bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and experimental validation of IL-17 pathway and key genes as central roles associated with inflammation in hepatic ischemia–reperfusion injury
Authors: Tan Siyou , Lu Xiang , Chen Wenyan , Pan Bingbing , Kong Gaoyin , Wei Lai
Published: March 2024

Hepatic ischemia–reperfusion injury (HIRI) elicits an immune-inflammatory response that may result in hepatocyte necrosis and apoptosis, ultimately culminating in postoperative hepatic dysfunction and hepatic failure. The precise mechanisms governing the pathophysiology of HIRI remain incompletely understood, necessitating further investigation into key molecules and pathways implicated in disease progression to guide drug discovery and potential therapeutic interventions. Gene microarray data was downloaded from the GEO expression profile database. Integrated bioinformatic analyses were performed to identify HIRI signature genes, which were subsequently validated for expression levels and diagnostic efficacy. Finally, the gene expression was verified in an experimental HIRI model and the effect of anti-IL17A antibody intervention in three time points (including pre-ischemic, post-ischemic, and at 1 h of reperfusion) on HIRI and the expression of these genes was investigated. Bioinformatic analyses of the screened characterized genes revealed that inflammation, immune response, and cell death modulation were significantly associated with HIRI pathophysiology. CCL2, BTG2, GADD45A, FOS, CXCL10, TNFRSF12A, and IL-17 pathway were identified as key components involved in the HIRI. Serum and liver IL-17A expression were significantly upregulated during the initial phase of HIRI. Pretreatment with anti-IL-17A antibody effectively alleviated the damage of liver tissue, suppressed inflammatory factors, and serum transaminase levels, and downregulated the mRNA expression of CCL2, GADD45A, FOS, CXCL10, and TNFRSF12A. Injection of anti-IL17A antibody after ischemia and at 1 h of reperfusion failed to demonstrate anti-inflammatory and attenuating HIRI benefits relative to earlier intervention. Our study reveals that the IL-17 pathway and related genes may be involved in the proinflammatory mechanism of HIRI, which may provide a new perspective and theoretical basis for the prevention and treatment of HIRI.
The newly assembled chloroplast genome of Aeluropus littoralis: molecular feature characterization and phylogenetic analysis with related species
Authors: Ben Romdhane Walid , Al-Doss Abdullah , Hassairi Afif
Published: March 2024

Aeluropus littoralis, a halophyte grass, is widely distributed from the Mediterranean to the Indian subcontinent through the Mongolian Gobi. This model halophyte has garnered increasing attention owing to its use as forage and its high tolerance to environmental stressors. The chloroplast genomes of many plants have been extensively examined for molecular, phylogenetic and transplastomic applications. However, no published research on the A. littoralis chloroplast (cp) genome was discovered. Here, the entire chloroplast genome of A. littoralis was assembled implementing accurate long-read sequences. The entire chloroplast genome, with an estimated length of 135,532 bp (GC content: 38.2%), has a quadripartite architecture and includes a pair of inverted repeat (IR) regions, IRa and IRb (21,012 bp each), separated by a large and a small single-copy regions (80,823 and 12,685 bp, respectively). The features of A. littoralis consist of 133 genes that synthesize 87 peptides, 38 transfer RNAs, and 8 ribosomal RNAs. Of these genes, 86 were unique, whereas 19 were duplicated in IR regions. Additionally, a total of forty-six simple sequence repeats, categorized into 32-mono, four-di, two-tri, and eight-tetranucleotides, were discovered. Furthermore, ten sets of repeats greater than 20 bp were located primarily in the LSC region. Evolutionary analysis based on chloroplast sequence data revealed that A. littoralis with A. lagopoides and A. sinensis belong to the Aeluropodinae subtribe, which is a sister to the Eleusininae in the tribe Cynodonteae and the subfamily Chloridoideae. This subfamily belongs to the PACMAD clade, which contains the majority of the C4 photosynthetic plants in the Poaceae. The newly constructed A. littoralis cp genome offers valuable knowledge for DNA barcoding, phylogenetic, transplastomic research, and other biological studies.
An efficient data sheet based parameter estimation technique of solar PV
Authors: Charu K. M. , Thakur Padmanabh , Rawat Nikita , Ansari Fahim , Gupta Sandeep , Kumar Mukesh
Published: March 2024

This work develops an efficient parameter estimation technique, based on manufacturer datasheet, to obtain unknown parameter of solar photovoltaic (PV), precisely. Firstly, a nonlinear least square objective function, in terms of variables given in manufacturer datasheet, has been developed. Then, two optimization techniques, namely the Particle Swarn Optimization (PSO) and Harmony Search (HS) are applied on the developed objective function to achieve the optimized result. Further, the correctness of the developed technique is tested by estimating the performance indices, namely percentage maximum power deviation index (%MPDI) and overall model deviation index (OMDI), of two different solar PV, viz., Kyocera KD210GH-2PU (poly-crystalline), and Shell SQ85 (mono-crystalline). It is shown that developed method with PSO outperforms the HS. The developed method with PSO gives the values of %MPDI and OMDI of 0.0214% and 0.213, only. Also, the existing methods, based on hybrid, multi-objective function, numerical method, have been considered for the comparative analysis. It is revealed through the comparative studies that the developed method with PSO has smaller value of MPDI (= 0.0041%) and OMDI (0.005) than the other existing methods. Further, the convergence of the developed method has also been estimated to check the speed of estimation. It is shown that the developed technique converges only in 5 s. In addition, the developed technique avoids the need of extensive data as it is based on manufacturer datasheet.
Ferritin heavy chain supports stability and function of the regulatory T cell lineage
Authors: Wu Qian , Carlos Ana Rita , Braza Faouzi , Bergman Marie-Louise , Kitoko Jamil Z , Bastos-Amador Patricia , Cuadrado Eloy , Martins Rui , Oliveira Bruna Sabino , Martins Vera C , Scicluna Brendon P , Landry Jonathan JM , Jung Ferris E , Ademolue Temitope W , Peitzsch Mirko , Almeida-Santos Jose , Thompson Jessica , Cardoso Silvia , Ventura Pedro , Slot Manon , Rontogianni Stamatia , Ribeiro Vanessa , Domingues Vital Da Silva , Cabral Inês A , Weis Sebastian , Groth Marco , Ameneiro Cristina , Fidalgo Miguel , Wang Fudi , Demengeot Jocelyne , Amsen Derk , Soares Miguel P
Published: March 2024

Regulatory T (TREG) cells develop via a program orchestrated by the transcription factor forkhead box protein P3 (FOXP3). Maintenance of the TREG cell lineage relies on sustained FOXP3 transcription via a mechanism involving demethylation of cytosine-phosphate-guanine (CpG)-rich elements at conserved non-coding sequences (CNS) in the FOXP3 locus. This cytosine demethylation is catalyzed by the ten–eleven translocation (TET) family of dioxygenases, and it involves a redox reaction that uses iron (Fe) as an essential cofactor. Here, we establish that human and mouse TREG cells express Fe-regulatory genes, including that encoding ferritin heavy chain (FTH), at relatively high levels compared to conventional T helper cells. We show that FTH expression in TREG cells is essential for immune homeostasis. Mechanistically, FTH supports TET-catalyzed demethylation of CpG-rich sequences CNS1 and 2 in the FOXP3 locus, thereby promoting FOXP3 transcription and TREG cell stability. This process, which is essential for TREG lineage stability and function, limits the severity of autoimmune neuroinflammation and infectious diseases, and favors tumor progression. These findings suggest that the regulation of intracellular iron by FTH is a stable property of TREG cells that supports immune homeostasis and limits the pathological outcomes of immune-mediated inflammation.
SO2 capture and detection with carbon microfibers (CMFs) synthesised from polyacrylonitrile
Authors: Yañez-Aulestia Ana , López-Cervantes Valeria B. , Esparza-Schulz J. Marcos , Solis-Ibarra Diego , Ibarra Ilich A. , Cordero-Sánchez Salomón , Sánchez-González Elí , Ojeda-López Reyna
Published: March 2024

Carbon microfibers (CMFs) are low-cost and robust SO2 adsorbents, exhibiting cyclability, good SO2/CO2 selectivity, and photoluminescence response to SO2.
A neural network potential energy surface assisted molecular dynamics study on the pyrolysis behavior of two spiro-hydrocarbons
Authors: Xiao Hang , Yang Bin
Published: March 2024

Neural network molecular dynamics research reveals that the molecular structure of spiro-polycyclic hydrocarbon fuels determines the initial pyrolysis reactions as well as the subsequent combustion performance and coking behavior.
Vibrational dynamics and spectroscopy of water at porous g-C3N4 and C2N surfaces
Authors: Ojha Deepak , Penschke Christopher , Saalfrank Peter
Published: March 2024

The vibrational dynamics and (time-dependent) vSFG spectra of deuterated water molecules at g-C3N4 and C2N surfaces have been studied using DFT-based AIMD simulations.
Recent progress in 2D and 3D metal–organic framework-based membranes for water sustainability
Authors: Banglani Talib Hussain , Chandio Imamdin , Ali Akbar , Memon Ayaz Ali , Yang Jun , Kazi Mohsin , Thebo Khalid Hussain
Published: March 2024

Metal–organic frameworks (MOFs) have emerged as promising candidates for high-performance separation processes due to their desirable porous structure and highly tunable properties.
Design of S, N-codoped Co–Fe dual-atom sites for efficient alkaline oxygen reduction
Authors: He Ning , Sun Yuanmiao , Chen Xiaoyang , Wang Jiaqi , Liang Guojin , Mo Funian
Published: March 2024

Employing atomic interface tuning enhances diatomic catalysts. We rationally designed and synthesized Co–Fe dual-atom sites on S, N-codoped carbon, demonstrating exceptional electrocatalytic activity for the oxygen reduction reaction.
Correction: An optical sensor for the sensitive determination of formaldehyde gas based on chromotropic acid and 4-aminoazobenzene immobilized in a hydrophilic membrane
Authors: Fernández-Ramos M. D. , Moraga-Cabezas A. , Medina-Castillo Antonio L. , Capitán-Vallvey L. F.
Published: March 2024

Correction for ‘An optical sensor for the sensitive determination of formaldehyde gas based on chromotropic acid and 4-aminoazobenzene immobilized in a hydrophilic membrane’ by M. D. Fernández-Ramos et al., Analyst, 2023, 148, 4533–4538, https://doi.org/10.1039/D3AN01056B.
A novel B,O,N-doped mesogen with narrowband MR-TADF emission
Authors: Knöller Julius A. , Sönmez Burcu , Matulaitis Tomas , Gupta Abhishek Kumar , Zysman-Colman Eli , Laschat Sabine
Published: March 2024

Modification of a MR-TADF core with mesogenic units allowed for the design a liquid crystal exhibiting narrowband sky-blue MR-TADF and self-assembly in a columnar mesophase.
Distribution of basal plane dislocations in 4-degree off-axis 4H-SiC single crystals
Authors: Lu Sheng'ou , Xu Binjie , Wang Yazhe , Chen Hongyu , Hang Wei , Wang Rong , Yuan Julong , Pi Xiaodong , Yang Deren , Han Xuefeng
Published: March 2024

The basal plane slip model in 4H-SiC was developed to investigate the effects of off-axis angles on total resolved shear stress. The results showed that the TRSS changed from 6-fold to 4-fold symmetry with the increasing off-axis angles.
Recent progress in the advanced strategies, rational design, and engineering of electrocatalysts for nitrate reduction toward ammonia
Authors: Shafiq Faiza , Yang Lei , Zhu Weihua
Published: March 2024

Electrocatalytic nitrate reduction to ammonia offers a sustainable pathway for the synthesis of ammonia, its modular design and versatility make it suitable for addressing environmental nitrate pollution and sustainable nitrogen management.
Inducing ring distortions in unsubstituted metallophthalocyanines using axial N-heterocyclic carbenes
Authors: Kidd Steven R. , Zhou Wen , Warren Jeffrey J. , Leznoff Daniel B.
Published: March 2024

Ring-unsubstituted metallophthalocyanines with N-heterocyclic carbenes are soluble in a variety of solvents. The axial NHC ligands generate ruffle and dome-type distorted Pc-rings, with very prominent deformations in the di-axially substituted PcFeII.
Correction: Acridine-based copper(i) PNP pincer complexes: catalysts for alkyne hydroboration and borylation of aryl halides
Authors: Olding Angus , Lucas Nigel. T. , Ho Curtis C. , Bissember Alex C.
Published: March 2024

Correction for ‘Acridine-based copper(i) PNP pincer complexes: catalysts for alkyne hydroboration and borylation of aryl halides’ by Angus Olding et al., Dalton Trans., 2024, 53, 4471–4478, https://doi.org/10.1039/D3DT04269C.
A perspective on renewable production of amino acids from biomass through the chemocatalytic method
Authors: Ding Maofeng , Song Song , Li Xingang
Published: March 2024

This perspective showcases recent advances in amino acid synthesis from biomass through the chemocatalytic method.
Effect of in-plane and out-of-plane bifurcated microfluidic channels on the flow of aggregating red blood cells
Authors: Gholivand Amirreza , Korculanin Olivera , Dahlhoff Knut , Babaki Mehrnaz , Dickscheid Timo , Lettinga Minne Paul
Published: March 2024

Taking microfluidics to the third dimension causes scrambling of memory effects in blood flow due to out-of-plane vessel structures.
Multi-stimuli-responsive polymer degradation by polyoxometalate photocatalysis and chloride ions
Authors: Gu Chen , Li Chifeng , Minezawa Noriyuki , Okazaki Susumu , Yamaguchi Kazuya , Suzuki Kosuke
Published: March 2024

By utilizing the photocatalysis of a polyoxometalate, [γ-PV2W10O40]5−, we developed a system for multiple-stimuli-responsive polymer degradation that allows degradation of various polymers when multiple stimuli, specifically, light and Cl−, are present.
Electrochemical conversion of 5-hydroxymethylfurfural over CuNi bimetallic catalysts: the synergistic effect of interfacial active sites
Authors: Zhao Yiwei , Zhang Chao , Xing Shuangxi , Jin Zuhang , Xiao Tingting
Published: March 2024

ECO of HMF to FDCA and ECR to BHMF with high yield have been studied on CuNi-based bimetallic catalysts. The presence of the Cu–O–Ni interfacial area was beneficial for promoting the catalytic performance in ECO.
sp2–sp cross-carbanion coupling at a rare-earth center leading to the formation of carbon–carbon double bonds
Authors: Chai Zhengqi , Lv Ze-Jie , Liu Wei , Yang Jinxiao , Wei Junnian , Zhang Wen-Xiong
Published: March 2024

The reaction of rare-earth azametallacyclopentadienes with terminal alkynes provides rare-earth metallacycles with cumulated double bonds in three steps: alkynyl C–H bond activation, sp2–sp cross-carbanion coupling and subsequent isomerization.
Correction and Removal of Expression of Concern: Highly stereoselective gram scale synthesis of all the four diastereoisomers of Boc-protected 4-methylproline carboxylates
Authors: Sun Kehuan , Tao Cheng , Long Bohua , Zeng Xiaobin , Wu Zhengzhi , Zhang Ronghua
Published: March 2024

Correction and Removal of Expression of Concern for ‘Highly stereoselective gram scale synthesis of all the four diastereoisomers of Boc-protected 4-methylproline carboxylates’ by Kehuan Sun et al., RSC Adv., 2019, 9, 32017–32020, DOI: https://doi.org/10.1039/C9RA06827A.
The deubiquitinase function of ataxin-3 and its role in the pathogenesis of Machado-Joseph disease and other diseases
Authors: Potapenko Anastasiya , Davidson Jennilee M. , Lee Albert , Laird Angela S.
Published: March 2024

Machado-Joseph disease (MJD) is a devastating and incurable neurodegenerative disease characterised by progressive ataxia, difficulty speaking and swallowing. Consequently, affected individuals ultimately become wheelchair dependent, require constant care, and face a shortened life expectancy. The monogenic cause of MJD is expansion of a trinucleotide (CAG) repeat region within the ATXN3 gene, which results in polyglutamine (polyQ) expansion within the resultant ataxin-3 protein. While it is well established that the ataxin-3 protein functions as a deubiquitinating (DUB) enzyme and is therefore critically involved in proteostasis, several unanswered questions remain regarding the impact of polyQ expansion in ataxin-3 on its DUB function. Here we review the current literature surrounding ataxin-3's DUB function, its DUB targets, and what is known regarding the impact of polyQ expansion on ataxin-3's DUB function. We also consider the potential neuroprotective effects of ataxin-3's DUB function, and the intersection of ataxin-3's role as a DUB enzyme and regulator of gene transcription. Ataxin-3 is the principal pathogenic protein in MJD and also appears to be involved in cancer. As aberrant deubiquitination has been linked to both neurodegeneration and cancer, a comprehensive understanding of ataxin-3's DUB function is important for elucidating potential therapeutic targets in these complex conditions. In this review, we aim to consolidate knowledge of ataxin-3 as a DUB and unveil areas for future research to aid therapeutic targeting of ataxin-3's DUB function for the treatment of MJD and other diseases.
Hearing and Functioning in Everyday Life Questionnaire: Psychometric Evaluation and Revision
Authors: Karlsson Elin , Manchaiah Vinaya , Mäki-Torkko Elina , Granberg Sarah , Gustafsson Johanna , Dahlström Örjan , Widén Stephen
Published: March 2024

Purpose:

The aim of the current study was to explore the construct validity and internal consistency reliability of the International Classification of Functioning, Disability and Health (ICF)–based original English version of the Hearing and Functioning in Everyday Life Questionnaire (HFEQ) and to revise the HFEQ based on the results.

Method:

This study used a cross-sectional survey design. The data were collected using an online survey. Adults with self-reported hearing disability (
n
= 513) from the United States were included. The ICF components of body functions, activity and participation, and environmental factors were tested as the underlying structure of the HFEQ using confirmatory factor analysis and then adjusted by triangulation with previous content validation.

Results:

The results of the current study confirmed the ICF components of body functions, activity and participation, and environmental factors as underlying constructs of the HFEQ. However, after triangulation with previous content validation, fine adjustments were made. The revised version of the HFEQ includes two removed items and a fine-tuned factor structure.

Conclusion:

The results confirm that the structure of the HFEQ aligns with the ICF, and the overall results indicate that HFEQ has acceptable construct validity and internal consistency.
Cross‐Project Defect Prediction Using Transfer Learning with Long Short‐Term Memory Networks
Authors: Tao Hongwei , Fu Lianyou , Cao Qiaoling , Niu Xiaoxu , Chen Haoran , Shang Songtao , Xian Yang
Published: March 2024

With the increasing number of software projects, within‐project defect prediction (WPDP) has already been unable to meet the demand, and cross‐project defect prediction (CPDP) is playing an increasingly significant role in the area of software engineering. The classic CPDP methods mainly concentrated on applying metric features to predict defects. However, these approaches failed to consider the rich semantic information, which usually contains the relationship between software defects and context. Since traditional methods are unable to exploit this characteristic, their performance is often unsatisfactory. In this paper, a transfer long short‐term memory (TLSTM) network model is first proposed. Transfer semantic features are extracted by adding a transfer learning algorithm to the long short‐term memory (LSTM) network. Then, the traditional metric features and semantic features are combined for CPDP. First, the abstract syntax trees (AST) are generated based on the source codes. Second, the AST node contents are converted into integer vectors as inputs to the TLSTM model. Then, the semantic features of the program can be extracted by TLSTM. On the other hand, transferable metric features are extracted by transfer component analysis (TCA). Finally, the semantic features and metric features are combined and input into the logical regression (LR) classifier for training. The presented TLSTM model performs better on the f‐measure indicator than other machine and deep learning models, according to the outcomes of several open‐source projects of the PROMISE repository. The TLSTM model built with a single feature achieves 0.7% and 2.1% improvement on Log4j‐1.2 and Xalan‐2.7, respectively. When using combined features to train the prediction model, we call this model a transfer long short‐term memory for defect prediction (DPTLSTM). DPTLSTM achieves a 2.9% and 5% improvement on Synapse‐1.2 and Xerces‐1.4.4, respectively. Both prove the superiority of the proposed model on the CPDP task. This is because LSTM capture long‐term dependencies in sequence data and extract features that contain source code structure and context information. It can be concluded that: (1) the TLSTM model has the advantage of preserving information, which can better retain the semantic features related to software defects; (2) compared with the CPDP model trained with traditional metric features, the performance of the model can validly enhance by combining semantic features and metric features.
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
Authors: Zhang Hengmin , Yang Jian , Zhang Bob , Tang Yang , Du Wenli , Wen Bihan
Published: March 2024

An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data. Its versatility enables its application to various clustering problems, making it a valuable contribution to unsupervised learning tasks. To optimise the proposed model, the authors have developed an efficient algorithm that utilises the standard Sylvester equation to compute the coefficient matrix. By setting the derivatives to zero, computational efficiency is maintained without compromising accuracy. Additionally, the authors have introduced smoothing strategies to make the non‐convex and non‐smooth terms differentiable. This enables the use of an alternative iteration re‐weighted procedure (AIwRP), which distinguishes itself from other first‐order optimisation algorithms by introducing auxiliary variables. The authors provide a provable convergence analysis of AIwRP based on the iteration procedures of unconstrained problems to support its effectiveness. Extensive numerical tests have been conducted on synthetic and benchmark databases to validate the superiority of their approaches. The results demonstrate improved clustering performance and computational efficiency compared to several existing spectral clustering methods, further reinforcing the advantages of their proposed framework. The source code is available at https://github.com/ZhangHengMin/LGR_LSRLRR.
Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction
Authors: Wang Xiang , Liu Hanzhong , Zhang Lei , Gao Yang , Wu Yifei
Published: March 2024

A dual‐motor servo mechanism is a high‐order and strong‐coupling system with unknown nonlinearity, which brings challenges to controller design to realize high‐performance tracking and synchronization. This article proposes a finite‐time command filtered control strategy to address this problem. In tracking control design, finite‐time command filters are adopted to obtain the derivatives of virtual controllers, and the “explosion of complexity” problem in backstepping is thus solved. An improved compensation system is designed to reduce filtering errors. The tracking control is developed based on the combination of finite‐time control and command filtered approach. Moreover, to deal with unknown nonlinearities and uncertainties, fast finite‐time extended state observers are developed to observe lumped disturbances for the load and motor, respectively. In synchronization control design, two opposite control actions are developed using the speed difference to force two motors to rotate synchronously. The finite‐time convergence of the tracking and synchronization errors is proved. The efficiency of the proposed control strategy is verified via experiments conducted on a dual‐motor servo turntable.
Mitigation of limitation imposed on hosting capacity in low voltage networks by their distribution transformer loading and degradation considerations
Authors: Ame‐Oko Agaba , Lavrova Olga
Published: March 2024

A distribution transformer's thermal operating conditions can impose a limitation on the Hosting Capacity (HC) of an electrical distribution feeder for PV interconnections in the feeder's low‐voltage network. This is undesirable as it curtails PV interconnection of both residential and commercial customers in the secondary networks at a time when there are record numbers of interconnection requests by utilities' customers. The authors analyse the limitations on HC due to transformer loading and degradation considerations. Then, the paper proposes a battery energy storage system (BESS) dispatch strategy that will mitigate the limitation on distribution feeder HC by distribution transformers. Three scenarios of HC were simulated for a test network—HC evaluation without restrictions by the distribution transformer (scenario 1), HC evaluation with restrictions by the distribution transformer (scenario 2), and HC evaluation without restriction by the distribution transformer, and with the implementation of the proposed BESS mitigation strategy (scenario 3). Simulation results show that transformer lifetime is depleted to about 6% of expected lifetime for unrestricted HC in scenario 1. Curtailing the HC by 32% in scenario 2 improves the lifetime to 149% of expected lifetime. Implementing the proposed BESS in scenario 3 improves the transformer lifetime to 127% and increases the HC by 62% above the curtailed value in scenario 2, and by 10% above the original HC in scenario 1. The BESS strategy implementation produced cost savings of 49% and 27% of the transformer cost in scenarios 2 and 3, respectively, due to deferred transformer replacement. Conversely, there is a 1600% replacement cost incurred in scenario 1, which underscores the need for a mitigation strategy. The proposed BESS strategy does not only improve the HC of a distribution feeder but also increases a distribution transformer's lifetime leading to replacement cost savings.
Probing the inner Galactic halo with blue horizontal-branch stars
Authors: Culpan R. , Dorsch M. , Geier S. , Pelisoli I. , Heber U. , Kubátová B. , Cabezas M.
Published: March 2024

Context. Stars that are found on the blue horizontal-branch (BHB) evolved from low-mass stars that have completed their core hydrogen-burning main sequence (MS) stage and undergone the helium flash at the end of their red giant phase. Hence, they are very old objects that can be used as markers in studying galactic structure and formation history. The fact that their luminosity is virtually constant at all effective temperatures also makes them good standard candles.

Aims. We have compiled a catalogue of BHB stars with stellar parameters calculated from spectral energy distributions (SEDs) constructed using data from multiple large-scale photometric surveys. In addition, we update our previous Gaia Early Data Release 3 (EDR3) catalogue of BHB stars with parallax errors less than 20% by using the SED results to define the selection criteria. The purpose of these catalogues is to create a set of BHB star candidates with reliable stellar parameters. In addition, they provide a more complete full-sky catalogue with candidate objects found along the whole BHB from where RR-Lyrae are found on the instability strip to the extreme horizontal-branch (EHB).

Methods. We selected a large dataset of Gaia Data Release 3 (DR3) objects based only on their position on the colour-magnitude diagram (CMD), along with the tangential velocity and parallax errors. The SEDs were then used to evaluate contamination levels in the dataset and derive optimised data quality acceptance constraints. This allowed us to extend the Gaia DR3 colour and absolute magnitude criteria further towards the EHB. The level of contamination found using SED analysis was confirmed by acquiring spectra using the Ondrejov Echelle spectrograph, attached to the Perek 2m telescope at the Astronomical Institute of the Czech Academy of Sciences.

Results. We present a catalogue of 9172 Galactic halo BHB candidate stars with atmospheric and stellar parameters calculated from synthetic SEDs. We also present an extended Gaia DR3-based catalogue of 22 335 BHB candidate stars with a wider range of effective temperatures and Gaia DR3 parallax errors of less than 20%. This represents an increase of 33% compared to the our 2021 catalogue, with a contamination level of 10%.
Preferential acceleration of heavy ions in magnetic reconnection: Hybrid-kinetic simulations with electron inertia
Authors: Jain Neeraj , Büchner Jörg , Bárta Miroslav , Bučík Radoslav
Published: March 2024

Context. Solar energetic particles (SEPs) in the energy range 10 s KeV nucleon−1–100s MeV nucleon−1 originate from the Sun. Their high flux near Earth may damage the space-borne electronics and generate secondary radiation that is harmful for life on Earth. Thus, understanding their energization on the Sun is important for space weather prediction. Impulsive (or 3He-rich) SEP events are associated with the acceleration of charge particles in solar flares by magnetic reconnection and related processes. The preferential acceleration of heavy ions and the extraordinary abundance enhancement of 3He in the impulsive SEP events are not understood yet.

Aims. In this paper we study the acceleration of heavy ions and its consequences for their abundance enhancements by magnetic reconnection, an established acceleration source for impulsive SEP events in which heavy-ion enhancement is observed

Methods. We employed a two-dimensional hybrid-kinetic plasma model (kinetic ions and inertial electron fluid) to simulate magnetic reconnection. All the ion species are treated self-consistently in our simulations.

Results. We find that heavy ions are preferentially accelerated to energies many times higher than their initial thermal energies by a variety of acceleration mechanisms operating in reconnection. The most efficient acceleration takes place in the flux pileup regions of magnetic reconnection. Heavy ions with sufficiently low values of charge-to-mass ratio (Q/M) can be accelerated by pickup mechanism in outflow regions even before any magnetic flux is piled up. The energy spectra of heavy ions develop a shoulder-like region, a nonthermal feature, as a result of the acceleration. The spectral index of the power-law fit to the shoulder region of the spectra varies approximately as (Q/M)−0.64. The abundance enhancement factor, defined as the number of particles above a threshold energy normalized to the total number of particles, scales as (Q/M)−α, where α increases with the energy threshold. We discuss our simulation results in the light of the SEP observations.
22Ne distillation and the cooling sequence of the old metal-rich open cluster NGC 6791
Authors: Salaris Maurizio , Blouin Simon , Cassisi Santi , Bedin Luigi R.
Published: March 2024

Recent Monte Carlo plasma simulations carried out to study the phase separation of 22Ne in crystallizing carbon-oxygen (CO) white dwarfs (WDs; the most abundant metal after carbon and oxygen) have shown that, under the right conditions, a distillation process that transports 22Ne towards the WD centre is efficient and releases a considerable amount of gravitational energy. This can lead to cooling delays of up to several Gyr. Here we present the first CO WD stellar evolution models that self-consistently include the effect of neon distillation and cover the full range of CO WD masses for a twice-solar progenitor metallicity, which is appropriate for the old open cluster NGC 6791. The old age (about 8.5 Gyr) and high metallicity of this cluster – and hence the high neon content (about 3% by mass) in the cores of its WDs – maximize the effect of neon distillation in the models. We discuss the effect of distillation on the internal chemical stratification and cooling time of the models, confirming that distillation causes cooling delays of up to several Gyr that depend in a non-monotonic way on the mass. We also show how our models produce luminosity functions (LFs) that can match the faint end of the observed WD LF in NGC 6791, for ages consistent with the range determined from a sample of cluster eclipsing binary stars and the main sequence turn-off. Without the inclusion of distillation, the theoretical WD cooling sequences reach magnitudes that are too faint compared to observations. We also propose James Webb Space Telescope observations that would independently demonstrate the efficiency of neon distillation in the interiors of NGC 6791 WDs and help resolve the current uncertainty on the treatment of the electron conduction opacities for the hydrogen-helium envelope of WD models.
Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network
Authors: Ramesh Babu T.S. , Thangamani K. , Kishore Mendu Jugal , Guru Jawahar J. , Pavan Kumar D. , Garigipati Satish , Maksudovna Khristina
Published: March 2024

The current research work is mainly concentrated on the mechanical properties concrete blended with marble stone power resulted from waste sludge marble processing it has a high specific area. M25 grade concrete mix design was considered for this research work. The mechanical properties of concrete i.e. compressive strength, unit weight, splitting tensile strength, modulus of elasticity and flexural strength were considered for the study. The compressive strength of these mixes was measured on 150mm ×150mm × 150mm cubes and tension test split tensile test 150 mm dia × 300 mm height cylinders. The concrete unit weight was considered for calculating the elastic modulus of concrete. The investigational values were matched with ACI, CEB-FIP, BIS and AASHTO LRFD empirical equation and regression analysis was done. The empirical equation result was compared with regression analysis of Artificial Neural Network, and conclusion was brough down that regression analysis of artificial neural network had better prediction than that of above-mentioned empirical equations. The study concluded that 15% replacement of marble power attained highest strength and optimum replacement, 25% replacement was concluded as economical replacement to attain designed strength.
Effect of ECAP process on deformability, microstructure and conductivity of AA5083 under thermal effect
Authors: Singh Nagendra , Kumar Agrawal Manoj
Published: March 2024

An alternate method of alloying is to use extreme plastic deformation on commercially available AA5083 to generate an ultrafinegrained microstructure. The objective of this approach is to improve mechanical characteristics without sacrificing corrosion resistance and biocompatibility. Anisotropy in mechanical properties is introduced by plastic deformation leading to the production of a distinct texture. This is a crucial concept to understand in order to build and model structural devices and components from a perspective based approach. The ultrafine-grained structure of AA5083, which was obtained by equal channel angular pressing, is examined in this work. Ex-situ and indirect in-situ thermal studies are used to supplement this investigation while the material is heat treated at different annealing temperatures. The results show that the elastic properties undergo very small change during the annealing process, in contrast to other parameters as thermal expansion, internal friction, or hardness. The strong relationship between the elastic anisotropy and texture highlights the importance and possibilities of using texture into the design and customization of mechanical characteristics. Pure deforms plastically in order to improve mechanical qualities while maintaining biocompatibility and corrosion resistance. Analysis of the materials elastic inhomogeneity and crunchiness in detail. In comparison to other characteristics like as inner conflict thermal enlargement or hardness, the results demonstrate that elastic properties barely marginally change during annealing. The microstructure fragmentation had no influence on the conductivity of the AA5083, which oscillated at 18 MS/m after the ECAP procedure. According to the findings, all deformed specimens strain hardening exponent and capacity were lower than they were in their as-received state. Investigated was the effect of size of grains on the strain hardening comportment of the ECAPed AA5083.
Harmony in HR: Exploring the Synergy of Artificial Intelligence and Green Practices for Sustainable Workplaces”
Authors: Suryanarayana Reddy M.R.S. , Deepthi Sajja , Bhattaru Sarathsimha , Srilakshmi V. , Singh Harminder
Published: March 2024

This study investigates the pivotal role of Artificial Intelligence (AI) in the implementation and enhancement of Green Human Resource Management (GHRM) practices within contemporary organizations. Recognizing the imperative for businesses to align with sustainable principles, the research explores how AI technologies contribute to the adoption and optimization of eco-friendly initiatives in the realm of human resource management. The study delves into specific AI applications, such as predictive analytics, machine learning algorithms, and data-driven decision-making, to elucidate how these technologies can assist in identifying, recruiting, and nurturing environmentally conscious talent. Furthermore, the research investigates the potential of AI to streamline HR processes, reduce resource wastage, and foster a corporate culture committed to environmental sustainability. Through a comprehensive analysis of case studies and empirical evidence, this study aims to elucidate the practical implications, benefits, and challenges associated with integrating AI into GHRM practices. Saving the environment should be a top priority for every company. The majority of companies, however, do not prioritize eco-friendly policies and procedures these days. Making a profit and competing are their only concerns. Because of this, abandoning the organization's dedication and to environmental protection becomes its biggest drawback. However, there are groups who make it their mission to encourage eco-friendliness and green activities. In this research, we look at how green HRM is affected by several eco-friendly strategies.
Pro-tech head protector
Authors: Shivaprasad Doma , Surendar Medipally , Srinivas S. , Satyaveni Oleti , Kavya Chokkampeta , Rao Gundavarapu Mallikarjuna , Usanova Kseniia Iurevna
Published: March 2024

Solar-based E-Uniform furnished with better protection to the soldiers who are working in extreme weather. Solar Panels are wont to power up the interior circuitry of the E-uniform. A 12 V DC lead-acid rechargeable battery is employed for storing the energy. We are using a conventional battery charging unit also for giving supply to the circuitry. ATmega16a microcontroller is the heart of the circuit as it controls all the functions. The project is operated in two modes like summer mode and winter mode. By selecting the mode of operation, we are operating the system such that it can drive the body temperature according to heater/cooler. The heater/cooler in turn will help us to provide a cooling or warming effect inside the uniform which helps the soldier to bear any kind of external environment. The metal sensor will detect the metal-like bomb, any other planted weapon in-ground and intimate the soldier with a buzzer indication. The GSM is interfaced with the microcontroller and GPS is additionally interfaced such that the tracking of the whole soldier is observed. And the location is messaged to the particular concerned person /dept. This Uniform will make the soldier work in any kind of environment without any stress or distraction.
Cloud Verse: Mapping the new frontiers of cloud computing
Authors: Bommala Harikrishna , Harshith Tej Doli , Ramesh Katravath , Sahil Md , Siri Dharmapuri , Iurevna Usanova Kseniia
Published: March 2024

The endeavors to explore and map the dynamic terrain of cloud computing, designated as the CloudVerse. Through a meticulous examination of recent advancements and emerging patterns in cloud technologies, this study aims to furnish a comprehensive portrayal of the present state and future trajectories of cloud computing. Utilizing a blend of literature review and industry scrutiny, the paper identifies pivotal domains of innovation within the CloudVerse, encompassing hybrid cloud infrastructures, serverless computing models, edge computing paradigms, and AI-driven cloud solutions. Furthermore, it delves into the ramifications of these advancements across diverse sectors and deliberates on strategic imperatives for enterprises embracing cloud technologies. Ultimately, this inquiry strives to demarcate the contours and potentials inherent in the CloudVerse, proffering nuanced insights for navigating the intricacies of contemporary cloud computing landscapes.
Zone-II & III: Machine Learning based Rice Yield Prediction in Andhra Pradesh
Authors: Ramisetty Sowjanya , Bansode Devdas , Atmakur Vijay Kumar , Ghantasala Gnanasudha Pradeep , Ushasree D. , Kumar Manish
Published: March 2024

In a unique approach, this research predicts rice yield in Zones II and III of Andhra Pradesh using machine learning algorithms. Because food security and agricultural sustainability are becoming more and more important, an accurate assessment of crop yields is necessary for agricultural planning and decision-making. By using machine learning approaches, we hope to develop robust prediction models that can forecast rice yields depending on a variety of agronomic and environmental conditions. Our plan includes collecting a lot of data on variables such as soil qualities, weather patterns, crop management practices, and historical yield records from the target regions. Using careful feature engineering and data preprocessing, we find relevant predictors and derive significant insights for rice yield estimation. Next, we employ state-of-the-art machine learning methods, like Support Vector Machines, Random Forest, and Gradient Boosting, to build trustworthy prediction models. These models are trained on historical data and then cross-validated to guarantee accuracy and generalizability. Our goal is to combine domain expertise in agriculture with cutting-edge machine learning techniques to provide farmers, policymakers, and other agricultural stakeholders with insightful understandings of the dynamics of rice production. In Zones II and III of Andhra Pradesh, this will make it easier to allocate resources and make improve agricultural output and well-informed decisions sustainability.
Personalizing the E-Commerce – Experience: A Recommendation System
Authors: Lakshmi Kanth Mangalagiri , Abdul Mujeeb Mohd , Harshitha Manda , Rajinesh Chennoju , Madhu Bhukya , Vijendar Reddy G. , Sobti Rajeev
Published: March 2024

You In the fiercely competitive landscape of the E-Commerce industry, the significance of Personalization cannot be overstated when it comes to retaining customers and bolstering revenue streams. Employing a recommendation system proves to be a highly efficacious strategy for achieving this personalization objective, as it furnishes users with pertinent product suggestions tailored to their preferences and behaviors. The focal point of this project is the development of a recommendation system tailored for an E-commerce platform, poised to elevate user experiences and amplify sales. Our methodology involves a comprehensive analysis of user data coupled with the application of machine learning algorithms, all aimed at refining and optimizing the recommendation engine. The findings from our project unveil a marked advancement in both user engagement and conversion rates. Rigorous testing has underscored the substantial efficacy of personalized recommendations in reinforcing the competitive edge of E-commerce platforms. As the demand for personalized interactions continues to rise among consumers, our system is dedicated to delivering a seamless and customized shopping experience, fostering customer loyalty, and propelling sustainable business growth.
Image reconstruction techniques using deep learning quality segmentation
Authors: Rajya Lakshmi Adidela , Suresh Sara , Mutalik Desai Prashanth , Aerranagula Veerender , Mounika N. , Kaur Namita
Published: March 2024

Translational CT (TCT), in developing nations, a low-end computed tomography (CT) technology are relatively common. The limited-angle TCT scanning mode is often used with large-angle scanning to scan items within a narrow angular range, reduce X-ray radiation, scan long objects, and prevent detector discrepancies.. However, this scanning mode greatly reduces the picture quality and diagnostic accuracy due to the added noise and limited-angle distortions. A U-net convolutional neural network-based approach for limited-angle TCT image reconstruction has been created to reconstruct a high-quality image for the limited-angle TCT scanning mode (CNN). The limited-angle TCT projection data are first examined using the SART method, and the resulting picture is then fed into a trained CNN that can reduce artifacts and maintain structures to provide a better reconstructed image. Simulated studies are used to demonstrate the effectiveness of the algorithm designed for the limitedangle TCT scanning mode. In contrast to certain modern techniques, the developed algorithm considerably lowers noise and limited-angle artifacts while maintaining image structures.
A brain tumor identification using convolution neural network and fully convolution neural network
Authors: Mruthyunjaya  , Mandala Suresh Kumar
Published: March 2024

Brain tumor identification, along with an investigation, is harmful to the patient. Segmentation, therefore, of paying attention to near-neighborhood growth remains accurate, effective, and healthy. Fully Convolution Neural Network (FCNN) is a reliable picture model to capitulate the hide quality. The form of the multifaceted with the incessant pixels taught with the crest state and the symbolic picture taught. In this research, the making of a totally convoluted method to obtain the participation of a random element and the production of correspondingly large-scale output with a resourceful assumption and information.. The approach has had several difficulties, as measurements are accurate for a variety of images. The improvement in the mortality rate of the programmed order is a critical condition. The scheduling of the mind tumor is an exceedingly troublesome task in the exceptional spatial and basic fluctuation that accompanies the local brain tumor. In this research, a programmed detection of Brain tumors proposed using the characterization of CNN. The most critical method of construction is the completion of the use of small holes. CNN's has less predictability and 97.5 accuracies.