bluuebunny/crossref_metadata_2025_split huggingface dataset:
Permutation Entropy Does Not Track the Electroencephalogram-Related Manifestations of Paradoxical Excitation During Propofol-Induced Loss of Responsiveness: Results From a Prospective Observational Cohort Study
Authors: Ostertag Julian , Zanner Robert , Schneider Gerhard , Kreuzer Matthias 
Published: February 2024

BACKGROUND:
During the anesthetic-induced loss of responsiveness (LOR), a “paradoxical excitation” with activation of β-frequencies in the electroencephalogram (EEG) can be observed. Thus, spectral parameters—as widely used in commercial anesthesia monitoring devices—may mistakenly indicate that patients are awake when they are actually losing responsiveness. Nonlinear time-domain parameters such as permutation entropy (PeEn) may analyze additional EEG information and appropriately reflect the change in cognitive state during the transition. Determining which parameters correctly track the level of anesthesia is essential for designing monitoring algorithms but may also give valuable insight regarding the signal characteristics during state transitions.

METHODS:
EEG data from 60 patients who underwent general anesthesia were extracted and analyzed around LOR. We derived the following information from the power spectrum: (i) spectral band power, (ii) the spectral edge frequency as well as 2 parameters known to be incorporated in monitoring systems, (iii) beta ratio, and (iv) spectral entropy. We also calculated (v) PeEn as a time-domain parameter. We used Friedman’s test and Bonferroni correction to track how the parameters change over time and the area under the receiver operating curve to separate the power spectra between time points.

RESULTS:
Within our patient collective, we observed a “paradoxical excitation” around the time of LOR as indicated by increasing beta-band power. Spectral edge frequency and spectral entropy values increased from 19.78 [10.25–34.18] Hz to 25.39 [22.46–30.27] Hz (P = .0122) and from 0.61 [0.54–0.75] to 0.77 [0.64–0.81] (P < .0001), respectively, before LOR, indicating a (paradoxically) higher level of high-frequency activity. PeEn and beta ratio values decrease from 0.78 [0.77–0.82] to 0.76 [0.73–0.81] (P < .0001) and from −0.74 [−1.14 to −0.09] to −2.58 [−2.83 to −1.77] (P < .0001), respectively, better reflecting the state transition into anesthesia.

CONCLUSIONS:
PeEn and beta ratio seem suitable parameters to monitor the state transition during anesthesia induction. The decreasing PeEn values suggest a reduction of signal complexity and information content, which may very well describe the clinical situation at LOR. The beta ratio mainly focuses on the loss of power in the gamma-band. PeEn, in particular, may present a single parameter capable of tracking the LOR transition without being affected by paradoxical excitation.
Drying Characteristics of Cacao Beans using Modified Solar Tunnel Dryer Type Hohenheim
Authors: Khathir* Rita , Kurniawan Edi , Yunita Yunita , Syafriandi Syafriandi 
Published: February 2024

Drying cacao has been conducted by open-sun drying systems by farmers worldwide. To improve the cacao drying, the use of solar dryers can be applied. The objective of this study was to evaluate the drying characteristics of using a modified solar tunnel dryer type Hohenheim in drying cacao. As a comparison, the sun-drying method was also conducted. The parameters observed were temperature, relative humidity (RH), weight loss, moisture content, fat content, hardness, and drying rate. Results showed that the average temperature of the Hohenheim dryer was higher at about 10°C than the ambient temperature. However, the Hohenheim dryer's drying temperature fluctuated due to the oscillation of solar irradiation. The drying process took time for 12h in 2 days. The humidity in the drying chamber was high, above 50%, representing that the dryer needed additional fans to improve its air circulation. The final moisture content of cacao dried using Hohenheim dryer and sun-drying was 12.7 and 17.4%, respectively. The drying rate of cacao dried using a Hohenheim dryer was double that of sun-drying. Therefore, the dryer can speed up the drying time and protect the cacao from contamination.
Auswirkungen der Medizinprodukteverordnung auf ML-Lösungen in Schweizer Spitälern
Authors: Russ Christian , Stalder Philipp H. , Rufinatscha Stefanie , Pimentel Tibor , Geissmann Lukas 
Published: February 2024

ZusammenfassungKünstliche Intelligenz (KI) ist schon länger in den Spitälern direkt und indirekt präsent. Oftmals ist KI für Arbeitsplatzfunktionen im Bürobereich wie z. B. in Spracherkennungssoftware verfügbar, teilweise auch in Personal- und Ressourcen-Optimierungssoftware. Das Spektrum reicht speziell im medizinischen Bereich von datengetriebenen Analysen und Informationsunterstützungssystemen bis hin zur Generierung von Diagnose- und Therapievorschlägen für das medizinische Personal. Jedoch sind vielen Akteuren in den Spitälern der Umfang und die Auswirkung von KI-Technologien gar nicht wirklich bewusst. Noch weniger bekannt sind dabei die regulatorischen Vorgaben in Kombination mit dem Einsatz von Maschinellem Lernen (ML). Basierend auf einer repräsentativen Befragung von allgemeinen Spitälern in der Schweiz wurde der aktuelle Stand der KI-Nutzung erhoben. Auf dieser Basis werden die Anforderungen an ML-Systeme in Bezug auf die Medizinprodukteverordnung und deren Auswirkung in Hinblick auf den konformen Einsatz von medizinischer Software analysiert. Wir präsentieren einen Vorschlag, wie ML-Systeme besser mit den Regulatorien in Einklang gebracht werden können. Im Ausblick wird auf die möglichen Grenzen und Notwendigkeiten für zukünftige Weiterentwicklungen eingegangen.
Production and evaluation of an antiserum against envelope protein VP28 of white spot syndrome virus
Authors: Van Hau Nguyen , Trong Tri Do Nguyen , Thanh Nguyen Le , Hong Linh Le , My Trinh Nguyen Thi 
Published: February 2024

Virus-associated white spot syndrome (WSSV) is one of the most popular diseases in shrimp, causing a huge economic loss globally and also in Vietnam. Protein VP28 plays an important role in the initial steps of WSSV infection into shrimp cells. This protein binds to the shrimp cells as a viral adhesion molecule and then helps the virus enter the host cells. Therefore, many studies and applications related to the control of this virus have targeted VP28 as a potential antigen. To facilitate the study and application of VP28, this study focused on the development of a VP28-specific antiserum. The E. coli BL21(DE3)/pQE30-vp28 cells were cultured in LB medium supplemented with 100 µg/mL ampicillin and 0.5 mM IPTG was added to induce the expression of VP28. The cells were then disrupted by sonication and the supernatant fraction was used to purify VP28 using Ni-NTA affinity chromatography. The purified VP28 was injected into rabbits following a 90-day immunization protocol. The serum was then collected and validated for the ability to detect VP28 in Western Blot and ELISA. We found that the obtained antiserum could bind to both the recombinant and native VP28 in Western Blot assay. We also demonstrated that the antiserum could recognize VP28 in ELISA with the sensitivity of <0.39 ng/wells VP28 and the titer of 1/1,280,000. We successfully produced an anti-VP28 antiserum which can be used as a primary antibody in Western Blot and ELISA.
Explorando los imaginarios sociales sobre la paz en niños de la vereda Palmarito en Fortul-Arauca: un enfoque visual
Authors: Ortiz Barroso Sandy , Cáceres Cortés Henry 
Published: February 2024

En el siguiente artículo se presentan los resultados de la investigación realizada en el Centro Educativo Palmarito, del municipio de Fortul en el departamento de Arauca; una región afectada por el conflicto armado en Colombia. Su objetivo fue describir los imaginarios de paz presentes en niños y niñas de quinto grado entre los 9 y 11 años de edad. Para ello, se adoptó una metodología de corte cualitativo, a partir del método etnográfico, donde la recolección de información se dio desde talleres de expresión artística como el dibujo, la pintura y el collage; y la aplicación de entrevistas semiestructuradas. Los hallazgos revelaron que los niños y las niñas perciben la paz como la ausencia de guerra y conflictos, la protección del medio ambiente, la satisfacción de necesidades básicas, al igual que como estados de bienestar, tranquilidad, armonía y felicidad y la implementación de diversas tácticas para la resolución de los conflictos de manera pacífica. En este sentido, estos hallazgos se consolidan como un recurso valioso para desarrollar estrategias y herramientas que promuevan la construcción de la paz en Colombia. La originalidad está dada por la relevancia del arte como elemento para poder analizar la paz como categoría principal y para establecer relaciones entre los imaginarios con la sociedad; además, previo a la revisión de literatura, se puede determinar que este estudio es pionero en su naturaleza puesto que, en el departamento de Arauca y en el municipio de Fortul no se han desarrollado investigaciones dirigidas a indagar en cómo los niños piensan e imaginan la paz.
Extractive Knowledge:
Authors: McHugh Nancy , Kennedy Samantha , Wright Ashley 
Published: February 2024

Extractive knowledge is prevalent in higher education community engagement and is a type of epistemic injustice that is harmful to the marginalized communities and community nonprofits that many universities, particularly predominately white institutions, seek to engage. Extractive knowledge results from what we can think of as transactional relationships with community members or community nonprofits. These are largely superficial but impactful, relationships that perpetuate injustice in higher education spaces that imagine themselves to be working to create greater justice. This paper has two aims: 1. To develop the concept of extractive knowledge in community engagement, showing the ways that it is a type of epistemic injustice. 2. To share strategies and examples for more epistemically just approaches to community engagement that shape knowledge in ways that are epistemically responsible, in partnership with communities, and in alignment with community goals and outcomes. We provide the Fitz Center for Leadership in Community Practice Principles as an approach that can move higher education institutions toward transformative community engagement. The paper finishes with the Fitz Center’s Health Equity Program and another partnership as examples of the use of these Practice Principles to leading toward reciprocal, responsible, community-driven, transformational community engagement.
Relationship between Socio-economic Factors and Electrical Energy Consumption of Customer Groups in Indonesia
Authors: Mire Muhammad Saleh , Budi Suharto Rachmad 
Published: February 2024

The research aim was to study Socio-Economic Analysis and its Relationship with Electrical Energy Consumption of Customer Groups in Indonesia using secondary data from 2018-2022 covering 34 provinces in Indonesia. Data sources generally come from Central Bureau of Statistics (BPS) and State Electricity Company (PLN) Indonesia.
The results of the analysis show that GDP per capita, education and MSMEs have a significant negative influence on poverty in Indonesia. Furthermore, GDP per capita is the only variable that has a significant positive effect on electricity consumption, while education, MSMEs and poverty have no effect on residential electricity consumption.
In the industry group, all variables have a significant effect on household consumption, except for education which has an insignificant effect, GDP per capita and MSMEs have a significant positive effect on electricity consumption, apart from that, education and poverty also have an effect but are not significant in the Business group. The research results also show that poverty does not have a significant impact, but GDP per capita, education and MSMEs have a significant positive influence on social electricity consumption. Furthermore, in the Government Office Buildings (GOB) group, GDP per capita and MSMEs have a significant positive effect, however, education and poverty do not have an influence on electricity consumption in this group. Finally, in the Public Street Lighting (PSL) group, GDP per capita, MSMEs and poverty have no effect, but MSMEs have an influence on electricity consumption.
Efficient Task Scheduling Approach in Edge-Cloud Continuum based on Flower Pollination and Improved Shuffled Frog Leaping Algorithm
Authors: Dankolo Nasiru Muhammad Dankolo , Radzi Nor Haizan Mohamed , Mustaffa Noorfa Haszlinna , Talib Mohd Shukor , Yunos Zuraihati Mohd , Gabi Danlami 
Published: February 2024

The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. Existing research used metaheuristic algorithm to solve tak scheduling problem, however, must of the existing metaheuristics used suffers from falling into local mina due to their inefficiency to avoid unfeasible region in the solution search space. Therefore, there is a dire need for an efficient metaheuristic algorithm for task scheduling. This study proposed an FPA-ISFLA task scheduling model using hybrid flower pollination and improved shuffled frog leaping algorithms. The simulation results indicate that the FPA-ISFLA algorithm is superior to the PSO algorithm in terms of makespan time, resource utilization, and execution cost reduction, especially with an increasing number of tasks.
Prioritized Text Detergent: Comparing Two Judgment Scales of Analytic Hierarchy Process on Prioritizing Pre-Processing Techniques on Social Media Sentiment Analysis
Authors: Zaki Ummu Hani’ Hair , Ibrahim Roliana , Abd Halim Shahliza , Kamsani Izyan Izzati 
Published: February 2024

تستخدم معظم الشركات بيانات وسائل التواصل الاجتماعي للأعمال. يقوم تحليل المشاعر تلقائيًا بجمع التحليلات وتلخيص هذا النوع من البيانات. من الصعب إدارة بيانات وسائل التواصل الاجتماعي غير المنظمة. حيث تمثل البيانات المزعجة او غير متناسقة تحديًا لتحليل المشاعر. نظرًا لأن أكثر من 50٪ من عملية تحليل المشاعر هي معالجة مسبقة للبيانات، فإن معالجة بيانات الوسائط الاجتماعية الضخمة تمثل تحديًا أيضًا. إذا تم إجراء المعالجة المسبقة بشكل صحيح، فقد تتحسن دقة البيانات. أيضًا، يعتمد سير العمل في تحليل المشاعر بشكل كبير. نظرًا لعدم وجود تقنية معالجة مسبقة تعمل بشكل جيد في جميع المواقف أو مع جميع مصادر البيانات، فإن اختيار أهم المصادر أمر بالغ الأهمية. تحديد الأولويات هو أسلوب ممتاز لاختيار الأكثر أهمية.باعتبارها إحدى طرق اتخاذ القرار متعدد المعايير (MCDM)، تُفضل عملية التحليل الهرمي (AHP) التعامل مع تحديات صنع القرار المعقدة باستخدام عدة معايير. تم استخدام درجات نسبة الاتساق (CR) لفحص المقارنات الزوجية لتقييم AHP. استخدمت هذه الدراسة مقياسين للحصول على الحكم الأكثر اتساقًا. أولاً، مقياس حكم Saaty (SS)، ثم المقياس المتوازن المعمم (GBS). لقد تم التحقق فيما إذا كان هناك مقياسان مختلفان لحكم AHP سيؤثران على صنع القرار. المعايير الرئيسية لتحديد أولوية تقنيات المعالجة المسبقة في تحليل المشاعر هي علامات الترقيم والإملاء والرقم والسياق. تحتوى هذه المعايير الأربعة أيضا معايير فرعية. تكون مقارنات الزوجية GBS أقرب إلى قيمة CR من SS، مما يقلل من نسب وزن البدائل.تشرح هذه الورقة كيف يساعد AHP في اتخاذ القرار المنطقي. يمكن أن يكون تحديد أولوية تقنيات المعالجة المسبقة باستخدام AHP نموذجًا لمراحل تحليل المشاعر الأخرى. باختصار، تضيف هذه الورقة مساهمة أخرى إلى مجال تحليلات البيانات الضخمة.
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
Authors: Al Abid Faisal Bin , Bakri Aryati Binti , Alam Md. Golam Rabiul , Uddin Jia , Chowdhury Shefayatuj Johara 
Published: February 2024

يعد طرد الموظفين من المنظمات مشكلة خطيرة. يجب حل مشكلة تدوير الموظفين أو اطردهم من داخل المنظمة نظرًا لأن لها تأثيرًا سلبيًا على المنظمة. يعد الاكتشاف اليدوي لتسرب الموظفين أمرًا صعبًا للغاية، لذلك تم استخدام خوارزميات التعلم الآلي ML بشكل متكرر لاكتشاف تسرب الموظفين بالإضافة إلى تصنيف الموظفين وفقًا للاستبدالهم.
باستخدام التعلم الآلي، بحثت دراسة واحدة فقط في تصنيف الموظفين حتى الآن. تم اقتراح نهج جديد لاتخاذ القرار متعدد المعايير MCDM إلى جانب مبدأ DE-PARETO لتصنيف الموظفين. يشار إلى هذا باسم مخطط SNEC .
تم تصميم نموذج AHP-TOPSIS DE-PARETO PRINCIPLE (AHPTOPDE) الذي يستخدم نظام MCDM على مرحلتين لتصنيف الموظفين. في المرحلة الأولى، تم استخدام عملية التسلسل الهرمي التحليلي AHP لتعيين الأوزان النسبية لعوامل إنجاز الموظف. في المرحلة الثانية، تم استخدام TOPSIS للتعبير عن أهمية الموظفين في إجراء تصنيف الموظفين. تم تطبيق قاعدة 20-30-50 البسيطة في مبدأ DE PARETO لتصنيف الموظفين إلى ثلاث مجموعات رئيسية وهي الموظفون المتحمسون والسلوكيون والمضطربون. يتم بعد ذلك تطبيق خوارزمية الغابة العشوائية كخوارزمية أساسية لإطار عمل الموظفين المقترح للتنبؤ بخسارة الموظفين على أساس الفصل والذي يتم اختباره على مجموعة بيانات قياسية لنظام معلومات الموارد البشرية HRIS، ويتم تقييم النتائج التي تم الحصول عليها باستخدام طرق تعلم الآلة الأخرى. تتمتع خوارزمية Random Forest ML في مخطط SNEC بدقة إجمالية مماثلة أو أفضل قليلاً وMCC مع تعقيد زمني أقل مقارنةً بمخطط ECPR باستخدام خوارزمية CATBOOST
Use of Climate Smart Agricultural Technologies in dry-season peri-urban agriculture in West Africa Sahel: A case study from Saga, Niger
Authors: Tambol¹ Tinawaen , Derbile Emmanuel K. , Soulé Moussa 
Published: February 2024

Abstract

Climate change affects peri-urban agricultural systems. However, most studies focused on impacts on peri-urban and urban agriculture. This study only investigated peri-urban farming systems in West African Sahel cities. Globally, agricultural productivity improvement requires applying technologies and resource access, particularly in dry-season farming. The achievements of Sustainable Development Goals (SDGs) in developing countries rely on utilising Climate-Smart Agriculture Technologies (CSAT) to address climate change, youth unemployment and food insecurity. The study employed a mixed-method research design, employing field and household surveys of 142 peri-urban smallholder farmers, key informants, and desktop-based research in collecting data. The results showed that biopesticides/crop and pest management are the most used CSAT in dry-season farming (p = .002). These technologies eradicate pests and disease outbreaks of crops, vegetables and farm animals. The other technologies included fertilizer micro dose, organic manure and compost application, flood-tolerant improved varieties, irrigation based on green energy, tele-irrigation, early maturing varieties and planting pits. These technologies were ranked 2nd, 3rd, 4th, 5th, 6th, 7th, 8th and 9th respectively, using mean weighted values. The study underpins local climate change trends and assessment, together with the availability, opportunities and implicit implications of scaling up CSAT. The study also recommends including peri-urban agriculture in climate and land use planning policy, programmes and projects in Niamey city.
Economic burden of breast cancer prevalence by 2030 in India: Projections using Autoregressive Integrated Moving Average (ARIMA) model
Authors: Pillai Rakesh N , Alex Aleena , S Narassima M , Verma Vivek , Shaji Ajil , Pavithran Keechilat , Vijaykumar D. K. , John Denny 
Published: February 2024

Abstract

Background
Breast cancer is an important public health issue in India comprising 28 percent of all diagnosed cancers with a high economic burden. This study provides a new way to predict the number of patients with breast cancer (based in prevalence rates) and estimated its economic burden in India based on the autoregressive integrated moving average (ARIMA) model.
Methods
Data on the number of patients with breast cancer in India from 2000 to 2019 (prevalence) were obtained from the Global Burden of Disease databases. The ARIMA model was used to fit and predict the number of patients with breast cancer (prevalence) till 2030. The direct and indirect economic burden of breast cancer was estimated by the bottom-up approach and the human capital approach, respectively.
Results
The results of coefficient of determination (0.99), mean absolute percentage error (25%), mean absolute error (1794.555), and root mean squared error (2233.528) showed that the ARIMA (2,2,0) model fitted well. Akaike information criterion (543.13) and Bayesian information criterion (546.69) indicated the ARIMA (1, 1, 1) model was reliable when analyzing our data. The result of the relative error of prediction (0.23%) also suggested that the model predicted well. The number of patients with breast cancer from 2019 to 2030 was predicted to be about 1.12 million, 1.18 million, 1.25 million, 1.32 million, 1.38 million, 1.44 million, 1.51 million, 1.56 million, 1.62 million, 1.68 million, 1.74 million, and 1.80 million respectively. The total economic burden of breast cancer from 2019 to 2030 was estimated to be $8.16 billion, $9.06 billion, $10.01 billion, $11.01 billion, $12.05 billion, $13.16 billion, $14.36 billion, $15.66 billion, $17.08 billion, $18.6 billion, $20.23 billion respectively.
Conclusion
In India, the number of people with breast cancer and its financial burden will both keep rising. Between 2020 and 2030, India will see an average annual increase in the number of breast cancer patients of 0.05 million (5.6 per cent). In the meantime, an average of $19.55 billion more would be spent annually on breast cancer in India.
Intercomparison of DCA and EPR scoring for validation with individual physical dosimetry
Authors: Chang Kang-Wei , Cheng Po-Ching , Lin Yi-Chun , Lee Shih-Ying , Huang Wen-Sheng , Chiu Chuang-Hsin 
Published: February 2024

Abstract

Radiation is widely used in industrial, medical, agricultural, and military applications. The improper use and disposal of manmade radiation sources have resulted in various events that have caused different levels of human radiation exposure. These experiences indicate that estimating only the amount of radioactive contamination and dose after an incident was not sufficient to realize in detail and determine the exact exposure dose owing to the incident. Therefore, a retrospective assessment of radiation exposure and dose reconstruction is a necessary and crucial method for risk analysis. In this studies, we used one healthy volunteer peripheral blood and fingernail samples for the project were irradiated with 0–5 and 0–20 Gy Co-60 irradiation for establish a dose-dependent curve with DCA and EPR dose-response curve assays, respectively. Further, another 20 volunteers participated in this clinical trial; their DCA and EPR scores were calculated, and followed by an evaluation of their equivalent radiation doses and corresponded with their monthly physical dosimetry. Through this study, we established the dose-response curve of DCA and EPR after radiation exposure, and calculated the correlation between physical dosimetry and biological doses by 20 volunteers participating in clinical trials. This evidence will promote estimating the personal absorbed doses and as a reference for medical treatment for the safety of radiation workers and normal populations.