bluuebunny/crossref_metadata_2025 huggingface dataset:
Property Tuning through Fine Size Control and Hierarchical Nanostructuring of Metal Oxide Nanoparticles Supported in Porous Matrices: a Review
Authors: de Oliveira Cristine , Sigoli Fernando , Mazali Italo
Published: May 2024

In the nanoscale, matter presents different properties compared to its bulk counterparts, owing to the considerable increase of the surface/bulk ratio, as well as the occurrence of quantum confinement effects. One method to fine control the growth of nanoparticles, their size and nanostructure is to use metalorganic deposition combined with a porous matrix as host, where pores act as nanoreactors for nanoparticle growth, resulting in chemically integrated systems. In this review, we look at the history and achievements of the chemical method of impregnation-decomposition cycles for the precise size control, property tuning and tailored synthesis of metal oxide nanoparticles. We give an overview of the various oxide nanoparticles and nanomaterials developed over the years, and how the method of impregnation-decomposition cycles allowed the synthesis of pure, doped and core-shell oxide nanoparticles, as well as the tuning of their properties through the combined fine control of nanoparticle size, nanostructure, and composition.
Development of die drawing design factor prediction models for trenchless rehabilitation of water pipes: a case study
Authors: Oh Yoojin , Park Haekeum , Kim Kibum , Kim Taehyeon , Hyung Jinseok , Koo Jayong
Published: May 2024

Maintenance and replacement of aging water pipes are critical for urban development. To this end, trenchless rehabilitation methods that do not require excavation offer an efficient replacement for aging water pipes. Thus, this study developed a trenchless method using die drawing, which continuously inserts polyethylene (PE) liners into the reach point while maintaining traction in the host aging pipe. If the traction is removed after a certain period, the initially contracted liner pipe undergoes expansion under natural restoration and tightly adheres to the inner wall of the host pipe to achieve structural regeneration of the aging pipe. This study aimed to determine the factors influencing the die drawing process using a rehabilitation design. Accordingly, we experimented with the die drawing method to achieve structural reinforcement using high elasticity PE liners. Thereafter, based on the experimental data, we developed prediction models to estimate traction, pipe restoration rate after traction release, and pipe restoration period. The developed models estimated the minimum required restoration period and provided deeper insights into the restoration behavior of the die drawing method employed in pre-equipment maintenance before on-site construction.
Comparison of bias correction methods to regional climate model simulations for climate change projection in Muger Subbasin, Upper Blue Nile Basin, Ethiopia
Authors: Dinku Manamno Beza , Gibre Alene Moshe
Published: May 2024

The objective of this study was to evaluate the best performed bias correction methods to simulate the regional climate models for future climate change projections in Muger Subbasin. Delta change methods perform very well with a coefficient of correlation of 0.99 and a percent of bias –3. When we compare its corrected simulation result with observed data, the delta change method seems to have with no biases for maximum temperature, but increases by 1.67 °C from the mean for minimum temperature of 0.39 and 38.41 mm for monthly and annual precipitation, respectively. Delta change methods underestimate the model result for both temperature and precipitation. Linear scaling and variance scaling methods overestimate the maximum temperature of the simulation by 0.002 and 0.004 °C from the mean of the observed data, but it underestimates 1.59 and 1.56 °C the minimum temperature, respectively. The long-term temperature projection values (2060–2090) are higher than the near-term projections (2030–2060) for both RCP2.6 and RCP8.5 scenarios. Similarly, the change in annual precipitation for the long-term is higher than the near-term projections. As a conclusion, the results draw attention to the fact that bias-adjusted regional climate models data are crucial for the provision of local climate change impact studies in the Muger Subbasin.
Impact of leachate on groundwater quality using physicochemical characteristics
Authors: Weju Tarekegn Tadesse , Getaneh Zerihun
Published: May 2024

This study assesses the impact of Koshe open dump site leachate on nearby groundwater quality. Groundwater quality is threatened by open dump sites. Groundwater samples around Koshe open dump sites showed elevated levels of various physicochemical characteristics, including Electrical conductivity (EC), Potassium (K), Iron (Fe), Chromium (Cr3), Lead (Pb), Mercury (Hg), Total Alkalinity, Nitrate (NO3−), Phosphate (PO4+), Cadmium (Cd), Bicarbonates (HCO3−), Arsenic (As), Salinity, Cobalt (Co), and Silicon (Si), exceeding Ethiopian, WHO, and EPA drinking-water quality standards. Among the sampled wells, the one located at Ayer Tena High School, upstream of Koshe, exhibited significantly lower concentrations of parameters indicating leachate impact on groundwater quality As, Cd, Cr3, Pb, Hg, Molybdenum (Mo), NO3-, K, and PO4+ compared to others. The presence of these parameters in nearby groundwater wells suggests a substantial impact of the Koshe dump site on groundwater quality. Traditional landfills and dump sites must be outlawed, and new hygienic landfills must be constructed in a convenient location to end the continued groundwater pollution.
ECOSSISTEMA DE INOVAÇÃO E A INDÚSTRIA CRIATIVA
Authors: Felizola Matheus Pereira Mattos , Marques Jane Aparecida , Silva Amanda Luiza Soares
Published: May 2024

The purpose of the present research was to investigate the agents involved in an innovation ecosystem within the realm of the creative industry, drawing on relevant international literature. The interest emerged from the need to assess the existence of international examples identifying new innovative protagonists. To this end, a systematic review of publications indexed in the Web of Science database was undertaken, using the content analysis method based on Bardin (2016). After developing the protocol for filtering and analysis, 46 articles published on the platform between 2020 and 2024 were identified and examined. It is possible to observe that the discussion about innovation ecosystems and the creative industry transcends regional boundaries, addressing the need to integrate both urban and rural areas. This integration is achieved through the creation of innovation districts, innovation zones, creativity collectives, creative cities, and smart cities, all spaces guided by sustainability concerns, with the purpose of unifying the interests of industry, civil society, government, and academia. For the effective generation of innovative products, it becomes indispensable to have creative professionals endowed with specific managerial skills, supported by well-defined business models and organizational flows. Furthermore, it is essential to maintain constant attention to aspects related to intellectual property rights and the implementation of public policies that promote the development of the creative industry.
The Features of Shared Genes among Transcriptomes Probed in Atopic
Dermatitis, Psoriasis, and Inflammatory Acne: S100A9 Selection as the
Target Gene
Authors: Wang Wei , Hwang Sungbo , Park Daeui , Park Yong-Doo
Published: May 2024

Background:

Atopic dermatitis (AD), psoriasis (PS), and inflammatory acne (IA) are
well-known as inflammatory skin diseases. Studies of the transcriptome with altered expression
levels have reported a large number of dysregulated genes and gene clusters, particularly those involved
in inflammatory skin diseases.

Objective:

To identify genes commonly shared in AD, PS, and IA that are potential therapeutic targets,
we have identified consistently dysregulated genes and disease modules that overlap with
AD, PS, and IA.

Methods:

Microarray data from AD, PS, and IA patients were downloaded from Gene Expression
Omnibus (GEO), and identification of differentially expressed genes from microarrays of AD, PS,
and IA was conducted. Subsequently, gene ontology and gene set enrichment analysis, detection
of disease modules with known disease-associated genes, construction of the protein-protein interaction
(PPI) network, and PPI sub-mapping analysis of shared genes were performed. Finally, the
computational docking simulations between the selected target gene and inhibitors were conducted.

Results:

We identified 50 shared genes (36 up-regulated and 14 down-regulated) and disease modules
for each disease. Among the shared genes, 20 common genes in PPI network were detected
such as LCK, DLGAP5, SELL, CEP55, CDC20, RRM2, S100A7, S100A9, MCM10, AURKA,
CCNB1, CHEK1, BTC, IL1F7, AGTR1, HABP4, SERPINB13, RPS6KA4, GZMB, and TRIP13. Finally,
S100A9 was selected as the target gene for therapeutics. Docking simulations between
S100A9 and known inhibitors indicated several key binding residues, and based on this result, we
suggested several cannabinoids such as WIN-55212-2, JZL184, GP1a, Nabilone, Ajulemic acid,
and JWH-122 could be potential candidates for a clinical study for AD, PS, and IA via inhibition
of S100A9-related pathway.

Conclusion:

Overall, our approach may become an effective strategy for discovering new disease
candidate genes for inflammatory skin diseases with a reevaluation of clinical data.
The Cross-Talk of Non-coding RNAs and Inflammation in Human Cancer
Authors: Li Jiayi , Lei Xiaoyong , Yang Xiaoyan
Published: May 2024

Despite advanced clinical treatment, the mortality rate of cancer patients is high. Recent
studies have linked the development of cancer to inflammation. Many cancers are exacerbated
by the emergence of inflammatory responses, and non-coding RNAs play an important
role in inflammation. Non-coding RNAs include microRNAs, circular RNAs, long-chain noncoding
RNAs, etc. The non-coding RNA regulatory network composed of microRNAs, circular
RNAs and long-chain non-coding RNAs is involved in the regulatory process of multiple gene
expression. They can act on various signaling pathways, such as wnt/β-catenin, nuclear factorkappa
B, phosphatidylinositol 3 kinase/ AKT, mitogen-activated protein kinase, and so on. These
signaling pathways can control the occurrence of inflammatory response to some extent, such
as regulating the expression of inflammatory cytokines (such as interleukin-6, interferongamma,
tumor necrosis factor-α, and so on), making them upregulated or down-regulated.
Therefore, it is important to study the role of non-coding RNAs in inflammation to contribute to
the future of cancer.
Flavonoids and Organic Acids Affect Phase II Metabolism based on the Regulation of UGT1A1 Expression and Function
Authors: Zhang Lin , Zhang Xuerong , Wang Caiyan
Published: May 2024

Background:

Exogenous substances modulate metabolism by regulating the expression
and function of UDP-glycosyltransferases (UGTs). However, the exact mechanism in the
intestine was rarely understood. Herein, we explored the effects of representative flavonoids and
organic acids on the regulation of UGT1A1.

Methods:

MTT assays and western blot analysis were used to explore the effect of polyphenols.
X-ray diffraction was used to reveal the catalytic mechanisms of UGTs.

Results:

MTT assays showed that these compounds basically had no cytotoxicity, even in concentrations
up to 200 μM. Then, through western blot assays, UGT1A1 expression was increased
after being treated with liquiritigenin and caffeic acid. Furthermore, liquiritigenin and
caffeic acid enhanced the nuclear translocation of Nrf2. Moreover, a 2.5-Å crystal structure of
the complex containing UGTs C-terminal domain and organic acid was solved, and the UDPGA
binding pocket could be occupied by organic acid, suggesting the enzyme activity might be impaired
by organic acid.

Conclusion:

Above all, liquiritigenin and caffeic acid maintained the metabolism balance by
upregulating the expression of UGT1A1 via Nrf2 activation and inhibiting the enzyme activity
in Caco-2 cells.
Classification of Various Plant Leaf Disease Using Pretrained Convolutional Neural Network On Imagenet
Authors: Hukkeri Geetabai S , Soundarya B C , Gururaj H L , Ravi Vinayakumar
Published: May 2024

Introduction/Background

Plant diseases and pernicious insects are a considerable threat in the agriculture sector. Leaf diseases impact agricultural production. Therefore, early detection and diagnosis of these diseases are essential. This issue can be addressed if a farmer can detect the diseases properly.

Objective

The fundamental goal of this project is to create and test a model for precisely classifying leaf diseases in plants.

Materials and Methods

This paper introduces a model designed to classify leaf diseases effectively. The research utilizes the publicly available PlantVillage dataset, which includes 38 different classes of leaf images, ranging from healthy to disease-infected leaves. Pretrained CNN (Convolutional Neural Network) models, includingVGG16, ResNet50, InceptionV3, MobileNetV2, AlexNet, and EfficientNet, are employed for image classification.

Results

The paper provides a performance comparison of these models. The results show that theEfficientNetmodel achieves an accuracy of 97.5% in classifying healthy and diseased leaf images, outperforming other models.

Discussion

This research highlights the potential of utilizing advanced neural network architectures for accurate disease detection in the agricultural sector.

Conclusion

This study demonstrates the efficacy of employing sophisticated CNN models, particularlyEfficientNet, to properly identify leaf diseases. Such technological developments have the potential to improve disease detection in agriculture. These improvements help to improve food security by allowing for preventive actions to battle crop diseases.
Recent Advances in Unconventional Machining of Smart Alloys for use in Critical Manufacturing Sectors
Authors: Sampath Santosh , V. Sampath , S. Srivatsan
Published: May 2024

Nowadays, numerous metallic alloys are known to exhibit smart behavior;
these metallic materials are categorized as shape memory alloys (SMAs). Shape
memory alloys belong to a group of smart alloys that have the potential to recover their
original shape from a deformed shape when triggered by factors, such as heat,
electricity, and stress. This shape change gives rise to SMART behavior (Stimulated
Martensite - Austenite Reverse Transformation). Shape memory alloys have attractive
characteristics, such as high recovery force, high strength, etc. Shape memory alloys
find their use in many applications i.e., aerospace, biomedical, automobile, robotics,
etc. The ever-increasing demand for shape memory alloys among industries is
attributed to their ability to respond to different machining processes. Conventional
machining processes (CM) and unconventional machining (UCM) processes are the
two major types of processes upon which the studies on shape memory alloys have
been carried out. The machining studies carried out reveal that the use of conventional
machining to process shape memory alloys to various products is considered
undesirable since it causes damage and introduces changes in the characteristics of the
material. Unconventional machining processes are therefore preferred. Various types of
unconventional machining processes like laser beam machining (LBM),
electrodischarge machining (EDM), electrochemical machining (ECM), abrasive jet
machining (AJM), abrasive water-jet machining (AWJM), etc., generally involve
machining of shape memory alloys in an unconventional way so that the wear rate and
surface roughness are reduced. A study of unconventional machining processes is
therefore considered essential contributing further to the domain of smart materials.
Hence, through this review, the mechanism of shape memory alloys and their
applications, various types of unconventional machining processes, and their recent
advances are highlighted.
Didactic digital tools and autonomous learning in information technology engineering students at Uleam, Chone Extension
Authors: Mera-Santander Nubia Aracely , Rivadeneira-Zambrano Fabricio
Published: May 2024

The technological scenario has transformed the way people communicate, learn and carry out daily activities. Since the COVID-19 pandemic, it has been proven that technology has provided many advantages, but challenges related to access and security have also been generated, making it essential to guarantee that all people have the same opportunities related to scientific access. The objective was to evaluate the use of digital didactic tools in the autonomous learning of information technology engineering students of the ULEAM Chone extension, the study was descriptive with the quantitative approach, the inductive-deductive method was applied, the review of information and the statistical method. Among the instruments used in the work, a structured survey was used for the 16 teachers and information technology students with a total population of 193 students, applying the Larry and Murray formula with a sample of 89 schoolchildren. It is concluded that digital tools offer advantages in autonomous learning such as time optimization, in addition to allowing the analysis of various investigative approaches, even though there are factors that affect the educational field for the application of digital tools such as social, cultural, political and economic.
Smart Aquaculture in Internet of Things-based Catfish Farming
Authors: Kurniawan Budi Kusnanto  , Aris Nasuha
Published: May 2024

The primary objective of developing the project titled "Smart Aquaculture in Internet of Things-based Catfish Farming" is to create a specialized tool for catfish farming that facilitates automated monitoring and control of water quality, eliminating the need for manual intervention at the aquaculture pond. The collected data is made accessible through a web monitoring system. The tool aims to mitigate catfish mortality risks, enhance yield, and streamline the cultivation process. The development process of this tool encompasses several stages, which are as follows: (1) Requirements Analysis, involving the identification of necessary tools and materials for the project; (2) Implementation, encompassing the design and fabrication of the tool, outlining the circuit scheme, and detailing the step-by-step manufacturing process; (3) Testing, describing the procedures and results of evaluating the tool's performance. The monitoring system employs PH- 4502C sensors, DS18B20 temperature sensor, and HC-SR04 level sensor, all controlled by ESP32 DevKit. Comparative analysis against standard measuring instruments demonstrates an average error percentage of 1.64% for pH, 0.88% for temperature, and 0.70% for water level measurements. Additionally, the data transmission test reveals a delay of 19.16 seconds, while the actuator response test, based on sensor readings, successfully operates within the system's intended parameters.
Monitoring Smart Applications for Monitoring and Controlling of IoT-Based Strawberry Hydroponic Plants
Authors: Willi Bianyosa Arif Wibiya  , Aris Nasuha
Published: May 2024

Hydroponic farming has become an attractive option in strawberry cultivation as it provides better control over the growing environment of the plants. However, proper management and continuous monitoring are challenges often faced by farmers in hydroponic farming practices. Therefore, in this study, we designed an IoT-based application that aims to monitor and control strawberry hydroponic farming through smartphone devices. The method used in this research involves developing an application that connects with various sensors installed in the hydroponic farm environment. The data obtained from the sensors is transmitted in realtime through the IoT network. In addition to the monitoring function, the application is also equipped with a control system that can be customized according to the needs of farmers. The result of this research is an application that can work from a short distance (local) or a long distance (cloud). The application is equipped with a hazard alarm notification system. The feature allows farmers to take action to maintain the health and quality of strawberry plants. The use of this application is expected to help make it easier for farmers to monitor and control hydroponic farming to be more efficient and optimize crop yields.
Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations
Authors: Zhu Lingxuan , Mou Weiming , Wu Keren , Lai Yancheng , Lin Anqi , Yang Tao , Zhang Jian , Luo Peng
Published: May 2024

This study evaluated the capabilities of the newly released ChatGPT-4V, a large language model with visual recognition abilities, in interpreting electrocardiogram waveforms and answering related multiple-choice questions for assisting with cardiovascular care.
Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review (Preprint)
Authors: Anthonimuthu Danny Jeganathan , Hejlesen Ole , Zwisler Ann-Dorthe Olsen , Udsen Flemming Witt
Published: May 2024

BACKGROUND

Multimorbidity, defined as the coexistence of multiple chronic conditions, poses significant challenges to health care systems on a global scale. It is associated with increased mortality, reduced quality of life, and increased health care costs. The burden of multimorbidity is expected to worsen if no effective intervention is taken. Machine learning has the potential to assist in addressing these challenges since it offers advanced analysis and decision-making capabilities, such as disease prediction, treatment development, and clinical strategies.

OBJECTIVE

This paper represents the protocol of a scoping review that aims to identify and explore the current literature concerning the use of machine learning for patients with multimorbidity. More precisely, the objective is to recognize various machine learning models, the patient groups involved, features considered, types of input data, the maturity of the machine learning algorithms, and the outcomes from these machine learning models.

METHODS

The scoping review will be based on the guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). Five databases (PubMed, Embase, IEEE, Web of Science, and Scopus) are chosen to conduct a literature search. Two reviewers will independently screen the titles, abstracts, and full texts of identified studies based on predefined eligibility criteria. Covidence (Veritas Health Innovation Ltd) will be used as a tool for managing and screening papers. Only studies that examine more than 1 chronic disease or individuals with a single chronic condition at risk of developing another will be included in the scoping review. Data from the included studies will be collected using Microsoft Excel (Microsoft Corp). The focus of the data extraction will be on bibliographical information, objectives, study populations, types of input data, types of algorithm, performance, maturity of the algorithms, and outcome.

RESULTS

The screening process will be presented in a PRISMA-ScR flow diagram. The findings of the scoping review will be conveyed through a narrative synthesis. Additionally, data extracted from the studies will be presented in more comprehensive formats, such as charts or tables. The results will be presented in a forthcoming scoping review, which will be published in a peer-reviewed journal.

CONCLUSIONS

To our knowledge, this may be the first scoping review to investigate the use of machine learning in multimorbidity research. The goal of the scoping review is to summarize the field of literature on machine learning in patients with multiple chronic conditions, highlight different approaches, and potentially discover research gaps. The results will offer insights for future research within this field, contributing to developments that can enhance patient outcomes.

INTERNATIONAL REGISTERED REPORT

PRR1-10.2196/53761
Resting Heart Rate and Associations With Clinical Measures From the Project Baseline Health Study: Observational Study (Preprint)
Authors: Feng Kent Y , Short Sarah A , Saeb Sohrab , Carroll Megan K , Olivier Christoph B , Simard Edgar P , Swope Susan , Williams Donna , Eckstrand Julie , Pagidipati Neha , Shah Svati H , Hernandez Adrian F , Mahaffey Kenneth W
Published: May 2024

BACKGROUND

Though widely used, resting heart rate (RHR), as measured by a wearable device, has not been previously evaluated in a large cohort against a variety of important baseline characteristics.

OBJECTIVE

This study aimed to assess the validity of the RHR measured by a wearable device compared against the gold standard of ECG (electrocardiography), and assess the relationships between device-measured RHR and a broad range of clinical characteristics.

METHODS

The Project Baseline Health Study (PHBS) captured detailed demographic, occupational, social, lifestyle, and clinical data to generate a deeply phenotyped cohort. We selected an analysis cohort within it, which included participants who had RHR determined by both ECG and the Verily Study Watch (VSW). We examined the correlation between these simultaneous RHR measures and assessed the relationship between VSW RHR and a range of baseline characteristics, including demographic, clinical, laboratory, and functional assessments.

RESULTS

From the overall PBHS cohort (N=2502), 875 (35%) participants entered the analysis cohort (mean age 50.9, SD 16.5 years; n=519, 59% female and n=356, 41% male). The mean and SD of VSW RHR was 66.6 (SD 11.2) beats per minute (bpm) for female participants and 64.4 (SD 12.3) bpm for male participants. There was excellent reliability between the two measures of RHR (ECG and VSW) with an intraclass correlation coefficient of 0.946. On univariate analyses, female and male participants had similar baseline characteristics that trended with higher VSW RHR: lack of health care insurance (both P<.05), higher BMI (both P<.001), higher C-reactive protein (both P<.001), presence of type 2 diabetes mellitus (both P<.001) and higher World Health Organization Disability Assessment Schedule (WHODAS) 2.0 score (both P<.001) were associated with higher RHR. On regression analyses, within each domain of baseline characteristics (demographics and socioeconomic status, medical conditions, vitals, physical function, laboratory assessments, and patient-reported outcomes), different characteristics were associated with VSW RHR in female and male participants.

CONCLUSIONS

RHR determined by the VSW had an excellent correlation with that determined by ECG. Participants with higher VSW RHR had similar trends in socioeconomic status, medical conditions, vitals, laboratory assessments, physical function, and patient-reported outcomes irrespective of sex. However, within each domain of baseline characteristics, different characteristics were most associated with VSW RHR in female and male participants.

CLINICALTRIAL

ClinicalTrials.gov NCT03154346; https://clinicaltrials.gov/study/NCT03154346
Impacts of temperature and coating pigment ratios on the corrosion rate of ss400 steel
Authors: Budiarto Untung , Firdhaus Ahmad , Hakim Muhammad Luqman , Tuswan Tuswan , Yusuf Fauzan Ammar Fata
Published: May 2024

Steel is the primary shipbuilding material; however, it erodes quickly. Adequate protection requires hard, durable, and adhesive coatings. This study examines how aluminium-graphite pigment and heat treatment affect epoxy-coated SS400 steel plate corrosion, adhesion, and coating resilience. This study used a 1:1 and 3:1 pigment ratio with 100°C and 150°C heat treatment. The coating layer was 250 μm thick and comprised 80% epoxy and 20% aluminum-graphite. The maximum adhesion strength, 19.62 MPa, was achieved with an aluminium-graphite pigment ratio of 1:1 and 100°C heat treatment. The top coating resistance was 6.86 Joules under identical conditions. The lowest corrosion rate, 0.047 mmpy, was at a 3:1 aluminum-graphite ratio and 150°C heat treatment. This discovery has significant consequences for shipbuilding steel corrosion resistance.
Fabrication of pbs films for air mass filter of solar simulator
Authors: Hilmi Isom , Kusuma Damar Yoga , Soetedjo Hariyadi , Hidayah Qonitatul , Salamah Umi
Published: May 2024

The production of solar panels is continuously increasing due to increasing demands at industrial and residential levels. This also leads to an increasing demand for solar simulator testing tools. A solar simulator is a tool to assess a solar panel's performance in lab and industry scales. One of the main components of the solar simulator is the Air Mass Filter (AMF). The primary function of AMF is to remove unwanted wave bands from the solar simulator light source (e.g., Xe arc lamp) so that the filtered spectrum is commensurate to that of solar irradiation. An AMF can be produced by fabricating a thin material layer on a transparent substrate like glass. The film would absorb certain wave bands in different ways. This paper reports the fabrication of the chalcogenide PbS thin films for applying AMF. The thermal evaporation technique is used for the film fabrication. PbS is known for its versatility for applications in different optical devices due to its tailorable optical properties. Different amounts (in grams) of PbS source powders are used to deposit the PbS thin films. The optical properties of the films are then examined using UV-Vis spectroscopy. The distributions of the transmittance intensity of the Xe-arc-lamp light with and without the use of the films as an optical filter are then examined using a solar simulator. From the experiments, the film deposited using a 0.012 g PbS powder source is regarded as the optimum one regarding the transmittance intensity distribution.
Kinetic and combustion characteristics of oil palm empty fruit bunch biochar using thermogravimetric analysis
Authors: Pansawati Indah Sakina , Agustin Yustika , Ahda Yusuf
Published: May 2024

The usage of renewable energy is a mitigation phenomenon majorly impacting the power sectors, with biomass being one of the sources directly replacing coal in various applications. This leads to the portrayal of biomass having the potential to be a carbonaceous material, namely the Empty Fruit Bunch (EFB) of oil palm. To increase the characteristics of EFB, it can be converted into carbon-based products through thermochemical processes, such as hydrothermal carbonization. Therefore, this study aimed to compare the characteristics of feedstock and biochar EFB using the TGA method. The heating rate used in this study is 10 – 30°C/min at five °C/min intervals. The effect of heating rate on kinetic parameters and thermal (DTG, TGA) and combustion (T ignition, T burn out) characteristics was also determined. This study carried out the HTC process at temperatures of 210ᵒC and 230ᵒC. The results showed that biochar EFB had a higher ignition, burnout temperature, and activation energy than raw EFB. Ignition temperatures for EFB-HT210°C and EFB-HT230°C were 297°C and 298°C; burnout temperatures for EFB-HT210°C, EFB-HT230°C were 407°C and 450°C; and the activation energy for EFB-HT210°C, EFB-HT230°C were 58.84 kJ/mol and 62.16 kJ/mol. Besides the characteristics of biomass, the heating rate also affects combustion. This proved that increased heating rate caused higher ignition and burnout temperature and decreased activation energy. The results also indicated that the difference in heating rate influenced the peak temperature in DTG.
EDITORIAL
Authors: Siswomihardjo Widowati
Published: May 2024

Greetings to the Readers of Jurnal Teknosains!We are proud to present the latest edition of Jurnal Teknosains in Volume 13, Number 2, June 2024. In a world that is constantly evolving, innovation and sustainable development are crucial foundations for progress in the fields of technology and science. This edition takes us through a series of research articles that highlight various important aspects in this regard, ranging from the development of renewable energy technologies to efforts in addressing global pandemics. In broad strokes, we endeavor to provide an overview of the eight research articles in the field of technology and science published in this June 2024 edition.
Teacher Training Program for Translation Technology against the Background of Industry-Education Integration
Authors: Xu Yangzi
Published: May 2024

As neural machine translation technology has entered a stage of rapid development and large-scale application, people’s understanding of translation technology has also undergone significant changes, and translation technology has become a major social phenomenon in the new era. This article analyzes the current situation and the main problems faced by the translation technology curriculum and faculty in universities within China. Taking the teacher training program in the shape of university-enterprise cooperation as an example, this article discusses the contents, methods, values, expected outcomes and suggestions on optimization of the program, aiming at providing references for the cultivation of translation talents and the training of translation teachers.
A Practical Study on Teaching of Community Hosted Bilingual Popular Science Course
Authors: Li Xinleer , Liu Xiaozhe , She Lina
Published: May 2024

The community hosted projects play an important part in community service. Among its various offerings, the community hosted popular science course has gained great love by both students and parents due to its interest and practicality. Drawing from practical experience, this study explores the teaching of community hosted bilingual popular science course. Based on the characteristics of the service objects and the requirements of hosted courses, it analyzes feasible teaching methods in combination with practical samples, so as to increase students' scientific knowledge reserve, improve their English proficiency, hone their skills in telling Chinese stories in English, and make community hosted courses more interesting and meaningful.
Research on Academic English Writing Teaching Based on Production-oriented Approach
Authors: Li Suzhen
Published: May 2024

Academic English writing is a challenging task in college English. Under traditional teaching methods, although teachers invest a lot of energy and time, little effect is achieved. This paper is based on the Production-oriented Approach proposed by distinguished Professor Wen Qiufang. Under the guidance of the teaching concept and teaching assumptions of this theory, this paper, taking a specific writing topic as an example, elaborates on how to design the three phases of motivating, enabling and assessing. In order to verify the effectiveness of this teaching method, the paper also analyzes and summarizes the collected questionnaires and interview texts. Academic English writing teaching guided by the Production-oriented Approach can help students reduce anxiety, make students' input learning more targeted, and greatly improve their reading and writing abilities.
Unveiling the Magic: A Scholarly Exploration of Harry Potter and the Philosopher’s Stone
Authors: Vyas Amritha
Published: May 2024

Unveiling the Magic: A Scholarly Exploration of Harry Potter and the Philosopher's Stone” goes through the rich tapestry of J.K. Rowling’s seminal work, dissecting its layers of meaning and cultural significance. This paper employs literary analysis to unravel the intricate themes, character dynamics, and narrative techniques present in the first installment of the Harry Potter series. Through a scholarly lens, it examines the symbolism of the Philosopher’s Stone, the nuances of alchemical allegory, and the portrayal of magic as a metaphor for empowerment and self-discovery. By illuminating these aspects, this research contributes to a deeper understanding of how the wizarding world of Harry Potter resonates with readers, captivating audiences across generations and cultures.
Application of Universal Cooperative Principles in Agricultural Cooperatives: A Case Study from Nepal
Authors: Pandey Ghanshyam , Khadka Chiranjeewee , Poudel Arbin , Cudnilova Eva
Published: May 2024

This study examines the use of universal cooperative principles by agricultural cooperatives in Nepal, highlighting their importance and the challenges they face. Data from 45 cooperatives, including savings and credit cooperatives (n=17) and multipurpose cooperatives (n=28), and 135 respondents in Tulsipur Sub-Metropolitan City, Nepal were analyzed quantitatively and qualitatively. The study suggests that principles such as democratic member control, voluntary and open membership, and member economic participation are critical to the effective and sustainable operation of agricultural cooperatives in Nepal. These principles promote members' sense of responsibility and ownership by ensuring transparency, fairness, and democratic decision-making. However, the research also identifies several constraints facing Nepal's agricultural cooperatives, including limited access to finance, inadequate infrastructure, governance issues, lack of technical expertise, and political interference. These challenges could hinder cooperatives' ability to expand into new markets, provide essential services to members, and support the long-term growth of Nepal's agricultural sector. The study concludes that addressing these issues and promoting the adoption of universal cooperative principles are essential to strengthening agricultural cooperatives in Nepal and enabling them to significantly improve the livelihoods of farmers and rural communities.
Effect of rhizobial inoculation on the nodulation, growth and yield of Soybean in the Savannah regions of Nigeria
Authors: Adeshina D.A. , Chuwang P.Z. , Odoh N.C. , Adeboye S.E.
Published: May 2024

Rhizobial inoculation is the introduction of rhizobium bacteria in a high concentration into the soil before or during the planting of crops. Field experiments were conducted during the rainy seasons of 2020, 2021, and 2022 at the Research farm of the Department of Crop Sciences, Faculty of Agriculture, University of Abuja, Gwagwalada, the Southern Guinea Savanna of Nigeria. The study aimed to analyse the effect of Bradyrhizobium japonicum inoculation on the nodulation, growth and yield parameters in Soybean. The treatments consisted of three Soybean varieties, namely TGX 1485-1D (early maturing), TGX 1448–2E (medium maturing), and TGX1987–10F (medium maturing) and Two levels of inoculant (control, with inoculant), The experiment was laid out in a randomized complete block design (RCBD), with three replicates and 54 plots. Agronomic and cultural practices were duly observed, and data were collected for growth and yield parameters. Data were subjected to analysis of variance (ANOVA) using the ‘agricolae’ package in the R Statistical Programme (R version 4.2.2.), T-test was conducted using the SPSS statistical package (Version 23), and the Duncan Multiple Range Test (DMRT) and Standard error (SE) were used to separate significant means at (P ≤ 0.05). Results showed that for all varieties of Soybean observed, the inoculated had the best performance (2685kg/ha, 2842.3kg/ha, 3038.5Kg/ha for TGX 1485-1D, TGX 1448–2E and TGX1987–10F respectively best compared to the control.
Assessing the Impact of Seasonal Decomposition on the Time Series Analysis Accuracy: A Comprehensive Study
Authors: Raghuvanshi Shivam
Published: May 2024

Abstract: Time series forecasting plays a pivotal role in decision-making across various domains, ranging from finance to healthcare and weather prediction. The accurate prediction of future values in a time series is vital for informed planning and resource allocation. The aim of this study is to explore whether the utilization of seasonal decomposition techniques, such as classical decomposition, X-12-ARIMA, and seasonal decomposition of time series (STL), can improve the effectiveness of time series forecasting models by separating the data into its distinct components, including trend and seasonality. We conduct a comprehensive analysis using real-world time series data, employing popular forecasting models like ARIMA, exponential smoothing, and machine learning-based approaches. By comparing the forecasting accuracy of these models with and without the application of seasonal decomposition techniques, we provide empirical evidence to support the hypothesis. Our research results provide valuable insights into the tangible ad- vantages of integrating seasonal decomposition techniques in time series forecasting, potentially contributing to enhanced decision support systems across diverse application domains.
AURA-The Privacy Preserving Multifunctional Desktop Voice Assistant
Authors: Dhumal Aditi , Yadav Vishal , Dhere Aniket , Bagal Navnath
Published: May 2024

Abstract: The “AURA” is the project which proposes the development of the versatile desktop voice assistant which mainly focuses on the privacy of the user.The convenience of voice interaction has surged in popularity, but concerns about user privacy remain. Conventional cloud-based voice assistants raise anxieties regarding data collection, storage, and potential misuse. This survey paper explores the burgeoning field of privacy-preserving desktop voice assistants powered by Artificial Intelligence (AI). We delve into the core challenges of on-device speech recognition, natural language understanding, and response generation while maintaining user privacy. We conclude by outlining open research questions and future directions for this evolving field, paving the way for the development of secure and user-centric voice interaction experiences on desktops.
Cybersecurity Considerations in Disaster Recovery Planning
Authors: Gudimetla Sandeep Reddy
Published: May 2024

Abstract: This article talks about the important link between cybersecurity and disaster recovery planning, showing how important it is to include strong security measures in disaster recovery plans. It looks at the risks and weaknesses that come up during disaster recovery, like being more open to online threats, having security controls broken, and the chance that vulnerabilities will appear again during the recovery process. Some of the most important things that the piece talks about to lower cyber risks are strong backup and recovery plans, data encryption, access controls, and authentication measures. It also stresses how important it is to have a clear plan for how to handle an event, regular training and education programs for cybersecurity, and ongoing improvement through testing and using new technologies. Case studies and examples from real life are used to show what happens when safety measures aren't up to par and how important it is to plan for all possible disasters.
Advanced Ensemble Framework for Diabetes Outcome Forecasting
Authors: Suresh Adithya
Published: May 2024

Abstract: Diabetes is one of the chronic diseases, which is increasing from year to year. Developing an automated system that can detect diabetes patients plays an important role in medical science. A stack classifier model is designed for the detection of diabetes by combining three base estimators such as Random Forest Classifier, LightGBM Classifier, and K-Nearest Neighbors Classifier, and Logistic Regression as meta-classifiers. The data preprocessing includes transforming categorical variables into numerical format. Each base learner is trained on the preprocessed data and predictions are made. In the meta learner stage, Logistic Regression is trained to make predictions based on the predictions of the base learners. The goal of the meta learner is to learn how to combine the predictions of the base learners to make a more accurate final prediction on whether the patient is diabetic or not. The use of a stacking classifier improves prediction accuracy compared to using a single classifier. The developed model gives an accuracy of 98%. The 5-fold cross validation is used to get a more robust estimation of generalization error. Thus, the developed model offers a means to enhance early detection and elevate the quality of care for diabetic patients.
A Critical Examination and Scrutiny between Tata Steels and JSW Steels Limited in India
Authors: Vennila Dr. R. , Sushmitha A S
Published: May 2024

Abstract: Over the past few years, the Indian steel sector has advanced quickly thanks to solid foundations. The industry is receiving all of the necessary components needed for rapid expansion. The industry is receiving billions of dollars in investments from the private sector and advantageous industrial changes from the government. Due to the robust domestic demand from the building, automotive, and infrastructure sectors, the industry was able to maintain its positive growth momentum even during the difficult economic downturn. With a stellar history, the nation is now well-known in the global steel sector. The remarkable performance of the industry has attracted global steel companies from all over the world. For instance, India's production of crude steel reached 56.6 million metric tonnes in 2009, a modest year-over-year increase of 2.7%. Conversely, a number of Asian nations, including South Korea and Japan, experienced a sharp drop in their production levels. This further demonstrates the Indian steel industry's robustness and resilience against outside risk factors. The impact of the steel industry on two significant businesses, Tata Steels and JSW Steels, is discussed in this essay. Additionally, the author has attempted to use ratio analysis in the study to highlight Tata Steels' and JSW Steels' financial performance.
Enhanced Ridesharing Using Directions API and Geolocation
Authors: Krishnan J Navneeth , Sebastian Joel , Joseph John K , George Asha J , Meckamalil Rotney Roy
Published: May 2024

Abstract: In the ever-evolving realm of urban transportation, the fusion of technological advancements and ubiquitous mobile connectivity has sparked a paradigm shift in how cities are navi- gated. This shift has led to innovative approaches in ridesharing and crowdsourcing, offering promising solutions to tackle traffic congestion, reduce emissions, and prioritize travel needs in urbanareas. Unlike traditional carpooling methods, where arrange-ments are made in advance, ridesharing in smart cities operates on real-time matching of drivers and riders, with priority given to factors such as destination and purpose.This study delves into the intricate dynamics of ridesharing and crowdsourcing for smart city transportation, investigating the complex interplay between technology and social factors.Additionally, it considers aspects of security, policy, and pricing strategies to ensure a seamlessand equitable experience for all stakeholders.Drawing insights from comprehensive case studies and practical implementations, this exploration highlights the advantages of ridesharing and crowdsourcing, including the reduction of carbon dioxide emis- sions and the prioritization of travel needs based on purpose. It offers guidance for stakeholders navigating the complexities and embracing the transformative potential of these innovative solutions in shaping the future of urban mobility.
Digital Gram Panchayat
Authors: Parade Ms. Rutuja D.
Published: May 2024

Abstract: While digital Gram panchayat monitoring your security system, there are a lot of factors to take into account. It is the duty of every village to accurately record the details of every villager. Every village uses the same system, and at the end of the year, they all submit a finalized unit record file of villagers. The administrator can show the information if there are plans or possibilities for farmers. The administrator has access to this Web application. The administrator has complete control over the user's information, forms, and profile on the system