bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Malocclusions Among Schoolchildren from Southwestern Romania
Authors: Petrescu Stelian-Mihai-Sever , Ionescu Mihaela
Published: March 2024

Malocclusions have a continuously increasing prevalence from a generation to another as a result of climate changes, soil, atmosphere and water pollution. All of these aspects have unfavorable consequences on the nutritional scheme. Thus, nutrition together with other etiopathogenic factors contribute to complex alterations in the somatic development of the entire organism and, implicitly, of the cephalic extremity. The study included 4147 children from randomly selected schools from Vâlcea County, Romania. The aim of this study is to determine the prevalence of malocclusions in schoolchildren from Vâlcea County, Romania, according to the three main classes of malocclusions (according to Angle’s classification), age groups (from 6 to 10 years old and from 11 to 14 years old), gender (male and female) and place of origin (rural and urban). It is also aimed to compare the results obtained with similar ones from the specialized literature.
Modulation of corticospinal excitability during action observation in patients with consciousness-related disturbances
Authors: Mancuso Mauro , Emanuele Marco , Mencarelli Lucia , Abbruzzese Laura , Basagni Benedetta , Zoccolotti Pierluigi , Capitani Simone , Neri Francesco , Santarnecchi Emiliano , Fadiga Luciano , Rossi Simone
Published: March 2024

Brain imaging studies have recently provided some evidence in favour of covert cognitive processes ongoing in patients with disorders of consciousness (DoC) (e.g., minimally consciousness states, vegetative state/unresponsive wakefulness syndrome) engaged in passive sensory stimulation or active tasks such as motor imagery. In this exploratory study, we used transcranial magnetic stimulation (TMS) of the motor cortex to assess modulations of corticospinal excitability induced by action observation in eleven patients with DoC. Action observation is known to facilitate corticospinal excitability in healthy subjects, unveiling how the observer’s motor system maps others’ actions onto her/his motor repertoire. Additional stimuli were non-biological motion and acoustic startle stimuli, provided that sudden and loud acoustic stimulation is known to lower corticospinal excitability in healthy subjects. Results indicate that some form of motor resonance is spared in a subset of patients with DoC with some significant difference between biological and non-biological motion stimuli. However, there was no covariation between corticospinal excitability and the type of DoC diagnosis (i.e., whether VS/UWS or MCS). Similarly, no covariation was detected with clinical changes between admission and discharge in clinical outcome measures. Both motor resonance and biological/non-biological motion discrimination correlated with the amplitude of the N20 somatosensory evoked potentials following the stimulation of the median nerve at the wrist (i.e., the temporal marker signalling the activation of the contralateral primary somatosensory cortex). Moreover, the startle-evoking stimulus produced an anomalous increase in corticospinal excitability, suggesting a functional dissociation between cortical and subcortical circuits in patients with DoC. Further work is needed to better comprehend the conditions in which corticospinal facilitation occurs and whether and how they may relate to individual clinical parameters.
Carbon Footprint of the Production Process of Tropical Banana Plantation Based on the Life Cycle Approach: A Case Study of Chengmai County, Hainan Province, China
Authors: KUANG Changgeng , SHI Xuesong , ZHAO Congju , YE Wenwei , MEI Minhua
Published: March 2024

Banana plantation is an important type of agro-ecosystem in the tropics, and it is important to carry out a quantitative assessment of the carbon footprint of the banana growing process for the development of low-carbon agriculture to cope with global warming. The carbon footprint of two banana cultivation processes was assessed using the life cycle assessment method through field trials and farmer surveys in Chengmai County, Hainan Province, China. The results showed that: (1) N2O emissions caused by the application of nitrogen fertilizers and compound nitrogen fertilizers were the largest source of carbon emissions from banana plantation farmland, and the production and transportation of common compound fertilizer were the second largest source of carbon emissions. Banana fruits and plants were the main contributors to carbon fixation in banana plantation ecosystems, with about 24.72 t CO2 eq hm-2 for Musa paradisiaca AA, and 34.66 t CO2 eq hm-2 for M. AAA Cavendish var. Brazil. (2) The annual carbon emissions of Musa paradisiaca AA and M. AAA Cavendish var. Brazil farmland systems were 35.40 t CO2 eq·hm-2 and 43.83 t CO2 eq·hm-2, respectively, and the annual carbon fixation was 38.23 CO2 eq·hm-2 and 48.17 CO2 eq·hm-2, respectively. The banana plantations had a negative carbon footprint per unit area, showing a net carbon sink function. (3) Banana is a plant with high carbon emission and strong carbon fixation capacity. Scientific management in the field can achieve the decrease of agricultural inputs, high quality and abundant agricultural products, and the reduction of carbon footprint of farmland.
The Effects of Local Food on Carbon Emissions: The Case of the Republic of Korea
Authors: Jung Da-Eun , Yang Sung-Bum , Yang Seung-Ryong
Published: March 2024

The study addresses the urgent environmental issue of climate change, focusing specifically on the role of local food, which is produced and consumed locally, helps reduce carbon emissions by eliminating the need for long-distance transportation. Through quantitative analysis, this study elucidates the potential benefits in environmental impact achieved through the consumption of local food: the significant reduction in carbon emissions. Specifically, the consumption of local food is found to yield an annual decrease of 2,421,296 tCO2 emissions, representing 2.5% of South Korea’s total greenhouse gas emissions from the transportation sector. This reduction further translates into an estimated economic value of USD 54.23 million (KRW 70.5 billion). This study underscores the potential of local food consumption as a tangible strategy to overcome environmental problems. Moreover, its academic contribution lies in its comprehensive analysis of the economic and empirical impacts of local food consumption on environment. Moving forward, we propose policies such as supporting local food distribution networks, providing public education on local food, fostering the local food industry, and providing incentives to revitalize local food consumption.
Three-Step Synthesis of N-(7-chloro-4-morpholinoquinolin-2-yl)benzamide from 4,7-Dichloroquinoline
Authors: Aparicio Acevedo Deiby F. , Ortiz Villamizar Marlyn C. , Kouznetsov Vladimir V.
Published: March 2024

The quinoline derivative, N-(7-chloro-4-morpholinoquinolin-2-yl)benzamide, was synthesized in a conventional three-step procedure from 4,7-dichloroquinoline using N-oxidation reaction/C2-amidation reaction/C4 SNAr reaction sequence. The structure of the compound was fully characterized by FT-IR, 1H‐, 13C-NMR, DEPT-135°, and ESI-MS techniques. Its physicochemical parameters (Lipinski’s descriptors) were also calculated using the online SwissADME database. Such derivatives are relevant therapeutic agents exhibiting potent anticancer, antibacterial, antifungal, and antiparasitic properties.
The Role of Thromboelastography as a Predictor of Acute Kidney Injury in COVID-19 Patients in ICU
Authors: Sukorini Usi , Puspitawati Ira , Wardhani Yulia , Munajih Muhammad Roihan
Published: March 2024

There is evidence that kidney involvement is frequently observed in COVID-19 patients, and can manifest as mild proteinuria to advancing acute kidney injury (AKI). One of the mechanisms is microvascular and macrovascular thrombosis caused by the hypercoagulation phase of the disease. Thromboelastography (TEG) is a valuable examination to detect significant hemostatic abnormalities, including the hypercoagulable state. This study analyzed the coagulation profiles, including TEG parameters, in COVID-19 patients who developed AKI compared to those who did not during their intensive care unit (ICU) stay, to identify predictors of AKI. Our single-center cohort retrospective study involved adult patients of COVID-19 in the ICU of Sardjito Hospital in Yogyakarta, Indonesia between May and September 2021. Patients were divided into two groups of AKI and non-AKI based on 2012 KDIGO definition and the elaboration by Indonesian Society of Nephrology. Variables showing a significant difference in the two groups were then analyzed using univariate and multivariate binary logistic regression. A total of 60 COVID-19 patients were included in the study, and 35% of them developed AKI. Compared to non-AKI patients, those with AKI exhibited a greater prevalence of diabetes mellitus (66.7% versus 35.9%, P = 0.023), higher D-Dimer levels (970 versus 685 ng/mL, P = 0.045), and higher values in TEG parameters of maximum amplitude/MA (74.6 versus 65.9 mm, P = 0.001) and coagulation index/CI (2.3 versus 1.0, P = 0.033). TEG parameter of MA emerged as the sole significant predictor for the development of AKI (OR, 6.33; 95% CI, 1.56 to 25.64). Our study validated the kidney involvement of COVID-19 infection, and showed that diabetes mellitus, high D-Dimer levels, and hypercoagulability serve as prominent risk factors in the development of AKI. Furthermore, TEG parameter of MA exceeding 70 mm is the single independent significant predictor of AKI.
A Relationship between the Subatomic Particles’ Mass and the Square of the Magnetic Flux Quantum Provides a Novel Significance of the Mass and the Wave Function
Authors: Fried Israel
Published: March 2024

The motivation for investigating the issues presented in this article stemmed from a need to understand better the relationship in long-established physics formulas and extract the information they provided using conventional methods. Based on the definition of magnetic flux quantization, which is based on a combination of fundamental physical constants, the Planck constant, and the particle’s elementary charge, this work explores the results that arise when this equation is combined with the equation of the Bohr-level electrostatic force acting on the electron, which leads to a new mathematical relationship between the combined expressions. The new relationship yields novel theoretical findings related to the known universal constants. Following this insight, the formalism developed in this paper indicates that the mass of the electron and other subatomic particles is associated with the magnitude of the square of the magnetic flux quantum, which makes up the particle. This conclusion is not as strange as it may seem, as the square of the magnetic flux quantum appears in the context of magnetic energy in a current loop and, according to Einstein’s special theory of relativity, energy is equivalent to mass. Another aspect described at the end of this paper demonstrates the connection between the square of the magnetic flux quantum through the Bohr radius and the significance of the wave function in the atom. The theoretical results are in full accordance with experimental results published by NIST CODATA 2018 that I’ve used, which validates the existence of the relationship.
A Systematic Literature Review of Zero Trust Architecture for UAV Security Systems in IoBT
Authors: Alquwayzani Alanoud Abdullah , Albuali Abdullah Abdulrahman
Published: March 2024

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.
Efficacy and Immunogenicity of rKVAC85B in a BCG Prime-Boost Regimen Against H37Rv and HN878 Tuberculosis Strains
Authors: Shin Eunkyung , Yun Jin-Seung , Lee Young-Ran , Cha Hye-Ran , Kim Soo-Min , Shin Sung-Jae , Lee Sang-Won , Chung Gyung Tae , Kim Dokeun , Yoo Jung Sik , Kim Jong-Seok , Jeong Hye-Sook
Published: March 2024

Mycobacterium tuberculosis was responsible for 1.3 million deaths worldwide in 2022. Bacillus Calmette-Guérin (BCG) is the only licensed vaccine against tuberculosis (TB); however, it has limited protective efficacy in adults. In this study, we constructed a recombinant vaccinia virus expressing Ag85B from M. tuberculosis using a novel attenuated vaccinia virus (KVAC103). We then analyzed the immunogenicity of prime-boost inoculation strategies using recombinant KVAC103 expressing Ag85B (rKVAC85B) compared to BCG. In both the rKVAC85B prime-boost and the BCG prime-rKVAC85B boost inoculation regimens, rKVAC85B induced the generation of specific IgG and the secretion of IFN-γ by immune cells. In vitro analysis of Mycobacterium growth inhibition revealed a comparable immune-mediated pattern of outcomes. Furthermore, bacterial loads in the lungs were significantly lower in mice inoculated with the BCG prime-rKVAC85B boost, than in the BCG-only group following a rechallenge infection with both H37Rv and HN878 strains of M. tuberculosis. These findings collectively suggest that KVAC103, incorporated into a viral vector, is a promising candidate for a novel TB vaccine platform that is effective against multiple TB strains, including H37Rv and HN878, and that rKVAC85B effectively stimulates immune responses against TB infection.
SARS-CoV-2 Vaccines-Related Endocrine Disorders: An Updated Narrative Review
Authors: Ishay Avraham , Oleinikov Kira , Shacham Elena Chertok
Published: March 2024

Abstract: The emergence of the COVID-19 pandemic has led to the rapid and worldwide devel-opment and investigation of multiple vaccines. While most side effects of these vaccines are mild and transient, potentially severe adverse events may occur and involve the endocrine system. This narrative review aims to explore the current knowledge on potential endocrine adverse effects following COVID-19 vaccination, with thyroid disorders being the most common. Data about pi-tuitary, adrenal, diabetes, and gonadal events will also be reviewed. This review also provides a comprehensive understanding of the pathogenesis of endocrine disorders associated with SARS-CoV-2 vaccines. A PubMed/MEDLINE, Embase database (Elsevier), and Google Scholar research were performed. Case reports case series, original studies, and reviews written in English and published online up to 31 August 2023 were selected and reviewed. Data on endocrine adverse events of SARS-CoV-2 vaccines is accumulating. However, their causal relationship with COVID-19 vaccines is not strong enough to make a definite conclusion, and further studies are needed to clarify the pathogenesis mechanisms of endocrine disorders linked to COVID-19 vac-cines.
Aflatoxin M1 in Raw Milk Collected from Specialized Dairy Farms and Local Markets in Selected Urban Centers of Eastern Ethiopia
Authors: Tesfaye Angassa Tadese , Kurtu Mohammed Yusuf , Mume Yesihak Yusuf , Mohammed Abdi Hassan
Published: March 2024

Aflatoxin M1 (AFM1), a carcinogenic toxin, mainly contaminates cow milk and poses significant challenges to the dairy industry and, thereby, public health in most tropical countries, including Ethiopia. This study aimed to investigate the prevalence and level of AFM1 in raw cow milk collected from Specialized Dairy Farms and Milk Vendors in three Urban Centers: Chiro town, Dire Dawa, and Harar cities in Eastern Ethiopia. 180 milk samples were collected from two major Milk Sources: Specialized Dairy Farms (N=90) and Milk Vendors (N=90) using a simple random sampling technique. AFM1 was analyzed using high-performance liquid chromatography. The study revealed that, 63.9% (115/810) prevalence and 0.179±0.48µg/L mean of AFM1 level in milk, which 39.13% and 26.08% exceed the tolerable limits of EU and FDA respectively. A 40.0% prevalence and 0.344±0.72µg/L average of AFM1 in the milk from Dire Dawa city was significantly higher than the samples from other Urban Centers. However, 30.43% and 29.57% prevalence as well as 0.055±±0.13µg/L and 0.140±0.33µg/L average of AFM1 in milk from Chiro town and Harar city, respectively were not significant. Furthermore, milk samples from Dairy Farms revealed a higher prevalence (57.39%) and level (0.252±0.64µg/L) of AFM1 than Milk Vendors, with a prevalence of 42.61% and an average of 0.107±0.21µg/L. Therefore, this study concludes that substantial milk samples were contaminated by AFM1 and urges the need to enhance farmers' awareness on mitigation.
Farmer Perceptions of Land Cover Classification of UAS Imagery of Coffee Agroecosystems in Puerto Rico
Authors: Klenke Gwendolyn , Brines Shannon , Hernandez Nayethzi , Li Kevin , Glancy Riley , Cabrera Jose , Neal Blake Hendrix , Adkins Kevin , Schroeder Ronny , Perfecto Ivette
Published: March 2024

Highly diverse agroecosystems are increasingly of interest as the realization of farms' invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings.  In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and assembled accuracy assessments for each classification. To bolster our understanding of the classifications, we interviewed farmers to understand their thoughts on how these maps may be best used to support their land management. The average overall accuracy (53.9%), though relatively low, was expected for such a diverse landscape with fine-resolution data. After sharing imagery and land cover classifications with farmers, we found that while the prints were often a point of pride or curiosity for farmers, integrating the maps into farm management was perceived as impractical. These findings highlight that while remote sensing of diverse agroecosystems may provide a detailed way of estimating land cover classes and ecosystem services for researchers and government agencies for example these maps may be of limited use to land managers without additional interpretation.
A Comprehensive Review of the Variability of Bovine Colostrum Components and Their Effect on Neonatal Calf Physiology
Authors: Da Silva Flávio Gomes , Silva Severiano R. , Pereira Alfredo M.F. , Cerqueira Joaquim Lima , Conceição Cristina
Published: March 2024

Most research on colostrum quality and colostrum management focuses on maternal IgG transfer to the newborn calf. However, in addition to being a source of antibodies, colostrum has other components that influence passive immune transfer, nutrition, gut maturation, and thermoregulation. In this review, the constituents in the bovine colostrum, as well as their variation, are explored and it is discussed the biological role of colostrum on the newborn calf. Protein is the nutrient in higher concentration and fat is the nutrient with the most variation. There is a pronounced amplitude in the total solids content of colostrum, but the average concentration does not vary much between studies (24.7%). Bovine colostrum major components can vary with several factors, such as the region, season, breed, dry period length, and nutritional aspects of the dam. Bioactive components, cells, and microbiome variability are less understood, besides IgG. Regardless, they play crucial distinct roles in the physiological development of the newborn. However, a multi-interactive effect between these components, cells, and microorganisms is more likely to occur. Recently researched components in colostrum like miRNA, nucleo(t)sides, the milk fat globule membrane, oligosaccharides, minor proteins, and the microbiome are examples of promising interest areas of study.
Fuzzy PID Control Design of Mining Electric Locomotive Based on Permanent Magnet Synchronous Motor
Authors: Ma Chi , Huang Baosheng , Basher Md Khairul , Rob Md Abdur , Jiang Yuqiang
Published: March 2024

Ensuring precise electric locomotive stopping is pivotal for achieving intelligent and unmanned auxiliary transportation systems. Currently, human drivers' expertise plays a central role in the stopping process, posing challenges for automation and cargo location accuracy, particularly in coal mining. This paper focuses on achieving accurate electric locomotive stopping under diverse conditions by utilizing permanent magnet synchronous motor-driven locomotives. This technique introduces a novel stopping control method that combines a fuzzy Proportional-Integral-Derivative (F-PID) controller and a vector control model for permanent magnet synchronous motors (PMSM). After this, we design the F-PID using the PMSM technique based on the new fuzzy rules for each sub-system. In the end, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed, which demonstrate the effectiveness of the proposed control method. From the simulation results, it confirming that the ability to achieve precise stopping under various working conditions.
Screening of Microalgae for Bioactivity with Antiviral, Antibacterial, Anti-inflammatory, and Anti-cancer Assays
Authors: Hernández-Urcera Jorge , Romero Alejandro , Cruz Pedro , Vasconcelos Vítor , Figueras Antonio , Novoa Beatriz , Rodríguez Francisco
Published: March 2024

Marine microalgae are a rich reservoir of natural compounds, including bioactives. Nonetheless, these organisms remain fairly unexplored despite their potential biotechnological applications. Culture collections with diverse taxonomic groups and lifestyles are a good source to unlock this potential and discover new molecules for multiple applications such as the treatment of human pathologies or the production of aquaculture species. In the present work extracts from 33 strains (including 20 dinoflagellates, 4 diatoms and 9 strains from other 7 algal classes), cultivated under identical conditions were examined for antiviral, antibacterial, anti-inflammatory and anti-cancer activities. Among these, antiviral and anti-inflammatory activities were detected in a few strains while antibacterial tests showed positive results in most assays. In turn, most trials did not show any anti-cancer activity. Wide differences were observed between species within the same class, in particular dinoflagellates which were better represented in this study. These preliminary findings pave the way for in-depth characterization of extracts with highest signals in each test, identification of compounds responsible of the biological activities found, and a further screening of the CCVIEO culture collection.
Advancements in DNA Barcoding: Revolutionizing Taxonomy and Biodiversity Studies
Authors: Odah Mohammad
Published: March 2024

DNA barcoding has emerged as a powerful tool in the field of taxonomy, transforming the way we identify and classify species. This review article aims to provide an up-to-date overview of the advancements in DNA barcoding techniques, their applications, and their impact on taxonomy and biodiversity studies. We will explore the evolution of DNA barcoding, the development of standardized barcode regions, and the challenges and limitations associated with this methodology. Additionally, we will delve into the diverse range of taxonomic groups for which DNA barcoding has been applied, highlighting key case studies and their contributions to our understanding of biodiversity. Furthermore, we will discuss the integration of DNA barcoding with other molecular and bioinformatic approaches, such as metabarcoding and machine learning, to enhance species identification and biodiversity assessment. This review aims to provide a comprehensive perspective on how DNA barcoding is reshaping the field of taxonomy and its implications for conservation, ecology, and evolutionary biology.
New Decomposition Models for Hourly Direct Normal Irradiance Estimations for Southern Africa
Authors: Daniel-Durandt Francisca Muriel , Rix Arnold Johan
Published: March 2024

The research develops and validates new decomposition models for DNI estimations from Southern African data. The results demonstrated improved DNI estimation accuracy compared to the baseline models across all testing and validation datasets. These outcomes suggest that utilising a localised model can significantly enhance DNI estimations for Southern Africa and potentially for developing similar models in diverse geographic regions worldwide. Furthermore, clustered models highlighted the potential advantages of grouping data based on shared geographical and climatic attributes. This clustering approach could enhance decomposition model performance, particularly when local data is limited or data is available from multiple nearby stations. The Southern African decomposition model, which encompasses a wide spectrum of climatic regions and geographic locations, exhibited notable improvements over the baseline models despite occasional overestimation or underestimation. The overall metrics affirm the substantial advancement achieved with the Southern African model. This study focused on validating the model for hourly DNI in Southern Africa within a range of clearness index-intervals from 0.175 to 0.875. Implementing accurate decomposition models in developing countries can accelerate the adoption of renewable energy sources, diminishing reliance on coal and fossil fuels.
Beyond the Double Helix: Unraveling the Intricacies of DNA and RNA Networks
Authors: Odah Mohammad
Published: March 2024

Advancements in genomics and molecular biology have propelled our understanding of genetic information far beyond the iconic double helix structure of DNA. This comprehensive review delves into the intricate world of DNA and RNA networks, exploring the complexities that extend beyond the classical model. We investigate the dynamic interactions, regulatory mechanisms, and functional implications of the broader genetic landscape, encompassing both coding and non-coding elements. From chromatin architecture to the diverse array of non-coding RNAs, this exploration seeks to provide a holistic perspective on the multifaceted roles played by DNA and RNA in cellular processes. The three-dimensional organization of genetic material within the cell has emerged as a crucial determinant of cellular function. Chromatin architecture, comprising DNA, histones, and other associated proteins, plays a dynamic role in regulating gene expression. We delve into the intricate choreography of chromatin remodeling, deciphering the interplay between transcription factors, epigenetic modifications, and higher-order structures that modulate gene activity. The exploration of chromatin dynamics unveils a nuanced understanding of how the genome responds to environmental cues, cellular signals, and developmental processes. Moreover, the once-dismissed non-coding portion of the genome has emerged as a key regulator of cellular function. Various classes of non-coding RNAs, such as microRNAs, long non-coding RNAs, and circular RNAs, have been implicated in diverse cellular processes, ranging from fine-tuning gene expression to modulating chromatin structure. The review critically examines the functional roles of these non-coding RNAs, shedding light on their involvement in cellular homeostasis, development, and disease. As I traverse this landscape beyond the double helix, our review synthesizes current knowledge on the intricacies of DNA and RNA networks. By exploring the regulatory mechanisms, functional implications, and emerging paradigms, we aim to inspire a deeper appreciation for the molecular choreography that underlies the cellular symphony of life. Furthermore, we discuss the implications of these findings in the context of disease, highlighting potential diagnostic and therapeutic avenues that arise from a comprehensive understanding of DNA and RNA networks. In doing so, this exploration not only broadens our theoretical understanding but also opens new frontiers for translational research in genetics and molecular medicine.
Software Effort Estimation using Ensemble Learning
Authors: Oshaibi M Farah , AlKhanafseh Mohammad , Surakhi Ola
Published: March 2024

Software project estimating (SPE) is a powerful but necessary step in the production of projects for software. Software project estimating includes several components, estimating software time, software resources, software costs, and software effort estimation (SEE). SEE seeks to estimate the number of "hours-person" and "months-person" of work required for developing or managing a software program. During the initial phase of the development of software, future efforts are impossible to predict. To estimate effort, many deep learning (DL) and machine learning (ML) models were previously created. For estimate, single-model techniques and ensemble methods were investigated in this research. Ensemble methods involve a combination of multiple separate models. Bagging, boosting, and voting were the ensemble methods looked into for estimation. Datasets considered for estimation were COCOMO81, COCOMONasa I, COCOMONasa II, Albrecht, Maxwell, China, Desharnais, Desharnais_1_1, Kitchenham, Boehm, and Belady. The evaluation criteria used MAE, RAE, RMSE, RRSE, and CC. The result from previous studies is that the total size of the set of data utilized is small in predicting the effort, as the largest size of the set of data used is the China dataset containing only 499 projects. So, in this study, the dataset has been merged to increase the total size of the set of data and increase the accuracy of prediction. The results indicated that the suggested merged dataset increased effort estimation accuracy.
On the Energy Dependence of the PL of RE Ions in LuBO3:RE (RE = Ce, Eu, Gd, or Tb)
Authors: Schröder Franziska , Reetz Sven , Jüstel Thomas
Published: March 2024

LuBO3 crystallizes in the calcite type (CaCO3) structure and is a widely applied inorganic host for luminescent materials and scintillators. Even though many scientific works have been published concerning the optical properties of rare earth doped LuBO3, so far, no study of the emission spectra as function of the excitation energy of such orthoborates has been conducted. Therefore, this work deals with the photoluminescence of RE doped LuBO3 with RE = Ce3+, Eu3+, Gd3+, or Tb3+, while an emphasize is laid on the energy dependence of these four luminescent compounds.
Analysis of the Combined Effect of Major Influencing Parameters for Designing High Performance Single (sBHE) and Double (dBHE) U-Tube Borehole Heat Exchangers
Authors: Kerme Esa Dube , Fung Alan S , Leong Wey H
Published: March 2024

In this paper, comprehensive analysis of combined effect of major influencing parameters on heat transfer in the single U-tube BHE (sBHE) and double U-tube BHE (dBHE) with two independent circuits was performed by using validated numerical heat transfer model. Geometrical parameters, such as shank spacing (with maximum, average and minimum values) and borehole diameter (large, medium and small borehole sizes) and borehole depth (shallow, average and deep borehole depths) as well as thermal conductivity of soil and grout which ranges from minimum to high value were considered. The combined impact of these parameters was included under four major cases: 1) combined effect of borehole depth, borehole size and shank spacing; 2) combined effect of borehole depth, and soil and grout thermal conductivity; 3) combined effect of soil and grout thermal conductivity and borehole size; and 4) combined effect of soil thermal conductivity, borehole size and shank spacing. Each of these major cases has nine different design options of both sBHE and dBHE. Series of results of heat transfer per unit borehole depth were generated for all the considered various cases. With the given parameters, the BHE case that provides highest heat transfer among the various cases of sBHE and dBHE were obtained.
DNA Damage Responses in Tumors Are Not Proliferative Stimuli but Rather They Are DNA Repair Actions Requiring Supportive Medical Care
Authors: Suba Zsuzsanna
Published: March 2024

Abstract

Background In tumors, somatic mutagenesis presumably drives DNA damage response (DDR) via altered regulatory pathways increasing genomic instability and proliferative activity. These considerations led to the standard therapeutic strategy against cancer: the disruption of mutation activated DNA repair pathways of tumors.
Purpose Justifying that cancer cells are not enemies to be killed, but rather they are ill human cells having the remnants of physiologic regulatory pathways.
Results 1. Genomic instability and cancer development may be originated from the flaw of estrogen signal rather than excessive estrogen signaling. 2. Healthy cells with genomic instability exhibit somatic mutations helping DNA restitution. 3. Somatic mutations in tumor cells aim the restoration of DNA damage rather than further genomic derangement. 4. In tumors, estrogen signal drives the pathways of DNA stabilization leading to apoptotic death. 5. In the peritumoral cellular infiltration, the genomic damage of tumor induces inflammatory cytokine secretion and increased estrogen synthesis. In the inflammatory cells, increased growth factor receptor (GFR) signal confers unliganded activation of estrogen receptors (ERs). 6. In tumor cells responsive to genotoxic therapy, constitutive mutations help the upregulation of estrogen signal and consequential apoptosis. In tumors non responsive to genotoxic therapy, the possibilities for ER activation via either liganded or unliganded pathway, are exhausted leading to farther genomic instability and unrestrained proliferation.
Conclusion Understanding the real character and behavior of human tumors at molecular level suggests that we should learn the genome repairing methods of tumors and follow them by supportive therapy rather than provoking additional genomic damages.
Multi-Dimensional Impacts of Climate Change on China’s Food Security during 2002-2021
Authors: Zhou Huanhuan , Cao Ning , Yang Lihua , Xu Jianjun
Published: March 2024

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p<0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.
The Mediterranean Diet, Its Microbiome Connections, and Cardiovascular Health: A Narrative Review”
Authors: Abrignani Vincenzo , Salvo Andrea , Tuttolomondo Antonino
Published: March 2024

Mediterranean Diet (MD), rich in minimally processed plant foods and in monounsaturated fats, but low in saturated fats, meat and dairy products, represents one of the most studied diets for cardiovascular health. It has been shown, from both observational and randomized controlled trials, that MD reduces body weight, improves cardiovascular disease surrogates such as waist-to-hip ratio, lipids, and inflammation markers, and even prevents the development of fatal and non-fatal cardiovascular disease, diabetes, obesity, and other diseases. However, it is unclear whether it offers cardiovascular benefits from its individual components or as a whole. Furthermore, limitations in the methodology of studies and meta-analyses have raised some concerns on its potential cardiovascular benefits.
MD is also associated with characteristic changes in the intestinal microbiota, mediated through its constituents. These include increased growth of species producing short-chain fatty acids, such as Clostridium leptum and Eubacterium rectale, increased growth of Bifidobacteria, Bacteroides and Faecalibacterium prausnitzii species, and reduced growth of Firmicutes and Blautia species. Such changes are known to be favorably associated with inflammation, oxidative status, and overall metabolic health.
This review will focus on the effects of MD on cardiovascular health through its action on gut microbioma.
An Improved Zero-Flowrate Switching Control Method to Reduce Switching Losses in a Hydraulic Actuator
Authors: Peng Shuang , Yin Fanglong , Hu Yong
Published: March 2024

Abstract—Hydraulic switching actuators are high efficiency, fast response, and low cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously the authors proposed a zero-flowrate switching method to reduce throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.
Stable Variable Selection Method with Shrinkage Regression Applied to the Selection of Genetic Variants Associated with Alzheimer’s Disease
Authors: Afreixo Vera , Tavares Ana Helena , Enes Vera , Pinheiro Miguel , Rodrigues Leonor , Moura Gabriela
Published: March 2024

In this work we looked for a stable and accurate procedure to perform feature selection in datasets with a much higher number of predictors than individuals, as in Genome-Wide Association Studies. Due to the instability in feature selection when many potential predictors are measured, a variable selection procedure is proposed that combines several replications of shrinkage regression models. A weighted formulation is used to define the final predictors. The procedure is applied to investigate Single Nucleotide Polymorphisms (SNPs) predictors associated to Alzheimer’s disease in the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset. Two data scenarios are investigated: one considering only the set of SNPs and another with the covariates age, sex, educational level and APOE4 genotype. The SNP rs2075650 and the APOE4 genotype are given as risk factors for AD, which is in line with the literature, and other four new SNPs are pointed, opening new hypotheses for in vivo analyses. These experiments demonstrate the potential of the new method for stable feature selection.
Systematic Development of application-oriented Operating Strategies at the Example of an Industrial Heating Supply System
Authors: Theisinger Lukas , Frank Michael , Weigold Matthias
Published: March 2024

The ongoing challenge to ensure a sustainable and affordable energy supply forces industrial companies to implement appropriate measures. These measures typically lead to an increased system complexity, which has to be addressed during operation. Whereas existing approaches from the field of supervisory and optimal control appear to be capable of mastering this issue, these are still not adopted in industry. Therefore, this work presents a procedure model for the systematic development of application-oriented operating strategies for industrial energy supply systems. The procedure model combines research approaches from the fields of sequencing control and approximate MPC to extract rule-based operating strategies. By splitting the procedure model into five phases, expert knowledge can be integrated in a target-oriented manner. Subsequently to the description, the procedure model is exemplary applied to the example of an industrial heating supply system. Throughout an optimization study, the developed operating strategy is compared to a MPC strategy as well as a baseline strategy. Whereas the conventional MPC approach is the upper bound with regard to optimality, the developed operating strategy is able to generate comparable results. Compared to the baseline strategy, a relative reduction in operating expenses of 5.4 % to 37.0 % are achieved in this specific use case.
Deep Learning for Automatic Grapevine Varieties Identification: A Brief Review
Authors: Carneiro Gabriel A. , Cunha António , Sousa Joaquim
Published: March 2024

The Eurasian grapevine (\textit{Vitis vinifera L.}) is the most widely grown horticultural crop in the world and is important for the economy of many countries. In the wine production chain, grape varieties play an important role, as they directly influence the authenticity and classification of the product. Identifying the different grape varieties is therefore fundamental for quality control and control activities, as well as for regulating production. Currently, ampelography and molecular analysis are the main approaches to identifying grape varieties. However, both methods have limitations. Ampelography is subjective and prone to errors and is experiencing enormous difficulties as ampelographers are increasingly scarce. On the other hand, molecular analyses are very demanding in terms of cost and time. In this scenario, Deep Learning (DL) methods have emerged as a classification alternative to deal with the scarcity of ampelographers and avoid molecular analyses. In this study, the most recent and current methods for identifying grapevine varieties using DL classification-based approaches are presented through a systematic literature review. The steps of the standard DL-based classification pipeline were described for the 18 most relevant studies found in the literature, highlighting their pros and cons. Potential directions for improving this field of research were also presented.
Neutrophil Elastase Degrades Histone Deacetylases and Sirtuin 1 in Primary Human Monocyte Derived Macrophages
Authors: Zheng Shuo , Bulut Gamze B. , Kummarapurugu Apparao B. , Ma Jonathan , Voynow Judith A.
Published: March 2024

Neutrophil elastase (NE) is taken up by macrophages, retains intracellular protease activity and induces a pro-inflammatory phenotype. However, the mechanism of NE-induced pro-inflammatory polarization of macrophages is not well understood. We hypothesized that intracellular NE degrades histone deacetylases (HDAC) and Sirtuins, disrupting the balance of lysine acetylation and deacetylation, and resulting in nuclear to cytoplasmic translocation of a major alarmin, High Mobility Group Box 1 (HMGB1), a pro-inflammatory response in macrophages. Human blood monocytes were obtained from healthy donors, or from subjects with cystic fibrosis (CF) or chronic obstructive pulmonary disease (COPD). Monocytes were differentiated into blood monocyte derived macrophages (BMDM) in vitro. Human BMDM were exposed to NE or control vehicle and the abundance of HDACs and Sirtuins was determined by western blotting of total cell lysates or nuclear extracts, or determined by ELISA. HDAC, Sirtuin, and Histone acetyltransferase (HAT) activities were measured. NE degraded most HDACs and Sirtuin (Sirt)1, resulting in decreased HDAC and sirtuin activities, with minimal change in HAT activity. We then evaluated whether the NE-induced loss of Sirt activity or loss of HDAC activities would alter the cellular localization of HMGB1. NE-treatment or treatment with Trichostatin A (TSA), a global HDAC inhibitor, both increased HMGB1 translocation from the nucleus to the cytoplasm, consistent with HMGB1 activation. NE significantly degraded Class I and II HDAC family members and Sirt 1 which shifted BMDM to a pro-inflammatory phenotype.