bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Clone Detection in Wireless Sensor Networks using ANN
Authors: V Sathya , David Preetha Evangeline , M Rajakumaran , S Hariprasath
Published: October 2023

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor node. Decreasing the measurement of information transmission in sensor networks becomes an important issue. Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks. Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, ANN algorithm has been implemented to detect the clone nodes. The performance has been compared with the existing work. The comparison has been done with time and efficiency of the existing and the proposed work. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. This algorithm is used to detect the clone nodes easily and it is time effective.
Correlation Analysis Between Six Air Pollutants and Emergency Visit Rate in Shandong, China
Authors: Zhao Hanzhu , Chen Cai , Chen Liang , Pinkerton Kent E. , Zhang Yanbing , An Haoyuan , Zhang Zhenlei , Tian Chongxuan , Song Junlin , Li Wei
Published: October 2023

Background
Although air pollution has improved, instances of extreme weather pollution have been observed. Impacts of air pollution on the human body have become a significant focus of research.
Purpose
Previous research primarily focused on selecting specific pollutants as exposure factors or investigating the association with mortality. This study intends to examine the correlation between exposure to six national standard pollutants (sulfur dioxide, nitrogen dioxide, ozone, carbon monoxide, Particulate matter with particle size below 10 microns, Particulate matter with particle size below 2.5 microns) and visiting rate. The findings will provide valuable insights for optimizing hospital resource allocation based on air quality conditions.
Method
In this study, a generalized additive model based on Poisson distribution was employed and the full pollution model, single pollution lag model, and gender-stratified single pollution lag model were utilized to analyze the effects of six pollutants exposure on the visiting rate, delayed visiting rate and the male to female ratio. The study was conducted in Shandong Province, China.
Result
The exposure of PM10, PM2.5 and NO2 was positively correlated with the visiting rate of the population in Jinan, different departments have different sensitivity to pollutants. The exposure to all six pollutants exhibited a noticeable lag effect on the visiting rate in the hospital. However, the optimal lag period of pollutants varied across different departments and differed to some extent between different genders. In general, women were more sensitive to the effects of pollutant exposure, specifically to PM10, SO2, PM2.5, and NO2, than men.
" Evaluating the Impact of Adaptive External Dictionaries on Cyberbullying Detection using Machine Learning: A Review"
Authors: Jehad Hamzeh , Alhija Mwaffaq Abu , Tarawneh Hassan
Published: October 2023

Cyberbullying has escalated due to social media's rapid growth, endangering internet security. Correct these harmful habits. ML is used to research cyberbullying on Twitter. This model is enhanced with adaptive external dictionary (AED). Terms that are negative and positive are produced manually. The dynamic lists of positive and negative words produced by AED sentiment analysis. The dataset has positive and negative tweet columns. Social media's fast expansion has increased cyberbullying, threatening online safety. Recognizing and addressing these risky activities quickly requires a comprehensive system. Uses ML to detect Twitter cyberbullying (ML). This model detects better using Adaptive External Dictionary.47K Kaggle tweets made the AED. Manual refinement only produces negative and positive phrases in the first portion, relevant to our topic. AED sentiment analysis creates dynamic lists of Positive Words (PW) and Negative Words (NW) in this study. Tweets are columns. Combining internet data with positive and negative word counts identifies cyberbullying.
J-Shaped association between heart rate and in-hospital mortality in patients with congestive heart failure in intensive care unit: a retrospective observational study
Authors: Zhang Kai , Han Yu , Gu Fangming , Gu Zhaoxuan , liang Jiaying , Zhao Jiayu , zhang Tianqi , Gao Min , Hou Zhengyan , Cai Tianyi , Gao Yafang , Hu Rui , Liu Tianzhou , Cui Dan
Published: October 2023

Background
Despite extensive evidence linking heart rate (HR) to the risk of all-cause mortality, little attention has been given to exploring this association in patients with congestive heart failure (CHF). This study aimed to assess the relationship between HR and in-hospital mortality in CHF patients using data from a large clinical population-based sample.
Methods
This retrospective observational study utilized the Medical Information Mart for Intensive Care IV database to extract all relevant data. In-hospital mortality served as the primary outcome measure. Data analyses involved restricted cubic spline regression, piecewise logistic regression, and multiple logistic regression models. Additionally, subgroup analysis was performed to examine the robustness of the main findings.
Results
The study included 15,983 participants with CHF, aged 72.9 ± 13.4 years. After adjusting for all factors, with each unit increase in HR, there was a 1% risk increase of patient death (95% confidence interval: 1.01 ~ 1.01, P < 0.001). Compared with individuals with HR Q2 (72–81 beats per minute (bpm) ), the adjusted OR values for HR and in-hospital mortality in Q1 (≤ 72 bpm), Q3 (81–93 bpm), and Q4 (＞93 bpm) were 1.18 (95% CI: 0.99 ~ 1.41, p = 0.07), 1.24 (95% CI: 1.04 ~ 1.47, p = 0.014), and 1.64 (95% CI: 1.39 ~ 1.94, p < 0.001), respectively. A dose-response relationship revealed an J-shaped curve between HR and the risk of in-hospital mortality, with an inflection point at approximately 76 bpm. Stratified analyses confirmed the robustness of this correlation.
Conclusions
In patients with CHF, there exists a J-shaped relationship between heart rate and in-hospital mortality, with an inflection point at 76 bpm. Nonetheless, further investigation through large randomized controlled trials is warranted in the future.
An In-depth Evaluation of Metagenomic Classifiers for Soil Microbiomes
Authors: Edwin Niranjana Rose , Fitzpatrick Amy Heather , Brennan Fiona , Abram Florence , O'Sullivan Orla
Published: October 2023

Background:
Recent endeavours in metagenomics, exemplified by projects such as the human microbiome project and TARA Oceans, have illuminated the complexities of microbial biomes. A robust bioinformatic pipeline and meticulous evaluation of their methodology have contributed to the success of these projects. The soil environment, however, with its unique challenges, requires a specialized methodological exploration to maximize microbial insights. A notable limitation in soil microbiome studies is the dearth of soil-specific reference databases available to classifiers that emulate the complexity of soil communities. There is also a lack of in-vitro mock communities derived from soil strains that can be assessed for taxonomic classification accuracy.
Results:
In this study, we generated a custom in-silico mock community containing microbial genomes commonly observed in the soil microbiome. Using this mock community, we simulated shotgun sequencing data to evaluate the performance of three leading metagenomic classifiers: Kraken2 with Bracken (both with a custom database derived from GTDB-TK genomes and its default database), Kaiju, and MetaPhlAn, utilizing their respective default databases for a robust analysis. Our results highlight the importance of optimizing taxonomic classification parameters, database selection, as well as analysing trimmed reads and contigs. We found that taxonomic classifiers limited bacteria, archaea and fungi yielded fewer errors than broader databases. Notably, an optimal classifier performance was achieved when applying a relative abundance threshold of 0.001% or 0.005%. The Kraken2 with a custom database demonstrated superior precision, sensitivity, F1 score, and overall sequence classification. Using a custom database, this database classified 99% of in-silico reads and 58% of real-world soil shotgun reads, with the latter identifying previously overlooked phyla using a custom database.
Conclusion:
This study underscores the potential advantages of in-silico methodological optimization in metagenomic analyses, especially when deciphering the complexities of soil microbiomes. We demonstrate that the choice of classifier and database significantly impacts microbial taxonomic profiling. Our findings suggest that employing Kraken2 with Bracken, coupled with a custom database of GTDB-TK genomes and fungal genomes at a relative abundance threshold of 0.001% provides optimal accuracy in soil shotgun metagenome analysis.
Serum Levels of Long Non-coding RNAs NEAT1, GAS5, and GAPLINC
Altered in Rheumatoid Arthritis
Authors: Tofigh Roghayeh , Hosseinpourfeizi Mohammadali , Safaralizadeh Reza , Ghoddusifar Sepideh , Baradaran Behzad
Published: October 2023

Background:

Rheumatoid arthritis (RA), an autoimmune joint inflammatory disease,
presents a significant challenge due to its prevalence, particularly among women, affecting around
6% of individuals over the age of 65. Novel insights into disease mechanisms are crucial for improved
diagnostic and therapeutic approaches.

Objective:

Long non-coding RNAs (lncRNAs) have emerged as potential contributors to the pathogenesis
of various autoimmune diseases, including RA. This study aims to investigate the unique
roles of four lncRNAs-NEAT1, GAS5, TMEVPG1, and GAPLINC-in the etiology of RA.

Methods:

Leveraging isolated serum samples from RA patients and healthy controls, we comprehensively
evaluated the expression profiles of these lncRNAs.

Results:

Notably, our findings unveil a distinctive landscape of lncRNA expressions in RA.
Among them, GAPLINC exhibited a significantly elevated average expression in the serum samples
of RA patients, suggesting a potential biomarker candidate for disease stratification. Importantly,
reduced expression of NEAT1 and GAS5 was observed in RA patients, highlighting their
possible roles as diagnostic and prognostic markers. Conversely, TMEVPG1 displayed unaltered
expression levels in RA samples.

Conclusion:

Our study introduces a novel dimension to RA research by identifying NEAT1,
GAS5, and GAPLINC as promising serological biomarkers. These findings hold significant clinical
implications, offering potential avenues for improved diagnosis, disease monitoring, and therapeutic
interventions in RA.
Effect of the Theory-driven Educational Intervention on Self-Care Behavior
and Glycosylated Hemoglobin Level in Patients with Type 2 Diabetes
Authors: Pourmohammad Mojgan , Maheri Mina , Khalkhali Hamid Reza , Moghaddam-Tabrizi Fatemeh , Didarloo Alireza
Published: October 2023

Background and aims:

The diabetics' lack of knowledge about self-care and incorrect
beliefs in this care are the reasons for their admission to hospitals. The present study aimed to
examine the impact of education based on the theory of planned behavior (TPB) on intention,
self-care behavior, and glycosylated hemoglobin (HbA1c) levels in patients with Type 2 Diabetes.

Methods:

The present study was conducted on 60 diabetic patients who were randomly classified
into intervention and control groups. In the intervention group, self-care education based on TPB
was held, but the control group only received routine care. The data were collected using a fourpart
questionnaire including characteristics, items of patients’ knowledge, items of TPB constructs,
and items of diabetes self-care. Data were analyzed in SPSS software.

Results:

In intervention group, mean score of self-care behavior and its domains significantly
changed from (total: 52.26±14.75, diabetic diet: 22.20±6.05, exercise: 5.17±4.04, blood sugar
testing: 5.03 ± 4.15, medication: 5.40±2.28, foot care: 13.47±8.42) into 76.66±8.87, 29.43±5.48,
7.60±2.60, 8.73±2.31, 6.48±1.09, 23.53±3.09, respectively three months after intervention
(p<0.01). In this case, these changes were not seen in the control group. The mean level of
HbA1c in the intervention group (6.38±0.16) was significantly lower than before the intervention
(7.56±1.08) and the control group (8.02±0.25) three months after intervention(p<0.01).

Conclusion:

Education based on the TPB was effective in improving the patients' self-care behavior
and HbA1c index. Therefore, we suggest all medical centers to use the TPB as an effective
and low-cost educational approach to improve diabetics' self-care behavior and health.
Cardiac Amyloidosis: A Contemporary Review of Medical and Surgical
Therapy
Authors: Brownell Drew , Pillai Aiswarya J. , Nair Nandini
Published: October 2023

Amyloidosis is a systemic disease initiated by deposition of misfolded proteins in the
extracellular space, due to which multiple organs may be affected concomitantly. Cardiac amyloidosis,
however, remains a major cause of morbidity and mortality in this population due to infiltrative
/restrictive cardiomyopathy. This review attempts to focus on contemporary medical
and surgical therapies for the different types of cardiac amyloidosis. Amyloidosis affecting the
heart are predominantly of the transthyretin type (acquired in the older or genetic in the younger
patients), and the monoclonal immunoglobulin light chain (AL) type which is solely acquired. A
rare form of secondary amyloidosis AA type can also affect the heart due to excessive production
and accumulation of the acute-phase protein called Serum Amyloid A” (SAA) in the setting
of chronic inflammation, cancers or autoinflammatory disease. More commonly AA amyloidosis
is seen in the liver and kidney. Other rare types are Apo A1 and Isolated Atrial Amyloidosis
(AANF). Medical therapies have made important strides in the clinical management of the two
common types of cardiac amyloidosis. Surgical therapies such as mechanical circulatory support
and cardiac transplantation should be considered in appropriate patients. Future research using
AI driven algorithms for early diagnosis and treatment as well as development of newer genetic
engineering technologies will drive improvements in diagnosis, treatment and patient outcomes.
A Monocytic Barrier to the Humanization of Immunodeficient Mice
Authors: Du Emily J. , Muench Marcus O.
Published: October 2023

Mice with severe immunodeficiencies have become very important tools for studying
foreign cells in an in vivo environment. Xenotransplants can be used to model cells from many
species, although most often, mice are humanized through the transplantation of human cells or tissues
to meet the needs of medical research. The development of immunodeficient mice is reviewed
leading up to the current state-of-the-art strains, such as the NOD-scid-gamma (NSG)
mouse. NSG mice are excellent hosts for human hematopoietic stem cell transplants or immune reconstitution
through transfusion of human peripheral blood mononuclear cells. However, barriers
to full hematopoietic engraftment still remain; notably, the survival of human cells in the circulation
is brief, which limits overall hematological and immune reconstitution. Reports have indicated
a critical role for monocytic cells – monocytes, macrophages, and dendritic cells – in the clearance
of xenogeneic cells from circulation. Various aspects of the NOD genetic background that affect
monocytic cell growth, maturation, and function that are favorable to human cell transplantation
are discussed. Important receptors, such as SIRPα, that form a part of the innate immune system
and enable the recognition and phagocytosis of foreign cells by monocytic cells are reviewed.
The development of humanized mouse models has taken decades of work in creating more immunodeficient
mice, genetic modification of these mice to express human genes, and refinement of
transplant techniques to optimize engraftment. Future advances may focus on the monocytic cells
of the host to find ways for further engraftment and survival of xenogeneic cells.
Evaluation of Clinical Characteristics and Outcomes of Chest Trauma Patients with COVID-19 Infection Undergoing Emergency Surgeries
Authors: Ahmadinejad Mojtaba , Soltanian Ali , Pak Haleh , Zolfaghari Maryam , Ahmadinejad Izadmehr
Published: October 2023

Background:

This study aims to examine the clinical characteristics and prognosis of
patients with chest trauma who were infected with COVID-19 and underwent emergency surgery.

Objective:

In light of the COVID-19 pandemic, this research investigates the impact of covid-19
on patients with chest trauma who underwent emergency surgery.

Methods:

This retrospective cohort study was conducted on 56 patients with chest trauma in two
groups with COVID-19, and no covid who underwent surgery in Shahid Madani Hospital.

Results:

Among the trauma patients, 21 were infected with COVID-19, and 35 were not. The predominant
causes of trauma were car and motorcycle accidents. Among COVID-19 patients, 3.3%
exhibited symptoms of fever, chills, cough, shortness of breath, and gastrointestinal symptoms,
while 5.9% had severe lung involvement confirmed by CT scan. Following surgery, 1.57% (12
individuals) of COVID-19 patients were transferred to the ICU, with an average hospitalization
duration of 1.11 days. In contrast, the average hospitalization duration for non-COVID-19 chest
trauma patients was 1.9 days (p =0.015).

Conclusion:

Patients with chest trauma who underwent surgery and were infected with COVID-19
demonstrated significant differences in average length of stay, ICU admissions, and pneumonia
incidence. However, there was no significant distinction in the mortality rate between the two
groups.
Modeling Molecular Study between SDO1/Inhibitors: Search of New Treatments for Amyotrophic Lateral Sclerosis
Authors: Mancini Daiana Teixeira , Militani Isabela Aparecida , de Castro Alexandre Alves , Assis Letícia Cristina , de Castro Ramalho Teodorico
Published: October 2023

Background:

The Amyotrophic lateral sclerosis (ALS) is a degenerative and most frequent
motor neuron disease characterized by the progressive impairment of upper and lower motor neurons. The
treatment of the disease is still palliative and limited to the use of only two drugs, riluzole and edaravone,
which only prolong survival by a few months. Taking into account the low number of therapy available
for this disease, identification of novel therapeutic strategies for ALS is urgently needed. The superoxide
dismutase 1 (SOD1) was the first gene in which mutations were found to be causative for the neurodegenerative
disease and has been used as a promising target for the ALS treatment.

Methods:

In this work we used powerful computational tools (in silico method) such as Ligand-based
Virtual Screening (SBVS), docking and molecular dynamics techniques to collaborate with the discovery
of new candidates for more potent drugs to be used in the ALS disease treatment.

Results:

Compound 1 shows good stability in the active site of the SOD1 enzyme, with an intermolecular
interaction energy of -154.80 kcal/mol. In addition, the presence of some amino acids such as Glu24,
Glu21, Pro28, Lys23 and Lys30 is important for to maintain stability of this compound inside SOD1.

Conclusion:

This study was essential due to a low number of therapy available for this disease until the
moment. With this study, it was possible to observe that Compound 1 is the most promising for the design
of SOD1 mutant enzyme potential inhibitors. However, experimental tests in the SOD1 mutant to validate
the inhibitory effect of Compound 1 will be required.
Design, Synthesis, and Pharmacological Evaluation of Novel Tacrine
Derivatives as Multi-target ANTI-Alzheimer’s Agents In Rat Models
Authors: R.S. Remya , N. Ramalakshmi , P. Muralidharan , C.N. Nalini
Published: October 2023

Background:

Alzheimer’s disease is a progressive neurodegenerative disorder for which no
curative drugs are available and treatment available is just palliative.

Objectives:

Current research focused on design of Tacrine-Flavone hybrids as multitargeted cholinesterase
and monoamine oxidase B inhibitors.

Methods:

A total of 10 Tacrine- Flavone hybrids were designed, synthesized and characterized. The in
vitro neurotoxicity and hepatotoxicity of the synthesized compounds determined using SHSY5Y cell
line and HEPG2 cell line. One most active compound (AF1) with least toxicity in in vitro studies was
chosen for in vivo studies. Acute and subacute toxicity of the novel compound AF1 conducted on
Wistar rats according to OECD guideline 423 and 407. The LD50 value of the novel compound calculated
according to Finney’s method using Probit analysis. Anti-Alzheimer’s activity studies conducted
on male Wistar rats. Behavioral studies conducted and AChE and MAO-B activity determined in rat
brain.

Results and Discussion:

All the compounds exhibited good inhibitory effect on MAO B and AChE.
The neurotoxicity studies of the active compound AF1 did not show toxicity up to 100μg. The hepatotoxicity
study of the most active compound AF1, showed the compound to be safe up to 200μg. The
LD 50 value of the novel compound after a single oral administration was found to be 64 mg/kg bodyweight
in rats. Subacute toxicity studies did not show any remarkable toxicity in the vital organs up
to 40 mg/kg. Activity studies showed comparable results with standard at 20 mg/kg.

Conclusion:

The results showed that the novel Tacrine-Flavone hybrids are multitarget-directed ligands,
which are safe and active compared to tacrine and can be a promising lead molecule for further
study.
Phosphodiesterase 2 and Its Isoform A as Therapeutic Targets in the
Central Nervous System Disorders
Authors: Metkar Sanjay K. , Yan Yuqing , Lu Yue , Lu Jianming , Zhu Xiongwei , Du Fu , Xu Ying
Published: October 2023

Cyclic adenosine monophosphates (cAMP) and cyclic guanosine monophosphate (cGMP)
are two essential second messengers, which are hydrolyzed by phosphodiesterase's (PDEs), such as
PDE-2. Pharmacological inhibition of PDE-2 (PDE2A) in the central nervous system improves cAMP
and cGMP signaling, which controls downstream proteins related to neuropsychiatric, neurodegenerative,
and neurodevelopmental disorders. Considering that there are no specific treatments for these
disorders, PDE-2 inhibitors' development has gained more attention in the recent decade. There is high
demand for developing new-generation drugs targeting PDE2 for treating diseases in the central nervous
and peripheral systems. This review summarizes the relationship between PDE-2 with neuropsychiatric,
neurodegenerative, and neurodevelopmental disorders as well as its possible treatment, mainly
involving inhibitors of PDE2.
Mathematical Development
Authors: Ghodhbani Abdelaziz , Haj Taïeb Ezzeddine , Akrout Mohsen , Elaoud Sami
Published: October 2023

This chapter gives a detailed description of the mathematical development
proposed for the study. The elasticity theory and the general theory of beams are
strongly present whereas some assumptions are adopted to simplify the analysis.
Numerical Calculation of Water Hammer
Authors: Ghodhbani Abdelaziz , Haj Taïeb Ezzeddine , Akrout Mohsen , Elaoud Sami
Published: October 2023

In this chapter, the Method of Characteristics (MOC) is detailed and used
to solve the mathematical models defined in the second chapter, where the
reservoirpipe-valve-system is considered. The wave-speed adjustment (WSA)
scheme is preferred for the MOC. The numerical method is applied to the elastic
pipelines on onehand and to the viscoelastic pipelines on the other hand.
Numerical Results for Elastic Pipelines
Authors: Ghodhbani Abdelaziz , Haj Taïeb Ezzeddine , Akrout Mohsen , Elaoud Sami
Published: October 2023

This chapter deals with the numerical results obtained from the simulation
of fluid transients in elastic pipes. The MOC with WSA scheme is used and the
numerical results are validated against experimental records. The comparison shows
good agreement between the two results which validate the earlier proposed models.
One-Dimensional Transient Flow in Pipelines Modelling and Simulation
Authors: Ghodhbani Abdelaziz , Haj Taïeb Ezzeddine , Akrout Mohsen , Elaoud Sami
Published: October 2023

This book presents numerical computational fluid dynamics (CFD) solutions for studying the effect of fluid-structure interaction (FSI) on evaluation of pressure waves in pipelines with cavitation. The authors develop a uniform one-dimensional model using coupled models. These models consider unsteady friction (UF), Poisson coupling, axial vibration (junction coupling), gas release and viscoelasticity.

The authors consider two cases: elastic pipelines and viscoelastic (VE) pipelines.

The book starts with a detailed literature review on the relevant methods for calculating transient fluid flow, followed by chapters that explain the mathematical development for calculations and the numerical steps for water hammer and transient cavitation. The concluding chapters present the results for the two pipeline cases.

The book is presented in simple language intended for engineering students who want to understand CFD simulations for transient flow in pipelines. Equations are explained in simple steps for easy understanding, and concepts are illustrated with detailed diagrams. The information and the codes demonstrated in the book will equip readers with the knowledge to study hydraulic problems where transients are caused by pump starting, stopping and failure.
Pithy & Comprehensive Review of Practical and Literal Models
Authors: Mishra Debajit , Jindal Muskan , Karras Dimitrios A.
Published: October 2023

The development and success of various smart cities is contingent on the
multiple models of expertise they employ and execute like a functional and smart
infrastructure to handle traffic chaos, a sustainable water recycling system, a smart
administration task manager, or an efficient waste management plant. The development
and efficacy of various smart cities are directly dependent on the efficiency of multiple
models it employees. Thus, the presented study aims to review, analyse and document
the various models that perform mundane tasks “smartly”, on the basis of key criteria
namely: efficacy on the task in hand, power and time consumption, human interaction,
upfront cost and operational task. These outcomes are then collated, and assayed by the
application of various mathematical and statistical models to determine their
performance as compared to the pre-existing non-technical approach of pursuing the
same. Finally, the purpose of this study is to present a complete analysis of the
performance of various models of smart cities to comprehend the profitability overall
and provide suitable points to improve the same.
Dynamic Involvement of Deep Learning and Big Data in Smart Cities
Authors: Shah Nidhi , Kapoor Arushi , Gupta Namith , Agarwal Vartika , Jindal Muskan
Published: October 2023

Deep learning is an extension of Artificial Intelligence (AI) or cognitive
learning that is used to optimize performance via the application of neural networks.
And, big data analytics includes managing a plethora of continuous streams of data
while obtaining valuable insights from them. Deep learning and Big Data analytics
have been implemented in various avenues to obtain real-time optimized results, like
biomedical applications, Computer Vision, and enhancing results for Internet of Things
applications. This study aims to provide a deep insight into the application,
performance, and values provided by Deep learning and Big-data analytics in the
various intricacies of smart cities, smart governance and workflows in the same.
Firstly, we provide applications or areas of smart cities that create Big-data, then
provide techniques and literature where Big-data analytics is used to handle the same.
Then, we present the different computing infrastructures used for IoT big data
analytics, which include cloud, fog, and edge computing. Finally, we provide insights
into various Deep learning modules that are successfully implemented in smart cities.
Power Generation Prediction in Solar PV system by Machine Learning Approach
Authors: Kumar Patnaik Rajesh , Sekhar Kolli Chandra , Mohan N. , Kirubakaran S. , Walia Ranjan
Published: October 2023

Solar energy is becoming more and more incorporated into the global power
grid. As a result, enhancing the accuracy of solar energy projections is crucial for
effective power grid planning, control, and operations. A fast, accurate and advanced
estimation method is desperately needed to prevent PV's detrimental consequences on
electricity and energy networks. For the optimum integration of solar technology into
existing power systems, which benefits both grids and station operators, accurate
prediction of solar production is crucial. The purpose of this research is to test the
effectiveness of the machine learning model for projecting PV solar output. Using
ANN in this research, weather parameters with the Power Generation for the next day
appear to have been predicted. The evaluation findings suggest that the models'
accuracy is sufficient to be employed with existing works and their approaches.
Machine learning was shown to be capable of accurately predicting power while
removing the difficulties associated with predicted solar irradiance data in this study.
Meteorite Finds in Africa
Authors: Ouknine Lahcen , Senesi Giorgio S. , Khiri Fouad , Ibhi Abderrahmane , Heikal Mohamed Th. S.
Published: October 2023

Africa is a favorable site for meteorite recovery, with a total number of
recoveries amounting to more than 1/6 of all meteorites recovered from the entire
world. This work deals with the classification of meteorite finds in Africa, the
distribution of their masses, and their alteration/weathering grades as affected by
various factors. The African meteorite population includes an abundance of stony
meteorites with a high percentage of the world collection of rare meteorites, i.e.,
Martian meteorites (62%), Ureilites (51%), Rumuruti (59%), Lunar (47%), and HED
(46%). Furthermore, an important increase in achondrite meteorites finds occurred in
the last two decades, compared to the Australian and Antarctic collections. The mass
distribution of the African meteorite population shows that most recoveries (72%) have
masses bigger than 100 g with peaks of about 1 kg, compared to about 0.1 kg for the
Australian collection and 0.01 kg for the Antarctic finds. The distribution of weathering
grades (W) shows the predominance of W1 (32%) and W2 (34%), which proves a
better preservation of meteorites in this continent. The factors influencing the
mechanism and rate of alteration of African finds include climate as the main factor,
the mass, the terrestrial age, and the initial porosity of the sample.
Meteorites of Morocco: Falls and Finds
Authors: Ibhi Abderrahmane , Khiri Fouad , Senesi Giorgio S. , Nachit Hassan
Published: October 2023

Since the first recorded discovery of a meteorite in 1937 near the Mrirt
village, a total of 1747 authenticated meteorites have been recovered in Morocco. The
collection includes 21 meteorites from authenticated observed falls, which comprise
five different types of meteorites, i.e., 17 ordinary chondrites including four LL6, one
EH7, one EH5, one H3-5, one H3-6, four H5, one CH, two L6 and two L4, one
carbonaceous chondrite, one eucrite unbrecciated, one shergottite basaltic achondrites
and one aubrite. The meteorite fall recovery rate in Morocco during the past 88 years
(from 1932 to 2020) on a surface area of 712. 5 km2
is relatively low, with
approximately four falls recorded every 10 years, equivalent to 0.4 falls per year per
2.11 km2
. A total of 1747 distinct and authenticated meteorite finds with a total mass of
6.175 kg have been described, which include 1674 stones (442 achondrites and 1232
chondrites), 37 iron, 24 stony-iron and 12 ungrouped meteorites. The rate of recovery
of meteorites (falls + finds) in Morocco exceeds that of most other countries of similar
size and climatic conditions. More than 95% of documented meteorites from Morocco,
including many rare types, have been recovered from the Eastern Moroccan Sahara,
which has been proven to be one of the most prolific world areas for meteorite finds.
Technology-Service Business Innovations through the Pandemic Era
Authors: Lee Joosung J.
Published: October 2023

In this Chapter, we will overview the cases of business innovation with a
focus on servitization and digitization. The Chapter will introduce innovative initiatives
in traditional markets, such as health and medicine-related, as well as manufacturing
spheres. Lastly, we will become familiar with more unconventional pandemic-induced
innovations within the clothing retail and fitness industries.
Technology Enterprise Business Models: A Handbook For The Post Pandemic Era
Authors: Lee Joosung J.
Published: October 2023

In the wake of the transformative global events since 2020, the economic landscape has undergone profound changes. Adapting to the new paradigms brought about by the pandemic requires innovative business models that seamlessly blend technology and offer hybrid online-offline services. This handbook is an essential guide for students and entrepreneurs navigating this evolving landscape. It equips readers with the knowledge and tools to create value and design effective online-offline business models that cater to the demands of the post-pandemic era.

Key Themes:

Technology-Service Management: Explore the concept of servitization, relevant frameworks, and the latest servitization trends that are reshaping industries.
Business Innovations: Learn how businesses have leveraged technology and service-oriented approaches to thrive during and after the pandemic.
Customer-Centric Models: Discover how to create business models that prioritize customer needs and preferences, effectively bridging the online and offline realms.
Value Innovation: Explore how the convergence of technology and services drives value creation and contributes to social welfare.
Real-World Examples: Gain insights from exemplary cases of servitization, illustrating how businesses have successfully overcome crisis situations.

In an era defined by rapid change and uncertainty, this book empowers readers to harness the potential of technology-driven service models. Whether you're a student seeking to understand these shifts or an entrepreneur looking to adapt and innovate, this resource provides invaluable insights and practical guidance for the post-pandemic business landscape.
How to Protect Your Skin from Harmful Radiation
Authors: Raza Ishaq Ali , Younis Tahira , Akbar Tahira , Mangat Muhammad Asad , Fatima Maliha , Cai Dongbo
Published: October 2023

Our interaction with the sun is still equivocal, to say the least. We like its
soothing influence on the body and soul, but we are afraid of its highly hazardous
heating ability and the long-term skin damage that can emerge from chronic sun
exposure. Scientists are consistently seeking to enhance sunblock products in
accordance with a need for better skin protection from the sun. Once human skin is
exposed to solar ultraviolet radiation (UVR), the synthesis of reactive oxygen species
(ROS) skyrockets. The influx of ROS leads to oxidative stress by mutating the natural
equilibrium toward a pro-oxidative state. Alteration in proteins and lipids, stimulation
of inflammation, immunodeficiency, DNA damage, and activation of signaling
pathways that influence gene transcription, cell cycle, proliferation, and apoptosis are
all illustrations of the detrimental effects of oxidative stress. This chapter provides new
insight into several Phyto-products having an antioxidant activity to suppress the UV
rays impact, the relationship between UVR-aging, current understanding of the
regulation of constitutive human skin pigmentation and responses to UV radiation, with
emphasis on physiological factors that influence those processes.
The Role of Natural Products in the Management of Skin Pigmentary Anomalies
Authors: Jiménez Ortega Luis Alfonso , Picos Salas Manuel Adrián , Gutiérrez Grijalva Erick Paul , Heredia José Basilio
Published: October 2023

The skin is one of the most important organs of the human body.
Dermatological ailments and pathologies are important for public health because they
cause physical damage and emotional and psychological repercussions that sometimes
present high healthcare expenses. Some of the most common pathologies are eczema,
psoriasis, acne, rosacea, pyoderma, scabies, tinea capitis, dermatitis, reactions of
poisonous insect or reptile bites hives, pigmentary anomalies such as vitiligo, albinism,
tinea versicolor, melasma, acanthosis nigricans, and café au Lait spots, such others, can
cause serious damage to health, for which extensive pharmacological treatments have
been proposed; however, they have serious side effects such as steroid treatments, so in
certain regions of the world, medicinal plants are used to treat dermatological
complications, where ethnopharmacological records date to treat or aid skin conditions,
mainly burns and scars. These effects are due to their anti-inflammatory, healing,
antimicrobial, and antioxidant properties, where the compounds most studied have
been phenolic (flavonoids such as phloretin), vitamins, and essential oils (terpenes).
Some species that stand out are the genera Dendrobium, Aloe, Acalypha, Acanthus,
Achillea, Actinidia, Calendula, Bulbine, Heparinum, Sanguisorba, and Buddleja,
among others. This chapter summarizes the most recent information regarding the
potential of natural products as biopharmaceutical agents against some of the most
evaluated skin pigmentary anomalies.
Identifying a Perceptually Congruent Frequency Range for Auditory Line Charts
Authors: Fitzpatrick Joe , Neff Flaithri
Published: October 2023

In this paper, three line chart sonification strategies are contrasted in a user-study examining performance outcomes and perceived difficulty. Auditory line charts are a simple and potentially effective form of parameter-mapping sonification and can be designed easily using freely-available software or a web app. However, an auditory graph’s efficacy is affected by a number of design factors such as presentation rate, tonality, and frequency range. Of these three factors, the frequency range remains relatively unexamined in sonification literature and, as such, is the focus of this paper. Three approaches relating to the frequency range are examined, including one that uses a form of amplitude compensation to account for the human frequency response. Results of a user study involving three groups of 16 participants show that a shorter range between 400 Hz and 1400 Hz performs just as well as a wider range between 65 Hz and 1480 Hz. Furthermore, the results suggest that using basic amplitude compensation on the wider range has no significant effect on performance or perceived difficulty.
Harmonices Solaris - Sonification of the Planets
Authors: Traver Peter , Bergh Emil
Published: October 2023

This project is a sonification of the planets in our solar system designed as a spatial audio installation. Audio for each planet was generated within Python using data from NASA about the planets (including Pluto). A Markov model across arbitrary pitch set space was used to generate pitch set collections for each planet with regard to the various parameters in the dataset. XP4Live is used for spatialization and visuals due to its real-time capability. The final piece, as presented, allows the audience to experience orbiting planet sound objects around them in space; the installation includes a mapping of the planets to faders on a MIDI controller allowing the audience to isolate individual planets to hear their sonic makeup and orbiting pattern. This model is presented in a spatial audio array of at least four speakers, but can also be presented as a binaural mix for virtual submission. Future work includes making this piece accessible to the public via a binaural rendering on a webpage, as well as VR implementation for enhanced interactivity.
Proof of Concept of a Generic Toolkit for Sonification: The Sonification Cell in Ossia Score
Authors: Poret Maxime , Celerier Jean-Michaël , Desainte-Catherine Myriam , Semal Catherine
Published: October 2023

A popular topic in sonification research is the development of a complete, user-friendly tool for sonification creation. A study of existing attempts at such tools highlights what seems to be the main challenge of this endeavor: exhaustiveness with regards to the great diversity of approaches for auditory display of information. Most tools are designed to allow for selecting among a few typical modalities, but could not really be used to create any kind of sonification. In order to tackle this issue, we proposed a theoretical model of the sonification process, which is intended to take all of its properties as a data observation technique into account. The goal for this model is to be translated into a user interface and programming approach as part of a sonification toolkit. In the present paper, we report our work in creating a proof of concept of such a toolkit using the ossia musical sequencing environment, chosen for its proximity to our objectives in terms of user interaction and library of functionalities. This prototype was tested to recreate two of our previous data sonification works. Most of the specificities of these case studies could be recreated properly, though some of the planned features, notably for grain synthesis, are currently missing from the ossia environment. For our future works, we will consider that the current state of this proof of concept is sufficient to start studying the user experience of sonification designers interacting with the toolkit.
Twice Stepped in Still Waters: Sonification and Interdisciplinarity as Artistic Research
Authors: Boehringer Jorge
Published: October 2023

Real-time EEG and sensor data sonification have been researched extensively. New implementations of these technologies in the fields of live electronic music performance and sonic art generally focus on instrumentalising brain waves as an interface, or are concerned with controlling brain waves through biofeedback. Twice Stepped in Still Waters is instead concerned with using bio and sensor feedback as a focused framework accommodating phenomenological listening for the performer. Furthermore, when presented before an audience, this activity results in circumstances for sound and listening (music). Currently available high-resolution consumer devices and open-source software have now rendered these technologies accessible to a wide pool of researchers from a variety of fields. The present work uses sonified real-time EEG and accelerometer data to situate phenomenological concerns of the performance situation within the field of artistic research. Discussion of the technical development and artistic context for the piece reveals a broad interdisciplinary scope. Twice Stepped in Still Waters may be therefore read as a case study offering an implementation and a performance methodology for sonification and focused listening afforded by these sensor technologies. Variations on the approaches described may be applied by other investigators working within or outside of the domain of artistic research.
Enhancement of Cardiac and Respiratory Sounds for Cellphone Reproduction by Means of Digital Sound Processing Methods
Authors: Echenique Maria Belen , Godoy Eduardo J. , Cádiz Rodrigo F. , Andia Marcelo E.
Published: October 2023

Telemedicine has become increasingly popular due to its convenience and accessibility. However, one of its drawbacks is the difficulty of performing lung and heart auscultation remotely. As a solution, we propose smartphone-based tele-auscultation for capturing lung and heart sounds. However, one of the obstacles to this approach is that low-frequency sounds, such as heart sounds, cannot be accurately reproduced by a smartphone speaker, due to their frequency response. To address this issue, we suggest using pitch-shifted versions of these sounds, specifically designed for hearing through smartphones. We conducted an initial evaluation of these processed sounds by obtaining 10 heart sounds and 20 lung sounds from open-source databases, which were pitch-shifted using algorithms based on Paul’s Stretch and SoundStretch libraries, respectively. These processed audios were validated by 40 final-year medical students using a web survey and conventional headphones and were compared against the original versions. The results showed that 72% and 80% of responses indicated that clinical information was preserved in the samples of respiratory and heart sounds, respectively. These findings suggest that pitch-shifted sounds could be potentially used in tele-auscultation devices such as smartphones. However, further research is needed regarding the recording and playback capabilities of smartphones.
Investigating Colour-Sound Mapping in Children and Adults: A Pilot Study
Authors: Cenerini Costanza , Vollero Luca , Pennazza Giorgio , Santonico Marco , Di Stefano Nicola , Keller Flavio
Published: October 2023

This paper presents an experimental study that investigates the mapping between color and sound in two groups of subjects, consisting of 8 children and 8 adults, respectively. The color was decomposed using the Hue-Saturation-Brightness representation, and the musical stimuli consisted of chords determined by three parameters: the Root Tone, the Mode, and the Octave. The results showed that both groups preferred the mapping Hue-Octave, Saturation-Mode, Brightness-Root Tone. The ANOVA test was applied to the results, and it showed a trend towards significance in children’s preferences, whereas adults’ results were not significant. Once the best mapping is defined, it will be implemented in a portable, embedded system for sensory substitution of sight with sound. This paper provides a promising starting point for further research in the field of affective sonification.