bluuebunny/crossref_metadata_2025 huggingface dataset:
Effective multi-class lungdisease classification using the hybridfeature engineering mechanism
Authors: Saju Binju , Tressa Neethu , Dhanaraj Rajesh Kumar , Tharewal Sumegh , Mathew Jincy Chundamannil , Pelusi Danilo
Published: November 2023

The utilization of computational models in the field of medical image classification is an ongoing and unstoppable trend, driven by the pursuit of aiding medical professionals in achieving swift and precise diagnoses. Post COVID-19, many researchers are studying better classification and diagnosis of lung diseases particularly, as it was reported that one of the very few diseases greatly affecting human beings was related to lungs. This research study, as presented in the paper, introduces an advanced computer-assisted model that is specifically tailored for the classification of 13 lung diseases using deep learning techniques, with a focus on analyzing chest radiograph images. The work flows from data collection, image quality enhancement, feature extraction to a comparative classification performance analysis. For data collection, an open-source data set consisting of 112,000 chest X-Ray images was used. Since, the quality of the pictures was significant for the work, enhanced image quality is achieved through preprocessing techniques such as Otsu-based binary conversion, contrast limited adaptive histogram equalization-driven noise reduction, and Canny edge detection. Feature extraction incorporates connected regions, histogram of oriented gradients, gray-level co-occurrence matrix and Haar wavelet transformation, complemented by feature selection via regularized neighbourhood component analysis. The paper proposes an optimized hybrid model, improved Aquila optimization convolutional neural networks (CNN), which is a combination of optimized CNN and DENSENET121 with applied batch equalization, which provides novelty for the model compared with other similar works. The comparative evaluation of classification performance among CNN, DENSENET121 and the proposed hybrid model is also done to find the results. The findings highlight the proposed hybrid model's supremacy, boasting 97.00% accuracy, 94.00% precision, 96.00% sensitivity, 96.00% specificity and 95.00% F1-score. In the future, potential avenues encompass exploring explainable machine learning for discerning model decisions and optimizing performance through strategic model restructuring.
Afrodemia
Authors: Saunders Catherine
Published: November 2023

This chapter examines the unique relationship between African American literature and the historically black institution, arguing that the cultural geographies that permeate the Black literary landscape comprise an academy of its own. This academy emerges in the afterlife of both African American literature and the historically black institution, enabling both to culminate their power through their interior essence. This chapter calls this interior essence Afrodemia—a physical space where learning and self-reflection proves a constant despite not constituting a static place. Afrodemia builds on Derrick Bell's short story “Afrolantica,” particularly, the “liberation of place not of mind” that a mass of land that solely grants access to African Americans engenders (Bell).The author examines Toni Morrison's novels Beloved and Paradise as evidencing Afrodemia in their depiction of griot figures who transform geographical space into a place of mental elevation and their challenge to the idea of paradise, fictional matrices that emerge as fact in the Black institution.
A Course Recommendation Algorithm for a Personalized Online Learning Platform for Students From the Perspective of Deep Learning
Authors: Xu Zhengmeng , Lin Hai , Wu Meiping
Published: November 2023

This paper mainly studies the content of the recommendation algorithm of learning resource courses in online learning platforms such as MOOC and mainly introduces the automatic encoder neural network that integrates course relevance to realize the personalized course recommendation model. The authors first introduce how to embed a course relevance decoder in an autoencoder neural network. Secondly, the proposed confidence matrix method is introduced to distinguish the recommendation effect of the learned to the unlearned courses, and the training process of the model is introduced. Then, the design content of the experiment is introduced, including the model structure, comparative experiments, parameter settings, and evaluation indicators. Finally, the experimental results are analyzed in detail from the horizontal and vertical aspects. It is hoped that this research can provide a reference for personalized recommendation of learning resources based on deep learning technology and big data analysis.
Comparison of Soil Properties in Different Fertilizer Input Systems in Lowland Rice at the Third Year in Transition
Authors: Gunarathne M. H. V. H. Y. , Duminda D. M. S. , Sriyani N. G.
Published: November 2023

Synthetic inorganic fertilizers (SIF) have the potential to impose detrimental environmental effects and are frequently utilized in Sri Lankan conventional rice farming. To maximize rice yield while maintaining soil health, soil nutrient management is vital. In this study, the soil properties of rice fields maintained using conventional (as recommended by the Department of Agriculture (DOA), 2013), reduced (50% DOA + 50% organic), and organic Input Management Systems (IMSs) were studied. The Rajarata University of Sri Lanka's Faculty of Agriculture established this experiment during the Maha season of 2020–2021 utilizing a Randomized Complete Block Design. At the initial, 50% flowering, and harvesting stages, soil samples were obtained from three distinct IMSs with three replicates at surface (0 - 15 cm) and subsurface (15 - 30 cm) soil depths. The data were analyzed using linear mixed effect models followed by Tukey's mean comparison. Three IMSs and three different stages of rice growth exhibited substantially varying soil pH, EC, available P, and exchangeable K values in this third transition year (p<0.05). Despite being highly varying across IMSs, soil CEC was not significantly different (p>0.05) among the stages of rice growth. Three IMSs' soil available N did not change significantly (p>0.05) yet differed across growth stages (p<0.05). In comparison to those obtained with conventional IMS, rice grain yield with organic IMS produced levels that were noticeably similar. The highest grain yield was produced with reduced IMS (p<0.05). This illustrates the possibility of boosting yields and sustaining soil fertility by substituting organic manure for 50% of SIF.
α-Synuclein pathology from the body to the brain: so many seeds so close to the central soil
Authors: Yang Yunying , Zhang Zhentao
Published: November 2023

α-Synuclein is a protein that mainly exists in the presynaptic terminals. Abnormal folding and accumulation of α-synuclein are found in several neurodegenerative diseases, including Parkinson's disease. Aggregated and highly phosphorylated α-synuclein constitutes the main component of Lewy bodies in the brain, the pathological hallmark of Parkinson's disease. For decades, much attention has been focused on the accumulation of α-synuclein in the brain parenchyma rather than considering Parkinson's disease as a systemic disease. Recent evidence demonstrates that, at least in some patients, the initial α-synuclein pathology originates in the peripheral organs and spreads to the brain. Injection of α-synuclein preformed fibrils into the gastrointestinal tract triggers the gut-to-brain propagation of α-synuclein pathology. However, whether α-synuclein pathology can occur spontaneously in peripheral organs independent of exogenous α-synuclein preformed fibrils or pathological α-synuclein leakage from the central nervous system remains under investigation. In this review, we aimed to summarize the role of peripheral α-synuclein pathology in the pathogenesis of Parkinson's disease. We also discuss the pathways by which α-synuclein pathology spreads from the body to the brain.
Melatonin improves synapse development by PI3K/Akt signaling in a mouse model of autism spectrum disorder
Authors: Wang Luyi , Xu Man , Wang Yan , Wang Feifei , Deng Jing , Wang Xiaoya , Zhao Yu , Liao Ailing , Yang Feng , Wang Shali , Li Yingbo
Published: November 2023

JOURNAL/nrgr/04.03/01300535-202407000-00043/figure1/v/2023-11-20T171125Z/r/image-tiff

Autism spectrum disorders are a group of neurodevelopmental disorders involving more than 1100 genes, including Ctnnd2 as a candidate gene. Ctnnd2 knockout mice, serving as an animal model of autism, have been demonstrated to exhibit decreased density of dendritic spines. The role of melatonin, as a neurohormone capable of effectively alleviating social interaction deficits and regulating the development of dendritic spines, in Ctnnd2 deletion-induced nerve injury remains unclear. In the present study, we discovered that the deletion of exon 2 of the Ctnnd2 gene was linked to social interaction deficits, spine loss, impaired inhibitory neurons, and suppressed phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt) signal pathway in the prefrontal cortex. Our findings demonstrated that the long-term oral administration of melatonin for 28 days effectively alleviated the aforementioned abnormalities in Ctnnd2 gene-knockout mice. Furthermore, the administration of melatonin in the prefrontal cortex was found to improve synaptic function and activate the PI3K/Akt signal pathway in this region. The pharmacological blockade of the PI3K/Akt signal pathway with a PI3K/Akt inhibitor, wortmannin, and melatonin receptor antagonists, luzindole and 4-phenyl-2-propionamidotetralin, prevented the melatonin-induced enhancement of GABAergic synaptic function. These findings suggest that melatonin treatment can ameliorate GABAergic synaptic function by activating the PI3K/Akt signal pathway, which may contribute to the improvement of dendritic spine abnormalities in autism spectrum disorders.
How do lateral septum projections to the ventral CA1 influence sociability?
Authors: Wang Dan , Zhao Di , Wang Wentao , Hu Fengai , Cui Minghu , Liu Jing , Meng Fantao , Liu Cuilan , Qiu Changyun , Liu Dunjiang , Xu Zhicheng , Wang Yameng , Zhang Yu , Li Wei , Li Chen
Published: November 2023

JOURNAL/nrgr/04.03/01300535-202408000-00033/figure1/v/2024-02-22T141052Z/r/image-tiff

Social dysfunction is a risk factor for several neuropsychiatric illnesses. Previous studies have shown that the lateral septum (LS)-related pathway plays a critical role in mediating social behaviors. However, the role of the connections between the LS and its downstream brain regions in social behaviors remains unclear. In this study, we conducted a three-chamber test using electrophysiological and chemogenetic approaches in mice to determine how LS projections to ventral CA1 (vCA1) influence sociability. Our results showed that gamma-aminobutyric acid (GABA)-ergic neurons were activated following social experience, and that social behaviors were enhanced by chemogenetic modulation of these neurons. Moreover, LS GABAergic neurons extended their functional neural connections via vCA1 glutamatergic pyramidal neurons, and regulating LSGABA→vCA1Glu neural projections affected social behaviors, which were impeded by suppressing LS-projecting vCA1 neuronal activity or inhibiting GABAA receptors in vCA1. These findings support the hypothesis that LS inputs to the vCA1 can control social preferences and social novelty behaviors. These findings provide new insights regarding the neural circuits that regulate sociability.
Crosstalk among mitophagy, pyroptosis, ferroptosis, and necroptosis in central nervous system injuries
Authors: Zhang Li , Hu Zhigang , Li Zhenxing , Lin Yixing
Published: November 2023

Central nervous system injuries have a high rate of resulting in disability and mortality; however, at present, effective treatments are lacking. Programmed cell death, which is a genetically determined form of active and ordered cell death with many types, has recently attracted increasing attention due to its functions in determining the fate of cell survival. A growing number of studies have suggested that programmed cell death is involved in central nervous system injuries and plays an important role in the progression of brain damage. In this review, we provide an overview of the role of programmed cell death in central nervous system injuries, including the pathways involved in mitophagy, pyroptosis, ferroptosis, and necroptosis, and the underlying mechanisms by which mitophagy regulates pyroptosis, ferroptosis, and necroptosis. We also discuss the new direction of therapeutic strategies targeting mitophagy for the treatment of central nervous system injuries, with the aim to determine the connection between programmed cell death and central nervous system injuries and to identify new therapies to modulate programmed cell death following central nervous system injury. In conclusion, based on these properties and effects, interventions targeting programmed cell death could be developed as potential therapeutic agents for central nervous system injury patients.
Ferroptosis mechanism and Alzheimer's disease
Authors: Feng Lina , Sun Jingyi , Xia Ling , Shi Qiang , Hou Yajun , Zhang Lili , Li Mingquan , Fan Cundong , Sun Baoliang
Published: November 2023

Regulated cell death is a genetically determined form of programmed cell death that commonly occurs during the development of living organisms. This process plays a crucial role in modulating homeostasis and is evolutionarily conserved across a diverse range of living organisms. Ferroptosis is a classic regulatory mode of cell death. Extensive studies of regulatory cell death in Alzheimer's disease have yielded increasing evidence that ferroptosis is closely related to the occurrence, development, and prognosis of Alzheimer's disease. This review summarizes the molecular mechanisms of ferroptosis and recent research advances in the role of ferroptosis in Alzheimer's disease. Our findings are expected to serve as a theoretical and experimental foundation for clinical research and targeted therapy for Alzheimer's disease.
The role of snapin in regulation of brain homeostasis
Authors: Li Jiawen , Huang Xinqi , An Yumei , Chen Xueshi , Chen Yiyang , Xu Mingyuan , Shan Haiyan , Zhang Mingyang
Published: November 2023

Brain homeostasis refers to the normal working state of the brain in a certain period, which is important for overall health and normal life activities. Currently, there is a lack of effective treatment methods for the adverse consequences caused by brain homeostasis imbalance. Snapin is a protein that assists in the formation of neuronal synapses and plays a crucial role in the normal growth and development of synapses. Recently, many researchers have reported the association between snapin and neurologic and psychiatric disorders, demonstrating that snapin can improve brain homeostasis. Clinical manifestations of brain disease often involve imbalances in brain homeostasis and may lead to neurological and behavioral sequelae. This article aims to explore the role of snapin in restoring brain homeostasis after injury or diseases, highlighting its significance in maintaining brain homeostasis and treating brain diseases. Additionally, it comprehensively discusses the implications of snapin in other extracerebral diseases such as diabetes and viral infections, with the objective of determining the clinical potential of snapin in maintaining brain homeostasis.
Heparin-Induced Thrombocytopenia in Hemodialysis Patients– The First Study from India
Authors: Sivaprakasam Yogalakshmi , Chadha Shiv , Kotwal Jyoti , Gupta Anurag , Tiwari Vaibhav , Bhargava Vinant , Mallik Manish , Gupta Ashwini , Bhalla Anil K. , Rana Devinder S.
Published: November 2023

Heparin-induced thrombocytopenia (HIT), a rare complication of heparin therapy, presents with thrombocytopenia. It leads to paradoxical thromboembolism and has high mortality if untreated. It is less recognized, especially in hemodialysis (HD) patients who are frequently exposed to heparin during dialysis because patients with renal failure may have many other causes of thrombocytopenia. We describe the clinical presentation, diagnosis, and treatment of five cases of confirmed HIT in hemodialysis (HD) patients at our center. The initial suspicion was made based on a high 4T score and positive gel card test followed by confirmation using the functional assay with heparin-induced platelet aggregation. These patients were treated according to the recent American Society of Hematology guidelines 2018 for HIT.
Dorfman–Chanarin Syndrome with Renal Involvement: A Rare Case Report and Literature Review
Authors: Agrebi Ikram , Jaziri Achraf , Kanoun Houda , Dammak Najla , Boudabous Mouna , Toumi Salma , Yaich Soumaya , Tahri Nabil , Kammoun Arwa , Makni Hafedh , Kammoun Khawla , Boudawara Tahya , Hmida Mohamed Ben
Published: November 2023

Dorfman–Chanarin syndrome (DCS) is a rare autosomal recessive disease. It is a multisystemic disease in which renal involvement is uncommon. We report the case of a woman with nephrotic syndrome associated with DCS. A 36-year-old woman was referred to the nephrology department for edema with known history for DCS. On physical examination, she had ichthyosiform erythroderma with generalized scaly skinand ascites. The ophthalmologic examination revealed a cataract in the right eye. Abdominal ultrasound examination showed hepatomegaly and splenomegaly. Laboratory tests showed normal renal and liver function. The blood cell count showed pancytopenia. Immunologic exams showed the presence of anti-mitochondrial antibodies. Kidney biopsy showed mesangial proliferative glomerulonephritis with extensive lipid vacuoles in the tubular epithelial cells. Immunofluorescence study showed mesangial deposits of IgG, C3, kappa, and lambda. To the best of our knowledge, this is the first case of DCS with renal involvement reported in an adult.
From farm to gut: Unraveling the role of millets in promoting metabolic well-being via gut microbiota
Authors: Singh S B , Meena Ajay Kumar , Sisodia Brijesh Singh , Sharma Savita , Sharma MM , Mansoria Poornima
Published: November 2023

The human gut microbiota plays a pivotal role in influencing various physiological functions and human health. Dysbiosis, the disruption of gut microbial composition, has been associated with the development of chronic diseases. Dietary interventions, including the consumption of millets, have emerged as a promising strategy to modulate gut microbiota and promote metabolic health. Millets, small-seeded grains cultivated for centuries, offer rich nutritional profiles and bioactive compounds. Their gluten-free nature makes them suitable for individuals with gluten sensitivity. The review explores the intricate relationship between millets and gut microbiota, emphasizing the mechanisms through which millets influence gut microbial composition and functionality. Millets' prebiotic properties and fermentation lead to the production of short-chain fatty acids, promoting gut barrier function and reducing inflammation. additionally, millet consumption may impact gut hormones and exhibit antioxidant and anti-inflammatory effects. The impact of millets on metabolic health is evident, with studies demonstrating improved glycemic control and lipid profiles. Understanding these mechanisms provides valuable insights for personalized dietary recommendations, gut microbiota-targeted interventions, and integrating millets into public health initiatives. Promoting millet cultivation aligns with sustainable food systems, making it a holistic approach to combat metabolic disorders and enhance overall human health.
Detecting circulating microbial cell-free DNA by next-generation sequencing in patients with Mycobacterium avium complex-lung disease: A pilot study
Authors: Tseng Yen-Han , Pan Sheng-Wei , Feng Jia-Yih , Su Wei-Juin , Huang Chi-Ying F , Chen Yuh-Min
Published: November 2023

ABSTRACT

Objectives:

Determining a diagnosis for non-Tuberculous mycobacterium (NTM)-lung disease (LD) remains difficult. The value of circulating cell-free DNA (cfDNA) secreted from microbes has been established in the detection of pathogens in septic patients. However, it is unknown whether NTM-derived cfDNA is detectable in plasma from patients with NTM-LD and whether this is associated with the disease status of NTM-LD, especially in patients with Mycobacterium avium complex (MAC)-LD.

Materials and Methods:

In this pilot study, from 2018 to 2019, we enrolled adult patients with MAC-LD at Taipei Veterans General Hospital in Taiwan for the detection of circulating cfDNA. We performed cfDNA extraction from plasma, next-generation sequencing (NGS) for nonhuman cfDNA, and sequence matching to a microbial database and then assessed the association between pathogen cfDNA and MAC-LD.

Results:

Two (40%) plasma samples from MAC-LD patients had detectable MAC-specific cfDNA, namely one instance of DNA polymerase III alpha subunit and one instance of ATP-binding cassette transporters permease. The plasma samples from the three other MAC-LD cases and the one tuberculosis control were negative for either NTM-derived cfDNA or tuberculosis-related cfDNA. In addition to MAC-specific cfDNA, Ralstonia solanacearum, Staphylococcus aureus, and Pasteurella multocida were the most observed bacteria in our patients. The two patients with MAC-cfDNA positivity yielded higher radiographic scores (P = 0.076) and presented a higher number of nonhuman reads than those without MAC-cfDNA positivity (P = 0.083).

Conclusion:

Using NGS method, we demonstrated MAC-cfDNA was detectable in patients with MAC-LD. Further large-scale research is warranted to assess the clinical value of detecting MAC-specific cfDNA in MAC-LD patients.
Diabetic Retinopathy Classification Using Deep Learning
Authors: Sathwik Abbaraju Sai , Agarwal Raghav , Jubilson E Ajith , Basa Santi Swarup
Published: November 2023

One of the main causes of adult blindness and a frequent consequence of diabetes is diabetic retinopathy (DR). To avoid visual loss, DR must be promptly identified and classified. In this article, we suggest an automated DR detection and classification method based on deep learning applied to fundus pictures. The suggested technique uses transfer learning for classification. On a dataset of 3,662 fundus images with real-world DR severity labels, we trained and validated our model. According to our findings, the suggested technique successfully detected and classified DR with an overall accuracy of 78.14%. Our model fared better than other recent cutting-edge techniques, illuminating the promise of deep learning-based strategies for DR detection and management. Our research indicates that the suggested technique may be employed as a screening tool for DR in a clinical environment, enabling early illness diagnosis and prompt treatment.
Dynamic Voltage Restorer to Mitigate Voltage Sag/Swell using Black Widow Optimization Technique with FOPID Controller
Authors: Srikanth Goud B. , Kiran Kumar M. , Ashok Kumar Narisetti , Naga Sai Kalyan CH. , Bajaj Mohit , Choudhury Subhashree , Shukla Swati
Published: November 2023

The efficiency with which electrical equipment use electricity is essential for several reasons. First, superior power quality (PQ) improves efficiency and facilitates peak performance in electronic equipment. This article's goal is to make the advantages of installing a Dynamic Voltage Restorer (DVR) to enhance PQ for energy users clearer. To improve DVR dependability and user friendliness, the suggested technique uses a hysteresis voltage control system that works with variable switching frequency. Simulation findings show that voltage compensation is successful under disturbances when a black widow optimization (BWO) based Factional order proportional derivative (FOPID) controller is used. This paper proposed is to improve PQ using a BWO- FOPID controller and compare the outcomes to those achieved from a previously developed PI controller in a distribution power system using MATLAB.
10‐GHz band 2 × 2 phased‐array radio frequency receiver with 8‐bit linear phase control and 15‐dB gain control range using 65‐nm complementary metal–oxide–semiconductor technology
Authors: Han Seon‐Ho , Koo Bon‐Tae
Published: November 2023

We propose a 10‐GHz 2 × 2 phased‐array radio frequency (RF) receiver with an 8‐bit linear phase and 15‐dB gain control range using 65‐nm complementary metal–oxide–semiconductor technology. An 8 × 8 phased‐array receiver module is implemented using 16 2 × 2 RF phased‐array integrated circuits. The receiver chip has four single‐to‐differential low‐noise amplifier and gain‐controlled phase‐shifter (GCPS) channels, four channel combiners, and a 50‐Ω driver. Using a novel complementary bias technique in a phase‐shifting core circuit and an equivalent resistance‐controlled resistor–inductor–capacitor load, the GCPS based on vector–sum structure increases the phase resolution with weighting‐factor controllability, enabling the vector–sum phase‐shifting circuit to require a low current and small area due to its small 1.2‐V supply. The 2 × 2 phased‐array RF receiver chip has a power gain of 21 dB per channel and a 5.7‐dB maximum single‐channel noise‐figure gain. The chip shows 8‐bit phase states with a 2.39° root mean‐square (RMS) phase error and a 0.4‐dB RMS gain error with a 15‐dB gain control range for a 2.5° RMS phase error over the 10 to10.5‐GHz band.
Machine Learning for Benchmarking Critical Care Outcomes
Authors: Atallah Louis , Nabian Mohsen , Brochini Ludmila , Amelung Pamela J.
Published: November 2023

Objectives: Enhancing critical care efficacy involves evaluating and improving system functioning. Benchmarking, a retrospective comparison of results against standards, aids risk-adjusted assessment and helps healthcare providers identify areas for improvement based on observed and predicted outcomes. The last two decades have seen the development of several models using machine learning (ML) for clinical outcome prediction. ML is a field of artificial intelligence focused on creating algorithms that enable computers to learn from and make predictions or decisions based on data. This narrative review centers on key discoveries and outcomes to aid clinicians and researchers in selecting the optimal methodology for critical care benchmarking using ML.Methods: We used PubMed to search the literature from 2003 to 2023 regarding predictive models utilizing ML for mortality (592 articles), length of stay (143 articles), or mechanical ventilation (195 articles). We supplemented the PubMed search with Google Scholar, making sure relevant articles were included. Given the narrative style, papers in the cohort were manually curated for a comprehensive reader perspective.Results: Our report presents comparative results for benchmarked outcomes and emphasizes advancements in feature types, preprocessing, model selection, and validation. It showcases instances where ML effectively tackled critical care outcome-prediction challenges, including nonlinear relationships, class imbalances, missing data, and documentation variability, leading to enhanced results.Conclusions: Although ML has provided novel tools to improve the benchmarking of critical care outcomes, areas that require further research include class imbalance, fairness, improved calibration, generalizability, and long-term validation of published models.
Requirements for Trustworthy Artificial Intelligence and its Application in Healthcare
Authors: Kim Myeongju , Sohn Hyoju , Choi Sookyung , Kim Sejoong
Published: November 2023

Objectives: Artificial intelligence (AI) technologies are developing very rapidly in the medical field, but have yet to be actively used in actual clinical settings. Ensuring reliability is essential to disseminating technologies, necessitating a wide range of research and subsequent social consensus on requirements for trustworthy AI.Methods: This review divided the requirements for trustworthy medical AI into explainability, fairness, privacy protection, and robustness, investigated research trends in the literature on AI in healthcare, and explored the criteria for trustworthy AI in the medical field.Results: Explainability provides a basis for determining whether healthcare providers would refer to the output of an AI model, which requires the further development of explainable AI technology, evaluation methods, and user interfaces. For AI fairness, the primary task is to identify evaluation metrics optimized for the medical field. As for privacy and robustness, further development of technologies is needed, especially in defending training data or AI algorithms against adversarial attacks.Conclusions: In the future, detailed standards need to be established according to the issues that medical AI would solve or the clinical field where medical AI would be used. Furthermore, these criteria should be reflected in AI-related regulations, such as AI development guidelines and approval processes for medical devices.
Benefits of Information Technology in Healthcare: Artificial Intelligence, Internet of Things, and Personal Health Records
Authors: Chang Hyejung , Choi Jae-Young , Shim Jaesun , Kim Mihui , Choi Mona
Published: November 2023

Objectives: Systematic evaluations of the benefits of health information technology (HIT) play an essential role in enhancing healthcare quality by improving outcomes. However, there is limited empirical evidence regarding the benefits of IT adoption in healthcare settings. This study aimed to review the benefits of artificial intelligence (AI), the internet of things (IoT), and personal health records (PHR), based on scientific evidence.Methods: The literature published in peer-reviewed journals between 2016 and 2022 was searched for systematic reviews and meta-analysis studies using the PubMed, Cochrane, and Embase databases. Manual searches were also performed using the reference lists of systematic reviews and eligible studies from major health informatics journals. The benefits of each HIT were assessed from multiple perspectives across four outcome domains.Results: Twenty-four systematic review or meta-analysis studies on AI, IoT, and PHR were identified. The benefits of each HIT were assessed and summarized from a multifaceted perspective, focusing on four outcome domains: clinical, psycho-behavioral, managerial, and socioeconomic. The benefits varied depending on the nature of each type of HIT and the diseases to which they were applied.Conclusions: Overall, our review indicates that AI and PHR can positively impact clinical outcomes, while IoT holds potential for improving managerial efficiency. Despite ongoing research into the benefits of health IT in line with advances in healthcare, the existing evidence is limited in both volume and scope. The findings of our study can help identify areas for further investigation.
Evaluating the Landscape of Personal Health Records in Korea: Results of the National Health Informatization Survey
Authors: Lee Kyehwa , Lee Yura , Lee Jae-Ho
Published: November 2023

Objectives: This study examined the adoption and utilization of personal health records (PHR) across Korean medical institutions using data from the 2020 National Health and Medical Informatization Survey.Methods: Spearheaded by the Ministry of Health and Welfare and prominent academic societies, this study surveyed PHR utilization in 574 medical institutions.Results: Among these institutions, 84.9% (487 hospitals) maintained medical portals. However, just 14.1% (81 hospitals) had web-based or mobile PHRs, with 66.7% (28 of 42) of tertiary care hospitals adopting them. Tertiary hospitals led in PHR services: 87.8% offered certification issuance, 51.2% provided educational information, 63.4% supported online payment, and 95.1% managed appointment reservations. In contrast, general and smaller hospitals had lower rates. Online medical information viewing was prominent in tertiary hospitals (64.3%). Most patients accessed test results via PHRs, but other data types were less frequent, and only a few allowed downloads. Despite the widespread access to medical data through PHRs, integration with wearables and biometric data transfers to electronic medical records remained low, with limited plans for expansion in the coming three years.Conclusions: Approximately two-thirds of the surveyed medical institutions provided PHRs, but hospitals and clinics in charge of community care had very limited PHR implementation. Government-led leadership is required to invigorate the use of PHRs in medical institutions.
Wymiar misyjny formacji w Wyższym Seminarium Misyjnym Księży Sercanów w Stadnikach
Authors: Poleszak Leszek
Published: November 2023

Formacja do prezbiteratu w Wyższym Seminarium Misyjnym Księży Sercanów w Stadnikach uwzględnia istotny element formacji charyzmatycznej i pastoralnej, jakim jest formacja do misji. Jest to konsekwencją charyzmatu Zgromadzenia Księży Najświętszego Serca Jezusowego, który zaangażowanie w misje traktuje jako jeden z ważnych wymiarów pracy apostolskiej i formę głoszenia miłości Najświętszego Serca Jezusowego. Celem artykułu jest przedstawienie różnorodnych wymiarów formacji misyjnej kandydatów do kapłaństwa, a także ukazanie jej owoców.

The missionary dimension of formation at the Major Mission Seminary of the Priests of the Sacred Heart in Stadniki: Formation for the priesthood at the Major Mission Seminary of the Priests of the Sacred Heart in Stadniki includes a main element of charismatic and pastoral formation, which is formation for missions. This is a consequence of the charism of the Congregation of the Priests of the Sacred Heart of Jesus, which treats involvement in missions as one of the important dimensions of apostolic work and a form of proclaiming the love of the Sacred Heart of Jesus. The aim of the article is to present various dimensions of the missionary formation of candidates for priesthood, as well as to show its fruits.
The Development of an E-book Based on Local Wisdom Around Bromo Tengger Semeru National Park to Train High School Students' Creative Thinking Skill
Authors: Nadya Eka Aristyasari  , Yuliani Yuliani , Indana Sifak
Published: November 2023

Objective: This research aims to produce an e-book based on local wisdom on the use of medicinal plants by the people around Bromo Tengger Semeru National Park on plantae material to train students' creative thinking skills. Method: The research uses the ADDIE development model (analysis, design, development, implementation, and evaluation). Data retrieval through a validation process by three validators, namely education experts, material experts, and biology teachers, practicality through readability tests. Results: The results of the e-book validation get an average high score with very valid criteria. The practicality of the e-book is measured based on the readability test. The readability test results show the readability level at level 10 so that it is suitable for use by grade X students. Novelty: Students' creative thinking skills can be trained by integrating local wisdom with various learning media such as books, modules, and student worksheets, both printed and electronic.
Digital Era for Quality Education: Effectiveness of Discovery Learning with Android to Increase Scientific Literacy
Authors: Karimah Uswatun , Sunarti Titin , Munasir Munasir
Published: November 2023

Objective: This study analyzes the effectiveness of discovery learning models integrated with Android. Method: The method used is the literature review method. A literature review is a type of research used to collect data and information from various references. This research analyzes 20 national and international articles that can be accounted for. The articles used are articles published in 2018-2023. The steps taken in this study are identifying topics, finding and selecting appropriate articles, analyzing and synthesizing literature, and concluding. Results: Based on the results of research and analysis, it can be supposed that (1) the application of the discovery learning model can improve students' scientific literacy; (2) The use of Android in learning can improve students' scientific literacy. Novelty: This research reveals that integrating discovery learning learning models with androids can improve students' scientific literacy. This discovery invites researchers, educators, and governments to develop and facilitate discovery learning integrated with Android.
Uprooting Entrenched Gender Biases in Climate-Smart Agriculture
Authors: Chakraborty Ananya , Elwell Natalie , Beal Catherine
Published: November 2023

This paper discusses the barriers to and enabling conditions for designing and implementing gender-responsive climate-smart agriculture (CSA) initiatives. Through examples, the paper identifies lessons and promising practices for addressing gender issues across the range of CSA interventions from farm level practices and systems approaches to the enabling environment. Through two deep dive case studies, the paper showcases the potential for CSA to contribute to gender-transformative results and offers recommendations for doing so.
The Efficacy and Safety of Oral Propranolol in Hemangioma of PHACES Syndrome: A Case Report
Authors: Kondo Rogério Nabor
Published: November 2023

PHACES syndrome is a rare condition characterized by the association of infantile hemangioma with malformations of the posterior fossa of the brain, arterial anomalies of the central nervous system, heart defects, ocular changes and sternal cleft. The use of propranolol in the treatment of infantile hemangioma is well established, but in PHACES syndrome there is still controversy. We use propranolol in this syndrome with good results and safety.
Finding Your First Job: Are Orthopedists in Training and Hiring Medical Practices on the Same Page?
Authors: Davis D David
Published: November 2023

A study of orthopedic surgeons in training and hiring practices that is designed to investigate the priorities of applicants and employers in the hiring process.

Introduction: This study was designed to determine important factors to hiring practices when evaluating the application of a potential hire and compare them with the factors emphasized by candidates as most important to them in a job.

Methods: This survey was designed to compare the priorities of hiring practices to job applicants with regards to several categories including: how applicants and jobs are identified, what factors might be important to a practice when evaluating job applicants and what factors might be important to a job applicant when applying. Hiring practices were further asked to elaborate on previous unsuccessful hires and the reasons for failure.

Results: Hiring practices and applicants agree that personal or professional referrals are the most important resource for finding a job, but disagree in the utility of recruiters and social media. Hiring practices and potential applicants agree that the need for a particular subspecialty and recommendations are the most important factors for a practice to consider when choosing a new hire. Applicants tend to place a higher value on commitment to a region, personal connections and fellowship prestige, while practices are more interested in recommendations from residency directors, prior employers, operative ability and community involvement. Applicants and hiring practices both understand that the ability to practice within one’s subspecialty, salary potential and a candidate’s preference for location are critical. Hiring practices underestimate the importance of a starting salary and signing bonus to an applicant and overestimate the importance of practice reputation and the availability of ancillary services.

Discussion/Conclusion: There are significant misunderstandings between young surgeons applying for their first job and hiring practices. To be successful young physicians should strive to understand the motivations of hiring groups. Similarly, orthopedic practices can save themselves significant time and money by understanding the motivations of surgeons entering the work force.
About sequentially open and closed subsets in product spaces
Authors: MUCUK Osman , TEKE Mina Betül
Published: November 2023

We remind two facts for topological spaces. The one is that in a Hausdorff space $X$ each sequence has a unique limit. This allows us to have a function from the set of all sequences in $X$ to $X$. Another is that in the first countable spaces some topological objects such as open subsets, closed subsets, closures and interiors of the sets, continuous functions and many others can be defined in terms of convergent sequences.

In this paper we compare these notions with their sequential versions in topological spaces. We will take the product spaces into account and give some results.
Sinergi Antara Pelaksanaan Pembelajaran Berdiferensiasi dengan Teaching at The Right Level dalam Menghadirkan Lingkungan Belajar Inklusif
Authors: Prihandini Dwi Rani , Azizah Siti Alfiyana , Atikah Isma
Published: November 2023

The current learning paradigm has shifted towards student-centered learning. Therefore, teachers need to design learning experiences while considering the characteristics of students comprehensively. This study aims to identify the positive impacts that arise from students and teachers during the implementation of differentiated learning activities with the Teaching at the Right Level (TaRL) approach in the classroom. The research method used is qualitative with a descriptive approach. The research subjects were the 11th-grade students of MIPA 5 at SMAN 1 Tanggul. The observation results indicate that students are more active in learning activities, and their participation in learning is better monitored. Based on the research results presented, it is evident that the implementation of differentiated learning with the TaRL approach has a positive impact on learning and helps create an inclusive and responsive learning environment to meet the needs of the students.
Pengaruh Motivasi dan Disiplin Kerja terhadap Kinerja Karyawan pada PT Mitra Dana Top Finance Cabang Bandung
Authors: Prayogi Muhammad Sandi , Atmawinata Maya R.
Published: November 2023

Muhammad Sandi Prayogi1,  

Program Studi S1 Manajemen, Universitas Teknologi Digital

muhammadsandiprayogi19@student.stembi.ac.id 1 ,

 

ABSTRACT

This study aims to determine the effect of work motivation and discipline on employee performance at PT. Mitra Dana Top Finance Branch Bandung. The method used is descriptive and quality with a quantitative approach. The population in this study were all employees of PT. Mitra Dana Top Finance Branch Bandung, while the sampling technique used the Non-Probability Sampling technique or saturated samples, amounting 40 respondents. The data collection methods used questionnaires, observation and literature studies, while data analysis methods used quality tests, classical assumption tests, and hypothesis testing using the Programs Statistics SPSS 26. The results of this study motivation have a positive and significant effect on employee performance with a tcount of 2.721 > ttable of 2.026 and sig. 0.010 < a 0.05, and work discipline also has a positive and significant effect on employee performance with a tcount of 2.707 > ttable of 2.026 and sig. 0.010 < a 0.05. The R2 value in this study was obtained at 45.2% which indicates that work motivation and discipline affect employee performance, while the remaining 54.8% is influenced by other factors that were not examined in this study.

Keywords: Motivation, Work Discipline and Employee Performance.
Cognitive flexibility and research output among librarians in polytechnic libraries in South-South, Nigeria
Authors: Oni Osaheni , Adomi Esharenana E.
Published: November 2023

This study investigated the cognitive flexibility and research output of librarians in polytechnic libraries in South-South, Nigeria. This study adopted an ex-post facto research design and used a questionnaire to collect data from librarians in polytechnic libraries in South-South, Nigeria. This study revealed a negative relationship between cognitive flexibility and the research output of librarians in polytechnic libraries in South-South Nigeria. This means that the relationship is limited. The study also pointed out that cognitive flexibility will significantly predict librarians’ career research output in polytechnic libraries in southern Nigeria. This study generated important findings that are capable of ensuring that librarians’ cognitive flexibility is reflected in their research output through effective self-development training programmes on task switching and adaptability to improve research output.
Development of an Animal Farm Robotic Feeding System
Authors: Uzedhe Godwin O. , Akinloye Benjamin O. , Febaide Isaac C.
Published: November 2023

Feeding of farm animals is an essential factor for animal growth and productivity. The traditional manual feeding systems of farm animals have been posed with lots of challenges ranging from the high cost of manpower to poor feed management. Existing automatic feeding systems are expensive and are usually fixed systems. This paper presents an autonomous robotic system that collects and delivers feed to farm animals. The system design consists of an automatic feed dispensing system and an unmanned ground robotic vehicle. The vehicle collects feeds from the feed dispensing unit for delivery at the animal pen house in a soft real-time order. An enclosed environment, as is found in many farm animal production settings, is used to enable auto-navigation of the robot system within the farm. Auto-navigation, feed collection and delivery functions are implemented using ultrasonic sensor and infrared (IR) proximity sensors in a microcontroller (Atmega328p) based hardware and firmware control algorithm. Control parameter variation was achieved through Bluetooth (HC-05) interface communication with a mobile device. Experimental test and data collection from the system indicates the system can autonomously supply 26.6kg worth of feed within 1hr at a speed of 1.233km/h and apply to feeding various kinds of farm animals.
The influence of addition maja fruit peel extract as inhibitor on the corrosion rate of stainless steel and carbon steel
Authors: Sintha  Soraya  Santi  , Ika  Nawang  Puspitawati  , Kindriari  Nurma  Wahyusi  , Siti  Mariyatul  Azizah  , Kevin  Nahila Wahyu Ranawijaya
Published: November 2023

Corrosion can cause serious damage, such as a piece of equipment or a decrease in tool life. The materials used in an industry, its use can be seen in factory flow pipes that carry a substance, which is one of the factors causing corrosion. The aim of this research is to determine the performance of maja rind extract as an inhibitor of stainless steel and carbon steel corrosion rates, to determine the inhibition efficiency of maja rind extract in controlling the corrosion rate of stainless steel and carbon steel. Method use in this reasearch extraction and polarization. The best concentration in controlling the corrosion rate of SS 304 was obtained at 100 ppm with a corrosion rate of 0.00963 mpy, for SS 316 it was obtained at 100 ppm with a corrosion rate of 0.00521 mpy, while on steel plate it was obtained at 100 ppm with a corrosion rate of 0.00774 mpy. The best inhibitor efficiency on SS 304 can reach 97.6% with the best concentration of 100 ppm, on SS 316 it can reach 99.4% with the best concentration of 100 ppm, and on steel plate it can reach 98.84% with the best concentration of 100 ppm.
Social values, criminal risks, and security
Authors: Fîrțală Valeriu , Cristea Darie
Published: November 2023

Compliance with the provisions of legal norms and prosocial conduct are directly related to the value system protected by these norms. The voluntary conformity of an individual to normative precepts is largely ensured by the consonance between the social values system to which significant majorities adhere in a society. The criminal risk increases as the values of the social group of belonging become more and more distant from the social values protected by normative acts. Such situations can be normal consequences of social change. The challenge posed by dissonances between formal and informal value systems has always been difficult for decision and policy makers to manage.