bluuebunny/crossref_metadata_2025 huggingface dataset:
Emergence of Multidrug Resistance Microbes: Bacteria, Fungi, and Viruses
Authors: Malhotra Neha , Kumar Pramod , Sethu Ramakrishnan , Rohaun Sanjay K.
Published: March 2023

Increased incidences of multidrug-resistant (MDR) microorganisms has
become a global health concern for humans, animals, and agriculture. The advent of
newer resistance mechanisms evolving in microorganisms at a high rate compared to
the treatments available urges the need to understand its origin and reservoirs. The
expanded use of antimicrobial drugs, inefficient diagnosis as well as broad use in
agriculture and veterinary contributes to the emergence of resistance in
microorganisms. Presently, almost all infectious agents (bacteria, fungi, and viruses)
have developed MDR. About 7 lac people die of bacterial resistance to antibiotics
every year, with an estimated ~10 million deaths by 2050. Similarly, MDR arising in
pathogenic fungi like Candida, Aspergillus, or Fusarium to the limited therapeutic
options is highly challenging. Bacteria and fungi develop resistance mainly due to
biofilm formation, increased efflux pump activity, drug target mutations, drug binding
alterations, chromosome abnormalities, and the ability to escape host immune defenses.
The co-existence of MDR bacteria and fungi forming biofilms is even much of an
alarm in medicinal applications. Apart from these, drug resistance to current antiviral
therapeutics has imposed significant risk amidst life-threatening diseases caused due to
viruses like HIV and influenza A. Owing to its severity and complexity, we aim to
illustrate the detailed mechanism and evolution of MDR in bacteria, fungi, and viruses.
We also review different approaches to deal with MDR, emphasizing alternatives,
vaccine development, global surveillance programs and stewardship measures to
combat resistance.
Natural Products: Antibacterial, Anti-fungal, and Anti-viral Agents
Authors: Rani Dey Shipa , Gogia Neha , Kumar Prasann
Published: March 2023

The existence of substantial evidence about the development of resistance to a drug among microbes has gained a lot of attention from the scientific world. To address this problem, researchers have been conducting experiments and testing strategies, including screening various molecules and using plant-derived natural products to ascertain if these substances can serve as an untapped source of antibacterial, anti-viral, and anti-fungal agents. The non-toxic, non-synthetic, causing minimal side effects, and cost-effective nature of these substances make the development of new anti-microbials heavily dependent on the use of many of these existing products and increase the demand for finding new natural products that are yet to be discovered. These plant-based natural products offer great promises to provide the best protection against infections and pathogenesis in many diseases. Furthermore, the biodegradable nature of many of these products increases their chances of being chosen by farmers and plant biologists to use to combat microbial pathogenesis. This chapter covers the current insights on the conflicts and opportunities of popular plant-derived natural anti-microbial compounds containing a reservoir of secondary metabolites, viz.. flavonoids, alkaloids, terpenes, coumarins, phenols and polyphenols. The chapter lists natural vegetable products, which serve as potent anti-bacterial and anti-fungal agents, and describes various plant extracts, which exhibit bacterial quorum sensing, biofilm as well as efflux pump inhibitory activity. Previous studies have demonstrated the effectiveness of these plant-based natural products in the treatment of neurodegenerative diseases as well. This chapter also summarizes the neuroprotective activity of these products and their potential to serve as therapeutic agents to block or delay the progression of disorders.
Amelioration in cross-matching policy with subtypes of A for priority-based demand
Authors:   Division of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, Tamil Nadu, India, Chithraponnu R. , Umamaheswari S. ,   Division of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, Tamil Nadu, India
Published: March 2023

Blood transfusion is a medical procedure that requires prolonged intervention. In clinical treatment, red blood cells (RBCs) play a vital role and most demanded product in blood transfusion. The ABO/RhD system was considered in several research projects in the absence of subtypes of blood inventory management (BIM). In the issuing process, without considering the age of the blood, it becomes a risk factor for the recipient after transfusion. To overcome this problem and provide effective treatment, BIM should enhance its stock of specific subtypes and classify the blood's age (shelf-life). In past, no studies on issuing policies have examined A_1 A_2 BO substitution in inventory management with a new A_1 A_2 BO compatible and A_2 O priority table. For this reason, in this paper blood units of different ages are examined from two perspectives: (1) the current age of each unit and its substitution possibilities, and (2) providing effective medical services. Furthermore, the proposed system can determine the optimal order up to level quantities. Medical procedures and inventory management can both be managed effectively with this model. Hence, the goal of this research proposal is to minimize wastage and shortages along with service level substitution with age-dependent demand. By providing a numerical example, the model can validate the fact that compatibility substitution reduces wastage and blood shortages. Using a cross-matching policy, the enhanced model significantly improves the objective of this model compared to ABO substitution.
Calibración, mantenimiento y reparación de equipos relacionados con la maquinaria agrícola
Authors:   Ministerio de Agricultura y Desarrollo Rural, Bogotá (Colombia),   Corporación colombiana de investigación agropecuaria, Mosquera (Colombia)
Published: March 2023

En este clip tecnológico se presenta el siguiente curso para la calibración, mantenimiento y reparación de equipos relacionados con la maquinaria agrícola como apoyo básico a los agricultores.
Desinfección de cebolla de rama
Authors:   Ministerio de Agricultura y Desarrollo Rural, Bogotá (Colombia),   Corporación colombiana de investigación agropecuaria, Mosquera (Colombia)
Published: March 2023

En este clip tecnológico el productor verá el paso a paso del proceso de desinfección de cebolla de rama, en este caso una productora oriunda de Aquitania Boyacá nos explica como se realiza este proceso en las hortalizas.
Cosecha a granel de maíz
Authors:   Ministerio de Agricultura y Desarrollo Rural, Bogotá (Colombia),   Corporación colombiana de investigación agropecuaria, Mosquera (Colombia)
Published: March 2023

Para el optimo desarrollo del cultivo de maíz y su posterior comercialización en diferentes productos, se muestra en el siguiente clip para sus buenas prácticas de manejo.
Selección de plántulas nativas
Authors:   Ministerio de Agricultura y Desarrollo Rural, Bogotá (Colombia),   Corporación colombiana de investigación agropecuaria, Mosquera (Colombia)
Published: March 2023

El MADR y Corpoica, muestra como seleccionar plántulas nativas para implementar un sistema silvopastoril
Antibacterial effect of Cannabidiol oil against Propionibacterium acnes, Staphylococcus aureus, Staphylococcus epidermidis and level of toxicity against Artemia salina
Authors: Pila Grace , Segarra Danny , Cerna Marco
Published: March 2023

Acne is one of the most common skin pathologies; one of the causes is Propionibacterium acnes, an anaerobic and gram-positive microorganism that lives in the hair follicles of the skin and currently presents resistance to antibiotic-based treatments; this research topic has the purpose of evaluating the antibiotic activity of Cannabidiol oil against Propionibacterium acnes, Staphylococcus aureus and Staphylococcus epidermidis and the level of toxicity against Artemia salina.

For the methodology, antibiograms were used by the Kirby-Bauer method, where the concentrations were evaluated: 0,8 %; 0,6 %; 0,4 %; 0,3 % and 0,1 %; Amoxicillin for positive control and Dimethyl sulfoxide (DMSO) for negative control; the percentage of inhibition against Propionibacterium acnes and two control bacteria were calculated: Staphylococcus aureus and Staphylococcus epidermidis. Once the percentage of inhibition was tested, a toxicity study was carried out against Artemia salina to determine its LD50.

The Cannabidiol oil obtained from the Ecuadorian company was used as the antibiotic agent to be evaluated, and it was found that at a concentration of 0,8%, it presented a percentage of inhibition of 91,2 %; 98,7 % and 93,6 % against Propionibacterium acnes, Staphylococcus aureus and Staphylococcus epidermidis, respectively, data that do not present a significant difference against Amoxicillin; for the Artemia salina test, an LD50 of 4,8 % was obtained; taking into account that the commercial oil has a presentation of 1,6 % (500 mg/30 mL), it results in a relatively innocuous product. Thus concluding that Cannabidiol oil is a very promising antibiotic due to the inhibition percentages presented and low toxicity.

Keywords: CBD, antibiograms, bioassay, LD50.
Fermentation of Agave americana L. sap produced in Cayambe – Ecuador
Authors: Munive Francisco , Páez María , Romero Granja Cristina , Espín Neyda , Casa-Villegas Mary
Published: March 2023

Fermentation of agave sap, also known as exudate, has become an ancestral practice throughout Ecuadorian Andean. In Cayambe, located in this region, grows Agave americana L., which is recollected, and its sap is fermented. The agave-based fermented beverage, locally named "tzawar mishki", exhibits variable features, mainly ethanol concentration. In this work, fermentation conditions of agave sap were studied to enhance ethanol yield. Two thermal treatments for raw exudate were evaluated, pasteurization at boiling point for 30 minutes and sterilization at 121°C for 15 minutes; fermentation temperature, 30°C and room (around 18°C); and two yeast strains. Thermal pretreatments have a positive impact on reducing sugars and sucrose concentration. In the first case, an increase of 76 % and 30 % has been reported, while sucrose concentration quadrupled and doubled in pasteurized and sterilized samples, respectively. The highest ethanol concentration (63,31 g/L) and the best yield (66,21 %) were accomplished through agave sap pasteurized and fermented for 96 hours at 30°C. Negligible differences have been evidenced in ethanol and other volatile compounds content between the two yeast strains evaluated.

Keywords: agave sap, ethanol, fermentation, fermentable sugars, yeast
Development of enhanced primer sets for detection of Norovirus and Hepatitis A in food samples from Guayaquil (Ecuador) by reverse transcriptase-heminested PCR
Authors: Salazar E. J. , Guerrero M. J. , Villaquiran J. A. , Suárez K.S. , Cevallos J.M.
Published: March 2023

Norovirus (NV) is an infectious biological agent that causes gastrointestinal problems of the original nonbacterial appearance of foodborne illnesses. The genotype of NV responsible for the most frequent NV disease outbreaks is GII, accounting for 60–80% of the cases. Moreover, original and new NV variants are continuously emerging, concurrent with the recent global increase in NV infections. Hepatitis A virus (HAV) is another foodborne pathogen frequently implicated in acute gastroenteritis cases around the world. The virus is transmitted among humans via the fecal-oral route, and infection by HAV causes the most severe form of viral illness acquired from foods. In this study, we implemented primer sets to detect NV genotypes I and II. We also developed primer sets for the detection of HAV. The primers were used in a heminested reverse transcriptase PCR (hnRT-PCR) protocol that was rapid and sensitive for detecting NVG1, NVGII and HAV virus in food. The hnRT-PCR was applied successfully to strawberries and spinach obtained from a local fresh-food market, where we could see NVGI, NVGII and HAV.
Keywords: Norovirus1; Hepatitis A2; gastroenteritis3; genotypes4; NVG15; NVGII6; hnRT-PCR7.
In vitro inhibition of xanthine oxidase by hydroalcoholic extracts of Corynaea crassa Hook. F
Authors: Lopez Barrera Alexandra Jenny , Gutiérrez Gaitén Yamilet Irene
Published: March 2023

Corynaea crassa is a hemiparasitic plant native to America, used for the treatment of erectile dysfunction and has been shown to have antimicrobial properties. However, it lacks other biological studies to justify its use in traditional medicine. The objective was to examine the in vitro inhibitory activity of xanthine oxidase in hydroalcoholic extracts of the species from Ecuador and Peru. The extracts obtained by maceration and the Allopurinol used as the reference drug, at concentrations of 10, 30, 40, 50 and 60 µg/mL, were tested to measure the degree of in vitro inhibition of xanthine oxidase employing spectrophotometric determination at 295nm, which is associated with the formation of uric acid. The two extracts showed significant inhibitory activity on xanthine oxidase in a concentration-dependent manner, with the highest percentages being observed at the highest concentrations, being higher for the extract from the Ecuadorian species with enzyme inhibition percentages comparable to Allopurinol. Median inhibitory concentration (IC50) values ​​of 15.35µg/mL and 17.42µg/mL were observed for the extracts from Ecuador and Peru, respectively, although the activity was more notable for the reference drug, which was shown to be an IC50 of 12.21 µg/mL. The results concluded the basis for the potential use of C. crassa in the treatment of hyperuricemia.

Keywords: xanthine oxidase, hydroalcoholic extracts, Allopurinol
Biotechnological plant breeding applied to purple blackberries
Authors: Morales Juan Marcelo , Andrade Patricia Marcela
Published: March 2023

The current project addresses the great potential of S. caripense Dunal (Tzimbalo) for intraspecific breeding and interspecific gene flow towards the related commercial crop S. muricatum Aiton (Pepino) to develop fruits with improved antioxidants, flavor, and fruit weight. This study aims to determine the interaction between genotype x altitude and identify significant differences between treatments according to fruit weight. Tzimbalo varieties GenPurpura, Gennbiotz, and GenDulce, were used. Fruit weight was analyzed using a factorial experiment under a completely randomized design (CRD). The interaction Var. x m.a.s.l. was significant (mean ± SE), Gennbiotz:a1 (4.88 g ± 0.44; C) and GenDulce:a2 (4.38 g ± 0.25; BC), followed by GenPurpura:a1 (3.33 g ± 0.36; AB); also the principal effect Var. was significant, Gennbiotz (3.93 g ± 0.23; B) and GenDulce (3.64 g ± 0.25; B), followed by GenPurpura (2.90 g ± 0.19; A). These results demonstrate distinctness, uniformity, and stability (DUS) of at least one tzimbalo variety. Fruit weight and other characteristics are relevant to improve quality and commercial potential. They are used to develop biofortified beer, jam, ice cream, and plant tissue culture media with sucrose and vitamins to strengthen biotechnological production in Cotopaxi-Ecuador.

Keywords: factorial experiment; tzimbalo varieties; fruit quality; genotype; agri-biotechnology.
Protocol for histological analysis of the interaction Vanilla planifolia - Fusarium oxysporum f. sp. vanillae
Authors: Quirino Villarreal Alejandro , Ramírez Vázquez Mónica , Velázquez López Olinda Elizabeth , Rivera-Fernández Andrés , Luna-Rodríguez Mauricio
Published: March 2023

Fusarium oxysporum f. sp. vanillae (Fov) is the main phytosanitary problem of Vanilla planifolia, invading the root and causing the rotting of up to 80% of the plants. The histological process is used to study the morphological characteristics of the tissues of interest and published a protocol to check Fov-V. planifolia interaction that was not reproducible under our conditions, so the study aimed to adapt a procedure that allows differential analysis of the mechanism of Fov invasion in V. planifolia by confocal microscopy. The bioassays consisted of analyzing Fov-infected roots. The experimental design consisted of three replicates evaluated at 12, 24, 36, 48, 60 and 72 hours post-inoculation. Roots without inoculum were used as controls. The samples were fixed in paraformaldehyde and 4% sucrose (PBS). Subsequently, the tissues were dehydrated by a combination of alcohols at different concentrations. The cuts were made with a microtome. The sections were observed under a Leica confocal microscope with a 63X objective with ap. No. 1.4, plus immersion oil; excitation lines: 405, 488, 532. The FAA + kerosene method was the procedure that allowed complete tissue sections.

Keywords: Fusariosis, Vanilla, interaction.
A Health App for Evidence-Based Postpartum Information: Development and Validation Study
Authors: Silva de Medeiros Máyra Cármem , de Oliveira Maiara Costa , Gurgel Leonandro Valério Barbosa , Ribeiro Rodrigues Anna Giselle Câmara Dantas , Micussi Maria Thereza Albuquerque Barbosa Cabral , Magalhães Adriana Gomes
Published: March 2023

Background

After childbirth, women undergo substantial physical and emotional changes. Therefore, it is important to provide them with information that helps them identify what is expected during this stage, as well as signs and symptoms that indicate complications after they have been discharged from the hospital.

Objective

This study aimed to develop a health app—Towards Motherhood—that provides evidence-based information about the postpartum period and evaluate the usability of the app with the target population.

Methods

This was a validation study involving 80 participants, including 24 professionals from the obstetric health field, 15 professionals from the technology field, and 41 postpartum women. The app was developed using React Native technology. Health professionals evaluated the app’s content using the Content Validity Index, technology professionals completed a validated evaluation to assess the appearance of the app, and postpartum women completed the System Usability Scale (SUS) to measure the usability of the app.

Results

The measurement of content validity using a Likert scale obtained an approval score of 99%. Regarding the app’s appearance, 92% of responses were positive, reflecting favorable approval. The SUS usability score was 86.2, which represents excellent acceptance.

Conclusions

The Towards Motherhood mobile app is a valid tool for promoting self-care during the postpartum period. The app’s evidence-based information, user-friendly design, and high usability make it an essential resource for women during this critical stage of their live.
Use of a Mobile Biofeedback App to Provide Health Coaching for Stress Self-management: Pilot Quasi-Experiment
Authors: Son Changwon , Hegde Sudeep , Markert Carl , Zahed Karim , Sasangohar Farzan
Published: March 2023

Background

Mental health is an increasing concern among vulnerable populations, including college students and veterans.

Objective

The purpose of this study was to determine if mobile health technology combined with health coaching can better enable a user to self-manage their mental health.

Methods

This study evaluated the mobile app “Biofeedback” that provided health coaching on stress self-management for college student veterans’ mental health concerns. Twenty-four college student veterans were recruited from a large public university in Texas during the spring 2020 semester, impacted by COVID-19. Ten participants were assigned to the intervention group where they used the mobile Biofeedback app on their smartphones and smartwatches, and 14 were assigned to the control group without the app; assignment was based on mobile phone compatibility. Both groups participated in one initial lab session where they learned a deep-breathing exercise technique. The intervention group was then asked to use the mobile Biofeedback app during their daily lives and a smartwatch, and the control group was asked to perform the breathing exercises on their own. Both groups filled out Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) self-assessments at 2-week intervals. At the end of the semester, both groups were given an exit interview to provide user experience and perceived benefits of health coaching via the mobile biofeedback app.

Results

The deep-breathing exercise in the initial lab session reduced stress in both groups. Over the course of the study, the app recorded 565 coached breathing exercises with a significant decrease (approximately 3 beats per minute) in participants’ heart rate during the 6-minute time period immediately after conducting the breathing exercises (Spearman rank correlation coefficient –0.61, P<.001; S=9,816,176). There was no significant difference between the two groups for PHQ-9 and GAD-7 scores over the course of the semester. Exit interview responses indicated that participants perceived that the mobile Biofeedback app improved their health and helped them address stress challenges. All participants reported that the intervention helped them manage their stress better and expressed that health coaching via a mobile device would improve their overall health.

Conclusions

Participants reported a positive perception of the app for their mental health self-management during a stressful semester. Future work should examine long-term effects of the app with a larger sample size balanced between male and female participants, randomized participant allocation, real-time detection of mental health symptoms, and additional features of the app.
Proactive and Ongoing Analysis and Management of Ethical Concerns in the Development, Evaluation, and Implementation of Smart Homes for Older Adults With Frailty (Preprint)
Authors: Wang Rosalie H , Tannou Thomas , Bier Nathalie , Couture Mélanie , Aubry Régis
Published: March 2023

UNSTRUCTURED

Successful adoption and sustained use of smart home technology can support the aging in place of older adults with frailty. However, the expansion of this technology has been limited, particularly by a lack of ethical considerations surrounding its application. This can ultimately prevent older adults and members of their support ecosystems from benefiting from the technology. This paper has 2 aims in the effort to facilitate adoption and sustained use: to assert that proactive and ongoing analysis and management of ethical concerns are crucial to the successful development, evaluation, and implementation of smart homes for older adults with frailty and to present recommendations to create a framework, resources, and tools to manage ethical concerns with the collaboration of older adults; members of their support ecosystems; and the research, technical development, clinical, and industry communities. To support our assertion, we reviewed intersecting concepts from bioethics, specifically principlism and ethics of care, and from technology ethics that are salient to smart homes in the management of frailty in older adults. We focused on 6 conceptual domains that can lead to ethical tensions and of which proper analysis is essential: privacy and security, individual and relational autonomy, informed consent and supported decision-making, social inclusion and isolation, stigma and discrimination, and equity of access. To facilitate the proactive and ongoing analysis and management of ethical concerns, we recommended collaboration to develop a framework with 4 proposed elements: a set of conceptual domains as discussed in this paper, along with a tool consisting of reflective questions to guide ethical deliberation throughout the project phases; resources comprising strategies and guidance for the planning and reporting of ethical analysis throughout the project phases; training resources to support leadership, literacy, and competency in project teams for the analysis and management of ethical concerns; and training resources for older adults with frailty, their support ecosystems, and the public to support their awareness and participation in teams and ethical analysis processes. Older adults with frailty require nuanced consideration when incorporating technology into their care because of their complex health and social status and vulnerability. Smart homes may have a greater likelihood of accommodating users and their contexts with committed and comprehensive analysis, anticipation, and management of ethical concerns that reflect the unique circumstances of these users. Smart home technology may then achieve its desired individual, societal, and economic outcomes and serve as a solution to support health; well-being; and responsible, high-quality care.
The Potential and Concerns of Using AI in Scientific Research: ChatGPT Performance Evaluation (Preprint)
Authors: Khlaif Zuheir N , Mousa Allam , Hattab Muayad Kamal , Itmazi Jamil , Hassan Amjad A , Sanmugam Mageswaran , Ayyoub Abedalkarim
Published: March 2023

BACKGROUND

Artificial intelligence (AI) has many applications in various aspects of our daily life, including health, criminal, education, civil, business, and liability law. One aspect of AI that has gained significant attention is natural language processing (NLP), which refers to the ability of computers to understand and generate human language.

OBJECTIVE

This study aims to examine the potential for, and concerns of, using AI in scientific research. For this purpose, high-impact research articles were generated by analyzing the quality of reports generated by ChatGPT and assessing the application’s impact on the research framework, data analysis, and the literature review. The study also explored concerns around ownership and the integrity of research when using AI-generated text.

METHODS

A total of 4 articles were generated using ChatGPT, and thereafter evaluated by 23 reviewers. The researchers developed an evaluation form to assess the quality of the articles generated. Additionally, 50 abstracts were generated using ChatGPT and their quality was evaluated. The data were subjected to ANOVA and thematic analysis to analyze the qualitative data provided by the reviewers.

RESULTS

When using detailed prompts and providing the context of the study, ChatGPT would generate high-quality research that could be published in high-impact journals. However, ChatGPT had a minor impact on developing the research framework and data analysis. The primary area needing improvement was the development of the literature review. Moreover, reviewers expressed concerns around ownership and the integrity of the research when using AI-generated text. Nonetheless, ChatGPT has a strong potential to increase human productivity in research and can be used in academic writing.

CONCLUSIONS

AI-generated text has the potential to improve the quality of high-impact research articles. The findings of this study suggest that decision makers and researchers should focus more on the methodology part of the research, which includes research design, developing research tools, and analyzing data in depth, to draw strong theoretical and practical implications, thereby establishing a revolution in scientific research in the era of AI. The practical implications of this study can be used in different fields such as medical education to deliver materials to develop the basic competencies for both medicine students and faculty members.
AI and IOT Based Road Accident Detection and Reporting System
Authors: More Adesh , Mahajan Mitali , Gholap Hemant
Published: March 2023

Abstract: Road accidents are increasing daily as the number of automobiles rises. An annual global death toll of 1.4 million and an injury toll of 50 million are reported by the World Health Organization (WHO). The absence of medical assistance at the scene of the accident or the lengthy response time during the rescue effort are the main causes of mortality. We can reduce delays in a rescue operation that has the potential to save many lives by using a cognitive agent-based collision detection and smart accident alarm and rescue system. To gather and send accident-related data to the cloud or server, the suggested system consists of a force sensor, GPS module, alarm controller, ESP8266 controller, camera, Raspberry Pi, and GSM module. The accident is then verified using cloud- based techniques for deep learning. accident is then verified using cloud-based techniques for deep learning. When the deep learning module notices an accident, it immediately alerts all nearby emergency services, including the hospital, police station, mechanics, etc.
Detecting Cloud Based Phishing Attacks Using Stacking Ensemble Machine Learning Technique
Authors: Chinguwo Michael Richard , Dhanalakshmi R.
Published: March 2023

Abstract: Cloud computing enables users to access computing services over the Internet, but this also presents a security risk due to the anonymous nature of the Internet. Social engineering attacks are one of the most common security breaches in cloud computing, where attackers trick cloud users to reveal sensitive information. Detecting phishing attacks in cloud computing is challenging, and various solutions have been proposed, including rule-based and anomaly-based detection methods. Machine learning techniques have proven to be effective in detecting and classifying phishing attacks, particularly for distinguishing between legitimate and phishing websites. This paper proposes an ensemble approach utilizing four different machine learning classifiers to detect phishing websites. The study analyzes various features, such as address bar-based, domain-based, and HTML & JavaScript-based features, and the findings reveal that the proposed ensemble approach outperforms the base classifiers, achieving the highest accuracy of 98.8%.
Fabrication of Multi-Purpose Solar Umbrella
Authors: Sumanth K , Teja K , Prasad R Kesava Vara , Kumar T Manoj , Srilatha Ch
Published: March 2023

Abstract: Heat waves often occur during sunny days in tropical regions during in summer season, with temperatures sometimes reaching over 40 to 48 degrees Celsius. These heat waves can cause heatstroke for human beings who work outside, this umbrella prototype is designed to cut of sunshine and protect them. This umbrella prototype is designed, where the fan is provided for cooling effect for a person who work outside in Sun. The designed umbrella uses solar cell attached on the above surface of the umbrella to convert solar energy into electricity. This energy is used to run a fan, light and also to charge the battery. When intensity of the sun is low the battery acts an backup for the fan, lights and mobile charging port. The key component to used for the functions is an electronic control module which includes charging circuit & discharging circuit. The charging circuit increases output voltage from the solar cell to the desired voltage to charge the battery. The discharge circuit can control electricity from the battery to drive the DC motor fan, LED indicator & charging port.
Quantum Error Correction with Quantum Autoencoders
Authors: Locher David F. , Cardarelli Lorenzo , Müller Markus
Published: March 2023

Active quantum error correction is a central ingredient to achieve robust quantum processors. In this paper we investigate the potential of quantum machine learning for quantum error correction in a quantum memory. Specifically, we demonstrate how quantum neural networks, in the form of quantum autoencoders, can be trained to learn optimal strategies for active detection and correction of errors, including spatially correlated computational errors as well as qubit losses. We highlight that the denoising capabilities of quantum autoencoders are not limited to the protection of specific states but extend to the entire logical codespace. We also show that quantum neural networks can be used to discover new logical encodings that are optimally adapted to the underlying noise. Moreover, we find that, even in the presence of moderate noise in the quantum autoencoders themselves, they may still be successfully used to perform beneficial quantum error correction and thereby extend the lifetime of a logical qubit.
Beta inversion effect of COVID-19 pandemic using capital asset pricing model
Authors: Al-Dwiry Mohammad , Amira Weaam
Published: March 2023

This paper aims to analyze the effect of the beta inversion on COVID-19 by applying the capital asset pricing model and difference-in-differences (DiD) model in the US covering the five-year period from April 26, 2017, to April 22, 2022. Coronavirus induced pandemic has altered the fundamentals of the market (Baker, Bloom, Davis, Kost, et al., 2020; Mazur et al., 2021). The higher the value beta, the greater the potential for better long-term returns, according to the capital asset pricing model (CAPM). This study showed that companies that appeared to be safe to invest in are suddenly more dangerous, and the opposite is also true. Such as industries that previously shown a contractionary effect — aviation and retail, during COVID-19 have shown more benign effects on the market. The DiD model also reveals the same. The World Health Organization (WHO) intervention had a negligible effect on the treatment group, according to the model. It is obvious that beta has been inverted before investing in these sectors. The companies that are expected to perform better like pharma and biotech, have underperformed. This study deploys the understanding of the capital asset pricing model to see how different markets performed during and before the pandemic.
Exploring the origins of vagrant Yellow-browed Warblers in Western Europe
Authors: Ozsanlav-Harris Luke , Phillips Robbie , Bailey Jake , Langley Liam , Wilson Kester , Inger Richard , Bearhop S.
Published: March 2023

Vagrancy, where individuals occur outside of known population
distributions, is a poorly understood ecological phenomenon. It can
however be a key driver of site colonisation and range expansion.
Evidence is emerging that presumed vagrant Siberian passerines in
Western Europe, e.g. Richard’s Pipits Anthus ricardii, are colonists,
with geolocator-tracked individuals returning to breed in Siberia after
wintering in Western Europe. As such, ‘vagrancy’ patterns in these taxa
could provide a model system to understand large-scale range shifts. For
example, determining the origins of vagrant individuals and linking
these to morphology and arrival date could help to identify the
potential drivers of range dynamics. Here, we investigate the origins of
vagrant Yellow-browed Warblers Phylloscopus inornatus (a migratory
Siberian breeding passerine) in Western Europe by analysing stable
hydrogen isotopes, morphology and phenology. We measure the isotopic
patterns of feathers grown on the breeding grounds and their relation to
those from two sub-species of Common Chiffchaff Phylloscopus collybita.
We found that Yellow-browed Warblers have similar hydrogen isotopic
signatures (δ2H) to the Siberian sub-species of Common Chiffchaff
Phylloscopus collybita tristis and δ2H values did not overlap with those
from the European nominate race of Common Chiffchaff Phylloscopus
collybita collybita. There was weak evidence that variation in δ2H
values was linked to differences in migratory distances in sampled
Yellow-browed Warblers. The variation in δ2H values for Yellow-browed
Warblers was similar to Chiffchaffs of the collybita and tristis
sub-species. This suggests that Yellow-browed Warblers in Western Europe
may originate from a relatively broad-front and not exclusively from an
expanding western breeding range margin. It is unclear if vagrant
Yellow-browed Warblers in Western Europe make viable return migrations
to Siberia. If they are, the subset of individuals that become colonists
could help us understand how vagrancy drives biogeographic processes,
such as the establishment of novel migration routes.
Reliability Analysis of Concrete Dam Using Spreadsheet Optimization
Authors: Majumdar Md. Rifat Bin Ahmed
Published: March 2023

A dam is a massive structure built to block the flow of water in a river
or stream, creating a reservoir. The water stored in the reservoir can
be used for various purposes such as generating electricity, irrigation,
and drinking water. Dams come in different types, but one of the most
durable and reliable types is the gravity dam. It is built mainly with
concrete and designed to hold back water using its weight. The upstream
side is where the water flows in, while the downstream side is where it
flows out. The safety of a gravity dam is analyzed through the
First-Order Reliability Method (FORM) which determines the probability
of failure or safety index. The study shows that the safety factor and
reliability index decrease as the dam height increases or as the dam
slope increases at a constant height. Additionally, the upstream slope
of earth core rockfill dams has higher safety factors and reliability
indexes than the downstream slope, making the latter the critical
failure mode.
Dealumination of Y zeolite through an economic and eco-friendly defect-engineering strategy
Authors: Dong Peng , Zhang Jinyu , Li Tiesen , Wang Chan , Xu Jingdong , Wang Tinghai , Yue Yuanyuan , Jiang Lilong , Bao Xiaojun
Published: March 2023

In this article, a sustainable defect-engineering strategy for
dealumination of Y zeolite is described. This strategy includes the
green synthesis of a well-crystallized Y zeolite with point defects
arising from the incorporation of Fe atoms by using a Fe-containing
perlite and the subsequent preparation of ultra-stable Y (USY) zeolite
by effective dealumination. The systematic characterizations verify that
Fe atoms originally existing in the perlite are incorporated into the
as-synthesized Y zeolite and function as point defects, leading to the
distortion of framework Al. The step-by-step investigation of the
dealumination process shows that vacancies are formed by the extraction
of framework Fe in the ammonium exchange, and the framework
dealumination is promoted under the combined effect of the distorted
framework Al and the formed vacancies during the steaming treatment. The
resulting USY zeolite owns excellent features in (hydro)thermal
stability, pore structure and acid property, and thus exhibits
outstanding catalytic cracking performance.
Volcanic Eruption Forecasting Using Shannon Entropy: Multiple Cases of Study
Authors: Rey-Devesa Pablo , Benítez Carmen , Prudencio Janire , Gutiérrez Ligdamis , Moreno Guillermo Cortés , Titos Manuel , Koulakov Ivan , Zuccarello Luciano , Ibáñez Jesús M.
Published: March 2023

The search for pre-eruptive observables that can be used for short-term
volcanic early warning remains a scientific challenge. Pre-eruptive
patterns in seismic data are usually identified by analyzing seismic
catalogues (e.g., the number and types of recorded seismic events), the
evolution of seismic energy, or changes in the tensional state of the
volcanic medium as a consequence of changes in the volume of the
volcano. However, although successful volcanic predictions have been
achieved, there is still no generally valid model suitable for a large
range of eruptive scenarios. In this study, we evaluate the potential
successful use of Shannon entropy as short-term volcanic eruption
forecasting extracted from seismic signals at five well studied
volcanoes (Etna, Mount St. Helens, Kilauea, Augustine, and Bezymianny).
We identified temporal patterns that can be used as short-term eruptive
precursors. We quantified how the Shannon entropy drops several hours
before the eruptions analyzed, between 4 days and 12 h before. When
Shannon entropy is combined with the temporal evolution of other
features (i.e., energy, kurtosis, and the frequency index) and
complementary information on types of seismic sources, the meaning of
physical changes in the volcanic system could be obtained. Our results
show that pre-eruptive variation in Shannon entropy offers is a
confident short-term volcanic eruption forecasting tool.
Investigating the Mainshock and Aftershock of the May 2006 Earthquake in Central Java for Aerothropolis Development at Yogyakarta International Airport
Authors: Saputra Hijrah , Amukti Rian , Saputro Sugeng Purwo , Adhi Mochamad Aryono , Pohan Ahmad S , Sismanto Sismanto , Nurcahya Budi Eka , Lewerrisa Richard , Koesuma Sorja
Published: March 2023

Research on the analysis of the source mechanism of the mainshock and
aftershock events of the May 27, 2006, Yogyakarta earthquake, which is
thought to have originated from the Opak fault and analysis of receiver
function data to model the subsurface velocity P of the Central Java
subsurface, to obtain a geological form model of the Opak fault. This
research aims to support the development of the Yogyakarta
Aerothroppolis area in terms of disaster analysis. The data used in this
study are remote Teleseismic receiver function data from the MERAMEX
station installed in 2004, and data for the Bantul earthquake event and
its aftershock event in 2006. The results obtained from the analysis are
that the Yogyakarta area is shaped like a half-graben close to
Yogyakarta International Airport. The fault that separates the western
part of Yogyakarta is still not identified. Based on the results of the
rupture process analysis of the source along the Opak fault plane, some
zones have not yet released their energy. The distribution of
aftershocks due to the mainshock on 27 May 2006 is spread around the
Opak fault, which is heading North-South, and West-East, which is
thought to have activated the minor fault to the east of the Opak fault.
The opak fault rupture area can be analyzed to have a Low Anomaly
velocity P value from the receiver function data and is the same as the
aftershock event obtained.
A Survey of Thunderstorms that Produce Megaflashes across the Americas
Authors: Peterson Michael Jay
Published: March 2023

We previously observed that long-horizontal lightning flashes exceeding
100 km in length, known as “megaflashes,” occur preferentially in
certain thunderstorms. In this study, we develop a cluster feature
approach for automatically documenting the evolutions of thunderstorm
systems from continuous lightning observations provided by the
Geostationary Lightning Mapper (GLM) on NOAA’s Geostationary Operational
Environmental Satellites (GOES). We apply this methodology to GOES-16
GLM observations from 2018 to mid-2022 to improve our understanding of
megaflash-producing storms. We find that megaflashes occur in long-lived
(median: 14 hours) storms that grow to exceptional sizes (median: 11,984
km2) while they propagate across long distances (622 km) compared to
ordinary storms. The first megaflashes are typically produced within 15
minutes of the storm reaching its peak intensity and extent, describing
the transition to mature convection. Most megaflashes occur 13 hours
after the initial megaflash activity, and are sufficiently close to
convection to suggest initiation in the convective line (where GLM has
difficulty detecting faint early light sources from these megaflashes).
In-situ generated megaflashes are rare, accounting for 2.7% of the
sample using a 50 km convective distance threshold, but also tend to
larger than normal megaflashes, possibly due to having direct access to
the electrified stratiform cloud through which megaflashes propagate.
Eye of Horus: A Vision-based Framework for Real-time Water Level Measurement
Authors: Erfani Seyed Mohammad Hassan , Smith Corinne , Wu Zhenyao , Shamsabadi Elyas Asadi , Khatami Farboud , Downey Austin R.J. , Imran Jasim , Goharian Erfan
Published: March 2023

Heavy rains and tropical storms often result in floods, which are
expected to increase in frequency and intensity. Flood prediction models
and inundation mapping tools provide decision-makers and emergency
responders with crucial information to better prepare for these events.
However, the performance of models relies on the accuracy and timeliness
of data received from in-situ gaging stations and remote sensing; each
of these data sources has its limitations, especially when it comes to
real-time monitoring of floods. This study presents a vision-based
framework for measuring water levels and detecting floods using Computer
Vision and Deep Learning (DL) techniques. The DL models use time-lapse
images captured by surveillance cameras during storm events for the
semantic segmentation of water extent in images. Three different
DL-based approaches, namely PSPNet, TransUNet, and SegFormer, were
applied and evaluated for semantic segmentation. The predicted masks are
transformed into water level values by intersecting the extracted water
edges, with the 2D representation of a point cloud generated by an Apple
iPhone 13 Pro LiDAR sensor. The estimated water levels were compared to
reference data collected by an ultrasonic sensor. The results showed
that SegFormer outperformed other DL-based approaches by achieving
99.55% and 99.81% for Intersection over Union (IoU) and accuracy,
respectively. Moreover, the highest correlations between reference data
and the vision-based approach reached above 0.98 for both the
coefficient of determination (R2) and Nash-Sutcliffe Efficiency. This
study demonstrates the potential of using surveillance cameras and
Artificial Intelligence for hydrologic monitoring and their integration
with existing surveillance infrastructure.
Future population-adjusted heat stress extremes over the Great Lakes Region
Authors: Chakraborty TC , Wang Jiali , Yang Zhao , Qian Yun , Pringle William James , Xue Pengfei
Published: March 2023

There are large uncertainties in our future projections of climate
change at the regional scale, with spatial variabilities not resolved
adequately by coarse-grained Earth System Models (ESMs). In this study,
we use pseudo global warming simulations driven by end of the century
upper end RCP (Representative Concentration Pathway) 8.5 projections
from 11 state-of-the-art ESMs to examine changes in summer heat stress
extremes using physiologically relevant heat stress metrics (heat index
and wet bulb globe temperature) over the Great Lakes Region (GLR). These
simulations, generated from a cloud-resolving model, are at a fine
spatiotemporal resolution to detect heterogeneities relevant for human
heat exposure. These downscaled climate projections are combined with
gridded future population estimates to isolate population versus warming
contributions to population-adjusted heat stress in this region. Our
results show that a significant portion of summer will be dominated by
critical outdoor heat stress levels within GLR for this scenario.
Additionally, regions with higher heat stress generally have
disproportionately higher population densities. Humidity change
generates positive feedback on future heat stress, generally amplifying
heat stress (by 24.2% to 79.5%) compared to changing air temperature
alone, with the degree of control of humidity depending on the heat
stress metric used. The uncertainty of the results for future heat
stress are quantified based on multiple ESMs and heat stress metrics
used in this study. Overall, our study shows the importance of
dynamically resolving heat stress at population-relevant scales to get
more accurate estimates of future heat risk in the region.
Using neural network to automatic manufacture product label in enterprise under IoT environments
Authors: Zhang Kai , Dong Chongjie
Published: March 2023

When the manufacturing industry is dealing with information technology, it has to face a large number of parameters and frequent adjustments. This study proposed artificial intelligence models to find out the hidden rules behind a large number of customized labels, through data processing and model building. Model and parameter experiments are used to improve the effectiveness of artificial intelligence models, and the method of cyclic testing is adopted to increase the diversity of the test set. The results of this paper, we integrate each stage and an auxiliary decision-making is established. The contributions of this paper, can improve the problem with reducing production line shutdown and improve factory productivity. The accuracy rate of the artificial intelligence model can be increased to 95%. The number of stoppages is reduced from 4 times to 1 time per month. Under full capacity, this assist the decision-making system can reduce loss cost.