bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study
Authors: Robinson Renee , Liday Cara , Lee Sarah , Williams Ishan C , Wright Melanie , An Sungjoon , Nguyen Elaine
Published: May 2023

Background

Artificial intelligence (AI) is a branch of computer science that uses advanced computational methods, such as machine learning (ML), to calculate and predict health outcomes and address patient and provider health needs. While these technologies show great promise for improving health care, especially in diabetes management, there are usability and safety concerns for both patients and providers about the use of AI/ML in health care management.

Objective

We aimed to support and ensure safe use of AI/ML technologies in health care; thus, the team worked to better understand (1) patient information and training needs, (2) the factors that influence patients’ perceived value and trust in AI/ML health care applications, and (3) how best to support safe and appropriate use of AI/ML-enabled devices and applications among people living with diabetes.

Methods

To understand general patient perspectives and information needs related to the use of AI/ML in health care, we conducted a series of focus groups (n=9) and interviews (n=3) with patients (n=41) and interviews with providers (n=6) in Alaska, Idaho, and Virginia. Grounded theory guided data gathering, synthesis, and analysis. Thematic content and constant comparison analysis were used to identify relevant themes and subthemes. Inductive approaches were used to link data to key concepts, including preferred patient-provider interactions and patient perceptions of trust, accuracy, value, assurances, and information transparency.

Results

Key summary themes and recommendations focused on (1) patient preferences for AI/ML-enabled device and application information, (2) patient and provider AI/ML-related device and application training needs, (3) factors contributing to patient and provider trust in AI/ML-enabled devices and applications, and (4) AI/ML-related device and application functionality and safety considerations. A number of participants (patients and providers) made recommendations to improve device functionality to guide information and labeling mandates (eg, link to online video resources and provide access to 24/7 live in-person or virtual emergency support). Other patient recommendations included (1) providing access to practice devices, (2) providing connections to local supports and reputable community resources, and (3) simplifying the display and alert limits.

Conclusions

Recommendations from both patients and providers could be used by federal oversight agencies to improve utilization of AI/ML monitoring of technology use in diabetes, improving device safety and efficacy.
Cost-Effectiveness Analyses of Digital Health Technology for Improving the Uptake of Vaccination Programs: Systematic Review (Preprint)
Authors: Wang Yingcheng , Fekadu Ginenus , You Joyce Hoi-sze
Published: May 2023

BACKGROUND

Vaccination is the most effective strategy to prevent infectious diseases, yet vaccination coverage has not reached the target level. To promote vaccination uptake, digital health interventions (DHIs) have been used in various vaccination programs.

OBJECTIVE

This study aimed to perform a systematic review of the cost-effectiveness analyses of DHIs for the improvement of the uptake of vaccination programs.

METHODS

A literature review was conducted in MEDLINE (Ovid), Embase (Ovid), APA PsycINFO (Ovid), Web of Science, Scopus, CINAHL Ultimate (EBSCOhost), Center for Review and Dissemination, and Institute for IEEE Xplore up to October 2022. Health economic evaluations that met the following inclusion criteria were included: (1) adult or pediatric vaccination programs; (2) interventions delivered through digital technology; (3) full-scale health economic analyses including cost-effectiveness, cost-utility, cost-benefit, or cost-consequence analyses; and (4) evaluations conducted by model-based or trial-based analyses. The quality of each included study was evaluated using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).

RESULTS

The systematic review included 7 studies. Four of the cost-effectiveness studies were conducted by model-based analyses, and 3 were trial-based analyses. One study reported the additional cost per quality-adjusted life years (QALYs) gained, whereas 6 studies reported the additional cost per individual vaccinated (or return case). The vaccines targeted the human papillomavirus (HPV) vaccine, influenza vaccination, measles-mumps-rubella (MMR) vaccine, and children immunization at different ages. The DHIs were delivered by television campaign, web-based decision aid, SMS text message, telephone, and computer-generated recall letters. The studies were classified as very good (n=5) and good (n=2) qualities. One study concluded that the DHI was cost-saving, and 6 studies concluded that the DHI was cost-effective.

CONCLUSIONS

This study is the first systematic review on cost-effectiveness analyses of DHIs to improve vaccination uptake. All included studies have good to very good quality on study assessment and reported the DHIs to be cost-saving or cost-effective in the improvement of vaccination uptake.

CLINICALTRIAL
Risk Prediction of Metabolic Syndrome for health management cohort:using Random Survival Forests (Preprint)
Authors: Zhu Jingchi , Qin Chunxiang , He Qingnan , Zhou Bingqian , Xia Yuanqin , Tan Xinyun
Published: May 2023

BACKGROUND

Metabolic syndrome (MetS) is a complex group of metabolic disorder syndromes that are risk factors for diabetes and cardiovascular disease. The main aims of this study were to: (1) to establish a MetS risk prediction model based on a routine health checkup cohort using the RSF algorithm, (2) to compare the prediction performance between the model established by the RSF algorithm and cox regression, and (3) visualize predictive models as a nomogram, which can be adapted for web-based use.

OBJECTIVE

The main aims of this study were to: (1) to establish a MetS risk prediction model based on a routine health checkup cohort using the RSF algorithm, (2) to compare the prediction performance between the model established by the RSF algorithm and cox regression, and (3) visualize predictive models as a nomogram, which can be adapted for web-based use.

METHODS

The model was based on data from 14,496 subjects aged≥18 years who had a comprehensive health examination and did not have MetS at baseline (2016), with a maximum follow-up of 5 years. A risk prediction model based on the RSF algorithm was developed by applying the physical examination data and compared with the Cox proportional hazards model. The Harrell consistency index (C-index) was used to discriminate the ability of the prediction model, and the Brier score (BS) was used to measure the accuracy of the model prediction results. A nomogram and a web-based application were constructed to vividly demonstrate the prediction model.

RESULTS

During the 5-year follow-up, 593 (4.09%) participants were diagnosed with MetS. In the RSF prediction model, 15 predictors were identified and then based on the Akaike information criterion strategy. we filtered the set of variables with the lowest OOB error rate (OOB=0.130) among the 15 predictors, ultimately containing seven predictors of WC, GLU, HDL-C, BMI, TG, SBP, and Age. In the testing dataset, the C-index scores of the RSF model, the simplified RSF model, and the Cox model were 0.984, 0.978, and 0.875, and the brier scores were 0.046,0.048 and 0.305, respectively, showing that the discriminatory ability and the accuracy of the prediction results of the RSF model were superior compared with the cox model.

CONCLUSIONS

We developed a MetS prediction model using the RSF algorithm, which was validated to outperform the cox model, and we constructed a nomogram that can be effectively used for the initial risk prediction of MetS. It is useful for the early identification and prediction of people at high risk of developing MetS.
Evaluating the Feasibility and Acceptance of a Mobile Clinical Decision Support System in a Resource-Limited Country: Exploratory Study (Preprint)
Authors: Ndlovu Kagiso , Stein Nate , Gaopelo Ruth , Annechino Michael , Molwantwa Mmoloki C , Monkge Mosadikhumo , Forrestel Amy , Williams Victoria L
Published: May 2023

BACKGROUND

In resource-limited countries, access to specialized health care services such as dermatology is limited. Clinical decision support systems (CDSSs) offer innovative solutions to address this challenge. However, the implementation of CDSSs is commonly associated with unique challenges. VisualDx—an exemplar CDSS—was recently implemented in Botswana to provide reference materials in support of the diagnosis and management of dermatological conditions. To inform the sustainable implementation of VisualDx in Botswana, it is important to evaluate the intended users’ perceptions about the technology.

OBJECTIVE

This study aims to determine health care workers’ acceptance of VisualDx to gauge the feasibility of future adoption in Botswana and other similar health care systems.

METHODS

The study’s design was informed by constructs of the Technology Acceptance Model. An explanatory, sequential, mixed methods study involving surveys and semistructured interviews was conducted. The REDCap (Research Electronic Data Capture; Vanderbilt University) platform supported web-based data capture from March 2021 through August 2021. In total, 28 health care workers participated in the study. Descriptive statistics were generated and analyzed using Excel (Microsoft Corp), and thematic analysis of interview transcripts was performed using Delve software.

RESULTS

All survey respondents (N=28) expressed interest in using mobile health technology to support their work. Before VisualDx, participants referenced textbooks, journal articles, and Google search engines. Overall, participants’ survey responses showed their confidence in VisualDx (18/19, 95%); however, some barriers were noted. Frequently used VisualDx features included generating a differential diagnosis through manual entry of patient symptoms (330/681, 48.5% of total uses) or using the artificial intelligence feature to analyze skin conditions (150/681, 22% of total uses). Overall, 61% (17/28) of the survey respondents were also interviewed, and 4 thematic areas were derived.

CONCLUSIONS

Participants’ responses indicated their willingness to accept VisualDx. The ability to access information quickly without internet connection is crucial in resource-constrained environments. Selected enhancements to VisualDx may further increase its feasibility in Botswana. Study findings can serve as the basis for improving future CDSS studies and innovations in Botswana and similar resource-limited countries.
Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial (Preprint)
Authors: Wilimitis Drew , Walsh Colin G
Published: May 2023

UNSTRUCTURED

Cross-validation remains a popular means of developing and validating artificial intelligence for health care. Numerous subtypes of cross-validation exist. Although tutorials on this validation strategy have been published and some with applied examples, we present here a practical tutorial comparing multiple forms of cross-validation using a widely accessible, real-world electronic health care data set: Medical Information Mart for Intensive Care-III (MIMIC-III). This tutorial explored methods such as K-fold cross-validation and nested cross-validation, highlighting their advantages and disadvantages across 2 common predictive modeling use cases: classification (mortality) and regression (length of stay). We aimed to provide readers with reproducible notebooks and best practices for modeling with electronic health care data. We also described sets of useful recommendations as we demonstrated that nested cross-validation reduces optimistic bias but comes with additional computational challenges. This tutorial might improve the community’s understanding of these important methods while catalyzing the modeling community to apply these guides directly in their work using the published code.
The Pragmatic Function of Vague Language in Business Letters Guided by the Relevance Theory
Authors: Qun Li , Bingwen Sun , Yueying Lu
Published: May 2023

Trade between China and foreign countries is increasingly frequent. As the medium of communication, business letters are playing a more and more important role in trading. It is easy to find that vague language is widely used in business letters. The successful use of vague language requires the recipient to be able to infer the writer’s intention correctly. This paper takes business letters collected online and offline as corpus, and will analyze the vague language from two aspects, that is, lexical aspect and syntactic aspect. Based on the analysis finally summarize the three main pragmatic functions of vague language in business letters, namely intent expression, self-protection and politeness.
Dalit aspects in the plays of Bohie Bhimmana and Girish Karnad: A Comparison
Authors: Reddy G. Kiran Kumar , Krupakar Paul
Published: May 2023

Girish Karnad , a genius, one of the most prominent English play-wrights. Bohie Bhimanna hails from Andhra Pradesh. Karnad from Karnataka, while both writers exposed contemporary social and political issues in their plays. They highlighted the darker aspects of life so as to revolutionize and reform the men and manners of the people. Both writers tried to voice the hardships, emotions, and feelings of the poor, down trodden and subjugated people in their works.
Existence and uniqueness of the generalized solution of a non-homogeneous hyperbolic differential equation modeling the vibrations of a dissipating elastic rod
Authors: Chávez Delgado Jhony Alfonso , Becerra Castañeda Augusto , Méndez Avalos Luis César , Rodríguez Delgado Eduardo , López Puycan Luis Asunción
Published: May 2023

The purpose of this mathematical paper is to establish a qualitative research of the existence and uniqueness of the generalized solution to a non-homogeneous hyperbolic partial differential equation problema subject to the contour condition u = 0 over Σ, and with initial conditions u(x, 0) = u0(x) in Ω, ∂ut(x, 0) = u1(x) in Ω. In the development of the research, the deductive method of Faedo-Garleskin and Medeiro is used to demonstrate the existence of the generalized solution that consists in the construction of approximate solutions in a finite dimensional space, obtaining a succession of approximate solutions to the non-homogeneous hyperbolic problem, that is, by means of a priori estimations, these successions of approximate solutions are passed to limit in a suitable topology. Then the initial conditions are verified and the uniqueness of the generalized solution is proved.
On graded G2-absorbing and graded strongly G2-absorbing second submodules
Authors: Alghueiri Shatha , Al-Zoubi Khaldoun
Published: May 2023

In this paper, we introduce the concepts of graded G2-absorbing and graded strongly G2-absorbing second submodules of graded modules over graded commutative rings. We give a number of results concerning these classes of graded submodules and their homogeneous components.
k-Zumkeller graphs through splitting of graphs
Authors: Kalaimathi M. , Balamurugan B. J.
Published: May 2023

Let G = (V,E) be a simple graph with vertex set V and edges set E. A 1−1 function f : V → N is said to induce a k-Zumkeller graph G if the induced edge function f ∗ : E → N defined by f ∗(xy) = f(x)f(y) satisfies the following conditions: 1. f ∗(xy) is a Zumkeller number for every xy ∈ E. 2. The total distinct Zumkeller numbers on the edges of G is k. In this article, we compute k-Zumkeller graphs through the graph splitting operation on path, cycle and star graphs.
Preparation of Herbal Hair Dye
Authors: Temkar Rani , Pagire Dipali
Published: May 2023

Abstract: Objective: To formulate and evaluate herbal hair dye by using herbal ingredients such as Henna, Guava leaves extract, Amla and Hibiscus. Materials and Method: Herbal based hair dye was formulated by using different plans such as psidium guajava leaf, henna, hibiscus and amla. All collected ingredients in the powder form are mixed uniformly to prepare a homogeneous mixture of powder form of dye. Result; The formulation shows the formulation shows good appearance, pH, texture and solubility. Conclusion; As compared to synthetic cures natural cures are generally more effective and safe as they are more secure with negligible secondary effects when shown with the synthetic based items. Henna is the more popular natural hair dye plant. The use of henna increases color intensity. This natural hair dye has the benefit of causing no skin damage, erythema development, or edema. It is made entirely of water soluble plant elements. We made the beneficial qualities of the natural hair dye in our study.
Achieving Maximum Power Point Tracking with Partial Shading
Authors: Fayaz Sherish , Saini Satish , Fayaz Ufaq
Published: May 2023

Abstract: In the past, gasoline consumption has been high and on the rise, resulting in a massive increase in the production and use of renewable energy. The world's interest in greener energy is increasing, and photovoltaic (PV) solar is becoming more common and expanding in value as a choice. PV energy management and harvesting provide many benefits, but there are some drawbacks, for instance, poor energy conversion efficiency brought on by electrical and optical losses. The rest of these issues might be the most difficult to handle because of the chance element connected to its creation and the partial shading phenomena. Therefore, partial shading reduces the impact on the functionality and is a crucial component of the load torque voltage regulation unit. Even though each method has a unique set of potential downsides, different approaches have been proposed and evaluated in the literature up to this point. The suggested MATLAB computation in this paper creates a PV array structure in three distinct settings under varied partial shading situations. Also, it investigates the performance spanning various colouring patterns of numerous power demand point target tracking.
Structural Design of Underwater Drone using Brushless DC Motor
Authors: Salunkhe Parag , Jaybhay Sarthak , Barbadekar Dr. Ashwinee
Published: May 2023

Abstract: The concept of drones involves aerial surveillance from a specific height. When constructing a Remotely Operated Vehicle (ROV) drone for underwater use, it is crucial to carefully consider the various structural components to ensure optimal performance and durability in harsh underwater conditions. This article provides an overview of the structural design of an ROV underwater drone, including key components such as the frame, buoyancy system, thrusters, and others. The backbone of an ROV is the frame, which is often composed of lightweight, high-strength materials like carbon fiber or aluminum. The design of the frame must be optimized for stability, strength, and maneuverability in the underwater environment. The buoyancy system, comprising the ballast and flotation devices, is essential for maintaining stability and enabling maneuverability at different depths. This drone can be operated remotely from a distance of up to 70-80 meters.
Authentication System for Enterprise Security
Authors: Suman Sourabh
Published: May 2023

Abstract: Authentication plays a central role in boosting an organization’s security posture. It helps enable an organization to keep its systems secure by permitting only authenticated users (or processes) to access the protected resources, such as computer systems, networks, databases, websites, and other network-based applications or services. Passwords are the more traditional form of authentication, but they constitute a weak form of protection; users are prone to bad password practices, such as reusing passwords, using predictable passwords, or even sharing passwords with others. To combat this issue, more companies are leveraging artificial intelligence (AI) and machine learning (ML) technologies, such as deep learning-based techniques, to develop better and more secure authentication approaches. AI/ML algorithms have been shown to bolster cybersecurity by protecting devices against cyber-attacks and preventing fraudulent activities. In this blog post, we introduce an AI solution based on deep learning and computer vision to perform face recognition-based biometrical authentication. So, what exactly does face recognition do? Face recognition is a broad problem of identifying or verifying a person in digital images or video frames through facial biometric patterns and data. The technology collects a set of unique biometric data of each person associated with their face and facial expression to authenticate a person. Face recognition technology is mostly used for two types of tasks:
Medicine Dispenser Using RFID
Authors: Paigankar Aryaman
Published: May 2023

Abstract: A medicine dispenser powered by a Atmel ATmega2560 controller was proposed in this article as a way to help people take their medications on schedule and in the recommended dosages given by their physicians. Only two out of fifty people use this innovative assistance due to its high cost, lack of information on the subject, and accessibility. It has been discovered that people are more concerned about their physique than their well-being, with many older people needing at least two assistive items per family by the year 2050. This device plan helps patients avoid this problem by reminding them to take their prescriptions on time and within the recommended window. It provides updates for patients, which is helpful for people who are aware of when to take their dosage and is particularly helpful for those who forget to do so. One of this device's key advantages is the ease of use and affordability of the framework. The device uses an Arduino MEGA, LCD display, Real-Time Clock (RTC) module, and RFID to inform patients and remind them to take their medications at the recommended time. This concise and useful framework can be of great use to older patients and those who are economically disadvantaged. Families with older citizens may find this medicine dispenser helpful as their responsibilities are reduced by reminders to take prescription medications as directed. The framework has also been connected to an online database to track the patient's medical history when needed.
Designing a SAAS Platform for Industry 4.0 Smart Manufacturing
Authors: Giri Abhinay
Published: May 2023

Abstract: The article discusses the concept of Industry 4.0 and its components, in the context of Software as a Service (SaaS) and the Internet of Things (IoT). It proposes a smart manufacturing platform built by utilizing web technologies such as AWS Cloud, React JS, Node JS, and MongoDB. The literature survey includes various research papers on integrating production systems into Industry 4.0 environments, the benefits, and challenges of implementing digital technology in manufacturing, and suggested frameworks for digital transformation and policy-based customization of workflow processes. The proposed system aims to optimize factory efficiency, improve production processes, enhance quality, and reduce costs through real-time data control, supply chain management, predictive maintenance, and remote monitoring.
Two-Unitary Decomposition Algorithm and Open Quantum System Simulation
Authors: Suri Nishchay , Barreto Joseph , Hadfield Stuart , Wiebe Nathan , Wudarski Filip , Marshall Jeffrey
Published: May 2023

Simulating general quantum processes that describe realistic interactions of quantum systems following a non-unitary evolution is challenging for conventional quantum computers that directly implement unitary gates. We analyze complexities for promising methods such as the Sz.-Nagy dilation and linear combination of unitaries that can simulate open systems by the probabilistic realization of non-unitary operators, requiring multiple calls to both the encoding and state preparation oracles. We propose a quantum two-unitary decomposition (TUD) algorithm to decompose a d-dimensional operator A with non-zero singular values as A=(U1+U2)/2 using the quantum singular value transformation algorithm, avoiding classically expensive singular value decomposition (SVD) with an O(d3) overhead in time. The two unitaries can be deterministically implemented, thus requiring only a single call to the state preparation oracle for each. The calls to the encoding oracle can also be reduced significantly at the expense of an acceptable error in measurements. Since the TUD method can be used to implement non-unitary operators as only two unitaries, it also has potential applications in linear algebra and quantum machine learning.
Robust quantum many-body scars in lattice gauge theories
Authors: Halimeh Jad C. , Barbiero Luca , Hauke Philipp , Grusdt Fabian , Bohrdt Annabelle
Published: May 2023

Quantum many-body scarring is a paradigm of weak ergodicity breaking arising due to the presence of special nonthermal many-body eigenstates that possess low entanglement entropy, are equally spaced in energy, and concentrate in certain parts of the Hilbert space. Though scars have been shown to be intimately connected to gauge theories, their stability in such experimentally relevant models is still an open question, and it is generally considered that they exist only under fine-tuned conditions. In this work, we show through Krylov-based time-evolution methods how quantum many-body scars can be made robust in the presence of experimental errors through utilizing terms linear in the gauge-symmetry generator or a simplified pseudogenerator in U(1) and Z2 lattice gauge theories. Our findings are explained by the concept of quantum Zeno dynamics. Our experimentally feasible methods can be readily implemented in existing large-scale ultracold-atom quantum simulators and setups of Rydberg atoms with optical tweezers.
Unitary Evolutions Sourced By Interacting Quantum Memories: Closed Quantum Systems Directing Themselves Using Their State Histories
Authors: Tavanfar Alireza , Parvizi Aliasghar , Pezzutto Marco
Published: May 2023

We propose, formulate and examine novel quantum systems and behavioral phases in which momentary choices of the system's memories interact in order to source the internal interactions and unitary time evolutions of the system. In a closed system of the kind, the unitary evolution operator is updated, moment by moment, by being remade out of the system's `experience', that is, its quantum state history. The `Quantum Memory Made' Hamiltonians (QMM-Hs) which generate these unitary evolutions are Hermitian nonlocal-in-time operators composed of arbitrarily-chosen past-until-present density operators of the closed system or its arbitrary subsystems. The time evolutions of the kind are described by novel nonlocal nonlinear von Neumann and Schrödinger equations. We establish that nontrivial Purely-QMM unitary evolutions are `Robustly Non-Markovian', meaning that the maximum temporal distances between the chosen quantum memories must exceed finite lower bounds which are set by the interaction couplings. After general formulation and considerations, we focus on the sufficiently-involved task of obtaining and classifying behavioral phases of one-qubit pure-state evolutions generated by first-to-third order polynomial QMM-Hs made out of one, two and three quantum memories. The behavioral attractors resulted from QMM-Hs are characterized and classified using QMM two-point-function observables as the natural probes, upon combining analytical methods with extensive numerical analyses. The QMM phase diagrams are shown to be outstandingly rich, having diverse classes of unprecedented unitary evolutions with physically remarkable behaviors. Moreover, we show that QMM interactions cause novel purely-internal dynamical phase transitions. Finally, we suggest independent fundamental and applied domains where the proposed `Experience Centric' Unitary Evolutions can be applied natuarlly and advantageously.
Perancangan UI/UX My Seven Berbasis Mobile Dengan Metode User Centered Design (UCD)
Authors: Pudjayadi Rama , Al Hakim Shidiq
Published: May 2023

Pada era digital saat ini, sistem pendidikan di indonesia perlu terus didorong untuk beradaptasi terhadap teknologi.  Dalam rangka adapatasi pada kebutuhan teknologi, terutama keniscayaan yang muncul karena pandemi COVID-19, sistem informasi yang terintegrasi dengan pembelajaran pada sekolah diperlukan untuk kelancaran proses pengajaran dan administrasi pendidikan. Oleh karena itu peneliti melakukan perancangan prototype berupa aplikasi informasi akademik pada tingkat SMK. Penelitian ini menggunakan  metode User Centered Desain (UCD), untuk dapat menghasilkan prototipe yang sesuai dengan harapan penggunanya. Melalui wawancara langsung kepada beberapa guru, murid dan tenaga administrasi, kemudian menganalisis dan membuatkan desain prototipe high fidelity yang dibutuhkan oleh pengguna. Untuk memastikan kesesuaian harapan pengguna dengan hasil desain, pada penelitian ini menguji prototipenya dengan instrument System Usability Design (SUS). Hasil dari pengujian diperoleh skor rata-rata dengan skor 74,4, hal ini menunjukan rancangan desain aplikasi MY SEVEN sebagai aplikasi sistem informasi akademik pada SMK sudah cukup baik untuk dapat dikembangkan aplikasinya dan diterapkan di sekolah.
Políticas públicas y educación de la primera infancia en la República Dominicana
Authors: Guzmán-Taveras Lourdes Natalia
Published: May 2023

Desde el 2013, en República Dominicana se declara la primera infancia de alto interés y surgen nuevos programas de atención integral. Este artículo presenta los resultados de una investigación para responder la pregunta: ¿Cuál es la alineación entre la evidencia investigativa sobre la educación de la primera infancia con la política educativa de República Dominicana y su implementación? Se trianguló información proveniente de: a) un marco conceptual de evidencias, b) el análisis documental de las políticas y su implementación y c) entrevistas a actores clave. Los resultados muestran variabilidad entre la educación obligatoria y las demás modalidades. Se requiere mejorar la alineación con la evidencia en la articulación de las instituciones, cobertura de atención, ingreso del personal docente e infraestructura y seguridad.
¿Los niños nacidos prematuros presentarán dificultades al momento de su inclusión educativa?
Authors: Dalbes Mariana
Published: May 2023

El presente artículo pretende compartir la inquietud sobre la inclusión en el ámbito escolar de los niños que nacieron con desventajas desde lo biológico dada su prematurez. Estos niños que nacen prematuros, por su inmadurez, sufren una serie de patologías que requieren cuidados especiales en los servicios de neonatología y un seguimiento posterior, a cargo de un equipo interdisciplinario de profesionales, para lograr minimizar sus secuelas y desarrollar plenamente sus capacidades.

Los bebés prematuros y de bajo peso presentan, en comparación con los nacidos a término, una serie de características que los colocan en situación de alto riesgo. Además, se trata de indagar si requirieron apoyos, si recibieron asistencia terapéutica, si la familia los acompañó en este proceso y en el arribo a la etapa escolar, para poner en evidencia si presentaron dificultades en su incorporación a la escuela (como dificultades en los aprendizajes de lectoescritura, por ejemplo).
The impact of the elasticity on the butterfly-modeled wing displacement under air laminar flow.
Authors: Kromba Ibrahim , Saffih Fayçal , Soulimane Sofiane , Bouhlel Mohamed Salim
Published: May 2023

When an airfoil is placed in a flow, it is subjected to forces whose
result consists mainly of a lift and drag force. On each section of the
profile, the local densities strongly depend on the wing having an
aerodynamic surface with the velocity of the flow. At first sight, an
aerodynamic profile can be considered a rigid body with which we
associate an initial takeoff angle. But, to optimize its performance
(maximize its lift and minimize its drag), it is vital to consider
deformations under the flow force. The profile deforms mainly in bending
and torsion. When this deformation takes place, it is called a flexible
profile. Our study on elasticity has shown, for a loading in
bending-torsion simulating an aerodynamic force, significant flexibility
of a material allows the optimization of a wing beat. Indeed, the
results indicate an increase in lift concentrated mainly in the wing
contour. Therefore, to maximize the drag the rigid profile of the
material is set. The rigid wing interacts with the air concentrated in
its center and ensures a planar flight. Second, the study made it
possible to affirm flight control. The wings’ position at ±20° from the
center of interaction showed that it was possible to ensure a better
displacement. The last simulation made it possible to study the
particles of collisions by using an approximate elasticity compromise at
572MPa and an angle of incidence of ±20° affirming an optimal contact
between the modeled wing and the laminar flow.
A pharmacovigilance study of the association between antipsychotic drugs and Venous thromboembolism based on Food and Drug Administration adverse event reporting system data
Authors: Yan Yu , Wang Ling , Yuan YanLing , Xu JiaYue , Chen YuXian , wu bin
Published: May 2023

Aims Venous thromboembolism (VTE) is a rare but serious adverse drug
reaction could be caused by antipsychotic drugs. However, the specific
correlation of VTE caused by antipsychotic drugs is still controversial.
This study explored the potential association between antipsychotics and
VTE. Method All VTE cases of antipsychotic drugs as primary suspected
medicines were extracted from the US Food and Drug Administration
adverse event reporting system (FAERS) from 2004 to
2021.Disproportionality analyses were conducted by estimating the
reporting odds ratio (ROR) and the information component (IC). Results
4, 455 VTE cases with antipsychotics as primary suspected drugs were
identified. The VTE signal was detected in haloperidol, olanzapine,
quetiapine and paliperidone. The RORs and the 95% confidence intervals
(95% CI) of t haloperidol, olanzapine, quetiapine and paliperidone were
(ROR=2.17, 95% CI(2.17-1.91), IC=1.1, 95%CI(1.52-0.66)), (ROR 2.53
95% CI 2.69–2.38 IC 1.31 95%CI 1.52-1.1), (ROR 1.37, 95% CI
1.47–1.28 IC 0.45 95%CI 0.67-0.23) and (ROR 1.6 95% CI 1.83–1.4 IC
0.67 95%CI 1.11-0.22), respectively. Pulmonary embolism occurred in
more than 50% of VTE events (2760 cases, 52.84%). The outcome
indicated that venous thrombosis caused by antipsychotics is usually a
serious consequence. Conclusion The current data mining of FAERS
suggested an association between VTE and antipsychotic drugs including
olanzapine, haloperidol, paliperidone and quetiapine, which reminds
health professionals to pay attention to the serious adverse drug
effects of antipsychotic drugs leading to venous thromboembolism.
Development of an adverse outcome pathway for deposition of energy leading to bone loss.
Authors: Sandhu Snehpal , Keyworth Mitchell , Karimi-Jashni Syna , Alomar Dalya , Smith Benjamin , Kozbenko Tatiana , Doty Stephen , Hocking Robyn , Hamada Nobuyuki , Reynolds Robert , Scott Ryan , Costes Sylvain , Beheshti Afshin , Yauk Carole , Wilkins Ruth , Chauhan Vinita
Published: May 2023

Bone loss, commonly seen in osteoporosis, is a condition that entails a
progressive decline of bone mineral density and microarchitecture, often
seen in post-menopausal women. Bone loss has been widely reported in
astronauts exposed to a plethora of stressors and in patients with
osteoporosis following radiotherapy for cancer. Studies on mechanisms
are well documented but the causal connectivity of events to bone loss
development remains incompletely understood. Herein, the adverse outcome
pathway (AOP) framework was used to organize data and develop a
qualitative AOP beginning from deposition of energy (the molecular
initiating event) to bone loss (the adverse outcome). A literature
review was conducted to compile and evaluate the state of knowledge
based on the modified Bradford Hill criteria. Following review of 1865
studies, an empirically supported AOP was developed, showing the
progression to bone loss through many factors affecting the activities
of bone-forming osteoblasts and bone-resorbing osteoclasts. The
structural, functional, and quantitative basis of each proposed
relationship was defined, for inference of causal changes between key
events. Current knowledge and its gaps relating to dose-, time- and
incidence-concordance across the key events were identified, as well as
modulating factors that influence linkages. The new priorities for
research informed by the AOP highlight areas for improvement to enable
development of a quantitative AOP used to support risk assessment
strategies for space travel or cancer radiotherapy.
Speciesenvironmental diversity relationships are shaped by the underlying speciesarea curves
Authors: Lamont Byron , Pausas Juli
Published: May 2023

The relationship of environmental (ED) or habitat (HD) diversity of a
landscape with its species richness (S) is of much interest. Based on
underlying speciesarea (SA) curves, we show that the standard linear
relationship lacks theoretical support. The SED relationship is the
product of numerous SA curves per habitat and number of distinct
habitats in the landscape. We recognize three basic SED patterns:
convex, unimodal, concave, based on three fundamental SA curves: power,
logarithmic and sigmoid. The preponderance of positive linear or absence
of SED/HD relationships reported so far can be attributed to six
causes. These include: only testing for linear relationships; limited
data sets that exclude small, unique or isolated habitats; regressions
are against non-causal variables; and use of biased data that have not
been ground-truthed. Hump-backed SED curves should apply widely in
regions with species-rich biota and need to resurrected, provided data
collected are sufficiently comprehensive and accurate.
Políticas Educacionais para o Ensino Médio Integrado
Authors: Marrafon Andrea Margarete de Almeida
Published: May 2023

Este artigo objetiva discutir as políticas educacionais voltadas para o currículo do Ensino Médio Integrado à Educação Profissional, especialmente a partir das principais alterações contidas na Base Nacional Comum Curricular - BNCC, aprovada pela Portaria n° 1.570 em 21/12/2017 e, nas Diretrizes Curriculares Gerais para a Educação Profissional e Tecnológica, aprovadas pela resolução CNE/CP nº 1, em 05 de janeiro de 2021. As reflexões apresentadas neste estudo têm como base uma pesquisa bibliográfica centrada nas regulamentações curriculares e nos estudiosos que discutem Currículo, Políticas Públicas, Educação Profissional e a Relação entre Trabalho e Educação. Com o desenvolvimento do estudo verificou-se que as propostas de alterações curriculares empreendidas a partir de 2017 evidenciam celeridade em contemplar e em ceder às pressões externas, sobretudo as ditadas pelas mudanças no modo de produção capitalista, que tem como marca o pragmatismo formativo e a visão utilitarista da educação.
UV-light induced DNA damage and repair in lymphocytes in photodermatoses
Authors: Horkay I , Tamási P , Csongor J.
Published: May 2023

Abstract i not available.
Some characteristics of the sensitizer in alkyl ethoxy sulphate
Authors: Walker AP , Ashforth GK , Davies RE , Newman EA , Ritz HL.
Published: May 2023

Abstract i not available.
Thymidine uptake by high-level epidermal cells. A potential error in studies of keratinocyte proliferation
Authors: Schellander F , Marks R.
Published: May 2023

Abstract i not available.
A critical view on citation index a discussion with ChatGPT
Authors:   C.A.L., 34110 Frontignan, France, Saint-Gregoire Pierre
Published: May 2023

This “opinion article” presents the “dialogue”, namely the series of questions addressed to chatGPT and its outputs, on the question of citation index and other metrics associated with scientific publication. The AI is asked to explain basic quantities (citation index, impact factor of journals, h-index, etc) and through different questions, to give outputs on different important problems, mainly related with citation index and its biases. The AI clearly expresses that the citation index alone should not be used for evaluation purposes, and is led to predict that in certain situations a high quality scientific article would be with a low citation index. The AI also replies that the citation index depends on several factors in a complex way, and is probably not defined in an unambiguous way from a mathematical point of view, but it appears unable to explain evolutions in the field of informetrics that occurred following issues with citation index. The article concludes that the citation index is irrelevant as it is not normalized and strongly depends on the publishing journal and databases, and that it is potentially dangerous for science.
Quantum Dots in Diagnostics of Infectious and Non- Infectious Diseases: Current Scenario and Future Prospectus
Authors: PR Kumar
Published: May 2023

Infectious and non-infectious diseases pose a tremendous challenge to global public health. Existing technologies for detecting infectious and non-infectious diseases are mostly tedious, expensive, and do not meet the World Health Organization’s (WHO) ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end user) criteria. Early diagnosis of diseases can lead to effective control and early intervention of the patient's condition. Conventional approach for diseases diagnosis are including culture and microscopy, immunology (ELISA, fluorescent immunoassays, magnetic immunoassays, RIA, lateral flow immunoassays) and PCR have drawbacks like these are expensive, inaccurate, and require skilled technicians and time consuming process, especially for the earlier and rapid detection of infectious diseases. Over the past few decades, quantum dot have attracted widespread attention due to its immense potential in the area of diagnostic medicine for early detection of disease without relying on visible symptoms. This is largely due to their unique optical properties such as high brightness, narrow emission band, and resistance to photo bleaching, multiplexing capacity, and high surface-to-volume ratio and this will make them excellent candidates for intracellular tracking, diagnostics, in vivo imaging, and therapeutic delivery. In this mini review, we examine recent advances in the diagnosis of infectious and noninfectious diseases, which has based on quantum dot nanomaterial. The current state-of-the-art and most promising quantum dot based technologies, including, QD based Lateral Flow Immunoassay, Quantum dot-based paper strip devices, QD based biomarkers, QD based biosensor devices etc. Quantum dot based techniques, devices are promising accessories in modern biomedical applications, and these techniques will go to become the future of next-generation diagnostics.
Augmented Reality Development Opportunities in Geometry Learning for Elementary Students
Authors: Fitrianingsih Elika Yuana , Akhyar Muhammad , Efendi Agus
Published: May 2023

Educational institutions will basically get many benefits from using technology, such as augmented reality technology which is designed to support the learning process in the classroom, plus augmented reality technology can be operated on smartphones. This study aims to analyze the opportunities for the use of smartphones in the context of innovation in the development of learning media with augmented reality formats. A qualitative approach was used in this study with a survey method. The population used is Madrasah Ibtidaiyah students with a sample was 127 students. The data collection technique in this study was a non-test technique, with the data collection instrument being a questionnaire. The results of this study indicate that smartphones are a technology that is quite familiar to students, considering that most students have them, students also like learning activities that utilize smartphones because they contain several components such as text, graphics, narration, video and even animation. The results of this study can certainly be the basis for developing an augmented reality-based learning media product considering the components that make students motivated to learn are contained in it. Through this research, it is hoped that new learning resource innovations will emerge with the hope that students can be facilitated in learning the material and mastering the various competencies they need.
Flipped Learning with Google Classroom in Improving Learning Outcomes and Independent Attitudes
Authors: Saputro Datuk Dwi , Rusnilawati
Published: May 2023

The application of the flipped learning model can improve student learning outcomes. This study aims to analyze the effectiveness of the application of the flipped learning model assisted by Google Classroom media in improving student learning outcomes and independence in solving social studies questions. This research is quantitative research with quasi-experiments. The population in this study were all students of an elementary school. While the sample in this study were 40 students of class V at one of the elementary schools. The research instruments used were test questions and student independence questionnaires. Researchers used validity and reliability tests on research instruments before being used in research. The prerequisite test results show that the data obtained is normally distributed and homogeneous. The data analysis technique used is the dependent t-test and the Manova test. Based on the results of the analysis, it was obtained: t-count > t-table, namely 4,918 > 1,685, so there is a difference in the use of the flipped learning model with the help of Google Classroom in improving student social studies learning outcomes; t-count > t-table, namely 6.972 > 1,685, there is a significant difference in independent attitude after applying the model flipped learning with the help of google classroom compared to before implementing; a significance value of 0.000 <0.05, there is a significant difference in learning outcomes and independent attitudes after implementing the flipped learning model with the help of google classroom compared to before implementing.
Learning and Assessment of HOTS among Senior High School Economics Students
Authors: Acheampong Kennedy , Dahlan Dadang , Disman  , Suryadi Edi , Ramdhany Muhamad Arief
Published: May 2023

In today's world, where globalization is rapidly increasing, critical thinking, rationality, and tolerance are essential for personal and interpersonal well-being. The study aims to analyze the impact of teaching methods, self-concept, and assessment on students' higher-order thinking skills (HOTS) in economics in senior high school (SHS). The research subjects involved 220 economics students from three SHS. The study used a quantitative survey method with the use of a designed questionnaire and used ordinal logistic regression to find the correlations between variables. The findings suggest that teaching methods, self-concepts, and assessment have a significant impact on students' understanding of economics subjects by promoting higher-order thinking skills. To improve Ghana's educational system and meet the Sustainable Development Goals (SDGs) 2030, the study also underlines the necessity of HOTS-oriented assessment in classroom instruction. Therefore, the study recommends the use of various instructional strategies, such as open-ended questions and practical problem-solving tasks that encourage students to manipulate unfamiliar or novel situations, rather than relying on recall or restatement of previously taught material. The implication of this study is that curriculum developers should take into consideration a well-structured question in the curriculum that will elicit students' high-order thinking skills.