bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Spectroscopy and Biological Activity Study of Some New Complexes with Schiff Base Derived From Malonic Acid Dihydrazide with 2-pyridine Crboxaldehyde
Authors: Hammoda Rehab Ghalib , Shaalan Naser
Published: October 2023

تم تحضير ثلاث معقدات جديدة Ni (II)و Cu (II) و Zn (II) باستخدام الليكند المحضر الجديد من تفاعل حامض مالونيك ثنائي هيدرازايد مع 2-بيريدين كربوكسالديهايد. حيث شخصت المعقدات لمحضرة وكذلك الليكند باستخدام تقنيات مختلفة مثل FT-IR و UV-Vis و Mass و 1H-NMR و 13C-NMR وتحليل العناصر CHN و تقدير محتوى  الكلور والموصلية المولارية والحساسية المغناطيسية والامتصاص الذري لتشخيص هذه المركبات. لكل معقد محضر جديد من النيكل والنحاس والزنك ، كشفت نتائج التشخيص عن معقدات ذات شكل هندسي ثماني السطوح سداسي التناسق.  تمت دراسة تأثير المواد المحضرة على الفعالية البيولوجية لاثنين من البكتريا موجبة الغرام Staphylococcus aureus و Bacillus subtitles واثنين من البكتيريا سالبة الجرام Escherichia coli و Pseudomonas aeruginosa  ، بالإضافة إلى candida fungusاثبتت جميع المركبات المحضرة قابلية تثبيطيه جيدة باستثناء معقد النيكل، الذي فشل في إحداث أي تأثيرات مثبطة فعالة ضد pseudomonas.
Population estimation of the Euphrates softshell turtle Rafetus Euphraticus in the Central Marshes (UNESCO site)
Authors: Taher Samer Ammar , Abdulhay Hind Suhail
Published: October 2023

تم تصنيف ترسة الفرات ملساء الصدفة  Rafetus euphraticus على أنها مهددة بخطر الانقراض ضمن القائمة الحمراء للاتحاد الدولي لحفظ الطبيعة، ويُعتقد أنها تعرضت لانخفاض كبير في أعدادها مؤخرًا. تقتصر معلومات الأنواع في العراق على عدد قليل من المسوحات السريعة مع القليل من المعلومات التفصيلية عن التربية والتوزيع. هدفت الدراسة الى تقدير اعداد سلاحف الفرات ملساء الصدفة  في الأهوار الوسطى باستخدام استقراء بسيط للعدد. تم استخدام طريقة المربع (بحجم 5 كم2 لكل منهما) لتسجيل توزيع سلحفاة الفرات ملساء الصدفة  داخل موقع الدراسة وتم إجراء عشرة مسوحات ابتداءا من شهر تشرين الاول 2021 إلى ايلول 2022 باستثناء موسم السبات (كانون الاول وكانون الثانيو شباط). تم تسجيلها داخل المياه عن طريق وضع الشباك في مناطق معينة بالأهوار الوسطى. اقترح الاستقراء البسيط لتعداداتنا لكامل الأهوار الوسطى أن يبلغ الحد الأقصى لحجم المجاميع السكانية 2526.55 فردًا /المساحة الكلية)  219.700 هكتار.( تعتبر الأهوار الوسطى موقعًا مهمًا لـ R. euphraticus حيث تم تسجيل إجمالي 46 فردًا.
Recurrency on the Space of Hilbert-Schmidt Operators
Authors: Moosapoor Mansooreh
Published: October 2023

في هذا البحث, تم برهان بانه اذا كانت  شبه الزمرة-C0 فوضوية وزائدة او فائقة الاختلاط فان الضرب من جهة اليسار المرتبط بشبه الزمرة-C0 في فضاء مؤثرات هلبرت-شميدت متكرر اذا وفقط اذا كان مفرط الدوران. كذلك, تم بيان انه في ظل بعض الشروط يكون تكرار شبه الزمرة-C0 وتكرار الضرب لشبه الزمرة-C0 من جهة اليسار المرتبط بها في فضاء مؤثرات هلبرت-شميدت متكافئين. علاوة على ذلك, بعض الشروط الكافية للتكرار وزيادة الدوران للضرب من جهة اليسار لشبه الزمرة -C0 تم عرضها بالاعتماد على المجموعات الجزئية المتشعبة.
Photo Degradation of Solochrom Violet Dye by ZnO: Experimental and Theoretical Study
Authors: Hamed Ameera Hassan , Mahmmood Zahraa A. , Hussein Ennas Abdul , Kadhim Mustafa M.
Published: October 2023

يشمل العمل الحالي التحلل الضوئي للصبغة البنفسجية سولوكروم باستخدام عمليات اكسدة متقدمة عند درجة حرارة ℃25 باستخدام الاشعة فوق البنفسجية H2O2 . تم اجراء التحفيز الضوئي لصبغة سولوكروم البنفسجية عند الطول الموجي  570 نانومتر مع ZnO. تم دراسة  تاثير عوامل مختلفة وهي تركيز الصبغة ,درجة الحموضة ,والتركيز الاولي لماادة بيروكسيد الهيدروجين ,وقت التشعبع . ودراسة الحركية على فترات مختلفة  كما  تم دراسة نسب التحلل بشكل عام.وجد ان معدلات التحلل الضوئي للصبغة  كانت اعلى في وجود H2O2و ZnO  مع الاشعة فوق البنفسجية .تم تحديد الطول الموجي الافضل . اثبتت عمليات الاكسدة المتقدمة فعاليتها العالية في تحلل معظم الملوثات في مياه الصرف الصحي . تم استخدام مقياس الطيف الضوئي لمراقبة التحلل الضوئي للصبغة .ركزت الحسابات النظرية على المواقع النشطة باستخدام طريقة the density functional theory في برنامجGaussian .
Behavior of Platinum-Group Elements during Hydrous Metamorphism: Constraints from Awaruite (Ni3Fe) Mineralization
Authors: Kutyrev Anton , Kamenetsky Vadim S. , Kontonikas-Charos Alkiviadis , Savelyev Dmitry P. , Yakich Tamara Yu. , Belousov Ivan A. , Sandimirova Elena I. , Moskaleva Svetlana V.
Published: October 2023

Natural Fe-Ni alloys are common in meteorites and, presumably, the Earth’s core, where they host significant platinum-group elements (PGE). However, little is known on PGE concentrations in hydrothermal or metamorphic Fe-Ni alloys (i.e., awaruite Ni3Fe) from terrestrial rocks. In this work, we examine the geochemistry of awaruite and related minerals from several placer deposits sourced from the suprasubduction ophiolitic (Kamchatsky Mys, Karaginsky Island, and Mamet) and Ural-Alaskan (Galmoenan) complexes of Kamchatka and the Koryak Highlands (Far East Russia) in order to assess the abundance of PGE in awaruite and constrain their mobility under metamorphic and hydrothermal conditions. Studied awaruite from ophiolitic and Ural-Alaskan type complexes formed via desulfurization of pentlandite during serpentinization. Three groups of platinum-group minerals (PGMs) are associated with awaruite from Kamchatsky Mys: (1) Pt-Fe alloys such as ferronickelplatinum (Pt2FeNi) or unnamed Ni2FePt alloys; (2) Os-Ir-Ru alloys of various composition; (3) Pd-Sb minerals which form together with serpentine during hydrothermal alteration. Despite the abundance of PGM inclusions, no significant PGE concentrations were measured in awaruite from the Kamchatsky Mys, Karaginsky Island, or Mamet ophiolites. In contrast, pentlandite relicts in awaruite from placers related to the Galmoenan Ural-Alaskan type complex contain exceptionally high, previously unreported, Os (up to 540 ppm). Awaruite that forms on behalf of this pentlandite does not show any significant Os enrichment. Rare Galmoenan awaruite analyses yield up to 3 ppm Pd. The new data are not in complete accordance with previous studies that reported relatively high (up to first 10 ppm) PGE content in awaruite. We attribute this to low PGE concentration in precursor sulfides and preferential partitioning of PGE into discrete secondary PGM within awaruite. Nevertheless, abundant inclusions of secondary PGM in awaruite provide evidence of PGE mobility during metamorphic and hydrothermal alteration of ultramafic rocks.
Uvarovite from Reduced Native Fe-Bearing Paralava, Hatrurim Complex, Israel
Authors: Futrzyński Jacek , Juroszek Rafał , Skrzyńska Katarzyna , Vapnik Yevgeny , Galuskin Evgeny
Published: October 2023

A new genetic type of chromium garnet—uvarovite with the simplified formula Ca3(Cr,Al,Ti4+,V3+)2(Si,Al)3O12—was detected in unusual wollastonite-gehlenite-bearing paralava within the Hatrurim Complex in Israel. The pyrometamorphic rocks of that Complex usually formed in the sanidinite facies (low pressure and high temperature) and, as a rule, under oxidized conditions. This paralava contains nodules and grain aggregates of native Fe, usually distributed linearly in the rock or located close to gaseous voids. The presence of native iron droplets in association with the “meteoric” phosphide—schreibersite, suggests that the formation of paralava occurred under high-reducing conditions and high temperature, reaching 1500°C. Uvarovite forms xenomorphic grains either randomly distributed within the rock or flattened crystals on the walls of gaseous voids. Analyzed uvarovite indicates a significant enrichment in Ti4+ (up to 8 wt.% TiO2) and V3+ (up to 4.5 wt.% V2O3), the highest concentrations documented for uvarovite. Unlike known uvarovite from different localities, uvarovite from this study does not contain Fe3+, and Fe2+ is present in insignificant amounts. The obtained structural data reveal that the high contribution of hutcheonite, Ca3Ti4+2SiAl2O12 (up to 18%), and goldmanite, Ca3V3+2Si3O12 (up to 11%), end-members increases the lattice parameter a to >12.00 Å. The crystallization of uvarovite occurs in the narrow interval of oxygen fugacity, a little above the iron-wüstite buffer ƒO2 ≥ ΔIW. Uvarovite xenomorphic grains formed due to the decomposition of wollastonite and chromite, including H2S from the intergranular melt/fluid according to the following reaction: Ca3Si3O9 + Fe2+Cr3+2O4 + H2S → Ca3Cr2Si3O12 + FeS + H2O, while the flattened crystals grew from specific melt that formed on the walls of the voids as a result of exposure of hot gas flow. The comparison of the obtained results with available chemical data from previous studies reveals a gap in the natural isomorphic series between andradite and uvarovite.
Motoric cognitive risk syndrome and its association with falls: a secondary analysis of the Mexican Health and Aging Study
Authors: Márquez Isabel , Carrillo-Vega María Fernanda , Pérez-Zepeda Mario Ulises , Cano-Gutiérrez Carlos
Published: October 2023

Objective. To reveal whether motoric cognitive risk syndrome (MCR) is associated with falls, recurrent falls, and complicated falls in older Mexican adults. Materials and methods. This is a secondary analysis of the Mexican Health and Aging Study. MCR was assessed in 2012 and included fall-related outcomes (recurrent [≥2], complicated [need for medical treatment] and number) in the 2018 follow-up. Competing risks analysis was performed, and subhazard ratios (sHRs) were estimated, adjusting for different variables. Negative binomial regression was used to estimate the incidence rate ratio (IRR) of the number of falls. Results. A total of 1 929 participants were included, with a median age of 62 years and 58.3% female. The prevalence of MCR was 17.4% and was associated with falls sHR 1.11 (95%CI: 1.11, 1.12), recurrent falls sHR 1.16 (95%CI: 1.15, 1.16) and complicated falls sHR 1.25 (95%CI: 1.24, 1.25). The number of falls was also independently associated with baseline MCR (IRR 1.19; 95% CI 1.01, 1.40; p=0.039). Conclusion. MCR is independently associated with falls. Increasing the evidence on how MCR anticipates burdensome problems in older adults could lead to actions to halt them; therefore, including it in screening assessments could be clinically useful.
The Mex-Cog cognitive assessment battery: discriminant analysis of the cognitive performance profile in older adults
Authors: Mejia-Arango Silvia , Aguilar-Navarro Sara , Mimenza-Alvarado Alberto
Published: October 2023

Objective. To analyze the cognitive profile of a clinical sample using the Mex-Cog cognitive battery and establish which cognitive measures and domains contribute most to group separation. Materials and methods. A group of 145 older adults previously diagnosed with dementia (n= 47), mild cognitive impairment MCI (n= 47), or as cognitively normal (n= 51) were assessed with the Mex-Cog cognitive battery. Six linear discriminant analyses (LDA) were estimated to compare dementia vs. cognitively normal, MCI vs. cognitively normal, and MCI vs. dementia, using ten individual measures and six cognitive domains. We used a leave-one-out cross-validation procedure to evaluate the predictive capacity of LDA models. Results. Discriminant functions using individual measures and domains distinguished correctly 100% of dementia and cognitively normal groups showing a memory and executive function profile. The predictive group membership for MCI versus cognitively normal varied between 82 and 85%, with a cognitive profile associated with attention-executive function followed by memory. Group separation between MCI and dementia was between 80 and 87%, characterized by orientation, memory, and visuospatial abilities. Conclusions. The Mex-Cog cognitive battery is useful for identifying cognitive impairment in older adults.
Determinants of retirement of formal and informal sector workers in Mexico: the role of health and economic security
Authors: Lee Zeewan , Aguila Emma , Wong Rebeca
Published: October 2023

Objective. We examine the socioeconomic and health drivers of retirement decisions and compare these determinants between formal and informal sector workers in Mexico. Materials and methods. Using data from the Mexican Health and Aging Study 2012 and 2015, we estimate conditional probit models of retirement using sociodemographic, health, health care utilization, health insurance, private pensions, and social security systems covariates. The Institutional Review Board at the University of Southern California reviewed and approved the research (IRB # UP-15-00023). Results. We find that the social security systems are an important determinant for retirement age for formal sector workers. The informal sector workers, who lack access to retirement benefits of the social security system, make retirement decisions mainly based on health and access to health insurance through social security. Conclusion. Despite the lack of access to social security benefits, informal sector workers do not respond strongly to socioeconomic factors in determining the timing of retirement. Strengthening access to better health care services could improve health, extend working lives, and promote healthy aging for workers in the informal sector.
Magnetic Resonance Imaging Evaluation of Sacroiliac Joints in Axial Spondyloarthritis: Does Phenotype or Gender Matter?
Authors: Pereira Gabriel Caetano , Machado Natalia Pereira , Gomes André Francisco , Assad Rodrigo Luppino , Carneiro Fabio Henrique , Azevedo Valderílio Feijó
Published: October 2023

Background
Axial spondyloarthritis (axSpA) represents a group of immune-mediated inflammatory diseases characterized by predominant involvement of the axial skeleton (sacroiliitis and spondylitis) but with distinguishing features. The objectives of this study were to analyze imaging differences (sacroiliac and spine) between different phenotypes and gender in axial SpA.
Method
A cross-sectional study was conducted to evaluate clinical data, laboratory findings, magnetic resonance imaging scores of sacroiliac joints (SPARCC and SSS), and cervical and lumbar spine radiographs (mSASSS). The study compared a cohort of patients with axial SpA based on SpA phenotype: radiographic and non-radiographic ax SpA and axial psoriatic arthritis (AxPsA), as well as gender.
Results
Ninety-four patients were recruited, with 62 patients in the axial SpA group and 32 patients in the axPsA group. The axial SpA group exhibited a higher frequency of HLA-B27 allele positivity, while the axPsA group showed older age (p = 0.01), higher frequency of peripheral arthritis (p < 0.001), and cardiovascular risk (p = 0.001). There was greater use of anti-TNF-alpha agents (p = 0.01) and NSAIDs (p = 0.026) in the axial SpA group and anti-IL-17A antibodies in the axPsA group (p = 0.002). There were no differences in disease activity, mobility, radiographic damage in the spine (mSASSS), or sacroiliac MRI scores (SSS and SPARCC) between the two groups. Regarding gender, in imaging exams, men had higher mSASSS (p = 0.008), SSS (p = 0.001), and fat metaplasia (MG) score based on SSS (p = 0.001), while women had significantly higher SPARCC scores (p = 0.039). In the male group, the presence of HLA-B27 allele had an impact on more structural lesions on MRI (SSS), p = 0.013.
Conclusion
In this study, the evaluation of sacroiliac joints by magnetic resonance imaging in patients with axial SpA did not show differences in phenotypes but did reveal differences based on gender, which may have an impact on future diagnostic guidelines. Further studies are needed to confirm these findings.
Core Components of Joint Health and Wellbeing Strategies: a pan-London audit study of all 33 local authorities
Authors: Asmar Marie Line El , Karki Manisha , Mall Bathsheba , Riboli-Sasco Eva , El-Osta Austen
Published: October 2023

Background
In the UK, Joint Strategic Needs Assessments (JSNAs) and Joint Health and Wellbeing Strategies (H&WS) were introduced to identify and help address the health needs of local communities. H&WS translate JSNAs into actionable outcomes and prioritise areas of focus, but their content and approach may vary across different local authorities (LAs) due to demographic and priority differences.
Objective
Characterise the key health and wellbeing components of existing and emerging health and wellbeing strategies of 33 local authorities in London.
Design
Audit study with content assessment.
Methods
An online search was conducted to identify extant H&WS documents. This search was supplemented with outreach to health and wellbeing boards to ensure that the latest documents were retrieved. A set of 62 health and wellbeing themes and words to be captured spanning 13 categories was developed by a team of researchers, and data collection was independently carried out by two researchers. Occurrences of words in the strategy documents were recorded, and a configuration matrix was created and used to determine data trends across the local authorities. A broad search of the context in which the search terms appeared was also performed to understand the trends.
Results
Thirty-three H&WS were analysed to identify key search term frequencies. The analysis encompassed strategies from 2015 to 2030, ranging from 7 to 94 pages. Mental health and youth terms emerged as the two top priorities across all strategies. Other frequent terms were related to access to healthcare, inequality, employment, smoking, housing, carers, and elderly individuals. Conversely, terms related to dental health, pollution, nutrition, sexual health, green spaces, breastfeeding, and climate were less cited.
Conclusion
This analysis provides insights into regional health priorities and a comprehensive overview of health and wellbeing strategies across London's local authorities. Despite certain limitations, the findings offer valuable insights for local authorities' strategic planning and future research.
Stacked Ensemble Based Deep Learning Approach for Plant Disease Classification and Farming Decision Support
Authors: Dhanasekaran Menaga , M Sudha
Published: October 2023

Plant disease detection is challenging and essential factor for crop yield. In broad-spectrum, most of the existing dataset used for disease prediction consists of observatory records of several plant image parameters with a greater number of diseased images and healthy images. Identifying the significant parameters from irrelevant parameters and redundant parameters for disease prediction is significant because irrelevant parameters may decrease the prediction accuracy. This research investigation describes the impact of disease prediction on single plant or multi-plant with the predicted labels, loss, accuracy and epochs for the both trainable parameters and non-trainable parameters. The prediction is intricate process in agricultural field because all decisions are made within a fact of uncertainty associated with the greater number of images. This research findings introduces a novel stacked ensemble computing approach for identifying incorrectly classified images and correct classified images. Single learning approach may suffer from statistical, computational and representational issues. To eliminate these issues, the proposed system combines multiple machine learning algorithms called ensemble learning, to detect the disease attacks in plants better than the existing conventional learning. Stacking is a two-level classification model, namely Base Learners (Level- 0) and Meta Learner (Level-1). These two-level classifications ensure the classification accuracy as high. Image dataset, image features are the inputs for the proposed model to support two level classification. The stacked ensemble learning is used for classification of diseases of various plant and extracts the shape features of affected plants. The proposed model is the first system, which is designed to detect single plant disease images and also multi-plant leaf disease images. To detect multi-plant leaf diseased images, the proposed model trained with more than 30,000 images in many levels. The experimental results show the proposed stacked ensemble learning method used for classifying the disease based on loss, accuracy and number of epochs in hyper parameter attained 99.93% of accuracy and outperformed when compared with other existing ensemble learning methods.
Effect of Lensectomy on incidence of retinal detachment in Non- Traumatic Ectopia Lentis
Authors: Alhaimi Fawzia , Al-Shamrani Mohammed
Published: October 2023

Purpose:
To evaluate the effect of lens aspiration and anterior vitrectomy in the development of retinaldetachment in eyes with non-traumatic ectopia lentis.
Methods:
This retrospective study evaluated patients withnon-traumatic ectopia lentis Traumatic cases and patients with Stickler syndrome were excluded. The eyes weredivided into two groups: eyes that had undergone lens aspiration and anterior vitrectomy with or without IOLimplantation (surgical group) and, eyes that had no surgical intervention (non-surgical group).
Result:
The studysample was comprised of 115 eyes of 63 patients. There were 36 (57.1%) and 27 (42.9%) females. The medianage of patients was 14 years (25% quartile, 8; minimum, 2 years and maximum, 55 years). There were 74 eyes inthe non-surgical group. There were 41 eyes in the surgical group that had undergone Lensectomy (31 limbalapproach and 10 pars plana) with intraocular lens implantation in 22 (19%) eyes..The incidence of retinaldetachment (n=25) was 21.7% (95% confidence interval: 17.7 to 25.4). 17 eyes (23%) in the non-surgical groupdeveloped retinal detachment and 8 eyes (19.5%) in the surgical group developed retinal detachment (P = 0.7).
Conclusion:
There was no difference in the incidence of retinal detachment between eyes with ectopia lentis thatundergone lensectomy with or without IOL implantation compared to eyes that had not undergone any surgery.However, larger studies are required to evaluate the effect of lens aspiration on the development of retinaldetachment in patients with ectopia lentis.
Passive flutter suppression with rotary nonlinear energy sink
Authors: Araujo Gabriel Placeres , Marques Flávio Donizeti , Silva José Augusto Ignácio da
Published: October 2023

The control of aeroelastic phenomena, such as flutter, is of great interest due to its high amplitude self-excited characteristic. Nonlinear Energy Sinks (NES) are vibration absorbers whose nonlinear coupling to the structure contributes to broad excitation ranges for passive suppression. This paper investigates the attachment of a rotary-type NES (RNES) to an aeroelastic typical section to suppress nonlinear flutter oscillations passively. An unsteady aerodynamic loads model is used based on the Theodorsen and Wagner approaches. Pitching structural nonlinearity is added, inducing limit cycle oscillations in the airfoil. The system is modeled and numerically simulated. A dynamic characterization is done, obtaining the mechanisms of action of RNES through a regime identification, and its typical bifurcation behavior is accessed. A parametric analysis based on the system bifurcation over different RNES configurations is used to understand how each design parameter influences vibration mitigation performance and how absorption regimes correlate with RNES effectiveness. An energy analysis is carried through to conceive the activation of the Targeted Energy Transfer suppression mechanism and an energy-based parametric analysis of RNES performance. The results indicate that NES efficiency for flutter postponement is related mainly to low-radius devices located near the leading edge. RNES mass and angular damping parameters also present an impact but are limited due to subcritical behavior.
Absolutely dating the European Neolithic through a rapid 14C excursion
Authors: Maczkowski Andrej , Pearson Charlotte , Francuz John , Giagkoulis Tryfon , Szidat Sönke , Wacker Lukas , Bolliger Matthias , Kotsakis Kostas , Hafner Albert
Published: October 2023

The discovery of abrupt radiocarbon (14C) excursions (Solar Energetic Particle events, or Miyake events) in sequences of radiocarbon measurements from calendar dated tree-rings, has yielded new opportunities to assign absolute, calendar dates to undated wood samples from widely ranging contexts in history and prehistory. We report on an important tree-ring and 14C-dating based study, which secures the Neolithic site of Dispilio, Northern Greece, a key site for the Aegean Neolithic, in absolute, calendar-dated time using the Miyake event of 5259 BC. The last ring of the 303-year-long juniper tree-ring chronology from Dispilio is dated to 5140 BC. Dispilio is thus the first prehistoric site absolutely dated through a 14C signature (Miyake event), but also the first absolutely, calendar-year dated prehistoric site in the wider Mediterranean region.
Exploring Perceptions and Factors Influencing HPV Vaccination Acceptance Among Egyptian Muslim Women: A Multidimensional Analysis
Authors: Namoos Asmaa , Abosamak NourEldin , Shaaban Bahaa , Abdelkarim Maryam , Bastaich Dustin , Ramadan Dina , Abdou Mostafa , Ramadan Rana , Sheppard Vanessa , Gal Tamas S
Published: October 2023

Background
Human Papillomavirus (HPV) is a major cause of cervical cancer, and effective vaccines have been developed to combat its impact. However, there is a lack of awareness among Egyptian women regarding HPV and its preventive measures.
Methods
This cross-sectional quantitative study aimed to explore factors influencing HPV awareness among Egyptian women. A survey was conducted to participants recruited from clinics at Alexandria University Hospitals in 2021. Inclusion criteria included being a woman aged 18 years or older. Data analysis involved a multivariable logistic regression model to assess associations between covariates and HPV awareness.
Results
The study included 99 participants, ranging from 18 to 55 years of age. The majority were married, had an education below high school, and had a monthly income between $100–300. Unmarried participants, those with higher education levels, and higher incomes demonstrated higher levels of HPV awareness. The logistic regression model indicated that education level and religiosity score were significant predictors of HPV awareness. Participants with higher education levels had 6.84 times higher odds of being aware of HPV, while those with higher religiosity scores had lower odds.
Conclusion
The results of this study highlight the need for programs that target less educated and highly religious populations to raise awareness about HPV and encourage HPV vaccination. Further studies should be conducted to better understand the complex interplay of demographic, cultural, and religious factors that influence HPV awareness and vaccination uptake.
Progression of Large Language Models for Clinical Decision Support: An Evaluation for Rare and Frequent Diseases using GPT-3.5, GPT 4 and Naïve Google Search
Authors: Varghese Julian , Sandmann Sarah , Riepenhausen Sarah , Plagwitz Lucas
Published: October 2023

Large Language Models (LLMs) like ChatGPT have become increasingly prevalent. Even without medical approval, people will use it to seek health advice, much like searching for diagnoses on Google.
We performed a systematic analysis of GPT-3·5 and GPT-4 for suggesting diagnosis, examination steps and treatment of newly processed 110 medical case reports from different clinical disciplines. Balanced groups of rare, less frequent and frequent diseases were used as input. For the diagnosis task a naïve Google search was performed as benchmark comparison. Performance was assessed by two independent physicians using a 5-point Likert scale.
The results showed superior performance of GPT-4 over GPT-3·5 considering diagnosis and examination and superior performance over Google for diagnosis. With the exception of treatment, better performance on frequent vs rare diseases was evident for all approaches.
In conclusion, the LLMs showed growing potential for medical question answering in two successive major releases. However, several weaknesses and challenges necessitate the utilization of quality-controlled and regulated types of AI-models to qualify as medical applications.
AI Luddites: Consumers Penalize Creative Work Output Generated by Artificial Intelligence
Authors: Chung Jaeyeon
Published: October 2023

Generative AI's expanding role extends beyond utilitarian tasks like coding, encompassing creative endeavors such as design and writing. Yet, this surge in adoption triggers resistance among creative professionals, who fear job displacement and societal disruption. This paper delves into consumer reactions when companies employ generative AI for creative tasks instead of humans. Five pre-registered experiments, involving brand posters, film scripts, and logos, unveil people’s reactions against AI-generated creativity. People penalize artwork after they learn that the work is produced by AI; this tendency is most pronounced among those with Luddite leanings, reminiscent of 19th-century textile workers who distrusted machines. Process evidence indicates that these people perceive AI output as lacking the procedural human touch essential to artistic creation, penalizing AI-generated work despite its high quality. Social implications are discussed, raising questions about a company's 'appropriate' use of AI, and its impact on perceptions of ethics and brand image. The paper also opens discussion on whether businesses should disclose their use of generative AI in creative tasks and, if so, to what extent.
VR and DL Empowered Progressive Muscle Relaxation for Sleep Facilitation and Monitoring
Authors: Cai Chuangxin , Liu Dong , Zou Yu , Lang Xu , Pan Zhigeng , Liu Yong
Published: October 2023

Insomnia is a widespread public health issue with global implications, garnering significant attention in the field of biomedicine. Sleep deprivation result in various problems, including affect one’s memory and cognitive abilities. With the development of modern technologies, such as deep learning (DL), virtual reality (VR), utilizing these technologies to improve sleep has become an open and hot research. In this paper, we developed the SleepSenseVR system with sleep behavior recognition algorithm based on deep learning and progressive muscle relaxation based on sleep state feedback (PMR-SSF) threapy to decrease sleep onset latency. The sleeping-aid system promotes progressive muscle relaxation (PMR) integrated DL, VR and multimedia technology for sleep assistance. We conducted user experiments, inviting 36 participants to test three different systems, including VR, VR combined with PMR, and VR combined with PMR-SSF. This paper empirically evaluates these three systems, and the experimental results show that PMR-SSF is an effective method for sleep promotion, providing theoretical and practical value for the rapid development of sleep medicine.
Stability Analysis of Hole Wall for Bored Piles
Authors: LONG Zhao , ZHANG Lei , HE Laping , GUO Zhiyuan , WANG Zhengzhen
Published: October 2023

Based on the theory of small hole expansion and elastic-plastic theory, this paper studied the instability mechanism of the hole wall of bored pile, gave the stress expansion solution of the soil layer after the excavation of pile holes in the semi-infinite elastic soil layer, and established its mechanical model. Then, the stability of hole wall of bored pile in cohesive soil layer and sandy soil layer was analyzed, and the calculation formula of pile hole wall stability was obtained. Finally the stability of hole wall of bored pile under the action of mud slurry was calculated, and the stress on the pile hole wall was analyzed when local instability and overall instability occur, respectively. The results show that in sandy soil layer, the safety factor of hole wall of bored pile when it is stable has no connection with the depth of pile hole, but is related to the density of mud slurry in the pile hole. For the region of third stage expansion project of Lanzhou Zhongchuan International Airport, the critical safety stability factor for the instability of hole wall of bored pile is 0.47. When the safety stability factor is less than 0.47, the soil layer of the hole wall of bored pile would be unstable, and the hole wall will collapse. In the unstable soil layers, the pile hole wall was prone to instability, and the stability of hole wall could be improved by appropriately increasing the gravity of mud slurry. With the increase of pile diameter, the lateral displacement and deformation of hole wall increase, and the displacement of soil layer increases when the hole wall is unstable, resulting in increasing the possibility of forming variable cross-section piles correspondingly.
Enhancing Wearable Motion Monitoring Devices: A Multi-level Attention Fusion Approach for Reliable Fatigue Assessment
Authors: Mu Dinghong , Wang Jian , Li Fenglei , Hu Wujin , Chen Rong
Published: October 2023

This study aims to create a cost-effective, reliable motion monitoring device that can thoroughly analyze a subject's fatigue. It achieves this by combining surface electromyography (sEMG) and accelerometer (ACC) signals using a feature fusion approach. The study introduces a multi-level attention mechanism for classification. This mechanism is based on convolutional neural networks (CNNs). During preprocessing, a local feature attention mechanism enhances local waveform features using the amplitude envelope. The model employs a dual-scale attention mechanism, which operates at both channel and neuron levels. These multi-level channel and neuron attention mechanisms improve the model's ability to learn from high-dimensional fused data, enhancing feature extraction and generalization. The local feature attention mechanism effectively boosts the model's classification accuracy and convergence, as evidenced by ablation experiments. The model, optimized with multi-level attention mechanisms, excels in accuracy and generalization, particularly in handling data with pseudo-artifacts. Computational analysis shows that the suggested optimization algorithm minimally affects CNN's training and testing times. In the end, the method in this study reaches recognition accuracies of 92.52%, 92.38%, and 92.30% and F1-scores of 91.92%, 92.13%, and 92.29% for the three fatigue states, confirming its reliability. This study offers technical support for the creation of affordable and reliable wearable motion monitoring devices.
The Clinical and Cost-Effectiveness of an Individualised Nutritional CAre (INCA) Bundle Versus Standard Care for Adults with Pressure Injuries Receiving Home Nursing Services: a Protocol for a Cluster Randomised, Pragmatic Clinical Trial with an Economic Evaluation.
Authors: Wong Alvin , Lai Precilla , Chong Hui Hsien , Lien Christopher Tsung Chien , Graves Nicholas
Published: October 2023

Background: Pressure injuries (PIs) represent a significant healthcare challenge in Singapore among the aging population. These injuries contribute to increased morbidity, mortality, and healthcare expenditure. Existing research predominantly explores single-component interventions in hospital environments, often yielding limited success. The INCA Trial aims to address this research gap by conducting a comprehensive, cluster-randomized controlled trial that integrates education, individualized nutritional support, and community nursing care. The study is designed to evaluate clinical and cost-effectiveness outcomes, focusing on PI wound area reduction and incremental costs associated with the intervention.
Methods: The INCA Trial employs a two-group, non-blinded, cluster-randomized, pragmatic clinical trial design, recruiting 380 adult individuals (age ≥ 21 years) living in the community with stage II, III, IV, and unstageable PI(s), who are receiving home-nursing service in Singapore. Cluster randomization is stratified by postal codes to minimize treatment contamination. The intervention arm will receive an individualized nutrition and nursing care bundle (dietary education with nutritional supplementation), while the control arm will receive standard care. The 90-day intervention will be followed by outcome assessments extending over one year. Primary outcomes include changes in PI wound area and the proportion of participants achieving a ≥ 40% area reduction. Secondary outcomes include health-related quality of life (HRQOL), nutritional status, and hospitalization rates. Data analysis will be conducted on an intention-to-treat (ITT) basis, supplemented by interim analyses for efficacy and futility and pre-specified sensitivity and subgroup analyses. The primary outcome for the cost-effectiveness analysis will be based on the change to total costs compared to the change to health benefits, as measured by quality-adjusted life years (QALYs).
Discussion: The INCA Trial serves as a pioneering effort in its approach to PI management in community settings. The study uniquely emphasizes both clinical and economic outcomes and melds education, intensive dietetic support, and community nursing care for a holistic approach to enhancing PI management.
Trial Registration: The trial is registered at www.clinicaltrials.gov (NCT06078488, 10th October 2023).
ChatGPT performance on scenario-based multiple-choice questions (MCQs) in medical physiology
Authors: Prabhu Girish , Prabhu Rekha
Published: October 2023

Background and objective:
With the rapid advancement of artificial intelligence, natural language processing models like ChatGPT have gained prominence in various educational domains. This study investigated the performance of ChatGPT in answering scenario-based multiple-choice questions (MCQs) within the intricate field of medical physiology.
Materials and methods
A comprehensive dataset of 50 scenario based MCQs covering cardiovascular system, respiratory system, Endocrinology, Renal system, central nervous system topics in medical physiology was compiled. ChatGPT was then tested with these questions, and its responses were evaluated based on accuracy and contextual appropriateness. The first response obtained was taken as the final answer for scoring and analysis. If the correct option was chosen by ChatGPT, 1 mark was awarded, and the wrong option was awarded zero mark.
Results
Out of 50 MCQs in various topics in medical physiology, ChatGPT attempted all the MCQs, and total score obtained is 30/50 (60%) marks. ChatGPT performed most accurately in respiratory system MCQs with 70% (7/10) and least accurately in renal system MCQs 50% (5/10).
Conclusion
ChatGPT attempted the scenario based MCQs and attained a satisfactory score.
A Novel Temporal Mixed-Integer Market Penetration Model for Cost-effective Uptake of Electric Boilers in the UK Chemical Industry
Authors: Patel Devan Nilesh , Matalon Pauline , Oluleye Gbemi
Published: October 2023

The UK chemical industry is the largest consumer of natural gas for process heating and power generation, with an annual consumption of 26.3 TWh and accounts for 2% of UK’s total emissions. Industrial electrification enables moving away from fossil fuels to electricity for generation of lower carbon process heating. This study aims to accelerate the adoption of electric boilers in the UK's chemical industry, aligning with the UK’s ambitious 2035 industrial decarbonisation goals while considering economic impacts, by designing market-based policy interventions and comparing two adoption patterns. A novel multi-period Mixed-Integer Market Penetration Optimisation Model is developed and applied to inform decisions about transitioning from natural gas to electric boilers. The model is applied to a case study of all the heating systems (490 boilers) in the UK chemical industry from 1 MW to 60 MW boilers. At 100% uptake of electric boilers in 2033, the total carbon emissions reduce by 89%, which is above the 2035 UK industry goal of 60% reduction. Results show that effectively implementing a gas tax, electricity subsidy, annual grant and carbon tax can generate sufficient demand-pull to reduce the cost of electric boilers from 30 to 85% depending on the boiler size. A carbon tax starting at £280 per tCO2e and reducing to £170 per tCO2e coupled with electricity subsidies is essential for this transition. The policies are designed such that a win-win is achieved between government and industry; specifically, revenue from the carbon tax and gas tax is used to support the grant and electricity subsidy thereby achieving cost neutrality for government. The research establishes a robust policy timeline that can drive industrial electrification in the UK's chemical sector. It highlights the need for a multi-faceted approach, incorporating various policy instruments to overcome the barriers of high initial capital costs.
Using an interpretable amino acid-based machine learning method to enhance the diagnosis of major depressive disorder
Authors: Ho Cyrus S. H. , Tan Trevor W. K. , Chan Yee Ling , Tay Gabrielle W. N. , Tang Tong Boon
Published: October 2023

Background
Major depressive disorder (MDD) is a leading cause of disability worldwide. It is, however, a condition that is frequently overlooked and inadequately managed, given that its diagnosis relies heavily on subjective methods. At present, there are no established biomarkers that have been validated for the purposes of diagnosing and treating MDD.
Objective
This study sought to assess the diagnostic and predictive potential of the differences in serum amino acid concentration levels between MDD patients and healthy controls (HCs), integrating them into interpretable machine learning models.
Methods
70 MDD patients and 70 HCs matched in age, gender and ethnicity were recruited for the study. Serum amino acid profiling was conducted by means of chromatography-mass spectrometry (LC-MS). A total of 21 metabolites were analysed, with 17 from a preset amino acid panel and the remaining 4 from a preset kynurenine panel. Logistic regression (with and without feature selection and hyperparameter optimization) was applied to differentiate MDD patients from HCs. Findings: The best-performing model utilized both feature selection and hyperparameter optimization, and it yielded a moderate area under the receiver operating curve (AUC) classification value of 0.76 on testing data. The top five metabolites identified by this model as potential biomarkers for MDD were 3-hydroxy-kynurenine, valine, kynurenine, glutamic acid, and xanthurenic acid.
Conclusions and Clinical Implications
Our study highlights the potential of using an interpretable machine learning analysis model based on amino acids to aid and increase the diagnostic accuracy of MDD in clinical practice.
Unravelling the complex causal effects of substance use behaviours on common diseases
Authors: Xue Angli , Zhu Zhihong , Wang Huanwei , Jiang Longda , Visscher Peter M. , Zeng Jian , Yang Jian
Published: October 2023

Substance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake. In this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes. Smoking initiation shows widespread risk effects on common diseases such as asthma, type 2 diabetes, and peripheral vascular disease. Alcohol consumption shows risk effects specifically on cardiovascular diseases, dyslipidemia, and hypertensive diseases. By integrating stratified regression, genetic correlation, and MR analyses, we find evidence of dosage-dependent effects of coffee and tea intake on common diseases (e.g., cardiovascular disease and osteoarthritis). We observe that the minor allele effect of rs4410790 (the top signal for tea intake level) is negative on heavy tea intake (ƀGWAS = -0.091, s.e. = 0.007, P = 4.90 × 10-35) but positive on moderate tea intake (ƀGWAS = 0.034, s.e. = 0.006, P = 3.40 × 10-8), compared to the non-tea-drinkers. Our study provides novel insights into the complexity of the health effects of SUB and informs design for future analysis to dissect the causal relationship between behavioural traits and complex diseases.
Comparison on the Influences of Personal Characteristics as Antecedents of Learning Agility
Authors:   Human Engagement Institute, Lee Hyuneung
Published: October 2023

As cutting-edge technologies such as generative AI are advancing rapidly, many people are looking for answers to the question of what abilities or skills are essential for organizational members. Learning agility can be presented as a candidate because it refers to attitudes or abilities that are required to quickly identify and acquire the knowledge and skills needed in a new situation. The purpose of this study is to identify personal characteristics that can predict learning agility and compare the influences of each factor. In this study, core self-evaluation (a construct that encompasses self-esteem, self-efficacy, internal locus of control, and emotional stability), emotional intelligence, job involvement, person-job fit, and LMXSC were selected as antecedents of learning agility because they cover perceptions on different domains and are related to job attitudes and performance. Analyzing data collected from 260 employees working in subsidiaries of a conglomerate, the researcher discovered that EI and job involvement significantly explain learning agility after controlling for other factors and that EI has a significantly stronger effect on learning agility than person-job fit and LMXSC. This study has significance because it contributes to the development of a holistic theoretical model of learning agility and shows which factors should be focused on while designing learning agility development programs
Structural Relationship Between Self-Leadership, Emotional Intelligence, and Career Decision-Making Self-Efficacy of College Students: Comparative Analysis of Competition Models
Authors:   Human Engagement Institute, Jung Daein , Park Jiwon
Published: October 2023

This study verified the direct and mediating effects of self-leadership, emotional intelligence, and career decision-making self-efficacy among 400 third and fourth graders nationwide, and confirmed the structural relationship between the model incorporating emotional intelligence and the model incorporating self-leadership. First, the direct effects of emotional intelligence, self-leadership sub-factors (behavioral perception and will, task motivation, constructive perception), and career decision self-efficacy were statistically significant, and only behavioral perception and will were found to be significant between emotional intelligence and career decision-making self-efficacy. In particular, the relationship between emotional intelligence and career decision-making self-efficacy is very strong, so the sub-factors of self-leadership and the path of career decision-making self-efficacy were not found to have a significant suppressive effect. Second, the direct effects of self-leadership sub-factors (behavioral perception and will, task motivation, constructive perception), emotional intelligence, and career decision self-efficacy were statistically significant, and the mediating effect of emotional intelligence was found to be significant. Third, among the models that treated emotional intelligence and self-leadership as independent variables, the model with self-leadership as an independent variable was found to be a model that could better explain the population. Based on these findings, academic and practical implications were presented.
Exact entanglement in the driven quantum symmetric simple exclusion process
Authors: Bernard Denis , Hruza Ludwig
Published: October 2023

Entanglement properties of driven quantum systems can potentially differ from the equilibrium situation due to long range coherences. We confirm this observation by studying a suitable toy model for mesoscopic transport: the open quantum symmetric simple exclusion process (QSSEP). We derive exact formulae for its mutual information between different subsystems in the steady state and show that it satisfies a volume law. Surprisingly, the QSSEP entanglement properties only depend on data related to its transport properties and we suspect that such a relation might hold for more general mesoscopic systems. Exploiting the free probability structure of QSSEP, we obtain these results by developing a new method to determine the eigenvalue spectrum of sub-blocks of random matrices from their so-called local free cumulants – a mathematical result on its own with potential applications in the theory of random matrices. As an illustration of this method, we show how to compute expectation values of observables in systems satisfying the Eigenstate Thermalization Hypothesis (ETH) from the local free cumulants.