bluuebunny/crossref_metadata_2025 huggingface dataset:
БАЛТИЯ В ЭПОХУ ВЕЛИКОГО ПЕРЕСЕЛЕНИЯ НАРОДОВ
Authors: В.И. КУЛАКОВ
Published: October 2024

В предлагаемой главе при помощи археологических источников выявлен процесс перемещений воинских формирований в части Балтии к северу от р. Немана. Кроме того, показаны истоки этого процесса, включавшие, кроме всего прочего, формирование в исторической Пруссии первой в Балтии дружины. Показаны этапы развития торгового пути Самбия-Эйямыги/Вирумаа. Важно отметить, что не последнюю роль в упомянутых этнических перемещениях в Балтии сыграли серьёзные изменения климата, произошедшие на берегах Балтийского и Северного морей в середине I тыс. н.э., а также трансгрессия уровня вод Балтики.

In this chapter, with the help of archaeological sources, the process of movements of military formations in the part of the Baltic north of the river is revealed. Neman. In addition, the origins of this process are shown, which included, among other things, the formation in historical Prussia of the first squad in the Baltics. The stages of development of the Sambia-Eyjamıgi/Viru County trade route are shown. It is important to note that serious climate changes that occurred on the shores of the Baltic and North Seas in the middle played an important role in the mentioned ethnic movements in the Baltics. I thousand years. AD, as well as transgression of the Baltic water level.
«ПРОТИВОЯДИЕ НЕГОДНИКАМ, УНИЖАЮЩИМ РОССИЙСКУЮ ИСТОРИЮ»: К ДИСКУССИИ БОЛТИНА И ЛЕКЛЕРКА
Authors: М.С. БОБКОВА
Published: October 2024

Глава посвящена отражению представлений о народах России в разгоревшейся в XVIIIвеке дискуссии между французскими авторами П.-Ш. Левеком, Н.Г. Леклерком и русским историком И.Н. Болтиным о природе русского характера, экономике России, принципах ее внешней политики. Дискуссия была инициирована российской императрицей Екатериной II и ее книгой по истории России, которую она адресовала своему внуку Александру. Французские врачи, пробыв в России довольно много времени, достигли значительных чинов и составили большие состояния. Вернувшись во Францию, они издали книги, где порочили историю и настоящее варварской России. Уделено внимание теоретической основе критики И.Н. Болтина — климатической теории Ж. Бодена.

The chapter is about the reflection of ideas about Russian folks in the discussion that flared up in the 18th century between the French authors P.-Ch. Levek, N.G. Leclerc and the Russian historian I.N. Boltin about the nature of the Russian character, the Russian economy, the principles of its foreign policy. The discussion was initiated by the Russian Empress Catherine II and her book on the history of Russia, which she addressed to her grandson Alexander. The French doctors, having spent quite a long time in Russia, achieved significant ranks and made large fortunes. Returning to France, they published books in which they discredited the history and present of barbaric Russia. Attention is paid to the theoretical basis of I.N. Boltin's criticism — the climatic theory of J. Bodin.
ЛАНДШАФТНОЕ ВАРВАРСТВО: ВЗАИМОДОПОЛНЯЮЩИЙ КОМПОНЕНТ ИСТОРИИ ВАРВАРОВ
Authors: В.П. БУДАНОВА
Published: October 2024

В исследовании рассматривается проблема взаимосвязи человека с природно-географической средой обитания, с климатическими условиями его выживания и жизнедеятельности в процессе исторической эволюции. Актуальность и целесообразность изучения роли природного фактора обусловлена потребностью системного анализа деструктивного действия географического детерминизма в процессе исторического становления и преодоления варварства. В качестве концептуальной основы впервые предложена модель ландшафтного варварства. Концепт «ландшафтное варварство» — это оценочная характеристика бесчеловечного, дикого поведения, враждебного, злонамеренного действия, жестокого, злобного поступка, побуждаемого взаимосвязью природы и человека, человека и природы в условиях и состоянии природно-географической среды обитания. На этой основе через эволюцию человека антропогенного периода определяются и раскрываются истоки насильственного поведения сапиенса.

The study examines the problem of human interaction with the naturaland geographical environment, with the climatic conditions of his survival and vitalactivity in the process of historical evolution. The relevance and expediency of studying the role of the natural factor is due to the needfor a systematic analysis of the destructive effectof geographical determinism inthe process of historical formation and overcoming barbarism. For the firsttime, a model of landscape barbarismwas proposed as a conceptual basis. The concept of «landscape barbarism» is an evaluative characteristic of inhuman, savage behavior, hostile, malicious action, cruel, malicious act, promptedby the interconnection of nature and man, man and nature in the conditions and condition of the natural and geographical habitat. On this basis, through the human evolution of the anthropogenic period, the originsof the violent behavior of sapiensare determined and revealed.
PULMONARY EMBOLISM MIMICKING ASTHMA EXACERBATION
Authors:   Resident Doctor, Department of Emergency Medicine, Sterling Hospitals, Ahmdeabad., Kapadia A. , Singh K. ,   Resident Doctor, Department of Emergency Medicine, Sterling Hospitals, Ahmdeabad., Panchal S.N ,   Emergency Registrar, Department of Emergency Medicine, Sterling Hospitals, Ahmedabad., Patel J. ,   Emergency Registrar, Department of Emergency Medicine, Sterling Hospitals, Ahmedabad.
Published: October 2024

Pulmonary Embolism poses a significant health threat. Pulmonary Embolism arises from the obstruction of pulmonary arteries, typically by blood clots originating from deep veins. Risk factors mirror those of deep vein thrombosis, encompassing genetic and acquired factors. Timely diagnosis is imperative due to substantial mortality and morbidity rates, with various diagnostic modalities employed. Treatment options include anticoagulants, thrombolytic, surgical embolectomy, and inferior vena cava filters. We present a case from our Emergency department, underscoring the importance of prompt diagnosis and intervention in managing PE. The case involved a 46-year-old male admitted who is known case of Asthma (on inhaled corticosteroids), who presented with dyspnoea, leading to the diagnosis of high-risk PE. Thrombolysis with Reteplase was initiated, highlighting the critical role of identifying the pulmonary embolism.
Formation of national varietal resources: status and prospects
Authors: Tkachyk S. O. , Zakharchuk O. V. , Kotsiubynska L. M. , Khomenko T. M. , Skubii O. A. , Zaval­niuk O. I. , Dubova I. Yu. , Stefkivska Yu. L. , Lynchak N. B.
Published: October 2024

Purpose. To study the current state and structure of national plant variety resources, analyse the dynamics of their formation, identify new challenges and threats to national interests and food security of the state. Methods. The research used general scientific methods including hypothesis, observation, search with elements of extrapolation from the source database, analysis, comparative evaluation and synthesis to draw conclusions. Results. The physical and geographical location of Ukraine in the centre of Europe determines the export­import segment of resources of varieties and hybrids, which depends on international trends and trends in the food market. In recent years, our country has lost its leading position in the market of varietal plant resources. At the beginning of the third quarter of 2024, the share of varieties of Ukrainian applicants in the State Re­gister of Plant Varieties Suitable for Distribution in Ukraine was lower than that of foreign varieties, slightly exceeding 44% (corn – 45.3%, sunflower – 32.9%, vegetables – 23.3%, rapeseed – 19.1%, beetroot – 19.2%). Currently, the priority of domestic breeding is maintained for the following groups: cereals – 52.3%, fodder – 64.2%, medicinal – 88.7%. According to experts, in the coming years three quarters of the varieties of plants grown in our country will be of foreign origin.  This situation is of great concern not only because of the increased dependence on imports, but also because of the real prospect of the decline of domestic breeding and the emergence of risks in the field of plant variety rights protection. The reasons for this state of national varietal resources and trends in the development of the seed industry of the main strategic varieties were analysed, taking into account the production of seeds of both foreign and domestic breeding, the market share of which was determined during the research. The volumes and the main producers of conditioned seeds in Ukraine were determined. Conclusions. The state of plant variety resources was analysed, trends and main problems arising in the process of their formation were identified. The main directions of development and implementation of the norms of the European national legislation in the field of protection of rights to plant varieties and seed production were determined.
Trihalomethanes (THMs) formation in chlorine-treated and -untreated wastewater and its horizontal and vertical distribution through the irrigation of agricultural fields
Authors: Aguilar-Santos Alma L. , Siebe Christina , Fuentes-García Ruth , Prado-Pano Blanca , Meza-González Jorge , Hernández-Quiroz Manuel , de Leon Claudia Ponce
Published: October 2024

This study examines the formation of trihalomethanes (THMs) in wastewater intended for crop irrigation and its relationship with dissolved organic carbon (DOC), aromaticity, and residual chlorine. The research takes a dual approach: assessing spatial distribution through field samples from canals now distributing treated, chlorinated wastewater and analysing vertical percolation of wastewater through soil previously irrigated with untreated, non-chlorinated wastewater for over 100 years. Spatial analysis reveals that THMs are present in wastewater before treatment, with concentrations increasing post-treatment. Although DOC levels decrease after treatment, their aromaticity remains unchanged, suggesting the persistence of labile DOC. The presence of THMs in treated wastewater from irrigation canals may result from shorter travel distances or increased chlorine use during the COVID-19 pandemic. Vertical soil column experiments indicate a correlation between THM generation, water source, and soil type. Results show that THMs are retained in the soil, where labile DOC is trapped, reducing its concentration while potentially releasing DOC from humic substances. Despite this, THM concentrations do not pose a risk to aquifers, though ongoing monitoring is important should soil and/or treatment methods be altered.
Investigating inland waterway transport through a sustainable development perspective: a case study of Magdalena River (Colombia)
Authors:   , Calderón-Rivera Natalia
Published: October 2024

The development of transport systems significantly influences economies, growth, and welfare of populations. However, these systems can have negative consequences, such as water and air pollution, traffic congestion, noise, and biodiversity loss. To address these challenges, it is essential to implement strategies that mitigate negative effects while improving the environmental, social, and economic conditions of the population. In this regard, inland water transport (IWT) is globally recognized as a more sustainable transport alternative due to its high cargo load capacities and comparatively lower environmental and social impacts. In Colombia, the Magdalena River – the country’s most important river basin – traverses approximately 1,600 km from the south (Paramo de las Papas) to the Caribbean Sea, where two important seaports, Cartagena and Barranquilla, are located. It primarily contributes to the transportation of bulk cargo, including hydrocarbons, using barge convoys pushed by pusher boats. Additionally, smaller vessels provide passenger and cargo services, which are vital for accessing health- care, education, and mobility services in remote regions. This research is intended to comprehensively investigate IWT using a sustainable development perspective, both globally and locally, with a focus on the Magdalena River in Colombia. The study employs a mixed-methods approach, incorporating a systematic literature review, interviews, and survey. The study identifies the three key elements of the IWT system – inland river ports, waterways, and inland fleets – and examines their characteristics. Additionally, it determines global barriers to and potential solutions for sustainable IWT development, with a particular focus on evaluating those relevant to the Colombian context. The findings indicate significant barriers, including governance issues, policy implementation challenges, inadequate infrastructure, technological deficiencies, and a lack of trained personnel in public entities. Moreover, the study identifies potential solutions, highlighting strategic planning, stakeholder integration, infrastructure optimization, and data generation to facilitate decision- making. Finally, the results underscore the low implementation levels of environmental, social, and economic plans for sustainable IWT development on the Magdalena River, indicating a need for comprehensive and strategic interventions.
Mechanisms of Bioactive Lipids to Modulate Master Regulators of Lipid Homeostasis and Inflammation in Metabolic Syndrome
Authors: Estefes-Duarte José Antonio , Espinosa-Sánchez Astrid , Pérez-Hernández Nury , Ortiz Mario I. , Fernández-Martínez Eduardo
Published: October 2024

Metabolic Syndrome (MetS) refers to the co-occurrence of a constellation of metabolic
diseases in the same individual, such as abdominal/visceral obesity, insulin resistance or diabetes,
alterations in the lipid profile (dyslipidemias), and/or hypertension, which promotes the
development of other cardiometabolic and hepatic diseases. Dyslipidemia and metabolic dysfunction-
associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver
disease (NAFLD), are common MetS pathologies closely related to lipid metabolism. Alterations
in the metabolism of proteins, carbohydrates, and lipids, caused by an excessive intake of
nutrients and abnormal accumulation of body fat, which promotes chronic low-grade inflammation,
are pivotal aspects of MetS development. To avoid damage caused by lipid overaccumulation,
the transcription factors responsible for regulating lipid homeostasis and inflammation
(named in this work master regulators) must modify their regular activity; however, the high
adiposity established for long periods causes the appearance of insulin resistance (the MetS triggering
factor most widely accepted in the literature). Fortunately, scientific evidence suggests
that the abnormal activity of these regulators can be conveniently modulated by distinct species
of bioactive lipids, among which unsaturated fatty acids stand out, offering new alternatives for
treating MetS. Therefore, this work aims to provide a general overview of scientific evidence
that supports the mechanisms of action and the effective modulation by bioactive lipids of some
master lipid-metabolism-and-inflammation regulators in diverse aspects of MetS.
A Study on the Rationality of Baicalein in the Treatment of Osteoporosis: A Narrative Review
Authors: Li Qi , Ma Xingyan , Xu Xiaodong , Zhang Chengming , Wang Weiguo
Published: October 2024

Baicalein (BN) is an active ingredient naturally present in Chinese herbs, such as Scutellaria
baicalein, Coptis chinensis, and Dendrobium officinale. It has a variety of pharmacological
activities, including antioxidant, anti-inflammatory and antibacterial effects. Therefore, Baicalein
(BN) is widely used in the field of medicine and is considered a potential natural medicine. Osteoporosis
(OP) is a bone metabolic disease characterized by decreased bone mineral density and
bone structure destruction, which is mainly caused by decreased bone formation and increased
bone resorption. With the continuous development of molecular biology, the signaling pathways
and gene targets of bone metabolism are also expanding. Recent studies have shown that baicalein
may affect the function of osteoblasts, osteoclasts, and bone marrow mesenchymal stem cells
through MAPK/ERK and MAPKs/NF-κB signaling pathways, so as to have a therapeutic effect
on OP. However, the specific mechanism of baicalein in the treatment of OP is still unclear. This
article reviews the literature, analyzes and summarizes the mechanism of action of baicalein, and
discusses its potential in the prevention and treatment of OP, so as to provide a basis for the clinical
application of baicalein.
M2-like Macrophages-derived CCL17 Promotes Esophageal Squamous Cell Carcinoma Metastasis and Stemness via Activating CCR4-mediated ERK/PD-L1 Pathway
Authors: Jin Chun , Lu Liangliang , Gao Jian , Chen Ling
Published: October 2024

Background and objective:

High morbidity, high mortality and poor
prognosis of esophageal squamous cell carcinoma (ESCC) highlights the urgent need
for novel therapeutic strategies against ESCC. The current study addresses the
precise role of M2-like macrophages-derived CCL17 in ESCC progression and to
thoroughly elucidate the intrinsic molecular mechanisms.

Methods:

In this work, for functional experiments, Eca109 cells cultivated in M2-CM
were treated with anti-IgG (50 μg/ml) or anti-CCL17 (50 μg/ml) to expound the tumorpromoting
effects of M2-like macrophage-derived CCL17 in ESCC. Moreover, for
rescue experiments, Eca109 cells were treated with CCL17 (50 ng/ml) and/or CCR4
antagonist AZD2098 (20 μM) to probe whether CCL17 could influence the malignant
behaviors including migration, invasion and stemness of ESCC cells via activating
CCR4/ERK/PD-L1 pathway.

Results:

Markedly enhanced CCL17 secretion was observed in M2-like macrophages.
CCL17 bound to CCR4 to activate ERK/PD-L1 signaling. M2-like macrophagesderived
CCL17 facilitated ESCC cell migration and invasion and enhanced stemness
characteristics of ESCC cells, which were partially reserved by AZD2098 treatment.
The tumor-promoting effects of M2-like macrophages-derived CCL17 on ECSS was
depended on the activation of CCR4/ERK/PD-L1 pathway.

Conclusion:

To conclude, M2-like macrophages-derived CCL17 could facilitate ESCC
cell migration and invasion and enhance stemness characteristics of ESCC cells via
activating CCR4/ERK/PD-L1 signaling.
Recent Update on Nanoparticles Based Approaches for Management of Cancer: Wave from Traditional to Advanced Technology
Authors: Sharma Abhishek , Modgil Mridul , Joshi Gaurav , Bisht Preeti
Published: October 2024

Cancer is the second most common cause of death worldwide and one of the biggest public health issues arising day by day. Cancer treatment has experienced significant progres-sions in recent years, as emerging technologies have provided innovative strategies to combat this intricate ailment. Among these developments, nanotechnology has shown itself to be a po-tentially useful tool in the fight against cancer. In the last few years, there have been several re-searches performed in the field of nanoparticles because of their several advantages as compared to conventional drug delivery using nanoparticles along with updating technologies like artificial intelligence (AI). The use of nanoparticles decreases the chance of undesirable side effects and shows its action on the targeted site with the help of designed carriers.AI based nanoparticles can’t only be used for achieving the targeted site of action but can also help us in advanced im-aging, drug release and optimizing the drug delivery in a more customized way, which opens the door of a new era for tailored made medicine.
Identification of Key miRNAs in Endometriosis
Authors: Blandino Francesca , Barbati Saviana Antonella , Forlani Luca , Coppola Giulia , Meschino Noemi , Cecchinelli Ilde , Mazzuca Antonietta Cosco , Veltri Valentina , Giannico Riccardo , Calugi Graziella
Published: October 2024

Introduction:

Endometriosis, a prevalent gynecological disorder characterized by the
presence of endometrial-like tissue outside the uterus, poses significant challenges in diagnosis
and management due to its unclear pathogenesis and lack of specific biomarkers.

Objective:

This study investigates the potential use of microRNAs (miRNAs) as key markers in
endometriosis by studying two cohorts of patients (14 patients diagnosed with endometriosis and
15 patients with gynecological benign lesions, different from endometriosis).

Methods:

MicroRNA sequencing analysis was tested within data management by a custom pipeline
designed by Eurofins Genoma Group.

Results:

We identified a specific miRNA expression profile associated with endometriosis to
feature specific disease molecular clusters to further elucidate the underlying mechanisms driving
endometriosis pathogenesis.
Data from the present study suggest a specific miRNA scar for endometriosis compared to other
gynecological diseases to develop screening tools in early diagnosis and to ameliorate the management
of the disease itself.

Conclusion:

This study lays the foundation for the identification of key miRNAs involved in the
disease pathogenesis to unveil the molecular signatures in the complex scenario of endometriosis.
Further validation and exploration of these findings are needed to develop tools to improve molecular
diagnosis and to create a machine-learning prediction algorithm in the future.
An Evidence-Based Comprehensive Review of Laughter Therapy in Depression Management
Authors: Pannu Arzoo , Goyal Ramesh K. , Kumari Parina
Published: October 2024

Depression is a widespread mental health challenge, necessitating diverse
therapeutic approaches. Emerging research suggests that laughter may offer
a valuable adjunctive intervention for individuals grappling with depressive
symptoms. This review systematically investigates the multifaceted relationship
between laughter and depression, elucidating the underlying mechanisms and potential
therapeutic benefits. A comprehensive literature search was conducted
across multiple electronic databases, including PubMed, PsycINFO, Scopus,
and Google Scholar. Keywords used in the search included “laughter therapy,”
“humor,” “depression,” “mental health,” and “psychological well-being.” The
search was limited to articles published in English and included both peer-reviewed
journal articles and relevant gray literature. Relevant data were extracted
from each study, including the study design, sample size, participant characteristics,
type of laughter intervention, duration and frequency of the intervention,
outcome measures, and key findings. The extracted data were organized into tables
to facilitate comparison across studies. By synthesizing findings from clinical
studies, neuroscience research, and anecdotal evidence, this review examines
the physiological, psychological, and social dimensions of laughter's impact on
depression. Special attention is given to neurochemical pathways, stress modulation,
cognitive restructuring, and social dynamics. The physiological effects of
laughter on depression encompass neurochemical regulation (endorphins, serotonin,
dopamine), stress reduction, and immune system modulation. Psychologically,
laughter contributes to cognitive reframing, enhanced coping mechanisms,
and mood regulation. Socially, it strengthens social bonds, mitigates social
isolation, and fosters a positive social environment. In conclusion, this review
synthesizes current knowledge on the healing potential of laughter in mitigating
depression, providing a holistic understanding of its multifaceted impact.
The findings underscore the importance of integrating laughter-based interventions
into mental health care practices and highlight avenues for future research
and clinical applications in the realm of depression treatment.
Bedaquiline Delivery Innovations: A Review on Advancing MDR-TB Treatment Strategies
Authors: Ahmad Asad , Akhtar Juber , Ahmad Mohammad , Badruddeen  , Khan Mohammad Irfan , Singh Aditya , Islam Anas
Published: October 2024

Multidrug-resistant tuberculosis (MDR-TB) poses a persistent challenge to
global health, necessitating continuous efforts to enhance treatment efficacy. Bedaquiline,
a cornerstone in MDR-TB management, presents biopharmaceutical challenges that impact
its therapeutic potential. This review provides a comprehensive analysis of recent innovations
in drug delivery strategies designed to optimize Bedaquiline's efficacy and improve
MDR-TB treatment outcomes. Through a systematic examination of various delivery systems,
including nanotechnology and formulation advancements, we explore their potential
in addressing drug solubility and bioavailability challenges. Emphasizing the integration of
Quality by Design (QbD) principles, this review aims to present a cohesive overview of
evolving Bedaquiline delivery innovations, providing valuable insights for researchers and
healthcare practitioners working towards advancing MDR-TB treatment strategies.
Novel Approaches for the Synthesis of Nanomaterials for Nanodevices in Medical Diagnostics
Authors: Puri Nidhi
Published: October 2024

In recent years, the field of nanotechnology has witnessed significant
advancements in the synthesis of nanomaterials tailored for applications in medical
diagnostics. Nanodevices, characterized by their miniature size and exceptional
properties, hold tremendous potential for revolutionizing healthcare by enabling rapid
and precise diagnosis of various diseases. This chapter provides an overview of
innovative strategies employed in the synthesis of nanomaterials specifically designed
for integration into nanodevices for medical diagnostics. The synthesis of
nanomaterials for nanodevices necessitates the development of precise and
reproducible methods capable of producing materials with desired properties such as
size, shape, composition, and surface functionalization. Traditional synthesis
techniques, including chemical vapor deposition, sol-gel processes, and physical vapor
deposition, have been augmented by novel approaches leveraging principles from
chemistry, physics, and materials science. One such approach is bottom-up synthesis,
which involves the self-assembly of atoms or molecules into nanoscale structures,
enabling precise control over size and morphology. Techniques such as molecular
beam epitaxy (MBE) and atomic layer deposition (ALD) offer atomic-level precision,
facilitating the fabrication of nanomaterials with tailored properties for specific
diagnostic applications. Additionally, advancements in nanomaterial synthesis have
been driven by the emergence of green synthesis methods, which utilize natural sources
such as plants, microbes, and biomolecules to produce nanomaterials with minimal
environmental impact. Green synthesis techniques not only offer a sustainable
alternative to conventional methods but also afford opportunities for the development
of biocompatible and biofunctionalized nanomaterials suitable for biomedical
applications. Furthermore, the integration of nanomaterials into functional nanodevices
requires precise control over material properties to ensure compatibility with diagnostic
platforms. Surface modification techniques, including functionalization with
biomolecules, polymers, and ligands, play a crucial role in enhancing the stability,
biocompatibility, and targeting capabilities of nanomaterials for diagnostic
applications. The chapter also discusses recent advancements in the synthesis of
multifunctional nanomaterials capable of simultaneous detection, imaging, and therapy,
offering integrated solutions for personalized medicine and point-of-care diagnostics. By harnessing the synergistic properties of nanomaterials, researchers are developing
next-generation nanodevices capable of revolutionizing medical diagnostics by
providing rapid, sensitive, and cost-effective solutions for disease detection and
monitoring.
Functionalization Strategies and Applications of Two-Dimensional Boron Nitride
Authors: Punetha Mayank , Zaarifi Abbas , Kuzmin Anton , Pillai Sadafara
Published: October 2024

Recently, 2D Boron Nitride (BN) and its derivatives have emerged as
materials of great interest due to their intriguing structure, similar to graphene, and
possessing remarkable physical, chemical, and optoelectronic properties. BN has
shown great applications in various fields, including electronics, energy storage and
conversion, advanced composites, lubricants, and many more. Moreover, the hybrid
materials of 2D BN with graphene and other nanomaterials have evolved as excellent
dielectric substrates widely used in electronic devices. However, the extensive
application of this material is severely restricted for various reasons. The book chapter
elaborates different 2D BN nanostructures with a focused view on their striking
applications. The mechanistic aspects of surface revamping through covalent
functionalization have been discussed for the readers' comprehensive overview and a
concise discussion on the challenges associated with this. The book chapter reviews the
application of BN in electronics, biomedical applications, and smart composites in
depth. This book chapter will provide a comprehensive outlook to the readers in
understanding the recent and significant epistemological evidence.
Property Stigma and Overhang Units: SEM-PLS Analysis of Clio2 Residence, Putrajaya
Authors: Huri Norulelin , Ahmad Baharum Zarita , Ting Kien Hwa  , Newell Graeme
Published: October 2024

Property stigma encompasses characteristics, features, social values, or events related to land and buildings that generate negative perceptions of a property or neighborhood. This stigma significantly contributes to the overhang of residential units in Malaysia. This study aims to develop a Partial Least Squares Structural Equation Modeling (SEM-PLS) model to analyze the impact of stigmatized property dimensions on Clio2 Residence, an overhang strata residential scheme in Putrajaya. The findings indicate that both external and internal stigmas are significant factors leading to unsold property units in Clio2 Residence.
HARDWARE SECURITY MODEL WITH VEDIC MULTIPLIER BASED ECC ALGORITHM ON HIGH-PERFORMANCE FPGA DEVICE
Authors:   Bhilai Institute of Technology, India, Singh Saurabh , Soni Sunita ,   Bhilai Institute of Technology, India
Published: October 2024

The key problem that the world is most concerned about is security. Data security is the process of preventing unauthorized access to sensitive data. It includes all of the cybersecurity measures you take to keep your data safe from unauthorized access, such as encryption and access restrictions (both physical and digital). Data security has always been of the utmost importance. We utilize cryptographic methods to improve the services of data security. The application of cryptographic algorithms achieves data encryption. Therefore, we developed two versions of ECC algorithms on FPGA for improved hardware security in this study. The FPGA device employed here is Kintex-7, and there are two types of ECC: standard ECC and Vedic multiplier-based ECC. Vedic multiplier-based ECC has discovered that it consumes less space than standard ECC. Not only does Vedic multiplier-based ECC save space, but it also saves electricity. As a result, it is determined that for improved hardware security with ECC enabled, Vedic Multiplier-based ECC should be used over standard ECC.
THE ENHANCEMENTS IN STORAGE CAPACITY AND LONG-TERM DATA RETENTION OF MULTIDIMENSIONAL FLASH MEMORY IN MODERN MICROCIRCUIT APPLICATIONS
Authors:   Bhilai Institute of Technology, India, Mathew Ajay
Published: October 2024

Generally, flash memory is a type of permanent memory for computers in which the contents can be reprocessed or erased electronically. Compared to programmable read-only memory that can erase electricity, operations on it can be performed on modules located in different locations. Flash memory is much less expensive than EEPROM, which is why it has become a dominant technology. Especially, in situations, this stable and long-term data retention is required. Its use is allowed in various cases like digital audio players, photo and video cameras, mobile phones and smartphones, and specialized Android applications on the memory card. Additionally, it is also used on USB flash drives, traditionally used to store and transfer information between computers. The proposed model provides enhancements to the storage capacity of various flash memory modules. In a saturation point, the proposed model achieved 93.03% of NOR Memory management, 89.31% of NAND Memory management, 94.25% of Ferroelectric RAM Memory management, and 94.53% of Magnetic RAM Memory management, 96.05% of Ovonic Unified Memory management and 96.16% of Salcogenide RAM Memory management.
OPTIMIZATION OF MANET WITH MIMO FOR FOREST APPLICATION USING ADVANCED ANTENNA MODELS
Authors:   SNS College of Engineering, India, K Periyakaruppan , D Manohari ,   St. Joseph Institute of Technology, India, M S Kavitha ,   SNS College of Engineering, India, B Chellaprabha ,   Karpagam Institute of Technology, India
Published: October 2024

In this proposed work, the impulse response of the channel was measured to estimate the PL of an ad hoc network with more than one antenna in different environments, such as indoors, outdoors, in a forest, or in a combination of propagation environments. Some of these places are: Also, a brand-new way to find a PL path with the lowest cost is suggested and put into action. Assuming that all communication nodes are within the network''s transmission range, the suggested method can find the path in the network that loses the least amount of data. But this is seen as a problem, and it is planned that it will be fixed in our next project. So, based on the results, the proposed protocol is made and tested to make sure that communication goes through a secure route with the least amount of packet loss. Along with the transmission range limit, the power limit would also need to be worked on in the future because it is thought to be another important part of mobile ad hoc networks. Another important part of mobile ad hoc networks is how much energy they need. MANET runs on batteries, so energy, or power, is one of the most important parts of how it works.
AN EFFECTIVE HEART DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUE
Authors:   Sona College of Technology, India, D Komalavalli , R Sangeethapriya ,   Sona College of Technology, India, R Indhu ,   Sona College of Technology, India, N Kanimozhi ,   Sona College of Technology, India, G Kasthuri ,   Sona College of Technology, India
Published: October 2024

Heart disease is the foremost significant causes of transience within the world nowadays. It is a vital challenge to predict the cardiovascular disease in the range of clinical data investigation. Machine Learning (ML) is the most popular and powerful approach that has been appeared to be effective in making decisions and predictions from the huge amount of information delivered by the healthcare industry. ML techniques are also used in recent developments in wide areas of the Internet of Things (IoT). There are various studies done to predict the heart disease with ML techniques and it gives only a glimpse of it. In this paper, a simple TensorFlow model is proposed to find out major features by applying ML techniques that result in better accuracy in the prediction of cardiovascular disease. The prediction model is presented with diverse combinations of features and known classification algorithms. This version for coronary heart disorder with the ML based TensorFlow Model produces a more desirable overall performance with a higher accuracy stage in prediction.
CLASSIFICATION OF QUERY RECOMMENDATION USING QUERY SEMANTIC FLOW GRAPH TECHNIQUE ON NOVEL AOL LOG METHOD
Authors:   Rathnavel Subramaniam College of Arts and Science, India, R Balakrishnan
Published: October 2024

Web mining is one among the thrust area of research in the data mining domain. The classification of query recommendation can be divided into two major classes that are document-based approach and log-based approach. Log-based method can get relatively good query recommendation and find query inner relation. Query flow graph is one of log-based method and get relatively good recommendation. However, query flow graph cannot get query semantic information. And there are many isolated nodes because of data sparseness. Therefore, word2vec is used to define the query semantic and add query semantic to query flow graph. That can be able to modify query transfer probability which is calculated by query flow graph. At the same time, we can get connection between the isolated queries that are related but no connection due to the data sparseness and the inaccuracy of session split. Empirical tests are conducted in accordance with the AOL log. From the results the efficiency of the approach in suggesting queries and F1 value is about 20% higher than the traditional query flow graph.
INFORMATION RETRIEVAL BUG LOCALIZATION WITH WAVELETS ANALYSIS
Authors:   University Oran 1, Algeria, S Zouairi , M K Abdi ,   University Oran 1, Algeria
Published: October 2024

Nowadays, maintaining an oversized and evolving computer code involves longer and value for the project team. In software maintenance, a bug report is employed to seek out a fault location. Once a bug report is received, it is suiTable.to automatically denote out the files that developers should change to repair the bug. This work develops a brand-new information retrieval (IR) system that allows representing textual data by signals. This new way of implementing gives us the chance to use various mathematical tools from the signal theory like Wavelets Transforms, unused nowadays within the field of IR. This paper proposes Wavelets Transforms for Bug Localization (WTBugLoc), a mathematical approach of IR-based bug localization using wavelet techniques. The results of the conducted experiments on the SWT (Standard Widget Toolkit) Eclipse project confirm the effectiveness of the proposed approach. The experiments also show that WTBugLoc outperforms method using the Vector Space Model (VSM).
SECURE ASSOCIATION RULE MINING ON VERTICALLY PARTITIONED DATA USING FULLY HOMOMORPHIC ENCRYPTION
Authors:   Manonmaniam Sundaranar University, India, M Yogasini , B N Prathibha ,   Manonmaniam Sundaranar University, India
Published: October 2024

Cloud Computing is a leading innovation technology that guides to access applications over the web. The data owner’s data can be gotten to and controlled in the cloud. Privacy has become conclusive in information-driven applications within the distributed outsourced information. There are numerous inquiries still coming up on the best way to accomplish a confided in a climate that monitors application and information in the cloud from unapproved users. For offering protection to the users, sporadically there is a need to encode the data before accomplishing any other process. The cryptography method is embraced for data privacy. In this paper, a privacy-preserving construction is intended for vertically partitioned data in the cloud with the assistance of the Fully Homomorphic Encryption method. In this work, the homomorphic encryption and the Fully Homomorphic Encryption method is taken into consideration. The performance of the Rule Mining algorithm namely Eclat is compared with the encryption algorithms. The examination result shows that the Fully Homomorphic Encryption is less time-consuming to generate rule in the cloud, regardless of the number of transactions.
MAPPING AND CLASSIFICATION OF SOIL PROPERTIES FROM TEXT DATASET USING RECURRENT CONVOLUTIONAL NEURAL NETWORK
Authors:   Government College of Engineering, Bargur, India, S Selvi , V Saravanan ,   Dambi Dollo University, Ethiopia
Published: October 2024

Accurate and effective mapping of soil properties is regarded as a critical task in environmental and agricultural management. The evaluation of properties of soil is a daunting task while monitoring and sensing the environment. Existing sampling methods is a time-consuming and laborious job and they are limited based on the regions. However, the need of soil analysis and its properties is essential at landscape level. In this paper, we use Recurrent Convolution Neural Network (RCNN) to assess the soil properties via its classification task. The model in turn is compared with conventional geostatistical spatial interpolation methods. The utilization of Recurrent Neural Network (RNN) aims at studying the spatial and temporal variability of the properties of soil that adopts Kriging interpolation technique. The simulation is conducted to study the efficacy of the model under different soil conditions and the efficacy of RCNN is reported. The results of simulation shows that the proposed method achieves higher rate of classification accuracy than other models.
REPLICATION AND MIGRATION COST MINIMIZATION OF CLOUD DATA CENTER
Authors:   Bharathiar University, India, T Arunambika , P Senthil Vadivu ,   Bharathiar University, India
Published: October 2024

Cloud Storage Providers (CSPs) provide geography features of an area data stores offering numerous classes for storage accompanied by various costs. One significant problem faced by cloud consumers is how to utilize these storage classes to deliver a device with the time-varying workload on its objects at a minimal price. This price includes the price of resident (for example, storage, put and get prices) and the possible migration price (for example, network price). This paper proposes the Replication and Migration Cost Minimization (RMCM) algorithm in Green Cloud Computing to tackle this issue. This algorithm is using VM’s direct migration method, which could decrease data centre prices and power usage by combining virtual resources. To decrease the price of data-placement for devices accompanied by varying workloads over time, developers must make optimal use of the price variation between storage and network services across multiple CSPs. This paper proposes an optimal cost-effective technique (OCET) for copying and migrating data into cloud data centres accompanied by numerous storage classes to attain this aim. This work goal to achieve price reduction in the load assign procedures in multiple data centre environments where virtual machines allocated to a provided data center taking into account energy price differences and the availability of local renewable power generation. The simulation outcomes demonstrate that the RMCM and OCET algorithm could reduce a replication and migration cost and decrease the power consumption of data centre in green cloud computing efficiently.
A FRAMEWORK FOR ANALYSING UNSTRUCTURED DATA IN COMPUTING DEVICES
Authors:   Sona College of Technology, India, J Dhayanithi , M Marimuthu ,   Sona College of Technology, India, G Mohanraj ,   Sona College of Technology, India, P Neelashkumar ,   Sona College of Technology, India
Published: October 2024

In recent years all the real-world digital equipment’s are generating enormous amount of data because of technological development. Those data are unstructured and hard to analyse. This framework tool is developed to view the data on different formats depending on the business needs by the customers or end users. Data forms are difficult to interpret manually. Structuring data is needed for the today’s business world. This system deals with files alone, as there are many problems in unstructured data. Manual listing and maintaining is hard as mistakenly the files are deleted and sometimes lost by the users. A tool was framed for analyzing file properties and showing our analysed report to the user which means they can make decisions based on their own business standards to improve the performance of hard drives. This framework will render different unstructured data analyses and provide some visual representation.
MINIMAX PROBABILITY BASED CHURN PREDICTION FOR PROFIT MAXIMIZATION
Authors:   St. Joseph’s College, India, V Jude Nirmal
Published: October 2024

Churn prediction has become a significant requirement for all customer centric organizations. Accurate prediction of churn can effectively improve customer loyalty and improve profits for the organization. This work presents an effective model that uses a combination of ensemble learning and minimax probability machines to provide a churn prediction system. The model has its major focus towards improving the profitability of the organization. The ensemble learning model has been designed to be computationally efficient, while the weight factors used in the minimax probability machines ensures reduction in losses, hence ensuring profitability. Experiments were performed and comparisons with existing models indicates that the model shows high performance, with 8% improved accuracy levels, indicating improved churn predictions.
EARLY ONSET DETECTION OF DIABETES USING FEATURE SELECTION AND BOOSTING TECHNIQUES
Authors:   Sri Venkateswara College of Engineering, India, Srivatsan Shruti , T Santhanam ,   DG Vaishnav College, India
Published: October 2024

Diabetes is one of the most common diseases present in human beings. It is well known that diabetes is a metabolic disease with no permanent cure but on early detection longevity can be increased. This research work focuses on predicting the early onset of diabetes. The diabetic dataset from UCI Machine Learning Repository is used. The necessary preprocessing techniques have been carried out to make the data more robust and suitable for further processing. This research work proposes two feature selection and ensemble boosting techniques resulting in four combinations(models) to predict the presence of diabetes in persons. Also, a novelty is introduced in further reducing the number of features selected by the feature selection techniques. The reduction in the number of features will reduce the memory and time complexity of the model. Among the models proposed, LightGBM(Light Gradient Boosting) with Recursive Feature Elimination (RFE) as feature selector has produced better performance. Further, LightGBM with least features gave satisfactory results.
CLASS WISE LINEAR DISCRIMINANT AND REGRESSION BASED BINARIZED NEAREST LEARNING IN DIGITAL MARKETING
Authors:   Bharathidasan University, India, K S Narayanan , S Suganya ,   Bharathidasan University, India
Published: October 2024

The employment of internet and social media has remodeled behavioral aspects of consumer or student communities and methods in which organizations or educational institutions perform their business pattern. Both social and digital marketing put forwards efficient scopes to educational institutions by way of reduced costs, enhanced brand perception and elevated sales. Nevertheless, notable disputes prevail from obstructive electronic word-of-mouth and invasive and annoying online brand existence. Nowadays, students use online promotions to know about best universities for education globally. This university choice and students’ feedback observed by student-experience shared across social media platforms. Several methods have been employed for selecting the university but not providing accurate information. This paper is motivated towards applying Machine Learning for learning, analyzing and classifying the student information based on the student experience by means of tweets in twitter. The twitter data with student tweets is collected from benchmark twitter dataset and applied to the proposed method, Class-wise Linear Discriminant and Regression-based Binarized Nearest Learning (CLD-RBNL). The CLD-RBNL method is split into two sections. First, preprocessing and relevant feature selection (i.e. tweets) are acquired by employing Class-wise Linear Discriminant-based Feature Selection (CLDFS) model to obtain dimensionality reduced tweets. To this result, Regression-based Binarized Nearest Neighor model is applied for maximum lead generation. The CLD-RBNL method is compared with other state-of-the-art methods and found to outperform in terms of sensitivity, specificity, processing time, lead generation accuracy and error rate.