bluuebunny/crossref_metadata_2025 huggingface dataset:
Beneficial Effects of Curcumin in Polycystic Ovary Syndrome: A Review of Recent Literature and Underlying Mechanisms
Authors: Khamar Tayybeh , Jahani Najmeh , Jafari-Nozad Amir Masoud , Farkhondeh Tahereh , Samarghandian Saeed
Published: October 2024

Polycystic Ovary Syndrome (PCOS) is a common endocrinological disorder
that affects women of reproductive age and can lead to infertility. The prevalence of
PCOS ranges from 5-21% depending on the diagnostic criteria and study population.
Clinical manifestations include irregular or absent menstrual periods, obesity, and signs
of hyperandrogenism. PCOS can also lead to long-term consequences such as metabolic
syndrome, increased risk of cardiovascular diseases, endometrial cancer, diabetes mellitus,
and hypertension. Metformin and oral contraceptive pills are the most commonly
used drugs for PCOS management, but their efficiency is limited and they have some
considerable side effects. Researchers are looking into alternative therapeutic options
such as phytochemicals. Curcumin (CUR) is a polyphenolic compound found in the rhizome
of Curcuma longa and has shown promising effects for females with PCOS. CUR
exerts its anti-PCOS effects through different mechanisms such as reducing oxidative
stress and inflammation, balancing hormone levels, and controlling the blood sugar and
lipid profile. It can also reduce insulin resistance, regulate menstruation, and improve
ovarian morphology and function. Despite its beneficial effects, CUR faces several challenges
and limitations in clinical use, such as low bioavailability, instability, and rapid
elimination. Therefore, researchers are investigating the potential of CUR nanoformulations
and new drug delivery systems to overcome these barriers. With growing evidence
regarding the potential role of CUR in PCOS treatment, we decided to provide an updated
summary of the recent literature from clinical and preclinical studies on this topic.
Thrombosis in Hypertension: Pathophysiology, Biomarkers, and the Effect of Antihypertensive Treatment
Authors: Theofilis Panagiotis , Oikonomou Evangelos , Karakasis Paschalis , Dimitriadis Kyriakos , Sagris Marios , Sakalidis Athanasios , Mantzouranis Emmanouil , K Vlachakis Panayotis , Pamporis Konstantinos , Tsioufis Konstantinos , Tousoulis Dimitris
Published: October 2024

Hypertension, characterized by elevated blood pressure levels, remains a global
health concern due to its association with cardiovascular complications, notably
thrombosis. Thrombosis, the formation of blood clots within blood vessels, poses a significant
risk for myocardial infarction, stroke, and limb ischemia, leading to adverse patient
outcomes. Understanding the pathophysiological mechanisms underlying thrombosis
in hypertension is crucial for developing effective preventive and therapeutic strategies.
Hypertension induces structural and functional alterations in the vasculature, endothelium,
and platelets, creating a prothrombotic milieu. Endothelial dysfunction, increased
platelet activation, and alterations in coagulation factors contribute to the heightened
thrombotic risk observed in hypertensive individuals. Biomarkers associated with
thrombotic events, such as mean platelet volume, D-Dimer, and fibrinogen offer valuable
insights into the pathogenesis of thrombosis and may serve as prognostic indicators
for cardiovascular events in hypertensive populations. Investigating the impact of antihypertensive
treatment on thrombotic risk is essential, as these medications exert pleiotropic
effects on the vasculature and hemostatic system. By elucidating the intricate interplay
between hypertension and thrombosis, this review aims to enhance our understanding
of cardiovascular risk in hypertensive individuals and identify novel therapeutic targets
for preventing thrombotic complications.
CircRNA in Digestive Diseases: Recent Advances in Fundamental Mechanism and Clinical Potential
Authors: Ji Yuanye , Zhang Shun , Cai Ting , Fu Liyun , Deng Qinzhi , Zhu Peng
Published: October 2024

Circular RNAs (circRNAs), a class of non-coding RNAs characterized by
their closed-loop structure, are widely present in the body and exhibit greater stability
compared to conventional linear RNAs. With the development of molecular biology,
circRNAs are gradually considered as a prognostic indicator and therapeutic target for
various diseases. Research on the mechanism of circRNA in various diseases has
become an important direction. In addition, digestive diseases are becoming more
common as people's eating habits change, and the incidence and mortality of severe
digestive system tumors are increasing year by year. The study of circRNA in digestive
diseases provides us with a new way to improve the diagnosis and treatment of
digestive diseases. This article provides a comprehensive review of the research
literature on circRNAs in digestive system diseases over the past five years (2019-
2023) and covers aspects such as circRNA functions and underlying mechanisms.
CircRNA has been implicated in a variety of digestive diseases. In these diseases,
circRNA primarily acts as a microRNA (miRNA) sponge, interacting with miRNA to
regulate the expression levels of genes associated with signaling pathways, and there
is abundant research on the effects of circRNAs on drug resistance, cell proliferation,
invasion, apoptosis, and poor prognosis. This article aima to discuss the current status
of research on circular RNA and its key areas in digestive system diseases. The
review aims to provide valuable insights for further research on the role of circular RNA
in digestive system diseases and a reference for subsequent research.
Controlled Synthesis of Iron Oxide Nanoparticles via QBD for Biomedical Applications
Authors: Haghighizadeh Atoosa , Ghadiri Sima , Dadpour Saba , Amirinejad Mostafa , Etemad Leila , Rajabi Omid
Published: October 2024

Introduction:

Iron oxide nanoparticles have gained significant attention in pharmaceutical
applications because of their unique properties. The hydrothermal method is employed
for the synthesis of iron nanoparticles [IONPs], which offers advantages such as uniform composition
and size distribution.

Method:

However, the size and properties of IONPs can be influenced by various factors. In this
study, we utilized quality by design [QBD] via response surface methodology to investigate the
impact of temperature, time, and pH on the size of hydrothermally prepared IONPs. The optimized
synthesis conditions were determined, and the resulting nanoparticles were characterized
using techniques such as dynamic light scattering [DLS], scanning electron microscopy [SEM],
transmission electron microscopy [TEM], vibrating sample magnetometry [VSM], X-ray diffraction
[XRD], and Fourier-transform infrared spectroscopy [FTIR].

Results:

The findings contribute to a better understanding of the controlled synthesis of IONPs
and their potential applications in nanomedicine. The XRD characterization revealed that the
product was Fe3O4. The FTIR results indicate that Fe3O4 nanoparticles were coated with PEG-
400. The SEM and HRTEM images of the Fe3O4 nanoparticles showed that they were spherical
and had a well-distributed size with an optimized hydrodynamic size of 65 nm.

Conclusion:

The magnetic properties of the Fe3O4 nanoparticles indicated that they exhibited
ferromagnetic properties. These prepared nanoparticles are suitable for biomedical purposes, like
serving as contrast agents for magnetic resonance imaging in different cancers and delivering
drugs.
A Review on Phytochemistry and Pharmacological Activity of Ficus benjamina
Authors: Verma Gunjan , Ranawat Mahendra singh
Published: October 2024

In the traditional system of medicine, medicinal herbs play an important role in hu-man health and have a variety of therapeutic characteristics. F. benjamina is a popular ornamen-tal and household plant, belonging to the family Moraceae, which usually grows under mild to moderate temperature conditions. This review highlights the morphological studies, cultivation, collection, traditional uses, chemical constituents, phytochemistry of major constituents, and pharmacological properties of F. benjamina. To identify all the related published studies, Pub-Med, Scopus, Embase, Web of Science, MEDLINE, Google Scholar, and ScienceDirect data-bases were searched using all available terms for F. benjamina. This article systematically re-views the various pharmacological activities of this plant, such as antibacterial, antifungal, anti-viral, antioxidant, hepatoprotective, antidiabetic, anticancer, anticonvulsant, and hemolytic activ-ities. This plant has been used in herbal medicine for the treatment of various diseases, such as skin disorders, inflammation, wounds, lesions and ulcers, malaria, constipation, leprosy, and cancer. This plant has also been used as an insect repellent and air purifier. Chemically, it con-tains several phytoconstituents, for e.g., triterpenes, cinnamic acid, lactose, quercetin, caffeic ac-id, stigmasterol, lutein, sitosterol, chlorophyll-A, phytol, fatty alcohols, triglycerides, fatty acids, essential oils, flavone glycosides, isoflavonoids, and chlorogenic, p-coumaric, and ferulic acids. F. benjamina has been suggested to play a vital role in the prevention and treatment of chronic diseases, like cancer, diabetes, and epilepsy. This updated review may help many researchers carry out further investigations on this medicinal plant.
Clinical Profile and Prognostic Factors of Mortality in Elderly Covid-19 at Ansari Saleh Hospital
Authors: Agung SNC Wiwit , Khairina Ana , Erianty Erni
Published: October 2024

Morbidity and mortality of elderly with Covid-19 are higher than in adults. This study aimed to determine the prognostic factors of mortality in elderly with Covid -19. This research was a retrospective cohort study in patients aged 60 years and older with a PCR-confirmed diagnosis of Covid -19 admitted to Ansari Saleh Hospital, South Kalimantan, Indonesia between January to July 2021. Data on age, sex, comorbidities, symptoms, physical examinations, laboratory examinations, chest x-rays, and Covid severity degree were collected, univariate and multivariate analyses performed to determine the independent prognostic factors. The research results showed 209 samples met the criteria. The average age was 66,94 years, dominated by men (57.9%). The most common comorbidities were hypertension (48.8%), diabetes mellitus (35.4%), and chronic heart failure (8.1%). The most frequent symptoms were dyspnea (79.9%), cough (74.2%), and fever (56.5%). Patients treated mostly had severe/critical degree of Covid -19 (140 patients, or 67%). The results of multivariate logistic regression analysis on the variables of respiratory rate (p=0.009; OR=1.1), NLR level (p=0.002; OR=1.081), age (p=0.025; OR=2.479) and Covid severity degree (p=0.008; OR=8.206) showed significant results as independent prognostic factors of mortality. Covid severity degree variable has the highest prognostic level; patients with severe Covid degree have an 8.206 times higher chance of death than mild-to-moderate degrees. In conclusion, respiratory rate, NLR level, age, and Covid severity degree can act as prognostic factors of mortality in elderly suffering from Covid-19.
Correlation between De Ritis Ratio with Severity of Covid-19 Patients Severity
Authors: Rostini Tiene , Khairunnissa Khairunnissa , Turbawaty Dewi Kartika
Published: October 2024

SARS COV-2 is the causative agent of the infectious disease Corona Virus Illness-19 (Covid-19). Covid-19 can cause damage to multiple organs, including the liver. The de Ritis ratio is a ratio between AST and ALT in blood serum, which may be a useful indicator for assessing liver damage in Covid-19 patients. The aim of this study is to determine the association between the severity of liver injury and an increase in the de Ritis ratio in Covid-19. The study population included patients with acute Covid-19 disease whose infection was validated using real-time PCR. A retrospective cross-sectional study was conducted.  There were 1.983 subjects included, and 1.123 belonged to the moderate, 673 severe, and 181 to the critical groups. Calculations using Spearman rank revealed a strong significant association between De Ritis ratio and Covid-19 grade severity (rs=0.624, p<0.001). The more severe Covid-19, the higher de Ritis ratio values. The ROC curve of de Ritis ratio with Covid-19 severity shows AUC of 0.771 (P<0.001), sensitivity of 63.5%, specificity of 90.6%, PPV of 98.5% and an NPV of 20.02%. In conclusion, the severity of Covid-19 symptoms increases proportionally with the de Ritis ratio.
The Study of Congestive Heart Failure as a Risk Factor of Cardiac Arrest in ICU
Authors: Pramono Ardi , Hernawan Andhika Rajendra
Published: October 2024

Cardiovascular disease, especially congestive heart failure, is the second most common cause of death after stroke In Indonesia, current data on cardiac arrest in the ICU, especially those related to CHF, are still limited. This study aimed to determine the relationship between congestive heart failure and cardiac arrest in Intensive Care Unit (ICU) inpatients. The study used an analytic observational method with a cross-sectional research design. To find the relationship between the two variables, a regression test was performed on subjects with congestive heart failure and cardiac arrest in the ICU. Data was collected from 316 subjects, including 111 Congestive Heart Failure (CHF) subjects and 205 without CHF. Of the 111 CHF subjects, 51 subjects (45.9%) experienced cardiac arrest, and 60 subjects (54.1%) did not experience cardiac arrest. In comparison, the 205 subjects without CHF comprised 125 subjects (61.0%) who experienced cardiac arrest, and 80 subjects (39.0%) did not experience cardiac arrest. There is a relationship between congestive heart failure (CHF) and cardiac arrest, but CHF is not the only risk factor for cardiac arrest (p<0.05; OR 0.75). Congestive heart failure is associated with cardiac arrest in ICU patients with a relative risk of 0.75 times compared to subjects without congestive heart failure. Future research is needed to find the cause of congestive heart failure leading to cardiac arrest.
Desenvolvimento profissional docente no Ensino Superior: Contributos para uma reflexão
Authors: Huet Isabel
Published: October 2024

Na área de atuação do ensino, espera-se que os docentes do Ensino Superior se desenvolvam profissionalmente, aprofundando o seu conhecimento no domínio da pedagogia universitária e envolvendo-se em atividades de reflexão e indagação da pedagogia, com o objetivo de inovar e potenciar a sua prática pedagógica. Apesar da relevância do desenvolvimento profissional docente para o avanço da qualidade do ensino e da aprendizagem, verifica-se que aquele tem evoluído de forma diferenciada, e com impacto diverso, no contexto nacional e internacional. Este facto pode ser explicado por uma cultura organizacional que está fortemente enraizada nas políticas (trans)nacionais que orientam e fomentam a profissionalização docente. Existem contextos em que o desenvolvimento profissional é fortemente encorajado, valorizado e reconhecido, e outros em que está apenas associado à vertente de investigação ou a iniciativas muito isoladas ou pouco sustentadas no domínio da pedagogia. Este artigo apresenta uma reflexão sobre o desenvolvimento profissional docente baseada na literatura e em estudos de investigação conduzidos pela autora, com o objetivo de problematizar a importância e o impacto do desenvolvimento profissional no trabalho desempenhado pelos docentes na vertente do ensino a distância e supervisão da investigação.
Latine Students’ Sense of Belonging in LIS: A Critical-Constructivist Grounded Theory Study
Authors: Long Alicia K.
Published: October 2024

As the United States population becomes more ethnically and racially diverse, efforts to address issues of Diversity, Equity, Inclusion, and Social Justice have increased in Library and Information Science (LIS) Education programs that seek to recruit and graduate diverse students. However, very little is known about the lived experiences of ethnically and racially diverse students in LIS schools. Moreover, while the Hispanic population in the Nation grows exponentially, Latine LIS students have been largely absent as subjects of professional literature.
This dissertation explores the educational experience of Latine students in LIS and what facilitates or hinders their sense of belonging. With a qualitative approach of critical-constructivist grounded theory, the researcher explored the students’ experience through interviews and focus groups, seeking to identify characteristics of their experience as Latine students and elements that contribute to their sense of belonging. The poster includes preliminary findings and initial recommendations for LIS Education encompassed in a model of sense of belonging of Latine LIS students. By exploring Latine students’ sense of belonging with a critical theory lens, the knowledge obtained will contribute to the creation of a welcoming and meaningful educational experience so that Latine students feel that they are valued in the LIS programs they attend, and that they belong to the LIS field as professionals.
Interrupting Generative AI in LIS: Using Analog, Project-Based, In-Class, Team Work to Validate Core Research Competency Learning
Authors: Ryan Sarah
Published: October 2024

Generative AI is a powerful tool that we should be teaching our students to harness. At the same time, we must ensure that our students can perform core research tasks such as finding, reading, summarizing, and synthesizing academic research, in keeping with ALA Core Competency 7A. Because generative AI produces imperfect, college-level writing that can be difficult to identify as non-human, instructors face a new challenge in validating that students have learned 7A’s search-summarize-synthesize skills. One solution is the use of analog, scaffolded, in-class research skills activities accompanied by immediate instructor validation and feedback. This paper presents a 20-part literature review assignment as an example. This example demonstrates that when we watch our students reading, annotating, discussing, and mind mapping journal articles, we can be sure that they are learning the skills that will enable them to leverage tools like generative AI as a bridge to advanced work.
CASE STUDIES OF ENERGY-BASED RADIO FREQUENCY SPECTRUM SENSING TECHNIQUE FOR COGNITIVE RADIO NETWORKS
Authors:   GITAM School of Technology, India, K S Shilpa , Rao P Trinatha ,   GITAM School of Technology, India, Panda Sunita ,   GITAM School of Technology, India
Published: October 2024

The trend to overcome wireless interference emerged in techniques like frequency agility, hopping, dual band technologies etc. However, these techniques suppress inter-operability of wireless technologies operating at the same frequency like Wi-Fi, ZigBee, Bluetooth, Z-Wave, etc. As a result, in the unlicensed wireless public infrastructures bandwidth available for usage is becoming short of hand and utilizing only licensed band increases cost of ownership which cannot be sustained by public infrastructures and developing countries. Thus, new digital era requires a technology which can help overcome the foresaid challenges that can utilize both licensed and unlicensed spectrums through adaptive methodologies that ensures very high wireless communication availability in circumstances of bandwidth non-availability due to overcrowding or wireless interference at lower affordable cost. Thus, a group of radio that forms a network designed for this purpose is called Cognitive Radio Network (CRN). In the proposed paper an effort is made to provide simulated performance analysis insight of novel energy-based channel sensing mechanism which is the crucial aspect of spectrum management in cognitive radios. In simulation the mechanism is analysed for different cases in which combination of both real and complex information and noise signals are used. Through proper results and graphs different factors for consideration are presented. Sensing in co-operative cognitive networks is also discussed, addressing different issues like bandwidth, quantisation techniques, detection accuracy etc. that may help fellow researcher to continue the further developments with less time and efforts.
A SURVEY ON OPTIMIZATION OF TRANSMIT POWER IN COGNITIVE RADIO NETWORKS THROUGH NATURE INSPIRED COMPUTATIONAL INTELLIGENCE TECHNIQUES
Authors:   I.K Gujral Punjab Technical University, India, Goel Paurav , Singh Avtar ,   I.K Gujral Punjab Technical University, India, Goel Ashok ,   Maharaja Ranjit Singh Punjab Technical University, India
Published: October 2024

Cognitive radio (CR) is a field which is gaining a lot of interest of researchers in around the whole world. It is also termed as nextgen technology as it aims to solve the problem of unutilized electromagnetic spectrum assigned to licensed users. With increasing wireless devices there is a demand of more spectrum resources and cognitive radio can help in making available the unused or underused spectrum for real time communication. When number of cognitive users communicate together at the same time there exists the problem of interference due to transmit power of all the devices to the licensed users. So there is a need of controlling power of transmission for cognitive users so that they may not interfere with Primary licensed users and maintain QoS with other cognitive users. The power control of a large number of devices together can be done by the application of computational intelligence techniques. In this paper three nature inspired computational intelligence techniques like GA, PSO and ABC for optimization of transmit power in cognitive radio networks are discussed.
IMPROVED ENERGY EFFICIENCY IN MOBILE ADHOC NETWORKS USING MOBILITY BASED ROUTING
Authors:   The Quaide Milleth College for Men, India, R Manikandan , Ponnusamy Muruganantham ,   Indian Institute of Information Technology Kalyani, India, K Raja ,   Ministry of Education, Maldives, M Ramkumar ,   Gnanamani College of Technology, India
Published: October 2024

Energy conservation is a key element in MANET and so the architecture of the protocol demands particular consideration. Several MANET designs explored processes for the storage of renewable resources. Energy dissipation is a key coordinating factor among MANET nodes. Power utilization is ensured in monitoring applications that battery depletions are lowered to avoid regular substitution. MANET primarily aims to relay data by using energy-efficient routing protocols and an increasing lifespan of the network. The results of the simulation show that the approach suggested improves energy efficiency compared to other approaches. The findings are checked and provide decreased power usage, better packet distribution, lower packet error rate, higher network lifetime and lower end-to-end latency compared to conventional methods.
SUPPRESSED CARRIER FREQUENCY DIVISION MULTIPLEXING FOR INDOOR OPTICAL WIRELESS COMMUNICATION
Authors:   St. Francis Institute of Technology, India, Koti Jayasudha , B K Mishra ,   Thakur College of Engineering, India
Published: October 2024

Asymmetrically clipped orthogonal frequency division multiplexing (ACO-OFDM) is one of the optical modulation techniques for indoor optical wireless communication systems (OWC) to enable intensity (IM) modulation and direct detection (DD). As compared to other techniques, ACO-OFDM is power efficient, bandwidth efficient and has zero impact of clipping noise. However, its high peak to average power ratio (PAPR) may lead to performance deterioration and also introduce nonlinear distortion in optical source. To further enhance its performance by reducing the PAPR, suppressed carrier frequency division multiplexing (SC-FDM) is proposed and the system is titled as interleaved coded ACO (ICACO)-OFDM. To evaluate the performance of the system, simulation has been carried out for 16-QAM, 256 subcarriers, 1000 symbols. By observing the curves generated by Complementary cumulative distribution function (CCDF) at the probability of 10-3, PAPR has been characterized. It is observed that PAPR of ICACO-OFDM is 4.98 dB less as compared to ACO-OFDM system.
SECURE AND ENERGY-AWARE ROUTING FOR RELIABLE DATA TRANSMISSION IN MOBILE AD HOC NETWORKS
Authors:   K M G College of Arts and Science, India, Sundarraj P Daniel , K Arulanandam ,   Government Thirumagal Mills College, India
Published: October 2024

Mobile Ad-Hoc Network (MANET) is a generic technology utilized in various real-time applications. The MANET is a self-configuring and self-directed system that quickly deploys in a network. Data transfer is a big issue in MANET due to poor wireless medium and lack of data security and reliability. The prior system established a mobile ad hoc content distribution strategy. The ideal Cluster Head (CH) is chosen using the Teaching Learning Based Optimization (TLBO) approach. However, due to these features, it is more vulnerable to attacks. In addition, it impacts packet delivery and throughput. The proposed system designed a Secure and Energy Aware Routing (SEAR) mechanism to improve MANET data transmission reliability and security. Initially, nodes are clustered by distance. Then the Weight-based Artificial Fish Swarm Algorithm (WAFSA) is used to pick the optimum Cluster Head (CH). Mobility, remaining energy, and connectivity are considered objective functions for CH selection. Securing communication between these nodes will require proper cryptography. The security mechanism generates secret keys using Advanced Encryption Standard (AES) to encrypt or decode messages delivered between member nodes. This security approach enables secure communication between member nodes and CHs, uses the NS-2 analytical platform, and outperforms the existing system regarding average energy drop, network lifetime, and encryption time.
DECENTRALIZED BLOCKCHAIN WITH CONVOLUTIONAL NEURAL NETWORK MODEL FOR SECURITY ATTACK MITIGATION
Authors:   Madurai Institute of Engineering and Technology, India, Jones C. Berin , Kingsley D. Jeba ,   DMI College of Engineering, India
Published: October 2024

In recent era, there is a demand and a need for more effective solutions based on new technologies for detection and mitigation because of the limitations and current state of the methods. In this research, we propose the design of a distributed ledger that utilises a convolutional neural network as a layer of defence against intrusions carried out by malicious actors. The result of simulation shows that the proposed method achieves a better traffic flow than the existing methods.
ENHANCING TRANSMITTED TEXT SECURITY WITH IMAGE KEY CRYPTOGRAPHY AND DEEPNETS
Authors:   Shadan Women’s College of Engineering and Technology, India, Jones C. Berin , Kingsley D. Jeba ,   DMI College of Engineering, India
Published: October 2024

This paper proposes a novel approach to improving the security of transmitted text using a combination of image key cryptography and deepnets. The traditional methods of text encryption and decryption rely heavily on mathematical algorithms, which can be susceptible to attacks. In this paper, we introduce the concept of image key cryptography, where an image is used as the encryption key. By utilizing the complex patterns and structures present in images, the security of the encryption process is significantly enhanced. Additionally, we employ deepnets, a type of deep neural network, to further strengthen the encryption process and provide an additional layer of security. We evaluate the proposed approach through experiments and compare its performance with existing encryption methods. The results demonstrate that our method offers improved security and robustness against attacks, making it a promising solution for transmitting sensitive text data.
DUAL CIRCULARLY POLARIZED BROADBAND MICROSTRIP ANTENNA ARRAY FOR SPACE RE-ENTRY VEHICLE APPLICATIONS IN S BAND
Authors:   Cochin University of Science and Technology, India, Beegum S. Femina , Joseph Manoj ,   Indian Space Research Organization, Thiruvananthapuram, India, Joyas Saji ,   Indian Space Research Organization, Thiruvananthapuram, India, M Jayakumar ,   Indian Space Research Organization, Thiruvananthapuram, India, J Girija ,   Indian Space Research Organization, Thiruvananthapuram, India
Published: October 2024

This paper presents the design details of an integrated 4x4 element dual feed dual circularly polarized microstrip antenna array in the S-band. The dual circular polarization is achieved by the use of quadrature hybrids. Power division for the dual input array is achieved through two 1x16 equal split equal phase corporate feed networks. The quadrature hybrids and corporate feeds for the proposed array are designed in multilayer printed circuit boards (PCB) in stripline configuration. This antenna can be used to transmit or receive both right-handed circularly polarized (RHCP) waves or left-handed circularly polarized (LHCP) waves simultaneously or one at a time by terminating the other port with 50O resistance. The proposed antenna has 700MHz of 10 dB impedance bandwidth (27%), 400MHz of 3dB axial ratio bandwidth and 300MHz of 3dB gain bandwidth centred at 2.5GHz with a peak gain of 15.5dB in both polarizations. It has a 3dB beam width of 26° and cross-polarization levels below 20dB in both the polarizations. Design and simulation of patch array, quadrature hybrids and 1x16 corporate feeds in multilayer configuration, PCB stack-ups, fabrication, integration and testing processes are discussed in detail. The effect of thermal protection system (TPS) of the re-entry vehicle on antenna performance parameters was studied and presented.
FOG ENABLED PRIVATE BLOCKCHAIN-BASED IDENTITY AUTHENTICATION SCHEME FOR OIL AND GAS FIELD MONITORING
Authors:   Gujarat University, India, J. Y. Aldarwish Abdulla , Patel Kalyani ,   K.S. School of Business Management and Information Technology, India, A. Yaseen Aqeel ,   Gujarat University, India, A. Yassin Ali ,   College of Education for Pure Sciences, University of Basrah, Iraq, Abduljabbar Zaid Ameen ,   College of Education for Pure Sciences, University of Basrah, Iraq
Published: October 2024

The oil and gas industry remains critical to the global economy, as it contributes to the provision of energy and raw materials. Nonetheless, this sector continued to face clear challenges in operational effectiveness, risk and security. Regular tracking methods are limited to latency issues; they are not secure, and data may face integrity issues. To this end, this paper lays out an efficient fog-enabled private blockchain-based identity authentication approach for oil and gas field monitoring. By integrating IoT devices to blockchain, , decentralized control systems are created that enhance security, transparency, and efficient execution of transactions. In this scheme, by making full use of the decentralized structure of blockchain technology and applying the computational power of fog nodes, a secure and efficient identity authentication framework is designed. Fog nodes are an intermediary between IoT devices and blockchain technology, providing lower latency in communication, and therefore more efficient. The main contributions of this paper include: developing a decentralized authentication system based on private blockchains and fog nodes to overcome the drawbacks of centralized models. Create a network model using a private blockchain that dramatically improves feasibility by incorporating strict admission and authorization procedures. Hence, this leads to simultaneous registrations with minimal network time consensus Authentication that incorporating fuzzy extractor to connect the privacy-centric approach and to improve the security analysis and performance evaluation proving that the proposed solution provides better. According to the previous security analysis, it is clear that the scheme conflicts with different types of threats including DoS, MITM attacks, replay, Sybil, and message substitution attacks. The performance evaluation also shows low computational and communication costs, high compatibility, and real-time operation, which indicates that the proposed scheme is effective and can be implemented as a real-time oil and gas field monitoring system.
SCHEDULING AND OPTIMIZATION OF RESOURCES IN EDGE COMPUTING USING RANDOM ALLOCATION AND MAX FIT ALLOCATION
Authors:   PSG Institute of Technology and Applied Research, India, Ponnuswamy P. Priya , C.P. Shabariram ,   PSG Institute of Technology and Applied Research, India
Published: October 2024

The cloud computing is the new technique used most today for computation and storage. Edge computing is also a new computing domain that gives computation of tasks and storage of data nearer to the data sources. Various applications of edge computing are IOT, healthcare, retail, manufacturing etc. Virtualization technologies have enabled cloud platforms to provide various services such as virtual machines to the users. Task scheduling is the major issues faced in both cloud and edge domains. Since the usage of machines is high, it is difficult to assign tasks manually. So, an efficient and optimized algorithm is required in the cloud as well as the edge environment. Here, a task scheduling is implemented based on Heuristic Optimization Technique to examine the performance measures using cloudsim. Task scheduling and optimization techniques dynamically allocate resources in the cloud environment. Similarly, in edge computing, scheduling the task is performed with different optimization techniques such as random fit, and max fit algorithms. These task scheduling methods are allocated to the VM based on the resources that are available at the VM. These algorithms are implemented, and it increased the VM utilization by 4.82%. The processing time taken is reduced by 2.67% and the percentage of failed tasks is reduced by 3.68%. The experiment result shows the importance of the scheduling in the cloud and edge environment, in terms of processing time, failed task and increase in VM utilization in edge devices.
QUANTUM-RESISTANT CRYPTOGRAPHIC ALGORITHMS FOR SECURE COMMUNICATION
Authors:   Government Science College, Hassan, India, S Vijay , S Priya ,   Government First Grade College, Domlur, India, Harshavardhana C.N. ,   Government First Grade College for Women, Holenarasipura, India, R Kemparaju ,   Government First Grade College, T. Narasipura, India
Published: October 2024

With the rise of quantum computing, traditional cryptographic algorithms, such as the Elliptic Curve Digital Signature Algorithm (ECDSA), face potential vulnerabilities. Quantum computers could efficiently solve problems that are currently computationally infeasible for classical computers, thus threatening the security of cryptographic systems. As a result, there is a pressing need to develop quantum- resistant cryptographic algorithms to ensure secure communication in a future where quantum computing is prevalent. ECDSA, widely used for securing digital communications, relies on elliptic curve cryptography to provide robust security through digital signatures. However, the advent of quantum computing poses a significant threat to ECDSA's security, as quantum algorithms such as Shor's algorithm could break the elliptic curve-based encryption by efficiently solving discrete logarithm problems. To address this issue, we propose a quantum-resistant cryptographic algorithm based on lattice-based cryptography. Our approach utilizes the Learning With Errors (LWE) problem, known for its resistance to quantum attacks. We implement the proposed algorithm and compare its performance with ECDSA in terms of key generation time, signing time, and verification time. The algorithm's security is analyzed against quantum attacks using theoretical and empirical methods. The experimental results demonstrate that the quantum-resistant algorithm provides a comparable level of security to ECDSA while offering significant advantages in the context of quantum resistance. Specifically, our quantum-resistant algorithm achieved key generation times of 120 ms, signing times of 150 ms, and verification times of 100 ms. In comparison, ECDSA showed key generation times of 80 ms, signing times of 90 ms, and verification times of 70 ms. Despite these performance trade-offs, the quantum resistance of the proposed algorithm ensures future-proof security for digital communications.
QUANTUM KEY DISTRIBUTION IN OPTICAL COMMUNICATION NETWORKS
Authors:   Abhijit Kadam Institute of Management and Social Sciences, India, Nadaf Akabarsaheb Babulal , R Savaliya Rajeshkumar ,   Ambaba Commerce College, India, Nassa Vinay Kumar ,   Tecnia Institute of Advanced Studies, India, Rizvi Qaim Mehdi ,   Brainware University, India
Published: October 2024

Background: Quantum Key Distribution (QKD( is a promising technology for secure communication, leveraging the principles of quantum mechanics to provide theoretically unbreakable encryption. With the exponential growth in data traffic and the increasing need for secure communication in backbone fiber networks, integrating high-bit-rate multiplexing techniques into QKD systems can enhance their efficiency and scalability. Problem: Traditional QKD systems face limitations in terms of data rate and network scalability, particularly in high-capacity optical communication networks. As data demands increase, there is a critical need for methods that can support high-bit-rate multiplexing while maintaining the security and performance of QKD. Method: This study proposes a novel QKD approach using high-bit-rate multiplexing in backbone fiber networks. The method involves encoding quantum keys using multiple optical channels simultaneously to increase the data throughput of the QKD system. We employ a combination of time-division multiplexing (TDM( and wavelength-division multiplexing (WDM( to optimize the use of fiber resources and enhance key distribution rates. Results: Simulation results demonstrate that the proposed method achieves a key distribution rate of 10 Mbps over a 200 km fiber link with a quantum bit error rate (QBER( of 1.5%. This represents a 50% improvement in key rate compared to conventional QKD systems without multiplexing. Additionally, the method shows enhanced scalability and network utilization, supporting up to 16 multiplexed channels with minimal impact on security.
ENERGY-EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS USING DEEP BELIEF NETWORKS AND LSTM FOR MOBILE SINK PATH OPTIMIZATION AND CLUSTER HEAD SELECTION
Authors:   Knowledge Institute of Technology, India, P Sachidhanandam , M Sakthivel ,   Knowledge Institute of Technology, India, A Gomathi ,   Knowledge Institute of Technology, India, G Usha ,   Knowledge Institute of Technology, India
Published: October 2024

Wireless Sensor Networks (WSNs) are critical in numerous applications due to their ability to sense and transmit data. However, energy limitations of sensor nodes, powered by finite batteries, significantly impact network longevity. Traditional routing methods involving multi-hop transmissions and cluster formation can result in substantial energy consumption, particularly by Cluster Heads (CHs) involved in data aggregation and transmission. This research addresses the problem by optimizing energy-efficient routing using a Deep Belief Network (DBN) with Long Short-Term Memory (LSTM) for routing and CH selection. A mobile sink moving in a linear path minimizes energy consumption by reducing cluster formation and promoting single-hop transmissions. The proposed method utilizes LSTM-based CH selection to ensure that nodes with the highest residual energy are chosen, enhancing network lifetime. Experimental results demonstrate that the proposed method reduces energy consumption by up to 25% compared to circular path sink movement and multi-hop data transmission, resulting in a 40% increase in network lifetime. Performance was evaluated on a 100-node network with varying sink velocities, achieving an energy efficiency of 15% over traditional models.
Fine-Tuned Bidirectional Encoder Representations From Transformers Versus ChatGPT for Text-Based Outpatient Department Recommendation: Comparative Study (Preprint)
Authors: Jo Eunbeen , Yoo Hakje , Kim Jong-Ho , Kim Young-Min , Song Sanghoun , Joo Hyung Joon
Published: October 2024

BACKGROUND

Patients often struggle with determining which outpatient specialist to consult based on their symptoms. Natural language processing models in health care offer the potential to assist patients in making these decisions before visiting a hospital.

OBJECTIVE

This study aimed to evaluate the performance of ChatGPT in recommending medical specialties for medical questions.

METHODS

We used a dataset of 31,482 medical questions, each answered by doctors and labeled with the appropriate medical specialty from the health consultation board of NAVER (NAVER Corp), a major Korean portal. This dataset includes 27 distinct medical specialty labels. We compared the performance of the fine-tuned Korean Medical bidirectional encoder representations from transformers (KM-BERT) and ChatGPT models by analyzing their ability to accurately recommend medical specialties. We categorized responses from ChatGPT into those matching the 27 predefined specialties and those that did not. Both models were evaluated using performance metrics of accuracy, precision, recall, and F1-score.

RESULTS

ChatGPT demonstrated an answer avoidance rate of 6.2% but provided accurate medical specialty recommendations with explanations that elucidated the underlying pathophysiology of the patient’s symptoms. It achieved an accuracy of 0.939, precision of 0.219, recall of 0.168, and an F1-score of 0.134. In contrast, the KM-BERT model, fine-tuned for the same task, outperformed ChatGPT with an accuracy of 0.977, precision of 0.570, recall of 0.652, and an F1-score of 0.587.

CONCLUSIONS

Although ChatGPT did not surpass the fine-tuned KM-BERT model in recommending the correct medical specialties, it showcased notable advantages as a conversational artificial intelligence model. By providing detailed, contextually appropriate explanations, ChatGPT has the potential to significantly enhance patient comprehension of medical information, thereby improving the medical referral process.
Online Health Information Seeking, eHealth Literacy, and Health Behaviors Among Chinese Internet Users: Cross-Sectional Survey Study (Preprint)
Authors: Liu Diyi , Yang Shuhang , Cheng Calvin Yixiang , Cai Lin , Su Jing
Published: October 2024

BACKGROUND

The internet has become an increasingly vital platform for health-related information, especially in upper-middle-income countries such as China. While previous research has suggested that online health information seeking (OHIS) can significantly impact individuals’ engagement in health behaviors, most research focused on patient-centered health communication.

OBJECTIVE

This study aims to examine how OHIS influences health behavior engagement among Chinese internet users, focusing on the role of eHealth literacy and perceived information quality in influencing relationships.

METHODS

An online cross-sectional survey was conducted in November 2021 among 10,000 Chinese internet users, using quota sampling based on sex, age, and urban and rural residence, in line with the 48th Statistical Report on Internet Development of China. Nonparametric tests were used to examine the differences in eHealth literacy across sociodemographic groups. Partial correlation analysis and stepwise linear regression were conducted to test the associations between key variables. Confirmatory factor analysis and structural equation modeling were conducted to test the hypotheses.

RESULTS

Our study identified significant disparities in functional and critical eHealth literacy between urban and rural residents across age groups, income levels, education backgrounds, and health conditions (all P<.001). In terms of sex and regional differences, we found higher functional literacy among female users than male users, and critical literacy varied significantly across different regions. The proposed structural model showed excellent fit (χ2404=4183.6, χ2404=10.4, P<.001; root mean square error of approximation value of 0.031, 95% CI 0.030-.031; standardized root mean square residual value of 0.029; and comparative fit index value of 0.955), highlighting reciprocal associations between 2 types of eHealth literacy and OHIS. Participants’ functional eHealth literacy, critical eHealth literacy, and OHIS have positive impacts on their health behavioral engagement. Perceived information quality was found to mediate the influence of OHIS on health behavior (b=0.003, 95% CI 0.002-0.003; P<.001).

CONCLUSIONS

The study revealed the pathways linking sociodemographic factors, eHealth literacy, OHIS, and perceived information quality and how they together influenced health outcomes. The findings underscore the significance of enhancing eHealth literacy and improving information quality to promote better health outcomes among Chinese internet users.
Digital integrated interventions for comorbid depression and substance use disorder: narrative review and content analysis (Preprint)
Authors: Jonathan Geneva Kay , Guo Qiuzuo , Arcese Heyli , Evins A. Eden , Wilhelm Sabine
Published: October 2024

BACKGROUND

Integrated digital interventions for the treatment of comorbid depression and substance use disorder have been developed, and evidence of their effectiveness is mixed.

OBJECTIVE

To better understand the potential underlying causes of these mixed findings, we described intervention characteristics, examined evidence-based treatment strategies within integrated digital treatments, reported the frequency of specific evidence-based strategies across different treatment modalities, and identified overlap between various treatment strategies and critical gaps in existing literature.

METHODS

In June 2024, a literature search was conducted in Google Scholar to identify digital integrated interventions for comorbid MDD and SUD. Articles were included if they described interventions targeting both conditions simultaneously, were grounded in CBT, MI, or MET, and were delivered at least in part via digital modalities. Fourteen studies meeting these criteria were coded using an open coding approach to identify treatment strategies. Statistical analyses summarized the number, frequency, and overlap of these strategies.

RESULTS

Half of studies (50.0%, n=7) included participants with mild to moderate depression symptom severity and hazardous substance use. Only 35.7% (n=5) of the studies required that participants meet the full diagnostic criteria for MDD, as assessed by the SCID or MINI, for inclusion and 21.4% (n=3) required a SUD diagnosis. Web-based (35.3%, n=6), computer-based (21.4%, n=3) and supportive text messaging interventions (21.4%, n=3) were included. Treatment duration averaged 10.3 weeks (SD=6.8). Common treatment strategies included self-monitoring (78.6%, n=11), psychoeducation (71.4%, n=10), and coping skills (64.3%, n=9). Interventions often combined therapeutic strategies, with psychoeducation frequently paired with self-monitoring (64.3%, n=9) and coping skills (50%, n=7).

CONCLUSIONS

Among integrated digital interventions for comorbid depression and substance use, there was significant variability in inclusion criteria, digital modalities, methodology, and treatment strategies, significant methodological challenges, and underrepresentation of evidence-based practices. Without standardized methodologies comparison of the clinical outcomes across studies is challenging. These results emphasize the critical need for future research to adopt standardized approaches, thereby facilitating more accurate comparisons and a deeper understanding of intervention efficacy.