bluuebunny/crossref_metadata_2025 huggingface dataset:
The Future of Strikes and Trade Unions
Authors: van der Velden Sjaak
Published: November 2024

In early modern times, workers, especially the unskilled, in many countries were already striking against low wages and long working hours before the advent of the trade union movement. These modern trade unions on the other hand were mainly a form of organization invented by skilled labor from around 1800. Trade unions became a part of the labor movement or the workers’ movement. For over a century the movement of the workers and the workers’ movement merged although this marriage was not always a very happy one. There have been periods of tensions between the two. Since the crisis of the 1970s both have been on the defensive, which can be seen from lowering union density rates and the plummeting of strike activity in most Western countries.

Many trade unions have been connected to the political part of the labor movement (more specifically social democracy) which in turn grew into the existing political and socioeconomic form of capitalism.1 Can a bureaucratic trade union movement that is so embedded in capitalist society be able to become the advocate of a future rise of working-class struggles? Is there a future for trade unionism or will another form of organization arise? And will the strike as a weapon of the working class really disappear as was predicted so many times? And was there a moment in time when both strikes and trade unions took the path that took them into the dangerous direction where they ended up in such life-threatening circumstances. Let’s go back in time to look for answers to these questions.
Tracking the non-breeding range of Rapa Shearwater Puffinus myrtae, a Critically Endangered seabird of the South Pacific Ocean
Authors: Jiguet Frédéric , Thibault Jean-Claude , Dufour Paul , Withers Tehani
Published: November 2024

We report the non-breeding range of an adult Rapa Shearwater Puffinus myrtae, as estimated from data collected by one light logger deployed from 31 August 2019 to 22 July 2020. The Rapa Shearwater is classified as “Critically Endangered”, with a strong decline in breeding numbers reported recently. As the species is threatened by various introduced mammals on the breeding colonies, the main objective of this tracking essay was to identify the oceanic regions where the birds forage during the non-breeding season. The non-breeding range of this bird was located south-east of Rapa Island, where fishery activities are limited. The conservation efforts for the Critically Endangered Rapa Shearwater should first focus on securing mammal-free sites for breeding colonies.
QUASI-ERGODICITY OF COMPACT STRONG FELLER SEMIGROUPS ON
$L^2$
Authors: Kaleta Kamil , Schilling René L.
Published: November 2024

We study the quasi-ergodicity of compact strong Feller semigroups
$U_t$
,
$t> 0$
, on
$L^2(M,\mu )$
; we assume that M is a locally compact Polish space equipped with a locally finite Borel measue
$\mu $
. The operators
$U_t$
are ultracontractive and positivity preserving, but not necessarily self-adjoint or normal. We are mainly interested in those cases where the measure
$\mu $
is infinite and the semigroup is not intrinsically ultracontractive. We relate quasi-ergodicity on
$L^p(M,\mu )$
and uniqueness of the quasi-stationary measure with the finiteness of the heat content of the semigroup (for large values of t) and with the progressive uniform ground state domination property. The latter property is equivalent to a variant of quasi-ergodicity which progressively propagates in space as
$t \uparrow \infty $
; the propagation rate is determined by the decay of . We discuss several applications and illustrate our results with examples. This includes a complete description of quasi-ergodicity for a large class of semigroups corresponding to non-local Schrödinger operators with confining potentials.
Pre-breeding highlights of intraspecific polymorphism and genetic estimates of seed traits of African yam bean (Sphenostylis stenocarpa Hochst Ex. A. Rich.) Harms breeding lines
Authors: Adewale Daniel B. , Ibiloye Rachael M. , Odetoye Adefunke A. , Paul Marvelous U. , Ojo Grace A. , Ogundare Emmanuel B. , Fasaanu Abosede O. , Aribilola Esther O.
Published: November 2024

Discriminatory morpho-metric features are obvious on legume seeds. This study utilized seven quantitative and 11 qualitative seed traits to characterize 139 African yam bean (AYB) breeding lines which were developed through single seed descent procedure. The seven quantitative data were subjected to analysis of variance, their means were combined with qualitative scores for genetic distance, principal component (PC) and clustering analyses. Significant (P ≤ 0.001) variation existed among the breeding lines for the seven traits. Mean ranges of seed length (SL), width (SW), thickness (ST) and a single seed weight (SSW) among the 139 breeding lines were respectively: 6.77–10.22 mm, 5.70–7.86 mm, 4.96–7.45 mm and 0.15–0.42 g. Positive and significant (P ≤ 0.05) genotypic correlation existed among SSW, SL, SW and ST. Seed colours, pattern, shapes, sizes, surface texture, brilliance varied among the breeding lines. Ranges of phenotypic and genotypic coefficient of variation and broadsense heritability were: 5.49–23.84%, 2.95–19.88% and 28.91–69.54% respectively. Fourteen (quantitative and qualitative) traits contributed higher (≥ 0.30) eigenvector loadings to the first three PC axes which explained 57.9% of the total variation among the breeding lines. Similarity among the lines was 0.75. Four clusters ensued in the dendrograph and each group had genetic similarities of: 0.85 (I), 0.82 (II), 0.78 (III) and 0.80 (IV). This research unveiled significant variation among AYB breeding lines with promising reliability for breeding opportunities of the qualitative and quantitative seed traits, which could contribute to higher grain yield and acceptability.
Exploring self-supervised learning biases for microscopy image representation
Authors: Bendidi Ihab , Bardes Adrien , Cohen Ethan , Lamiable Alexis , Bollot Guillaume , Genovesio Auguste
Published: November 2024

Self-supervised representation learning (SSRL) in computer vision relies heavily on simple image transformations such as random rotation, crops, or illumination to learn meaningful and invariant features. Despite acknowledged importance, there is a lack of comprehensive exploration of the impact of transformation choice in the literature. Our study delves into this relationship, specifically focusing on microscopy imaging with subtle cell phenotype differences. We reveal that transformation design acts as a form of either unwanted or beneficial supervision, impacting feature clustering and representation relevance. Importantly, these effects vary based on class labels in a supervised dataset. In microscopy images, transformation design significantly influences the representation, introducing imperceptible yet strong biases. We demonstrate that strategic transformation selection, based on desired feature invariance, drastically improves classification performance and representation quality, even with limited training samples.
Quantifying Salt Crystallization Impact on Evaporation Dynamics From Porous Surfaces
Authors: Jannesarahmadi Sahar , Aminzadeh Milad , Helmig Rainer , Or Dani , Shokri Nima
Published: November 2024

We investigated the effects of salt crystallization on the dynamics of saline water evaporation in porous media. Water mass loss rates from sand columns supplied with NaCl solutions at three concentrations were monitored under controlled ambient conditions. The formation and evolution of salt crystals over sand surfaces were synchronously imaged optically and thermally. Despite identical experimental and ambient conditions, we observed distinct crystallization dynamics that affected evaporative mass loss rates for similar salt concentrations, highlighting high variability of crystallization and its impact on evaporation. We observed the enhancement of maximum evaporation rates by factors of 3 to 14 under our experimental conditions and attributed this enhancement to the formation and evolution of porous crystalized salts at the surface. Additionally, visible intermittent temperature fluctuations of the salt crust were quantified using thermal imagery attributed to the dynamic processes of crystallization, dissolution and evaporation occurring simultaneously at the surface.
Parent–child interaction frequency: associations with age, sibling presence, and child health
Authors: Twork Kira , Ludwig Juliane , Kiess Wieland , Poulain Tanja
Published: November 2024

Objectives

Parent-child interaction plays a crucial role in child development. This study investigated associations between the frequency of parent-child-interactions and sociodemographic characteristics (age, sex, socio-economic status, family structure, number and age of siblings), physical and psychological symptoms in children, and mental health of parents.

Methods

The frequencies of 11 different parent-child interactions (shared reading, singing, moving, painting, building, puzzle, playing ball, role games, language games, number games and talking about problems) were assessed in 739 children aged 2–6.5 years-old using a standardised parental questionnaire, within a population-based cohort study in Leipzig, Germany. Physical and psychological symptoms were investigated using the HBSC Symptom-Checklist and parental depression symptoms using the Patient Health Questionnaire. We applied regression analyses to assess associations between variables.

Results

Shared reading was the parent-child interaction reported most frequently, with an average occurrence of several times a week. Number games were reported least frequently, with an average occurrency of every two weeks. Fewer parent-child interactions were significantly associated with higher child age, higher number of siblings, presence of older siblings and a lower level of physical and psychological symptoms. The other variables (sex, SES, living situation, presence of younger siblings or both (younger and older), depression symptoms of parents) were not significantly associated with the frequency of parent-child interactions.

Conclusion

The findings show that age of children and number as well as age of siblings at home may shape the frequency of parent-child interaction in preschool children. In addition, the findings suggest that parent-child interaction might be related to the health of children rather than the (mental) health of parents.

Impact

This study assessed the associations between the frequency of different types of parent-child interactions and sociodemographic as well as health-related parameters in a large sample of children.

There still exist sex-specific differences in the frequency of parent-child interactions related to traditional role models of girls and boys.

A higher frequency of parent-child interactions is associated with more physical and psychological symptoms in children.

Parent-child interactions are less frequent in families with more children, especially when older siblings are present.
Phenotypical differences of neutrophils patrolling tumour-draining lymph nodes in head and neck cancer
Authors: Ekstedt Sandra , Piersiala Krzysztof , Kolev Aeneas , Farrajota Neves da Silva Pedro , Margolin Gregori , Kumlien Georén Susanna , Cardell Lars-Olaf
Published: November 2024

Background

The complexity and heterogeneity of neutrophils are recognized, especially their roles in modulating inflammation and cancer immune responses. The detailed functions of neutrophils in human tumour-draining lymph nodes (TDLNs), specifically in the context of head and neck cancer, remain inadequately characterized.

Aim

This study aims to delineate the phenotypic diversity of neutrophils in TDLNs, non-tumour-draining lymph nodes (nTDLNs) from patients with oral squamous cell carcinoma (OSCC), and to evaluate their correlation with clinical outcomes.

Methods

A flow cytometry-based investigation.

Results

Neutrophils manifest a tissue-specific heterogeneity with significant phenotypic differences between compartments. A substantial fraction of neutrophils displayed an activated CD16highCD62Ldim profile in TDLNs, more prominent in patients with advanced T stages, implicating their involvement in the disease’s progression. Notably, the presence of this activated neutrophil phenotype in TDLNs was strongly associated with poorer patient prognosis.

Conclusions

The study confirms the heterogeneity of neutrophils in human TDLNs, aligning with findings from animal models but extending them to show clinical relevance in human disease. The correlation of neutrophil phenotypes with cancer progression and prognosis emphasizes the importance of these cells in the tumour-microenvironment. The data suggests a future possibility to develop targeted therapies that modulate the neutrophilic response in OSCC.
Reevaluating antibiotic prophylaxis: insights from a network meta-analysis on dry socket and surgical site infections
Authors: Rojhanian Tayebe , Sofi-Mahmudi Ahmad , Vahdati Amin
Published: November 2024

Data sources

Three databases (MEDLINE, Cochrane Library, and Scopus) were searched in December 2021 for 16 Randomised Clinical Trials (RCTs).

Study selection

Three reviewers reviewed the articles on oral antibiotic prophylaxis (ABP) for the prevention of surgical site infection (SSI) and dry socket (DS) after lower third molar (L3M) extraction using the PICO framework. From 1999 to 2021, RCTs involving healthy patients undergoing L3M extraction with ABP, placebo, or no therapy were included. Adverse effects (AEs) associated with antibiotic usage, along with the main outcomes (DS and SSI), were also documented.

Data extraction and synthesis

Three independent investigators selected articles based on pre-established inclusion criteria, with any disagreements resolved by consensus or additional researchers. PRISMA guidelines were followed, involving initial title and abstract screening, followed by full-text evaluation. Exclusion reasons were documented, and the most recent report was included when multiple reports on the same patients were found, with no language restrictions applied. Two investigators evaluated studies quality and quality of evidence respectively using the Cochrane Collaboration tool and GRADEpro GDT. They independently extracted data, focusing on the type of extraction and the number of extracted L3M. They also detailed the use of antibiotics, including dosage, dosage regimen, timing, and duration. Among 16 articles, 15 used a parallel arm design, while one used a crossover design. The antibiotics studied included Amoxicillin+Clavulanic acid (7 articles), Amoxicillin (6), Metronidazole (2), Azithromycin (1), and Clindamycin (2), all compared with no treatment or placebo. A pairwise meta-analysis was used to combine studies with equivalent treatment (direct estimation), and a network meta-analysis compared outcome variables across different treatments (indirect comparison).

Results

Two included articles had a low risk of bias and the level of evidence was low according to GRADE. Pooled results supported the use of antibiotics to reduce DS and SSI following L3M extraction with a number needed to treat 25 and 18, respectively.

Conclusions

Despite the fact that ABP reduces the risk of DS and SSI, it is recommended to consider systemic conditions and individual patient risk factors before prescribing antibiotics, due to global health threat.
Systematic assessment of the achieved emission reductions of carbon crediting projects
Authors: Probst Benedict S. , Toetzke Malte , Kontoleon Andreas , Díaz Anadón Laura , Minx Jan C. , Haya Barbara K. , Schneider Lambert , Trotter Philipp A. , West Thales A. P. , Gill-Wiehl Annelise , Hoffmann Volker H.
Published: November 2024

Carbon markets play an important role in firms’ and governments’ climate strategies. Carbon crediting mechanisms allow project developers to earn carbon credits through mitigation projects. Several studies have raised concerns about environmental integrity, though a systematic evaluation is missing. We synthesized studies relying on experimental or rigorous observational methods, covering 14 studies on 2346 carbon mitigation projects and 51 studies investigating similar field interventions implemented without issuing carbon credits. The analysis covers one-fifth of the credit volume issued to date, almost 1 billion tons of CO2e. We estimate that less than 16% of the carbon credits issued to the investigated projects constitute real emission reductions, with 11% for cookstoves, 16% for SF6 destruction, 25% for avoided deforestation, 68% for HFC-23 abatement, and no statistically significant emission reductions from wind power and improved forest management projects. Carbon crediting mechanisms need to be reformed fundamentally to meaningfully contribute to climate change mitigation.
Scalable, data-assimilated models predict large-scale shoreline response to waves and sea-level rise
Authors: Vitousek Sean , Vos Kilian , Splinter Kristen D. , Parker Kai , O’Neill Andrea , Foxgrover Amy C. , Hayden Maya K. , Thomas Jennifer A. , Erikson Li , Barnard Patrick L.
Published: November 2024

Coastal change is a complex combination of multi-scale processes (e.g., wave-driven cross-shore and longshore transport; dune, bluff, and cliff erosion; overwash; fluvial and inlet sediment supply; and sea-level-driven recession). Historical sea-level-driven coastal recession on open ocean coasts is often outpaced by wave-driven change. However, future sea-level-driven coastal recession is expected to increase significantly in tandem with accelerating rates of global sea-level rise. Few models of coastal sediment transport can resolve the multitude of coastal-change processes at a given beach, and fewer still are computationally efficient enough to achieve large-scale, long-term simulations, while accounting for historical behavior and uncertainties in future climate. Here, we show that a scalable, data-assimilated shoreline-change model can achieve realistic simulations of long-term coastal change and uncertainty across large coastal regions. As part of the modeling case study of the U.S. South Atlantic Coast (Miami, Florida to Delaware Bay) presented here, we apply historical, satellite-derived observations of shoreline position combined with daily hindcasted and projected wave and sea-level conditions to estimate long-term coastal change by 2100. We find that 63 to 94% of the shorelines on the U.S. South Atlantic Coast are projected to retreat past the present-day extent of sandy beach under 1.0 to 2.0 m of sea-level rise, respectively, without large-scale interventions.
Differential neural activity predicts the long-term stability of the effects of positive and negative expectations on pain
Authors: Wolf Maren-Isabel , Wittkamp Christoph Arne , Rose Michael
Published: November 2024

Expectations modulating pain perception is a well-researched phenomenon, but less is known about the persistence of expectation effects over longer time-courses. In this preregistered study, we examined the persistence of positive (placebo) and negative (nocebo) expectation effects over one week and investigated whether neural activity on day 1 (fMRI) can predict the stability of these effects one week later (n = 41). We tested whether expectations were reflected in EEG oscillatory activity at the second measurement. Both positive and negative pain modulation effects persisted over the tested time-period and did not undergo extinction. Expectations of higher compared to lower pain led to larger theta-to-alpha EEG activity. Most interestingly, differential neural activity in fMRI was correlated with persistent expectations. Individual differences in the persistence of positive expectation effects were related to reduced amygdala activity and enhanced activity in the anterior insula and dorsolateral prefrontal cortex (DLPFC) during the first session. In contrast, persistence of negative expectation effects was predicted by enhanced thalamus activity. Our findings indicate relatively stable placebo and nocebo effects over longer time courses, but this persistence is based on different neural areas for positive and negative expectations.
Green chemistry: magnetic dispersive solid phase extraction for simultaneous enrichment and determination of V, Ni, Ti and Ga in water samples by HR-CS ETAAS
Authors: Vázquez-Palomo L. , Montoro-Leal P. , García-Mesa J. C. , López Guerrero M. M. , Vereda Alonso E.
Published: November 2024

Innovative M@GO-MTS sorbent ensures simplicity, accuracy, reproducibility, cost-effectiveness, in saline environments for simultaneous detection of V, Ti, Ni and Ga.
Simple and easy functionalization of para-hydroxy POCOP-M (M = Ni(ii), Pd(ii)) pincer complexes: synthesis of multimetallic species
Authors: Serrano-García Juan S. , García-Eleno Marco Antonio , Arenaza-Corona Antonino , Rufino-Felipe Ernesto , Valdés Hugo , Hernandez-Ortega Simon , Morales-Morales David
Published: November 2024

A facile and efficient method to attain mono- and bi-metallic pincer complexes was developed. Complexes were easily isolated in moderate to good yields, representing a straightforward and attractive synthesis to get multimetallic pincer complexes.
Rosmarinic acid alleviated intestinal barrier damage caused by Escherichia coli by regulating the gut microbiota and inhibiting the NF-κB signalling pathway in mice
Authors: Yi Dandan , Liu Xia , Wang Menghui , Zhao Linyi , Liu Yu , Xu Zhiran , Peng Ying , Zhang Rui , Wei Qianyin , Liang Zhengmin , He Jiakang
Published: November 2024

Escherichia coli (E. coli) is a common zoonotic foodborne pathogen that poses a major threat to public health and economic development.
Cross-domain binding of anti-fibrillation peptide TNGQ to islet amyloid polypeptide provides cytoprotective effects in giant unilamellar vesicles and pancreatic β-cells
Authors: Abioye Raliat O. , Yiridoe Martha S. , Wang Chenyang , Avis Tyler J. , Ahmed Tamer A. E. , Hammami Riadh , Udenigwe Chibuike C.
Published: November 2024

IAPP fibrillation ruptures giant unilamellar vesicles and induces β-cell cytotoxicity. Anti-fibrillation peptide (TNGQ) reduces toxic IAPP fibril formation by producing off-pathway intermediates, reducing membrane rupture and β-cell cytotoxicity.
Esterified starches enhance short-term satiety in mice via structural and physicochemical alterations
Authors: Wang Tong , Liu Chang , Ma Rongrong , Pan Xiaohua , Shen Wangyang , Tian Yaoqi
Published: November 2024

Esterified starch increases RS content, chewiness, and viscosity through structural changes, thereby stabilizing postprandial blood glucose and delaying gastric emptying, resulting in a good short-term satiety.
Development of diarylpyrimidine derivatives (& other heterocycles) as HIV-1 and WT RT inhibitors
Authors: Dorababu Atukuri
Published: November 2024

Heterocyclic molecules, in particular diarylpyrimidine and diaryltriazines derivatives possessed excellent RT inhibitory and anti-HIV properties. Hence, molecules are suitable for design of potent anti-HIV drug molecules.
Exfoliated MoS2 nanosheets immobilized in porous microbeads as recoverable photocatalysts
Authors: Park Daehwan , Kim Jin Woong , Osuji Chinedum O.
Published: November 2024

Immobilization of exfoliated MoS2 nanosheets on polymer beads ensures high dispersion stability, resulting in excellent photocatalytic performance.
Starvation induces diffusion hindrance at the nanoscale in mammalian cells
Authors: Sareen Sakshi , Zgorzelska Alicja , Kwapiszewska Karina , Hołyst Robert
Published: November 2024

Prolonged starvation leads to intracellular diffusion hindrance, inducing a state of cellular dormancy with reduced energy consumption.
Biodegradable cellulose nanocrystal composites doped with carbon dots for packaging and anticounterfeiting applications
Authors: Singh Shiva , Dev Keshav , Bhardwaj Shakshi , Ramakanth Dakuri , Singh Khushboo Rani , Poluri Krishna Mohan , Ghosh Kaushik , Maji Pradip K.
Published: November 2024

This work focuses on water-based carbon dots and CNCs from Vigna mungo, used in anti-counterfeit inks and sensor films. These CDs are UV-visible, pH-sensitive, antimicrobial, and biodegradable, offering multifunctional packaging solutions.
Revealing the impact of CO2 exposure during calcination on the physicochemical and electrochemical properties of LiNi0.8Co0.1Mn0.1O2
Authors: Nel-lo Pascual Marc , Moreno Elías Martínez , Jøsang Leif Olaf , Merlo Maximiliano , Jacas Biendicho Jordi
Published: November 2024

The synthesis atmosphere plays a fundamental role in determining the physicochemical properties and electrochemical performance of NMC811 cathode materials used in lithium-ion batteries.
Synthesis of β-lactam-zidovudine pronucleosides as potential selective narrow-spectrum antibacterial agents
Authors: Rosales-Hurtado Miyanou , Faure Fanny , Sannio Filomena , Verdirosa Federica , Feller Georges , Carretero Elodie , Vo-Hoang Yen , Licznar-Fajardo Patricia , Peyrottes Suzanne , Docquier Jean-Denis , Gavara Laurent
Published: November 2024

Based on the Buchwald–Hartwig amination reaction, an original β-lactam pronucleosides series was synthesized and microbiologically evaluated.
A visible light-mediated deoxygenation protocol for the synthesis of dipeptides, amides and esters without racemization
Authors: Ren Ji-Wei , Tan Qing-Long , Zuo Jian , Miao Yan-Fei , Zhang Pan , Sun Jing-Hui , Han Yin-Feng
Published: November 2024

A green and sustainable visible light-induced triphenylphosphine-promoted deoxygenation strategy to generate acyl radicals from commercially available amino acids was developed for the synthesis of dipeptides, amides and esters in good yields.
Energy-storage materials with stable structure through carbide slag modification by acid impregnation and manganese doping
Authors: Gao Caiyun , Liu Xiangli , Zhang Yuan , Jin Fei , Li Dong
Published: November 2024

The energy-storage material synthesized by formic acid and manganese nitrate impregnation. The presence of two inert metal oxides, Mn2O3 and Ca2MnO4, which improves the problem of serious sintering of calcium carbide slag during the cycling process.
The scale-up of microwave flow syntheses by recirculation: the chlorine-free preparation of alkyl phenyl-H-phosphinates
Authors: Schindler József , Nagy Dorka , Harján Rebeka , Keglevich György
Published: November 2024

The MW flow esterification of phenyl-H-phosphinic acids with alcohols at ca. 150 °C in the presence of 5% of [bmim][PF6] afforded target alkyl phenyl-H-phosphinates with productivity of ca. 6–9 g h−1 by applying a recirculating mode of operation.
Exploring the molecular design principles for efficient diarylethene photoacid and photohydride generators based on the photochemical reaction mechanism
Authors: Su Yifan , Zheng Dexin , Ge Lingfeng , Yu Le , Lee Phillips David , Ma Jiani , Fang Yu
Published: November 2024

We selected two model molecules of photoacid generators (PAGs) and photohydride generators (PHGs), respectively, and elucidated their photochemical reaction mechanisms. The work would provide guidance for the development of efficient PAGs and PHGs.
Bis(methylene)-λ5-phosphane anions
Authors: Nomoto Akihiro , Sugamata Koh , Sasamori Takahiro
Published: November 2024

Novel anionic phosphorus-centered heteroallene type molecules, bis(methylene)-λ5-phosphane anions, were synthesized and fully characterized.
Cold sintering of nickel manganese oxide for thermistor fabrication
Authors: Fanghanel Julian , Yokomizo Satoshi , Funahashi Shuichi , Randall Clive A.
Published: November 2024

The cold sintering process densified NiMn2O4, achieving high densities while maintaining critical functional properties, therefore presenting a sustainable and energy-efficient alternative to conventional sintering techniques for NTC thermistors.
Towards advanced N-rich energetic explosives: based on tetrazole and triazole groups with large conjugated systems and extensive hydrogen bonds
Authors: Zhang Guofeng , Hao Xue , Zou Yongbin , Liu Shichang , Wei Junjie , Dong Zhen , Ye Zhiwen
Published: November 2024

The N3-3 molecule has achieved superior overall performance among N-rich energetic materials (Td = 302 °C and Dv = 9341 m s−1), which significantly surpasses that of HMX.
Formation of bismuth nanosheets on copper foam coupled with nanobubble technology for enhanced electrocatalytic CO2 reduction
Authors: Wu Kai , Yang Pengwei , Fan Shuaijun , Wu Yifan , Ma Jingxiang , Yang Lijuan , Zhu Hongtao , Ma Xiaoying , Gao Heli , Chen Wentong , Jia Jun , Ma Shuangchen
Published: November 2024

A simple three-step method was used to construct Bi nanosheets with abundant lattice dislocations on copper foam, coupled with nanobubble technology, enabling formate production at low potentials, with excellent selectivity and high current density.
Tunable color-stable hybrid white OLEDs by combining fluorescent and TADF emitters in a single emissive layer
Authors: Deori Upasana , Viswanathan Thamodharan , Yadav Nisha , Rajamalli Pachaiyappan
Published: November 2024

Tuning of hybrid white organic light-emitting diodes from cool and pure to warm white emission by varying the dopant concentration from 0.5 wt% to 1.0 wt%.
A three‐vector model predicting torque control of permanent magnet synchronous motor with a fixed weight coefficient
Authors: Qu Xingyu , Peng Chengkun , Lu Peng , Ge Bing , Zhang Shuang , Wang Qinghe , Li Zhenyang
Published: November 2024

The difficulty of adjusting the weighting coefficients of the cost function in traditional model predictive torque control is addressed by proposing a fixed weighting coefficient three‐vector model predictive torque control (FWC‐MPTC) strategy. The strategy applies three voltage vectors in a control period. The first voltage vector is selected by a fixed coefficient cost function, the second and third voltage vectors are determined by a cost function that includes only torque and flux, and the third voltage vector is no longer just a traditional zero vector. In addition, to solve the problem of poor disturbance immunity of the speed loop PI controller, an active disturbance rejection controller (ADRC) is introduced in the speed loop, and the error non‐linear function in the controller is rewritten into a smoother new function. The proposed control strategy reduces the torque and speed fluctuation of the traditional three‐vector model predictive control (TTV‐MPTC), improves the robustness of the system, avoids the difficulty of adjusting the weight coefficient in the traditional cost function, and reduces the computational complexity of the cost function.
Development of optimal participating strategy for source‐grid‐load‐storage integrated projects in electricity markets with multi‐stage joint optimization
Authors: Li Zihao , Yang Yu , Shi Yifan , Yao Li , Liu Wei , Wen Fushuan
Published: November 2024

To promote peer‐to‐peer trading in a distribution system with the franchise owned by the concerned distribution company respected, a so‐called “source‐grid‐load‐storage” (SGLS) integrated project is promoted in China. Given this background, this paper proposes a multi‐stage joint optimization model to optimize the participating strategy for SGLS‐IPs in electricity energy and ancillary service markets. A multi‐energy flow park model is presented with electricity, gas, and heat included. A two‐stage model for optimal participating strategy of SGLS‐IPs in electricity and ancillary service markets is then presented. Through scenario analysis of a sample system, the attained revenue of an SGLS‐IP in different markets is evaluated. Additionally, a bilevel Stackelberg game model is introduced for internal electric vehicle clusters (EVCs) within an SGLS‐IP, with the upper level representing an SGLS‐IP, and the lower level representing EV users engaging in the game. The effectiveness of the model is validated through case studies. Simulation results demonstrate that reasonable market participation and pricing strategies contribute to the efficient allocation of resources within a SGLS‐IP and a win‐win outcome for both the SGLS‐IP entity and EV users.
Distributed multi‐target tracking via consensus‐based Arithmetic Average fusion
Authors: Guan Xin , Lu Yu
Published: November 2024

This paper proposes a multi‐target tracking fusion algorithm based on consensus arithmetic averaging to address the limitations of the sensor detection field of view and information fusion difficulty when tracking multiple targets in a distributed Airborne passive bistatic radar (APBR) network. Labelled Multi‐Bernoulli (LMB) filters are executed locally when each node estimates multi‐target tracks. A consensus strategy is utilised to execute the information interaction among sensors, taking into account the limited detection field of view of a single sensor. The paper proposes the LMB Consensus Arithmetic Average (LMB‐CAA) fusion algorithm to address the issue of label inconsistency in multi‐sensor LMB density fusion. The proposed algorithm is based on label decomposition and reconstruction and aims to avoid the influence of label mismatch on the fusion effect while simultaneously ensuring that the fusion is closed during information interaction and fusion. Simulation results demonstrate that the proposed algorithm can stably estimate multi‐target tracks and improve the multi‐target tracking fusion accuracy of distributed APBR networks.
Design of a stagger‐tuned high‐power low‐stress capacitive wireless power transfer system
Authors: Williams Kyle John , Town Graham , Deilami Sara , Taghizadeh Foad
Published: November 2024

Capacitive power transfer (CPT) has emerged as a promising alternative to traditional inductive methods. CPT offers advantages like cost‐effectiveness, reduced weight and volume, and greater tolerance to alignment errors. However, the high‐Q resonant circuits used as matching networks can be susceptible to high voltage stress, especially when transmitting substantial power. Consequently, designing matching networks for CPT systems necessitates consideration of multiple parameters, including practical constraints such as component losses and breakdown thresholds. In this work an innovative algorithm is presented for designing practical matching networks in CPT systems. The algorithm conducts a methodical search of potential solutions, and converges on component values that maximize power transfer efficiency whilst also minimizing component voltage stress. The proposed algorithm is demonstrated theoretically and experimentally.
Exploring the Potential of Flow Batteries for Large-Scale Energy Storage Systems
Authors: Yadav Kanchan , Alsalami Zaid , Priydarshini G Kala , Vaidya P.R. , Thangam V. Thirumani , Kshirsagar Kundalik , Sujatha M.S.
Published: November 2024

Flow batteries have emerged as a promising technology for large-scale energy storage, offering unique advantages in terms of scalability, safety, and long cycle life. This paper explores the potential of flow batteries to support renewable energy integration and grid stability, analyzing their operational mechanisms, performance characteristics, and economic feasibility. A comprehensive review of various flow battery chemistries, such as vanadium redox and zinc- bromine, highlights the benefits and challenges associated with each type. Furthermore, the study addresses the role of flow batteries in addressing the intermittency of renewable energy sources, such as wind and solar power, emphasizing their suitability for utility-scale applications. Future developments and ongoing research efforts aimed at enhancing efficiency, reducing costs, and improving sustainability are also discussed, providing insight into the advancements required for widespread adoption of this technology.
Comparative Analysis of Supercapacitors vs. Batteries
Authors: Almusawi Muntather , Shukla Aasheesh , S Hemalatha , Kavitha P. , Gambhire G.M. , Pardeshi Pankaj R. , Pragathi B.
Published: November 2024

This paper presents a comparative analysis of supercapacitors and batteries as energy storage technologies, focusing on key performance metrics such as energy storage capacity, power output, efficiency, and charge/discharge cycles. Supercapacitors are known for their rapid charge and discharge capabilities, high power density, and longevity, making them ideal for applications requiring quick bursts of energy. Conversely, batteries, particularly lithium-ion, offer significantly higher energy density, enabling them to store more energy in a compact form factor, but they suffer from longer charging times and limited cycle life. This study highlights the trade-offs between the two technologies, providing insights into their suitability for various applications, from consumer electronics to renewable energy systems. The findings suggest that while supercapacitors excel in scenarios demanding high power and durability, batteries remain the preferred choice for applications requiring higher energy storage capacity. The analysis underscores the importance of selecting the appropriate energy storage solution based on specific application requirements.
Integration of Energy Storage with Wind Power Conversion Systems: Enhancing Grid Stability
Authors: Durgadevi G. , Nalawade M.K. , Sharma Kamal , Nishanthi  , Hameed Shnain Ammar , Sutar Vasundhara , Sujatha M.S.
Published: November 2024

The integration of renewable energy sources, particularly wind power, has become crucial for reducing carbon emissions and promoting sustainable energy systems. However, the variability and intermittency of wind energy present challenges to grid stability and reliability. This paper explores the integration of energy storage systems (ESS) with wind power conversion systems (WPCS) as a solution to enhance grid stability. The proposed approach involves using advanced energy storage technologies, such as battery energy storage systems (BESS) and flywheels, to mitigate the fluctuations in power output and ensure a stable power supply. The control strategies employed focus on optimizing the response of the ESS to wind variability, enhancing the power quality, and providing ancillary services such as frequency and voltage regulation. Simulation results demonstrate that the integration of ESS significantly improves the dynamic response of wind power systems, reduces power imbalances, and enhances overall grid stability. This research provides insights into effective energy management and control strategies that facilitate higher penetration of wind energy into modern power grids, contributing to a more resilient and efficient energy infrastructure.
Exploring Electromagnetic Engine Propulsion: Design of a Next-Gen Engine
Authors: Sai Tharun G. , Samhitha K. Anasuya , Honey D. , Harika CH. , Mohith B. , Nithin K. , Manoj Vasupalli
Published: November 2024

The pursuit of innovative and sustainable engine technologies has led to the exploration of electromagnetic solenoid engines as a potential alternative to traditional internal combustion engines, specifically within the context of electric vehicles (EVs). This work aims to design, build, and test a prototype electromagnetic solenoid engine, leveraging the principles of electromagnetism to convert electrical energy into mechanical motion suitable for EV applications. The solenoid engine operates by using electric current to generate a magnetic field within solenoids, which in turn drives a piston to produce linear motion. Through detailed simulations and experimental prototypes, key performance metrics such as energy efficiency, power output, thermal management, and system durability are examined. Additionally, the study investigates the impact of various design parameters, including solenoid coil configuration, magnetic materials, and control strategies, on the overall performance of the engine. The findings demonstrate the feasibility of using electromagnetic solenoids for electric vehicle propulsion, highlighting potential benefits in terms of reduced emissions, lower noise levels, and enhanced efficiency. This research contributes to the advancement of green propulsion technologies, providing valuable insights for the development of next-generation sustainable engines for electric vehicles.
AI-Driven Optimization of Fuel Cell Performance in Electric Vehicles
Authors: Badhoutiya Arti , R Srisainath , Shirbavikar K.A. , Bhuvaneshwari P. , Al-Farouni Mohammed , Narkhede Jitendra , Kumar N Anil
Published: November 2024

The increasing adoption of electric vehicles (EVs) is driving the need for efficient and sustainable energy sources, such as fuel cells, to enhance vehicle range and performance. This paper explores the application of AI-driven optimization techniques to improve the performance of fuel cells in electric vehicles. By leveraging machine learning algorithms, particularly reinforcement learning and predictive modeling, the system can optimize key parameters such as temperature, pressure, and hydrogen consumption in real-time, thereby maximizing efficiency and extending the operational lifetime of the fuel cells. The study demonstrates that AI-based approaches can significantly enhance energy output and fuel utilization while adapting to dynamic driving conditions. This research provides a promising pathway for improving fuel cell performance, thus promoting the broader adoption of hydrogen-based electric vehicles as a viable alternative to traditional internal combustion engines.
Machine Learning Algorithms for Predictive Maintenance in Hybrid Renewable Energy Microgrid Systems
Authors: Prabhakar P.B. Edwin , Rajarajeswari S. , Antad Sonali , Jeshurun Subramania Bala , Badhoutiya Arti , S Chandrika , Babu D. Suresh
Published: November 2024

The rapid expansion of hybrid renewable energy microgrid systems presents new challenges in maintaining system reliability and performance. This paper explores the application of machine learning algorithms for predictive maintenance in such systems, focusing on the early detection of potential failures to optimize operational efficiency and reduce downtime. By integrating real-time data from solar, wind, and storage components, the proposed models predict the remaining useful life (RUL) of critical components. The results demonstrate significant improvements in predictive accuracy, offering a robust solution for enhancing the reliability and longevity of renewable energy microgrids.
Thermal Performance Analysis of Ternary Hybrid Nanofluids in Solar-Powered Ships Using Parabolic Trough Solar Collectors
Authors: Obalalu A. M. , Oluwafemi Faramade Isaac , Olusesi O. J. , Salaudeen S.A. , Prasad Brijesh , Bajaj Mohit
Published: November 2024

The impact of Cattaneo–Christov heat flux on cylindrical surfaces using Carbon Nanotube (CNT) ternary Hybrid Nanofluids with convective boundary conditions is investigated in this work, especially within the context of solar-powered ships. A numerical simulation is performed to assess the thermal characteristics and effectiveness of CNT ternary Hybrid Nanofluids over traditional fluids. The thermal relaxation effects and the heat flux are attained using the Cattaneo–Christov heat flux model which leads to a better prediction of heat transfer processes in the nanofluids. By assessing the existing behaviors and energy transferal characteristics of CNT ternary hybrid nanofluids, the findings perfectly show that the nanoparticle impacts improving the thermal conductivity and heat transfer efficiency. This is useful for optimization of cooling systems of ships driven by solar energy. This work is beneficial to the efforts put towards designing and optimal thermal management strategies for solar-powered ships using nanofluid and novel heat transfer.
Blockchain Technology in Energy Markets: Enabling Peer-to-Peer Energy Trading
Authors: Aravind A.R. , Santhi G.B. , Patil S.T. , P Selvakumar , Sharma Gunjan , Dhamone Jeetendra , Ragu Nathan S.
Published: November 2024

This paper investigates the potential of blockchain technology to transform energy markets through peer-to-peer (P2P) energy trading. Blockchain enables decentralized, transparent, and secure energy transactions, allowing consumers to trade electricity directly, thereby reducing reliance on traditional centralized systems. The study examines the main challenges facing current energy markets, including inefficiencies, pricing complexities, and the integration of renewable energy sources. By utilizing smart contracts, blockchain automates and secures energy exchanges, giving consumers a more active role in the market. The paper also explores the technical aspects of implementing blockchain in energy trading, such as infrastructure needs and scalability issues, while addressing the regulatory, legal, economic, and environmental implications of this technology. Real-world examples and case studies underscore the potential of blockchain to foster more resilient, efficient, and sustainable energy markets.
Millet Crop Yield Variation through Feature Extraction Using XGBoost
Authors: Jagadamba K. Ujas , Hussain S.J. , Srinivas Reddy T. , Sree Harsha P. Om , Nikhil G.
Published: November 2024

Agriculture, being a vital industry, relies significantly on predicting and improving crop yields for sustainable food production. In this context, millet, a staple crop in various regions globally, holds immense agricultural importance due to its nutritional value and resilience to harsh environmental conditions. The approach outlined in this study revolves around the utilization of advanced machine learning techniques, specifically XGBoost, which is a robust gradient boosting algorithm known for its effectiveness in handling structured data and making accurate predictions. This algorithm is employed to create a predictive model for forecasting millet yields.
IoT Based Remote Patient Health Monitoring System
Authors: Ravi Kumar Sariki , Chandra Sekhar Rao T. , Venkata Suman Jami , Usha Rani B.
Published: November 2024

Regular health monitoring is essential for maintaining good health, but long hospital queues and the need for ambulatory monitoring in our fast-paced world underscore the necessity for a simple health monitoring system adaptable to various settings. This system addresses the increasing demand for monitoring primary health parameters, particularly among older individuals, where conventional healthcare infrastructure often falls short. To overcome these challenges, we propose a comprehensive health monitoring system leveraging Internet of Things (IoT) technology. By utilizing IoT, we can wirelessly capture and transmit health data, ensuring interoperability. Our system collects and transmits vital health parameters such as body temperature, blood pressure, pulse, and GPS location using an Arduino Board and Wi-Fi module for data processing and transmission, respectively. This approach allows for real-time data capture, analysis, and storage, with automatic alerts sent to healthcare professionals when critical conditions are detected. Overall, our system offers user-friendly health monitoring, timely intervention, and reduces the burden on overcrowded healthcare facilities.
Study of the Behavior of Block Replacement Model (BRM) Using Higher Order Markov Chain in Varying Inflationary Economy
Authors: Nadhamuni Reddy C. , Ramya K.
Published: November 2024

Influence of inflation on block replacement of the computers in ICT industry by using Markov chain is spotlighted in the present paper. The concept of minor, major repairs, breakdown and failure have been discussed in detail. Replacement decisions for variable maintenance costs has been thoroughly investigated and the results are presented. Replacement age in years is calculated for forecasted inflation, rapid increase in inflation and sluggish increase in inflation.