bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid of Solar Energy Harvesting using IoT and WSN Technology
Authors: S.Swapna Kumar Et al. 
Published: January 2024

Many experts consider WSNs to be one of the most important scientific topics. To fully utilize WSNs to increase the lifespan of sensors, however, is challenging due to the significant energy limits. Numerous methods for energy collecting, energy transfer, and energy conservation have been proposed. The internet of things (IoT) manages a vast infrastructure of web-enabled smart devices. It does this by using data collected from its surroundings. Therefore, such devices are composed of scalable, light, and power-efficient storage nodes that, in order to operate practically, need electricity and batteries. The effectiveness and durability of IoT devices are undoubtedly greatly influenced by energy harvesting. The LEACH protocol is used along with the solar EH approach. The battery's charging and discharging curves as well as the nodes' energy state are depicted graphically. The converter receives switching pulses from the microcontroller, which also displays output current, solar panel voltage, and supercapacitor voltage. The simulation findings show that after using the solar EH approach, the battery and network lifetimes are increased.
Temporal and Spectral Analysis of EMG for Classification of Muscular Paralysis
Authors: Shubha V Patel Et al. 
Published: January 2024

Loss of muscle function is the condition referred to as paralysis. Parts of the body may be completely paralysed or only partially. The quality of life is enhanced by the early identification of paralysis. In people with paralysis and neuromuscular diseases, EMG signals can be used to analyse muscular activation. In this study, EMG signals are analysed by feature extraction and divided into two categories: normal and paralysed. The obtained findings demonstrate that the extracted features in the suggested work perform better for EMG signal categorization. The conditions of Amyotrophic Lateral Sclerosis (ALS) and Myopathy are taken into consideration in this study to examine the paralysis state. Using time and frequency domain approaches, characteristics were retrieved from the EMG of healthy and paralysed participants. Multilayer Perceptron (MLP), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting (XGBOOST), and K-Nearest Neighbour (KNN) Classifiers are the classifier models used in the study. With time domain EMG information, classifiers like MLP, SVM, RF, XGBOOST, and KNN are used. The frequency domain EMG characteristics are applied to the MLP, RF, XGBOOST, and KNN classifiers. With time domain EMG features, MLP achieved a classification accuracy of 76.5%, SVM with 77.2%, RF with 76.1%, XGBOOST with 77.1%, and KNN with 75.8%. In comparison to classifier models employing time domain EMG information, the SVM classifier performs better. The classification accuracy for MLP, RF, XGBOOST, and KNN using frequency domain EMG features is 77.7%, 76.6%, and 75%, respectively. In comparison to other classifier models with frequency domain features, the MLP and RF classifiers perform better. Time and frequency domains of the EMG of Normal, ALS, and Myopathy diseases are investigated. It has been noted that the EMG signal and its characteristics differ significantly (p<0.05) between the Normal and Paralysis conditions. EMG is utilised in the current study to analyse and categorise paralysis, which helps with early diagnosis and improved treatment options.
Comparison of the Execution Step Strategies on Scheduling Data-intensive Workflows on IaaS Cloud Platforms
Authors: Jean Edgard Gnimassoun Et al. 
Published: January 2024

The IaaS platforms of the Cloud hold promise for executing parallel applications, particularly data-intensive scientific workflows. An important challenge for users of these platforms executing scientific workflows is to strike the right trade-off between the execution time of the scientific workflow and the cost of using the platform. In a previous article, we proposed an efficient approach that assists the user in finding this compromise. This approach requires an algorithm aimed at minimizing the execution time of the workflow once the platform configuration is set. In this article, we compare two different strategies for executing a workflow after its offline scheduling using an algorithm. The algorithm that we proposed in the previous study has outperform the HEFT algorithm.
The first strategy allows some ready tasks to execute earlier than other higher-priority tasks that are ready later due to data transfer times. This strategy is justified by the fact that although our scheduling algorithm attempts to minimize data transfers between tasks running on different virtual machines, this algorithm does not include data transfer times in the planned execution dates for the various tasks of the workflow. The second strategy strictly adheres to the predetermined order among tasks scheduled on the same virtual machine.
The results of our evaluations show that the best execution strategy depends on the characteristics of the workflow. For each evaluated workflow, our results demonstrate that our scheduling algorithm combined with the best execution strategy surpasses HEFT. The choice of the best strategy must be determined experimentally following realistic simulations, such as the ones we conduct here using the WRENCH framework, before conducting simulations to find the best compromise between cost and execution time of a workflow on an IaaS platform..
Unveiling the Veiled: Unmasking Fileless Malware through Memory Forensics and Machine Learning
Authors: Jyoshna Bejjam Et al. 
Published: January 2024

In recent times, significant advancements within the realm of malware development have dramatically reshaped the entire landscape. The reasons for targeting a system have undergone a complete transformation, shifting from file-based to fileless malware.Fileless malware poses a significant cybersecurity threat, challenging traditional detection methods. This research introduces an innovative approach that combines memory forensics and machine learning to effectively detect and mitigate fileless malware. By analyzing volatile memory and leveraging machine learning algorithms, our system automates detection.We employ virtual machines to capture memory snapshots and conduct thorough analysis using the Volatility framework. Among various algorithms, we have determined that the Random Forest algorithm is the most effective, achieving an impressive overall accuracy rate of 93.33%. Specifically, it demonstrates a True Positive Rate (TPR) of 87.5% while maintaining a zero False Positive Rate (FPR) when applied to fileless malware obtained from HatchingTriage, AnyRun, VirusShare, PolySwarm, and JoESandbox datasets. To enhance user interaction, a user-friendly graphical interface is provided, and scalability and processing capabilities are optimized through Amazon Web Services.Experimental evaluations demonstrate high accuracy and efficiency in detecting fileless malware. This framework contributes to the advancement of cybersecurity, providing practical tools for detecting against evolving fileless malware threats.
IoT Applications, Platforms, Systems, And Framework based on Blockchain
Authors: Mawahib Sharafeldin Adam Boush Et al. 
Published: January 2024

The Internet of Things (IoT) has lately evolved as a new technology capable of providing real-time and cutting-edge sensing capabilities to numerous industries such as healthcare, agriculture, smart cities, smart homes, and supply chain. Because of this technology's inherent promise, it has already seen exponential growth in a wide range of use-cases across numerous application domains. As academics around the world continue to examine its capabilities, there is widespread consensus that in order to get the most out of this technology and fully realise its potential, IoT must be built on a flexible network architecture with strong support for security, privacy, and trust. Blockchain (BC) technology, on the other hand, has lately emerged as a breakthrough technology with the promise to give several beneficial qualities such as robustness, support for integrity, anonymity, decentralisation, and autonomous control. Several BC systems are offered, which may be appropriate for various use-cases, including IoT applications. As a result, the integration of IoT with BC technology is seen as a potential solution to some critical concerns. To do this, a good grasp of the requirements of various IoT applications and the viability of a BC platform for a specific application satisfying its underlying requirements is required. This project explains many ways such as the gateway process and sensor device. By addressing the present blockchain concerns, IoT may enable a variety of security services, all of which are described in detail. Various authors present some common facts on the use of blockchain in IoT, which aids in a thorough understanding of the concept. Blockchain improves security and privacy in IoT platforms. In this project, an extra immutable ledger is created using all of the resources and information mentioned in the existing procedure. [1].
A Total Self Checking Comparator Implementable on FPGAS Using Bist Technology
Authors: Mounika Posham Et al. 
Published: January 2024

an integrated circuits (IC) "manufacturing tests" may be made easier to administer with the use of design for testability (DFT). Integrated circuits' embedded memory tests make use of the TSC (TSC) approach. We have shown the TSC method and several algorithms used in TSC for the purpose of testing embedded memory in this article. An address generator, controller, comparator, and memory are the four main components of this kind of memory TSC technology. This paper details the three memory TSC controller implementation techniques. The memory TSC controller is modelled in Verilog HDL, and its accuracy is checked using the RTL compiler before synthesis.
Here we provide a way to build TSC comparators for TSC systems that may be implemented on FPGAs—totally self-checking (TSC) systems—that can be used online. By directly measuring the output of each lookup table (LUT), this approach may be utilised to do comprehensive online diagnostics of all LUTs. This entails mapping the basic components of the comparator with a limited number of test patterns. With our technique, we can achieve exhaustive diagnosis with a small number of test patterns on the order of n [O(n)] (where n is the input number to the comparator) while yet covering all bases 100% of the time, even if we are just aware of the LUT's specs and not its exact structure. For systems that need absolute reliability, FPGAs will be a perfect fit. Our experiment also included a single-event upset (SEU) induced by neutron radiation to validate the soft error rate (SER) in a field-programmable gate array (FPGA) based on static random-access memory (SRAM).
Regulations on Conditions for Foreigners’ Housing Ownership in Vietnam: Inadequacies and Possible Solutions
Authors: Le T. S. , Nguyen X. Q. 
Published: January 2024

In Vietnam, the concept of “settling down, having a good career” becomes an important goal of each individual. It means having a stable place to live can be guaranteed when you get a job. Therefore, home ownership becomes a basic human right. In the current integration trend, when the opening to trade between countries around the world is deepening, the demand for house ownership is not only limited to Vietnamese citizens, but also to foreigners. Vietnam has also recognized the problem of foreigners owning houses in Vietnam, but there are still restrictions on the number of houses, the area of houses owned and other issues. Currently, the Government is implementing a policy to attract investment in housing in order to exploit the development potential of this field in Vietnam as well as to solve the outstanding housing problem and expand the housing market. Therefore, the issue of foreigners’ home ownership becomes an important concern and is one of the research subjects to implement this policy.The article presents the provisions of Vietnamese law, international law on home ownership rights of foreign individuals and organizations in Vietnam, as well as conditions for foreign individuals and organizations to own housing in Vietnam, a guarantee of human rights. In addition, the article also points out to the shortcomings of the national legal regulation, thus making some recommendations to overcome the difficulties of the real estate market and housing development in Vietnam.
PRAGMATICS APPROACH IN ENGLISH LANGUAGE TEACHING AT SMA GAJAH MADA 3 PALEMBANG
Authors: Eliza Tiara 
Published: January 2024

In pragmatics, meaning in communication plays a significant part in terms of verbal and nonverbal. It relies upon different settings, relationship among utterers, and social elements. Because the four language skills of reading, writing, listening, and speaking do not occur in isolation in communicative texts or activities, pragmatic is very important in English language teaching. Therefore, developing the language learner's good pragmatic competence should be taken into consideration. It is essential for people who speak the English language, whether native or non-native, to use clear, comprehensible, and educated English so that they can communicate effectively and avoid misunderstandings in social situations. One of the most effective approaches in the learning process, especially learning English at the basic level namely the Pragmatic approach, which is one approach that can be used as a tool to achieve a learning goal especially learning English. Therefore, the aim of this study was how the implementation of pragmatic approach in ELT. The result reveals that the utilizing of pragmatic approach in English language classes require students to play an active role in Learning Activities.
Keywords: Pragmatics Approach, English Language Teaching, Implementation of Pragmatic Approach
Financing and Management of Secondary Education in Delta State, Nigeria
Authors: Ossai Anthony Great 
Published: January 2024

Abstract
It is impossible to overstate the impact that funding has on the management and achievement of educational goals because it drives how fast education in Nigeria develops. This study examines the management of public secondary schools in Delta State, Nigeria in relation to finance. A descriptive survey design was chosen for the investigation. The population of the study consisted of all principals of public secondary schools in Delta State. A stratified random sampling technique was used to randomly select a sample of 160 principals for the investigation. The study was guided by three research questions and three hypotheses. The data were collected using a study instrument called the “Influence of Funding and Management of Secondary School Questionnaire” (IFMSSQ). The experts-validated version of the instrument yielded a Cronbach Alpha reliability coefficient of 0.82, which is considered reliable. Research problems were addressed using descriptive statistics such as mean and standard deviation, and Z-test, conducted at a significance level of 0.05, was used to assess hypotheses. According to the study, finance is a key factor in determining how learning materials, human resource management and facilities are delivered in the education system. Among other things, the researcher came to the conclusion that to fulfill the goals of secondary education, adequate methods of financing must be adopted. Among other things, the study recommended that the government allocate sufficient funds and provide educational materials for effective and efficient teaching and learning in public secondary schools in Delta State, Nigeria.
Guillermo de Conches. Philosophia mundi (Edición bilingüe). México: Nun (Sapientia Ediciones), 2023. Traducción de Carlos Domínguez, Claudio Calabrese y Ethel Junco.
Authors: Herrera Salas Mariana 
Published: January 2024

Reseña de:
Guillermo de Conches. Philosophia mundi (Edición bilingüe). México: Nun (Sapientia Ediciones), 2023. Traducción de Carlos Domínguez, Claudio Calabrese y Ethel Junco.
The mediating effect of forgiveness on the relationship between spirituality and psychological well-being in adults with history of childhood bullying
Authors: Theodora Michelle , Sahrani Riana , Roswiyani Roswiyani 
Published: January 2024

The long-term effects of childhood bullying on psychological well-being in adulthood have recently gained attention in research. This study examines the complex dynamics of the phenomenon by investigating the role of forgiveness as a mediator in the relationship between spirituality and psychological well-being among individuals who experienced bullying during their childhood. A purposive sample of 202 participants aged 19-40, who were bullied between the ages of 6-18, were recruited. The measurements used in the study included the Ryff Psychological Well-Being Scale (⍺ = .77) to measure psychological well-being; the Heartland Forgiveness Scale (⍺ = .82) to measure forgiveness; the Daily Spiritual Experiences Scale (⍺ = .94) to measure the spirituality of the participants; and the Olweus Bully/Victim Questionnaire (⍺ = .71) as a screening tool to confirm participants' experiences of bullying. Through mediation regression analysis with 5000 bootstrap samples using Macro PROCESS by Hayes, forgiveness emerged as a significant full mediator (β = .318, p .05, 95% CI: .212, .438). The study provides evidence that forgiveness enhances psychological well-being, suggesting that implementing a forgiveness program could reduce the long-term effect of childhood bullying.
An Updated Insight into Phytomolecules and Novel Approaches used in
the Management of Breast Cancer
Authors: Nooreen Zulfa , Tandon Sudeep , Wal Ankita , Rai Awani Kumar 
Published: January 2024

Abstract:
Breast cancer is a widespread condition that kills more women from cancer-related
causes than any other type of cancer globally. Women who have estrogen-dependent, initial metastatic
breast cancer frequently receive treatment with surgery, radiation therapy, and chemotherapy.
They may also get more specialized treatments like tamoxifen or aromatase inhibitors (anastrozole
or letrozole). The World Health Organisation reported in 2012 that by 2030, breast cancer
will be more common worldwide. There are several phytochemicals, such as isoflavones, coumestans,
lignans, and prenylflavonoides. Isoflavones have been shown in studies to prevent the spread
of breast cancer and to trigger apoptosis. Targeting BCs in metastatic breast cancer may be made
possible by combining well-formulated phytochemicals in nanoparticles or other novel drug delivery
agents with currently accepted endocrine and/or conventional chemotherapies. Cell signaling,
regulation of cell cycles, oxidative stress action, and inflammation could be positively impacted
by phytoconstituents. They have the ability to alter non-coding RNAs, to prevent the proliferation
and regeneration of cancer cells. The availability of novel approaches helps in disease targeting,
safety, effectiveness and efficacy. The current literature helps to know the available drugs i.e. phytoconstituents
or novel drug delivery like nanoparticle, microsphere, micelles, liposomes and neosomes.
The literature has been taken from PubMed, Google Scholar, SciFinder, or other internet
sites.
Novel Aspects and Directions in Pest Control and Management - Proteins
with Insecticidal Properties
Authors: Zhang Haiyan , Shahrajabian Mohamad Hesam , Cui Haoran , Kuang Yue , Sun Wenli 
Published: January 2024

Abstract:
In addition to the economic losses because of insect pests, a significant part of insect pests
can instantly lead to the deterioration and mildew of agricultural products, which all have great hidden
hazards to human health. In view of insect pests, the principle means of control and prevention
in China is spraying chemical agents. Nevertheless, spraying a large number of chemical factors to
control insect pests for a long time will not only have a consequential impact on the ecological environment,
but also make insect pests boost resistance, and because a large number of chemical residues
on the surface of crops will also have an unfavourable impact on the human body. The detection
and application of insecticidal proteins are of great significance for the progress of modern insecticidal
science. This article studies the research progress of insecticidal proteins and considering their
target pests, lists their common insecticidal utilization scenarios, and anticipates the development
direction of insecticidal proteins in the future.
Influence of SDS on the Growth of Natural Gas Hydrates in a
Sand Bed Depending on Saturation and Mineralization of Pore
Moisture
Authors: Reshetnikov Aleksey M. 
Published: January 2024

Introduction::
Evaluate the effect of SDS on induction time and conversion of water
to hydrate in a porous medium model depending on the saturation and salinity of pore moisture.

Methods::
The work presents data on the formation of natural gas hydrates in sand bed fraction
of 200-500 μm. The silica sand was saturated with water, solutions of SDS or NaCl, or a mixture
of these. The saturation was 50% or 100%. The experiments were carried out under isochoric
conditions at a temperature of 275 K and an initial pressure of 8 MPa.

Results::
It was shown that the main hydrate formation occurred in the first 60 minutes. The addition
of SDS 0.05-0.2 wt.% in the sand bed does not exhibit a promoting effect, as was previously
shown for pure water. The addition of NaCl 3 wt.% reduces the conversion of water to
hydrate by 1.6 and 2 times for 50% and 100% saturation of the sand bed.

Conclusion::
The optimal concentration of the SDS additive to the salt solution has been found
to reduce the inhibitory effect of the salt. The data obtained can be used to develop technologies
for storing and transporting natural gas using sand and seawater.
Kinetic Analysis of Solvent Effect in the Photocatalytic, Aerobic Oxidation
of Benzyl Alcohol over P25
Authors: Nosrati-Ghods Nosaibeh , Featherstone Nicholas Stuart , van Steen Eric 
Published: January 2024

Background::
Photocatalysis is of particular importance in the oxidation of alcohols to
aldehydes to increase the conversion of benzyl alcohol oxidation to benzaldehyde at high selectivity,
which could be useful for the pharmaceutical and perfumery industries.

Objective::
The oxidation of benzyl alcohol over P25 was investigated in various solvents (water,
benzotrifluoride, toluene and acetonitrile)

Methods::
The reaction was performed in an isothermal slurry batch reactor in the presence and absence
of UV-light. The products were analysed using GC-FID; the deposits formed on the catalyst
was analysed using TGA and FTIR.

Results::
In the presence of light, the reaction was very selective for the formation of benzaldehyde
(e.g., 99% selectivity at 53% conversion using acetonitrile as a solvent), whereas, in the absence of
light, the formation of higher molecular weight products was observed (e.g., 22% selectivity at
1.7% conversion using acetonitrile as a solvent). It was observed that the activity in the absence of
oxygen was initially high, but it dropped rapidly from initially 0.4 to 0 mmol g-1 h-1 after 2-4 h (using
acetonitrile as a solvent). This was attributed to the activity of the few oxidized sites present on
P25.

Conclusion::
Acetonitrile appears to be the most effective solvent, as it seems to interact least with
the catalytically active sites. The photocatalytic oxidation of benzyl alcohol over P25 does not only
yield products in the solution, but also deposits on the surface. The deposits can be removed in an
oxidative environment or an inert environment.