementary movements that present early in life. Subcortical brain volumes from brain magnetic resonance images acquired at the beginning and after the intervention, treatment adherence to Katona neurohabilitation therapy, and neurodevelopmental outcomes were collected. Absolute subcortical volumes increased after treatment, except for pallidum and thalamus. When these subcortical volumes were divided by the total intracranial volume, most volumes decreased, except those for the right amygdala and both hippocampi. The inhibition of subcortical function that results in cortical control and increased connectivity may explain these decreases. The regression analyses showed that after-treatment hippocampal volumes had a discrete predictive value. However, treatment adherence showed a clear association as a predictor of mental and psychomotor neurodevelopment after treatment. Thus, treatment adherence constitutes a relevant factor for the Katona neurohabilitation effectivity.
Precision-guided treatment improves outcomes for children with high-risk cancers
Authors: Ziegler David , Lau Loretta , Khuong-Quang Dong-Anh , Mayoh Chelsea , Wong Marie , Barahona Paulette , Ajuyah Pamela , Senapati Akanksha , Nagabushan Sumanth , Sherstyuk Alexandra , Altekoester Ann-Kristin , Fuentes-Bolanos Noemi , Yeung Veronica , Sullivan Ashleigh , Diamond Yonatan , Omer Natacha , Jessop Sophie , Battaglia Lauren , Zhukova Nataliya , Cui Louise , Lin Angela , Gifford Andrew , Fleuren Emmy , Dalla-Pozza Luciano , Moore Andrew , Khaw Seong_Lin , Eisenstat David , Gottardo Nick , Wood Paul , Tapp Heather , Alvaro Frank , McCowage Geoffrey , Nicholls Wayne , Hansford Jordan , Manoharan Neevika , Kotecha Rishi , Mateos Marion , Lock Richard , Tyrrell Vanessa , Haber Michelle , Trahair Toby , Cowley Mark , Ekert Paul , Marshall Glenn 
Published: October 2023

Abstract

Recent reports have shown that precision medicine can identify new treatment strategies for childhood cancer patients. However, it remains unclear which patients will benefit most from precision-guided treatment (PGT). Here we report 384 consecutive high-risk childhood cancer patients (with an expected cure rate of <30%) who had at least 18 months of follow-up on the ZERO Childhood Cancer Program PRISM trial. A total of 256 (67%) patients received PGT recommendations, of whom 110 (43%) received a recommended treatment. PGT resulted in a 36% objective response rate and improved 2-year progression-free survival compared with standard of care (26% vs. 12%; P=0.049) or targeted agents not guided by molecular findings (26% vs. 5.2%; P=0.003). PGT based on Tier 1 evidence, PGT targeting fusions or commenced prior to disease progression had the greatest clinical benefit. Our data show that PGT informed by comprehensive molecular profiling significantly improves outcomes for children with high-risk cancers.
The impact of supportive supervision of nurses on access to healthcare in Sub-Saharan Africa: A systematic review
Authors: Serapelwane Maserapelo Gladys , Bam Nokwanda Edith , Kovane Gaotswake Patience 
Published: October 2023

Abstract

Supportive supervision of nurses including access to healthcare is a global health concern predominantly in the Sub- Saharan countries. For improvement of access to healthcare, the nurses should receive supportive supervision in their working environment. Hence the current study aimed at systematically reviewing literature regarding the impact of supportive supervision of nurses on access to healthcare.
Methods: We searched for articles that were written in English from 2013 to 2023. Medline, PubMed, Science Direct, SA ePublication, Ebscohost, Scopus, Google Scholar, and Web of Science were data bases used for searching of articles. The instrument used to report the identified studies was the PRISMA checklist. Eleven questions appearing on the critical appraisal checklist for Joanna Briggs Institute was applied for quality assessment of studies that were meeting the criteria for review.
Results: A total of 274 articles were retrieved and data was extracted from 10 articles that passed legibility criteria. Factors related to the positive impact of supportive supervision of nurses on access to health care emerged. factors related to the negative impact of supportive supervision of nurses on access to health care is also discovered.
Conclusions: Improved work performance is evident on nurses receiving supportive supervision thus leading to improved access to healthcare. Poor access to healthcare services resulted because of unsupportive supervision and dictatorial leadership style.
Hybrid Approach for MRI Segmentation using Deep Learning and Machine Learning Algorithms
Authors: Mandala Suresh Kumar , Gurrapu Neelima 
Published: October 2023

Abstract
Accurate MRI segmentation is a crucial part of modern medical diagnostics and is essential for early disease diagnosis and effective treatment planning. Vision Transformers (ViT), Kernel-Based Convolutional Neural Networks (CNN), and Multi-Class Support Vector Machines (M-SVM) are all presented in this study as part of a novel hybrid approach to MRI segmentation that improves accuracy and efficiency.Our method employs ViT, which rapidly extracts high-level features from MRI patches, in combination with kernel-based convolutional neural networks, which are well-known for their ability to capture intricate patterns in image data. The M-SVM then refines the classification process, separating the pixels into distinct classes that are suggestive of different tissue types, and the segmentation phase begins without any problems. In addition to increasing the accuracy of MRI segmentation, initial findings suggest that this novel method might set an innovative standard for the analysis of medical images. This research has the potential to be an important development in medical imaging, which would significantly advance the current state of the art in healthcare technology by improving the accuracy with which diagnoses are made and the effectiveness of treatment plans.
Friction taper stitch welding of a duplex stainless steel
Authors: Ram Rapaka , Lessa Cleber Rodrigo de Lima , Lemos Guilherme Vieira Braga , Figueiredo Arlan Pacheco , Vicharapu Buchibabu , Clarke Thomas , De Amitava 
Published: October 2023

Abstract

Friction taper stitch welding (FTSW) is a novel technique that uses multiple inserts to conceal surface crack in a given substrate. The inserts are rotated and forced to fill the crack as plasticized material, and forge with the substrate in solid-state. The process is well suited for alloys such as duplex stainless steel, which suffers degradation of properties during fusion welding. A detailed experimental and theoretical investigation is presented here on FTSW of a duplex stainless steel (DSS). The experimental results show the presence of a ferrite-rich phase along the joint interface. The computed results from the numerical process model reveal a direct influence of thermal cycle on the ferritization along the joint interface. The welded joint area shows near homogeneous structure and properties similar to those of the substrate.
Intuitionistic Fuzzy Approch to Triopoly Games
Authors: Thasneem S. A.Sahathana , Sasikala G. 
Published: October 2023

Abstract
This paper proposes a technique for solving triopoly game with Triangular Intuitionistic Fuzzy Numbers as payoffs. The players in the game interacts strategically without cooperating with one another. The suggested method is applied in a numerical example of internet service providers, which is helpful for the suppliers to make decisions on their costs effectively.
A Polynomial Series-based data aggregation and spectrum aware clustering technique for a combined model of WSN and cognitive radios in IoT applications
Authors: Kalburgi Shivaraj Sharanabasappa , Manimozhi M. 
Published: October 2023

Abstract
Currently, the demand for wireless communication has increased drastically due to the emergence of IoT based applications. In this field, wireless sensor networks have acquired huge attention from the research community, academia, and industries. Generally, these sensor networks and IoTs operate in the license-free spectrum where numerous other devices also operate which leads to generating interference and impacts the Quality of Service (QoS) of these communication systems. To handle this issue, cognitive radio communication technology is a viable solution which facilitates opportunistic access to the spectrum which allows sensor networks to operate in licensed bands. This approach helps to mitigate the interference and improves the performance of the communication system. However, incorporating cognitive radio network with IoT and sensor networks is an encouraging method to proliferate the performance of wireless communication but CRs perform several tasks which consume excessive energy as the sensor networks are equipped with limited power and computation resources. Moreover, continuous data collection leads to gather huge amount of data which suffers from redundancy. Thus, the research community has suggested incorporating the aggregation method to discard the data redundancy. On the other hand, energy aware routing is also considered as novel solution to abate energy depletion during data exchange. In this work, we have focused on a combined model of WSN and cognitive radios for IoT based applications and presented a polynomial series-based data aggregation and spectrum aware clustering technique. The proposed approach achieves overall packet delivery as 95.47%, energy consumption as 5.216J and delay as 0.554 s, which shows better performance when compared with existing schemes in CRSNs.