bluuebunny/crossref_metadata_2025 huggingface dataset:
GeneXpert MTB/RIF Ultra in Pediatric Tuberculosis: How Disease Characteristics Modify Test Performances
Authors: Pace Domenico , Pellegrino Roberta , Dalpiaz Irene , Renni Marco , Galli Luisa , Chiappini Elena
Published: January 2025

Introduction:

The diagnosis of pediatric tuberculosis (TB) is challenging, due to the
lower sensitivity of microbiological tests, such as culture and microscopy, compared to their performance
in adult cases. Guidelines have introduced molecular tests, including GeneXpert MTB/
RIF and GeneXpert MTB/RIF Ultra. These tests use a real-time polymerase chain reaction
method and provide information on M. tuberculosis detection and drug-resistance-associated mutations
in less than 2 hours. This retrospective single-center study aimed to evaluate the accuracy of
GeneXpert and GeneXpert Ultra for the diagnosis of pediatric TB.

Methods:

This retrospective study was conducted on a total of 95 children diagnosed with probable
or confirmed TB disease (74 diagnosed with pulmonary TB, 21 with extrapulmonary TB),
who referred to the infectious disease unit at Meyer Children’s Hospital in Florence, Italy, and tested
with GeneXpert MTB/RIF or GeneXpert Ultra, from 2013 to 2023.

Results:

GeneXpert and GeneXpert Ultra demonstrated a detection rate of 0.357 (95% CI 0.180 to
0.535) and 0.537 (95% CI 0.417-0.657), respectively. No child was tested with both tests. Patients’
characteristics, including age and sex, did not significantly influence the test's performances.
Notably, GeneXpert Ultra had a significantly higher detection rate in children with extrapulmonary
TB (0.813, 95% CI 0.621 to 1.004) compared to that in children with pulmonary TB (p
= 0.020). Gastric aspirate was the most tested specimen. Specimens that did not require invasive
procedures for collection (including stool) yielded poor results. GeneXpert and GeneXpert Ultra
permitted rapid evaluation of genotypic drug-sensitivity testing (DST), even though limited to rifampicin
resistance, making necessary confirmation through phenotypic DST (performed on culture).

Conclusion:

The introduction of GeneXpert and GeneXpert Ultra improved TB diagnosis in children,
by providing microbiological information in a short time, complementing results from culture,
which remains the reference test in pediatric TB diagnosis.
The Intersection of Heart Failure and Iron Deficiency Anemia: Diagnostic and Therapeutic Approaches
Authors: Thammitage Maleesha BW , Moussa Naji , Rezvani Ali , Dhillon Damandeep Kaur , Gamarra Miryam Lisseth Obando , Singh Kanwaraj , Hawwa Abdul , Vincente Alejandra , Kaur Sehajpreet , Nemalapuri Kiranmayee Seshasai , Poonwassie Devika , Rai Manju
Published: January 2025

Iron deficiency anemia (IDA) is highly prevalent among individuals with heart failure
(HF), impacting 40-70% of patients and serving as a significant prognostic indicator. Linked
with oxidative metabolism and myocardial cell damage, IDA exacerbates HF symptoms, including
reduced exercise capacity, diminished quality of life, and heightened cardiovascular morbidity.
This review explores the diagnosis, treatment, clinical outcomes, prognostic indicators,
and forthcoming challenges associated with IDA in HF patients. Crucially, addressing IDA in
HF is critical for enhancing prognosis, including clinical outcomes, quality of life, hospitalizations,
and survival rates. While oral iron therapy shows efficacy in reducing mortality and hospitalizations,
it falls short in improving exercise capacity and quality of life, often deterring patients
due to side effects. In contrast, intravenous (IV) iron therapy is highly effective in enhancing
hematological parameters, functional capacity, and reducing HF hospitalizations. Optimizing
IV iron dosing based on individual patient characteristics is essential for balancing treatment efficacy
and adverse effects. Emphasizing individualized approaches, with IV iron emerging as a
superior option, underscores the necessity for ongoing research to refine dosing strategies and
explore novel therapies. Compliance remains paramount for positive outcomes with IDA treatment,
with oral supplementation being cost-effective and easily accessible. However, parenteral
supplementation proves beneficial for patients intolerant to oral therapy. Addressing IDA
through tailored interventions, including oral or parenteral supplementation, is pivotal in averting
complications and improving outcomes in HF patients. This paper consolidates insights into
the diagnosis, treatment, impact, pathophysiology, clinical outcomes, research gaps, and future
directions concerning IDA in HF patients, drawing on extensive literature to offer a comprehensive
understanding of this critical issue.
Successful Use of Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitors in Hypertriglyceridemia-induced Acute Pancreatitis: A Case Report
Authors: qi Rundi , Liu Hailei , Li Xin , Chen Minglong
Published: January 2025

Background:

Managing hypertriglyceridemia-induced acute pancreatitis (HTG-AP)
can be challenging, particularly due to the need for rapid triglyceride reduction to below
500mg/dL (5.645mmol/L).

Case Report:

This is a case describing a 39-year-old female patient who presented to the Emergency
Department with acute abdominal pain resulting from severe HTG-AP. However, under
conventional therapy with oral lipid-lowering drugs, the triglyceride levels remained uncontrolled.
Oral moderate-intensity statins could not only reduce low-density lipoprotein cholesterol
(LDLc) by 25%-50%. However, increasing the dose could not further reduce blood lipids while
increasing the risk of liver damage. After the administration of proprotein convertase subtilisin/
kexin type 9 inhibitor (PCSK9i), the triglyceride levels were well controlled with no additional
side effects, and the symptoms of the patients were completely relieved.

Conclusions:

In cases of unsatisfactory lipid control under conventional therapy, PCSK9i may
offer a viable option for managing HTG-AP.
Identification of a ceRNA Network Regulating Malignant Transformation of Isocitrate Dehydrogenase Mutant Astrocytoma: An Integrated Bioinformatics Study
Authors: Cui Yaqian , Zheng Hongquan , Zhou Zhengwei , Liu Suo , Shen Mingxue , Qiu Runze , Zhang Xiong , Li Yingbin , Fan Hongwei
Published: January 2025

Introduction:

Astrocytoma is the most common glioma, accounting for about 65% of
glioblastoma. Its malignant transformation is also one of the important causes of patient mortality,
making it the most prevalent and difficult to treat in primary brain tumours. However, little is
known about the underlying mechanisms of this transformation.

Methods:

In this study, we established a ceRNA network to screen out the potential regulatory
pathways involved in the malignant transformation of IDH-mutant astrocytomas. Firstly, the Chinese
Glioma Genome Atlas (CGGA) was employed to compare the expression levels of the differential
expressed genes (DEGs) in astrocytomas. Then, the ceRNA-regulated network was constructed
based on the interaction of lncRNA-miRNA-mRNA. The Gene Ontology (GO) and the
Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore the main functions of
the differentially expressed genes. COX regression analysis and log-rank test were combined to
screen the ceRNA network further. In addition, quantitative real-time PCR (qRT-PCR) was conducted
to identify the potential regulatory mechanisms of malignant transformation in IDH-mutant
astrocytoma. We constructed a ceRNA network with 34 lncRNAs, 29 miRNAs, and 71 mRNAs.

Results:

GO and KEGG analyses results suggested that DEGs were associated with tumor-associated
molecular functions and pathways. In addition, we screened two ceRNA regulatory networks
using Cox regression analysis and log-rank test. QRT-PCR assay identified the NAA11/hsa-
miR-142-3p/GS1-39E22.2 regulatory axis of the ceRNA network to be associated with the malignant
transformation of IDH-mutant astrocytoma.

Conclusion:

The discovery of this mechanism deepens our understanding of the molecular mechanisms
of malignant transformation in astrocytomas and provides new perspectives for exploring
glioma progression and targeted therapies.
Next Generation Diagnostics: Exploring the Potential of Microfluidic Devices
Authors: Dhiman Komal , Dhiman Tanuja , Som Shalini , Sharma Achla , Sharma Ankit , Kaundal Amit Kumar , Ankalgi Amardeep , Ashawat Mahendra Singh
Published: January 2025

In recent years, microfluidics systems have emerged as powerful tools for biological analysis,
integrating entire analytics protocols into a single chip platform. This article aims to review
recent developments in microfluidics systems for diagnostics applications, focusing on genes, proteins,
and cells. By categorizing fluids- manipulating mechanisms and biological detection approaches,
the articles provide an in-depth discussion of microfluidics-based diagnostics systems, including
materials and manufacturing techniques. The integration of microfluidics systems with diagnostics
shows promise for the development of practical point- of-care devices. The identification and monitoring
of Variants of Concern (VOCs) and Variants of Interest (VOIs) by WHO have significant
implications for diagnostics, public health measures, and vaccine development. Continuous, sequencing
and adaptation of diagnostic tests are essential for managing the impact of variants on diagnostics
and public health measures while advancing vaccine research and development.
Adverse Events Associated with Antivirals for COVID-19: An Analysis
Based on FDA Adverse Event Reporting System (FAERS)
Authors: Mohamad Radzuan Muhammad Ikhwan Syahmi , Karuppannan Mahmathi
Published: January 2025

Background:

The COVID-19 pandemic has called for the rapid development and use
of antiviral drugs to effectively control the disease. Nirmatrelvir/Ritonavir (Paxlovid), Molnupiravir, and Remdesivir have been pivotal in therapeutic approaches, although they raise concerns regarding adverse drug reactions (ADRs).

Objective:

This study aimed to thoroughly assess the ADRs associated with these drugs by utilizing the Adverse Event Reporting System (FAERS) database of the Food and Drug Administration
(FDA)

Methods:

ADR reports for Paxlovid, Molnupiravir, and Remdesivir throughout the period of January 2022 to May 2023 were extracted and classified according to the severity, type of reaction,
and demographic variables. Reporting Odds Ratios (RORs) with 95% confidence intervals were
calculated to evaluate the relationship between antiviral medications and various ADRs.

Results:

The study established notable correlations between Paxlovid and the recurrence of the disease (40.08%) and dysgeusia (16.29%). Molnupiravir was linked to gastrointestinal (16.73%) and
skin reactions (9.47%), while Remdesivir had impairments in the liver (25.21%) and kidneys
(13.34%). ADRs were more commonly observed in female patients treated with Paxlovid
(57.95%) and Molnupiravir (49.40%), whereas Remdesivir ADRs were mostly reported in males
(58.56%). Paxlovid and Remdesivir ADRs were frequently reported in adults between the ages of
18 and 64 (46.01% and 45.01%), while Molnupiravir ADRs were more common in older individuals aged 65 to 85 (40.38%).

Conclusion:

This thorough assessment emphasizes the importance of careful surveillance and control of ADRs linked to COVID-19 antiviral therapies. It is essential to customize treatments by
considering specific patient histories, particularly for pre-existing diseases.
The Role of Glial Cells in Autism Spectrum Disorder: Molecular Mechanisms and Therapeutic Approaches
Authors: Inamdar Aparna , Gurupadayya Bannimath , Sharma Himanshu
Published: January 2025

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by
social communication deficits and repetitive behaviors. Emerging evidence highlights the significant
role of glial cells, particularly astrocytes and microglia, in the pathophysiology of ASD. Glial cells
are crucial for maintaining homeostasis, modulating synaptic function, and responding to neural injury.
Dysregulation of glial cell functions, including altered cytokine production, impaired synaptic
pruning, and disrupted neuroinflammatory responses, has been implicated in ASD. Molecular
mechanisms underlying these disruptions involve aberrant signaling pathways, such as the mTOR
pathway, and epigenetic modifications, leading to altered gene expression profiles in glial cells.
Moreover, microglial activation and reactive astrocytosis contribute to an inflammatory environment
that exacerbates neural circuit abnormalities. Understanding these molecular mechanisms
opens avenues for therapeutic interventions. Current therapeutic approaches targeting glial cell dysfunction
include anti-inflammatory agents, modulators of synaptic function, and cell-based therapies.
Minocycline and ibudilast have shown potential for modulating microglial activity and reducing
neuroinflammation. Additionally, advancements in gene editing and stem cell therapy hold
promise for restoring normal glial function. This abstract underscores the importance of glial cells in
ASD. It highlights the need for further research to elucidate the complex interactions between glial
dysfunction and ASD pathogenesis, aiming to develop targeted therapies that can ameliorate the
clinical manifestations of ASD.
Association of Toll-like Receptor 4 Gene Polymorphisms with Diabetes Type 2 Patients in the Palestinian Population
Authors: Al-Razem Fawzi , B. Iqnaibi Enas , A. Abu Rmeileh Razan , I Ideis Lara
Published: January 2025

Background:

Toll-like Receptor 4 (TLR4) plays critical roles in innate immunity and
several other pathological responses, including a possible role in the susceptibility to Type 2
Diabetes Mellitus (T2DM). Understanding the relationship between TLR4 polymorphism and
T2DM is necessary to evaluate the role of innate immunity in diabetes.

Aim:

This study was conducted to evaluate the potential association between three TLR4 SNPs
(SNP ID rs11536858, rs4986790, and rs1927914) and risk susceptibility to T2DM in a crosssection
of the Palestinian population.

Methods:

A total of 96 individuals including 50 T2DM patients participated in this study. The
data were analyzed according to the TLR4 allelic variation results. DNAs were extracted from
blood samples collected from the T2DM patients and their matched healthy controls and used to
evaluate possible associations between the TLR4 SNP variations and T2DM. The genotypes of
TLR4 polymorphisms were analyzed by the Polymerase Chain Reaction-Restriction Fragment
Length Polymorphism (PCR-RFLP).

Results:

Three allelic variations were detected in the participating individuals. The distribution
of alleles between T2DM and healthy controls in the three SNPs did not show significant differences,
even though some variations tended to favor certain alleles. To look at potential associations
of TLR4 gene polymorphisms with the risk of T2DM development, we analyzed the allelic
variation in both T2DM patients and health controls. The rs4986790 TLR4 SNPs showed a significant
association with T2DM. There were 20% heterozygous alleles in T2DM patients compared
to 4.35% in healthy controls with Odds Ratio (OR) = 5.26 and 95% CI = 1.08, 25.6 (P =
0.0252), indicating the AG allele to be a risk factor. Both rs11536858 and rs1927914 alleles
demonstrated a potential association of their allelic variations as either a protective or a highrisk
factor.

Conclusion:

Our data have indicated that TLR4 rs4986790, rs1927914, and rs11536858 may
play a potential role in innate immunity and susceptibility risk to diabetes and can be potential
targets for therapeutic drugs.
Pathway Targeting and Mechanistic Elucidation of Phyto-compounds Relevant in Triple-negative Breast Cancer (TNBC)
Authors: Mir Wajahat Rashid , Bhat Basharat Ahmad , Sofi Shazia Shafi , Jan Nusrat , Jan Asma , Mir Manzoor Ahmad
Published: January 2025

Of the several forms of breast cancer, triple-negative breast cancer (TNBC) is the most
aggressive, is not responsive to traditional human/hormonal epithelial growth factor receptor 2
(HER2)-targeted therapies because the corresponding receptor targets are absent, TNBC tends to be
more invasive in form, metastasis, have an early recurrence rate and develop medication resistance.
For TNBC, some of the most popular types of treatments are resection, chemotherapy, and radiation
therapy. Several studies are being carried out for the development of novel treatment approaches for
improved TNBC diagnosis. As our knowledge of the molecular mechanisms behind the development
of cancer has grown, a vast array of anticancer drugs has been developed. The use of chemically
produced pharmaceuticals has not significantly raised the overall survival rate over the previous few
decades. As such, novel approaches and cutting-edge chemopreventive medications are needed to
improve the efficacy of existing TNBC therapies. Naturally occurring compounds derived from
plants called phytochemicals are valuable resources for the development of novel medications for
TNBC treatment. These phytochemicals often function by modulating molecular pathways associated
with the onset and propagation of TNBC. Some of the specific methods include boosting antioxidant
status, deactivating carcinogens, stopping proliferation, inducing cell cycle arrest, promoting
apoptosis, and immune system modulation. This review's main goal is to give a summary of the active
components of natural products, together with details on their molecular targets, pharmacologic
action, and current level of understanding. Several natural compounds that particularly target the
pathways linked to TNBC in our study have been thoroughly described by us. We have done extensive
research on many natural substances that could lead to the discovery of new targets for TNBC
detection.
A Study on the Regulation of TRPM8 Signaling Pathway by Interior-warming Medicines in Traditional Chinese Medicine
Authors: Wei Yuanjun , Xiong Chengcheng , Zhan Yanran , Fu Jiangbo , Yang Chaoyan , Chen Yanfen
Published: January 2025

Background:

Interior-warming medicines (Wēnlǐ herbs) have the effect of warming the
interior of the body and dispelling cold, and they are traditionally used for interior cold syndrome.
Currently, they are used for treating gastrointestinal disorders, rheumatoid arthritis, tumors, etc.
Transient receptor potential channel M8 (TRPM8) is a non-selective cation channel that can be activated
by low temperature and menthol. However, the mechanism of temperature regulation of interior-
warming medicines is not clear. This study designed an in vitro experiment on the TRPM8
signaling pathway using interior-warming medicines, aiming to investigate the relationship between
the hot property of interior-warming medicines and the regulatory effect of TRPM8.

Methods:

The breast cancer cell line 7 was cultured at different temperatures as a research model,
six kinds of interior-warming medicines were used, and medicated serums from rats were prepared
as test drugs. PCR and western blotting were carried out to investigate their effects on TRPM8
mRNA and protein expression. ELISA and flow cytometry were conducted to detect intracellular
cAMP and Ca2+ concentration.

Results:

Compared with the blank-containing serum group, interior-warming medicines had no
significant effect on the expression of TRPM8 at 37°C, while they could inhibit the expression of
TRPM8 at low temperatures (30°C). Moreover, the six herbs could increase intracellular cAMP
content and reduce Ca2+ concentration at different temperatures.

Conclusion:

The natural hot property of interior-warming medicines may be associated with the
regulation of the TRPM8 signaling pathway, causing Ca2+ influx blocking, which provides a deeper
experimental basis for their clinical application and new drug development.
Vehicle Detection through Self-supervised Learning: An In-depth Review and Critical Analysis
Authors: Tuteja Shikha , Tonk Ravinder , Kaur Taranjeet , Sharma Preeti , Sadana Priya , Kumar Rajeev , Kumar Sunil
Published: January 2025

The application of computer vision such as monitoring traffic, surveillance, autonomous
driving, and vehicle detection, is a crucial task. Traditionally, vehicle detection has been
addressed using methods based on supervised learning that involve a huge quantity of labelled
data. However, collecting and annotating huge amounts of data is expensive and time-consuming,
leading researchers to explore methods based on supervised learning that learn from unlabelled
data. The advanced techniques for vehicle identification utilizing self-supervised learning are
thoroughly reviewed and critically analysed in this paper. We start by defining self-supervised
learning and outlining its benefits and drawbacks in comparison to supervised learning. Then, we
go through the variety of techniques based on a self-supervised learning approach for vehicle
identification, including various pretext tasks, network structures, and training approaches that
have been put out in the literature. In this article, we review recent developments in selfsupervised
learning for vehicle identification, covering well-liked pretext problems, network designs,
and training methods. Furthermore, we critically analyse the strengths and limitations of
these methods, highlighting their practical implications and potential research directions. Researchers
and practitioners interested in creating reliable and effective vehicle detection systems
utilizing self-supervised learning might use the information presented in this study as a reference.
This review paper examines self-supervised learning techniques for vehicle detection, addressing
the limitations of traditional supervised methods that require extensive labeled data. It covers various
self-supervised approaches, including pretext tasks, network architectures, and training strategies.
The paper critically analyzes these methods, discussing their strengths, limitations, and
practical applications in traffic monitoring, surveillance, and autonomous driving. By evaluating
current techniques and identifying future research directions, this review provides a comprehensive
resource for researchers and practitioners developing efficient vehicle detection systems using
self-supervised learning.
A Comprehensive Survey of Skin Cancer Identification using Deep Learning
Authors: Ranjan Vibhav , Chaurasia Kuldeep , Singh Jagendra
Published: January 2025

In USA, out of all the carcinomas, one of the most rampant variety of carcinomas is
skin cancer, with an estimated one in five Americans developing it by the age of 70. As per the
Skin Cancer Foundation, in the USA alone, every hour more than 2 people succumb to skin cancer.
For melanoma skin cancer, the survival rate could be 99% considering a 5-year time frame if
it is detected early. Deep learning, a subdomain of AI, empowers computers to learn complex
patterns from massive amounts of data. Convolutional neural networks (CNNs), an eminent deep
learning architecture, along with its variations like VGG19, MobileNet, ResNet, ResNext, and
the latest Vision transformers excel at image recognition tasks, making them ideally suited for
analyzing medical images like skin lesions. This review explores the burgeoning utilization of
deep learning in skin cancer detection. The analysis of the constraints of conventional methods
and highlights of the potential of deep learning in achieving superior accuracy and objectivity
have been discussed in this study. The review methodology involves a comprehensive search of
relevant research papers and publications from Google Scholar. The review focuses on the studies
involving deep learning for classification or segmentation of skin cancer, enabling more efficient
and trustworthy AI systems. The findings reveal CNNs as the mainstay, with both traditional
training and transfer learning approaches proving effective. However, recent advancements
showcase the promise of vision transformers, ensemble methods, and hybrid models, alongside
innovative augmentation and optimization techniques, combining attention layers with state-ofthe-
art architectures, making clinically trustworthy systems using XAI techniques like GRADCAM,
leading to significantly improved efficiency. In conclusion, this review emphasizes the
transformative power of deep learning algorithms for the diagnosis of skin cancer, paving the
way for highly accurate, trustworthy, and accessible diagnostic tools and presents an analysis of
the latest developments related to AI and deep learning architectures and frameworks being applied
for diagnosis of skin cancer.
Arc Detection Method for Single-Phase AC Series Fault Based on Current Convolution
Authors: Ji Changan , Wang Kang , Wang Qunjing , Chen Quan , Fan Minghao , Xu Bin , Wang Xiaoming , Zhao Wenguang , Xiong Lei
Published: January 2025

Introduction:

Arc fault has become an increasingly prominent problem affecting the
safe operation of power distribution networks. Research on arc fault detection can effectively reduce
electrical fire accidents caused by arc faults, which is of great significance for ensuring the
safe and reliable operation of power distribution networks.

Methods:

In this paper, an arc fault detection method based on current convolution is proposed for
single-phase AC series arc faults. Firstly, the phase of the measured phase current is acquired
through the phase-locked loop. Then, the measured phase current is convoluted with the standard
sinusoidal signal whose phase is the same as the measured phase current, and the DC component
is obtained by low-pass filtering.

Results:

The occurrence of an arc fault is recognized by detecting the change in the DC component.

Conclusion:

Finally, the simulation results verify that the proposed method can detect the arc
fault quickly and accurately.
Development Status and Future Prospects of Strapdown Inertial Navigation Technology
Authors: Liu Hongbo , Wu Juncheng , Lin Yuze , Yang Xiaodong
Published: January 2025

Background:

Inertial navigation is a comprehensive technology involving precision
machinery, computer technology, microelectronics, optics, automatic control, materials, and other
disciplines and fields. Strapdown inertial navigation systems have gradually developed into the
mainstream and direction of inertial navigation systems because of their small size, low cost, simple
structure, and high reliability. The angular rate and acceleration information of the carrier relative
to the inertial space are measured by the inertial measurement unit (IMU), and the instantaneous
velocity and position information of the carrier are automatically calculated by Newton's law
of motion. It has the characteristics of not relying on external information, not radiating energy to
the outside world, not being disturbed, and good concealment. Therefore, it is widely used in aerospace,
aviation, and navigation, especially in the military field.

Objective:

This paper describes the development history of the Strapdown Inertia Navigation System
summarizes the research status of the Strapdown Inertia Navigation System, and looks forward
to its future development direction.

Method:

The key technologies of strapdown inertial navigation systems are investigated, and the
related research on strapdown inertial navigation technology is understood in detail. The hardware
composition and related algorithms of the strapdown inertial navigation system are analyzed in
detail.

Results:

Nowadays, strapdown inertial navigation technology is the mainstream of inertial navigation
technology. Compared with the gimbaled inertial navigation system technology, the
strapdown inertial navigation system has higher precision, smaller volume, and lower cost. At present,
the initial alignment technology, error compensation technology, navigation algorithm technology,
and inertial device technology of strapdown inertial navigation technology have made full
development.

Conclusion:

With the development of initial alignment technology, error compensation technology,
navigation algorithm technology, and inertial device technology, the accuracy, response speed
and anti-interference ability of strapdown inertial navigation technology have been significantly
improved. The development of strapdown inertial navigation is closely related to the gyroscope
technology which belongs to inertial device technology. The strapdown inertial navigation system
based on optical gyroscopes such as laser gyroscopes and fibre optic gyroscopes is mature, and the
MEMS strapdown inertial navigation system has a wide application prospect compared with the
optical gyroscope strapdown inertial navigation system.
Research Progress in Pre-Stage Deflection Jet Tube Type Electro-Hydraulic Servo Valve
Authors: LI Jianying , Chen Wanting , Guo Qi
Published: January 2025

Background:

The pre-stage deflection is a key aspect of the deflector jet tube electrohydraulic
servo valve, and its performance not only affects the pressure gain, flow gain, and other
important parameters of the servo valve, but also affects the dynamic and static characteristics of
the servo valve and electro-hydraulic servo system.

Objective:

This paper aimed to outline the working principle of the pre-stage deflector jet tube
type electro-hydraulic servo valve, and review and analyze its research performance development
in five aspects.

Method:

The research progress in the key indexes of servo valve performance at different stages,
the mechanism and phenomenon of the erosion and wear of the pre-stage, the mechanism and
characteristics of the pre-stage cavitation, the structural improvement and parameter optimization
of the pre-stage, as well as the pre-stage drive mode, has been summarized.

Results:

It has been found that although a large number of scholars at home and abroad have improved
the structure and driving mode of the front stage of the deflecting jet tubular electrohydraulic
servo valve and optimized the parameters to improve the performance of the deflecting
jet tubular electro-hydraulic servo valve, the internal flow field of the front stage is complex,
prone to erosion and cavitation and many complex phenomena, and there are still many aspects to
be improved and innovated.

Conclusion:

This paper has thus summarized the defects of the front-end stage, and put forward
three future innovations of miniaturization, intelligence, and multifunction, to contribute innovative
ideas to the design of the front-end stage of the deflection jet pipe electro-hydraulic servo
valve in the future.
Psychological Interventions for the Management of Irritable Bowel Syndrome: Understanding the Mind-Gut Connection
Authors: Verma Neha , Arora Anchal , Wal Ankita , Singh Charan , Rajesh KS , Singh Bhupendra , Sharma Mukesh Chandra
Published: January 2025

Objective:

This review examines the efficacy of psychological interventions
in the management of Irritable Bowel Syndrome (IBS).

Methods:

In the current study, a comprehensive analysis of the existing literature,
covering case studies and clinical trials, compiled from Google Scholar,
Sci-Hub, and PubMed, was performed. The research focused on the complex interplay
between psychological factors and irritable bowel syndrome (IBS), particularly
the ways in which mental and emotional states can impact IBS symptoms
and the effects of behavioral therapy on IBS management.

Results:

The efficacy of psychological therapies in addressing irritable bowel
syndrome (IBS) has proven effective. Cognitive Behavioral Therapy (CBT)
treats pain perception and gastrointestinal symptoms, whereas gut-directed hypnotherapy
is known for lowering symptoms and enhancing quality of life. Mindfulness-
based stress reduction and relaxation practices are effective for stress management,
but their availability is restricted. Personalized treatment strategies
tailored to individual requirements are vital for enhancing the advantages of these
therapies in IBS management.

Conclusion:

Psychological interventions provide a valuable and effective approach
to managing IBS. CBT, gut-directed hypnotherapy, and MBSR have
been shown to significantly improve symptoms and quality of life. Future research
should focus on improving these therapies to better address individual
symptoms and brain-gut connections. Incorporating neurological and neurophysiological
approaches may improve understanding and lead to more tailored
treatments. Expanding accessibility and encouraging collaboration between
healthcare providers and mental health specialists will be vital for optimizing
IBS management and improving patient outcomes.
Emerging Threat: A Review on Mucormycosis as a Serious Health
Challenge during the Pandemic
Authors: Bhoyar Mohanish , Khobragade Deepak , Daff Gauri , Gujarkar Praful , Kadiri Sunil Kumar , Tiwari Prashant
Published: January 2025

During the COVID-19 pandemic, many critically ill patients undergoing intensive care or
ventilation developed a fungal infection known as Mucormycosis. This infection is primarily caused
by ubiquitous fungi in the environment, such as species like Rhizopus arrhizus, Lichtheimia, Mucor,
and Rhizomucor, among others. Symptoms range from mild, such as fever and nasal congestion, to
more severe manifestations, like gastrointestinal bleeding and dark lesions in moist body areas such
as the nose and eyes. Mucormycosis can be fatal if not promptly treated with appropriate combination
therapy, and in severe cases, surgical removal of infected tissue may be necessary. This review
explores the historical background, epidemiology, and treatment strategies for Mucormycosis. It also
discusses its prevalence among COVID-19 patients, underlying causes, and management protocols.
Impact of Blockchain-Enabled IoT Applications for Smart Agriculture and Healthcare to Promote Sustainable Economic Growth and Smart Health Management Ecosystem in Industry 5.0
Authors: Bhavneet Kaur Sachdev  , Sumanta Bhattacharya
Published: January 2025

Within the framework of Industry 5.0, the incorporation of blockchainenabled IoT applications into smart agriculture and healthcare has significant
consequences for long-term economic growth and the creation of ecosystems for smart
health management. The environmental, economic, industrial, and stakeholder
implications of smart agriculture's transparent supply chains, which are made possible
by blockchain technology and precision farming techniques, lessen the environmental
impact of conventional farming by cutting down on resource use. Blockchain
technology and Internet of Things (IoT) devices safeguard patient records, allowing for
more eco-friendly procedures with less paper waste. These innovations maximize the
use of agricultural resources, which boosts output while decreasing expenditures from
an economic perspective. Better patient outcomes and lower healthcare costs are
possible because of blockchain technology's assurance of data integrity and
interoperability. This promotes a fairer and more inclusive economic climate, giving
smaller players a voice. Innovation and integration are propelled by the industrial
sector. By fostering an environment of open communication and cooperation, the tenets
of Industry 5.0 aim to bring together many sectors of the economy to improve
technological standards, strengthen cybersecurity, and standardize procedures.
Awareness, training, and community participation are all made easier by stakeholders,
which include NGOs. For these technologies to be adopted in an ethical and
responsible manner, their advocacy for legislation that supports them and the protection
of data ownership rights are vital. In the future, there will be more international
cooperation, new technological solutions to problems with energy efficiency, and the
creation of universal benchmarks.
Revolutionizing Hen Care in Smart Poultry Farming: The Impact of AI-Driven Sensors on Optimizing Avian Health
Authors: P. Deepan  , R. Vidya  , N. Arul  , S. Dhiravidaselvi  , Shashi Kant Gupta
Published: January 2025

Automation is taking over the entire globe. To boost efficiency, businesses,
governments, and nonprofits are all using automation in their own fields. The demand
for and necessity of automation is high in the agricultural industry. The majority of
nations have begun to supply and use smart farming solutions. This proposed study
focuses on smart poultry farming, an essential aspect of farming, and designs a new
prototype. A number of Indian farmers keep chickens as pets, yet their farms' output,
longevity, efficiency, and treatment of animals are all lacking.

Therefore, sustainable and lucrative farming is the outcome of integrating cutting-edge
technology such as robotics, Internet of Things (IoT) sensors, and artificial intelligence
(AI). This prototype incorporates a number of Internet of Things (IoT) sensors for
several features, such as lighting (LDR), air quality (MG135), water quality (pH),
temperature (DTH11), and lighting (LDR). Minimizing human intervention, keeping
tabs on the bird's well-being, making the most of available resources, and increasing
output are all outcomes of the automated system's development. With the help of an
AI-IoT smart system, poultry producers will be able to manage their farms more
efficiently and triumph over a number of obstacles.
Falsas dicotomías de la guerra durante el estallido social chileno
Authors: Hodge-Dupré Eduardo Andrés
Published: January 2025

El 18 de octubre de 2019, Chile experimentó uno de los eventos más significativos de su historia reciente, uno que marcó un punto de inflexión en su estabilidad social y política: una revuelta popular violenta que sacudió a Santiago y se extendió rápidamente por todo el país. Este artículo analiza los eventos de violencia ocurridos durante y desde entonces a fin de establecer si el país estuvo o no en guerra, como lo afirmó el expresidente Sebastián Piñera, o no lo estuvo, como lo sostuvo el General Javier Iturriaga. Así, plantea la hipótesis de que, por sus características, dicha violencia y desestabilización constituyen un conflicto o guerra de tipo híbrido, evalúa la plausibilidad de dicha hipótesis y examina sus implicaciones para la seguridad nacional.
Santiago: la Corte del Reino de Chile en el siglo XVII
Authors: Gloël Matthias
Published: January 2025

El trabajo postula la necesidad de investigar a la ciudad de Santiago de Chile del siglo XVII como Corte. Esta percepción de la ciudad como Corte se generaría fundamentalmente a través de la presencia de la Real Audiencia y del sello real, símbolo de la majestad monárquica. Para ello, se muestra la existencia de una literatura contemporánea que elogia la calidad de Corte de algunas ciudades de la monarquía. A continuación, se evidencia, también, la relación entre sello real y presencia simbólica del rey para, finalmente, mostrar que estas mismas condiciones se cumplen para el caso de Santiago de Chile del siglo XVII. Se concluye que la ciudad debe ser considerada como otra Corte real más en esta monarquía de Cortes.
La militarización de las emergencias civiles en Guatemala
Authors: Bueno Alberto , Martínez Rafael
Published: January 2025

Las Fuerzas Armadas de Guatemala son profusamente empleadas en emergencias civiles, para lo cual cuentan con capacidades específicas y desempeñan un rol central en los planes de protección civil. Esta participación se suma a una extensa lista de misiones impropias, donde el ejército se ha convertido en una administración comodín en el sistema político guatemalteco. En un país con grave riesgo de desastres naturales, con una administración débil y un pasado pretoriano, la militarización de estas políticas es un rasgo notorio del Estado. Este artículo analiza el marco político-institucional en el que se desarrollan estas misiones, explica dichas capacidades militares y plantea, en último término, cómo la debilidad democrática guatemalteca, junto con la militarización de amplios servicios públicos, corre un considerable riesgo de abrirle paso al militarismo en este país.
Older Adults’ Experiences With an Online Survey
Authors: Weir Kristie Rebecca , Maitah Yehya , Vordenberg Sarah E
Published: January 2025

The study explored older adults' perceptions after participating in an online survey about medication decisions, finding that approximately 80% of participants provided positive feedback about the research methodology and their experience.
Older Adults’ Experiences With an Online Survey (Preprint)
Authors: Weir Kristie Rebecca , Maitah Yehya , Vordenberg Sarah E
Published: January 2025

UNSTRUCTURED

The study explored older adults' perceptions after participating in an online survey about medication decisions, finding that approximately 80% of participants provided positive feedback about the research methodology and their experience.
Deep Learning for Dietary Assessment: A Study on YOLO Models and the Swedish Plate Model (Preprint)
Authors: Chrintz-Gath Gustav , Daivadanam Meena , Matta Laran , McKeever Steve
Published: January 2025

BACKGROUND

In recent years, the field of computer vision has seen remarkable advancements, particularly with the rise of deep learning techniques, in identifying objects in images. We investigate the application of object detection models, specifically You Only Look Once (YOLO), in the context of food and portion recognition.

OBJECTIVE

The objective of the study is to assess the performance of three YOLO models in accurately identifying food components within images and their proportions in terms of the Swedish plate model as per the guidelines of the National Food Agency.

METHODS

The research utilizes a custom dataset comprising 3707 images with 42 different food classes. Various preprocessing and augmentation techniques were applied to enhance dataset quality and model robustness. The performance of the three YOLO models (YOLOv7, YOLOv8, and YOLOv9) are evaluated using precision, recall, mean Average Precision (mAP), and F1 score metrics.

RESULTS

Our analysis demonstrates that YOLOv8 showed higher performance. While the metrics were satisfactory, the models still had difficulty distinguishing between different food items.

CONCLUSIONS

We determine that further enhancements to both the technology and the training are required for such tools to be included in health monitoring applications.
Application of Artificial Intelligence Communication Training Tools in Medical Undergraduate Education: mixed methods feasibility study within a Primary Care Context (Preprint)
Authors: Jacobs Chris , Johnson Hans , Tan Nina , Brownlie Kirsty , Joiner Richard , Thompson Trevor
Published: January 2025

BACKGROUND

Effective communication is fundamental to high-quality healthcare delivery, influencing patient satisfaction, adherence to treatment plans, and clinical outcomes. However, communication skills training for medical undergraduates often faces challenges in scalability, resource allocation, and personalization. Traditional methods, such as role-playing with standardized patients, are resource-intensive and may not provide consistent feedback tailored to individual learners' needs. Artificial Intelligence (AI) offers realistic patient interactions for education.

OBJECTIVE

This study aims to investigate the application of Artificial Intelligence (AI) -powered communication training tools in medical undergraduate education within a primary care context. The study evaluates the effectiveness, usability, and impact of AI virtual patients (VPs) on medical students' experience in communication skills practice

METHODS

A mixed methods sequential explanatory design was employed, comprising a quantitative survey followed by qualitative focus group discussions. Eighteen participants, including 15 medical students and 3 practicing doctors, engaged with an AI VP simulating a primary care consultation for prostate cancer risk assessment. The AI VP was designed using a large language model (LLM) and natural voice synthesis to create realistic patient interactions. The survey assessed five domains: fidelity, immersion, intrinsic motivation, debrief, and system usability. Focus groups explored participants' experiences, challenges, and perceived educational value of the AI tool.

RESULTS

A mixed methods sequential explanatory design was employed, comprising a quantitative survey followed by qualitative focus group discussions. Eighteen participants, including 15 medical students and 3 practicing doctors, engaged with an AI VP simulating a primary care consultation for prostate cancer risk assessment. The AI VP was designed using a large language model (LLM) and natural voice synthesis to create realistic patient interactions. The survey assessed five domains: fidelity, immersion, intrinsic motivation, debrief, and system usability. Focus groups explored participants' experiences, challenges, and perceived educational value of the AI tool.

CONCLUSIONS

AI can significantly enhance communication skills training for medical undergraduates by providing a scalable, accessible, and realistic simulation environment. Despite some technical challenges, the AI tool was well-received, indicating its potential for broader adoption in medical education. Continued development and refinement of AI technologies will be essential to prepare future healthcare professionals for real-world patient interactions.
Applications of Algebra in Topological Data Analysis: Bridging Algebra and Data Science
Authors: Kushlaf Asmaa Mohammed Ashour
Published: January 2025

Topological Data Analysis (TDA) has emerged as a powerful framework for understanding the shape and structure of
data. Algebra, particularly concepts from homological and computational algebra, plays a pivotal role in TDA by enabling the
extraction of robust topological features from complex datasets. This review explores the applications of algebra in TDA,
highlighting its contributions to data science. We discuss foundational concepts, methodologies, computational tools, and
practical applications, providing insights into the intersection of algebra and data-driven insights. We delve into the theoretical
foundations of TDA, highlighting the construction of simplicial complexes, the computation of homology and persistent
homology, and the development of efficient algorithms for large-scale data analysis. Furthermore, we examine the integration of
TDA with machine learning, its applications across various domains including image and signal processing, natural language
processing, and biosciences and discuss current challenges and future directions in the field. By bridging the gap between
abstract algebraic theories and real-world data analysis, this paper underscores the transformative potential of TDA in
advancing data science methodologies
Exploring the Benefits and Challenges of Additive Manufacturing in Small-Scale Production
Authors: Barka Osamah Ibrahim A.
Published: January 2025

Additive manufacturing in construction is beginning to move from an architect‟s modelling tool to delivering full-scale
architectural components and elements of buildings such as walls and facades. Building on the advances in AM in these
industries, there are several experimental applications of AM in the construction sector. This paper discusses large-scale additive
manufacturing processes that have been applied in the construction and architecture arena and focuses on „Concrete Printing‟,
an automated extrusion based process. The wet properties of the material are critical to the success of manufacture and a
number of new criteria have been developed to classify these process specific parameters. These criteria are introduced and key
challenges that face construction scale additive manufacturing are presented.