bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models
Authors: Palma Gabriel R. , Thornberry Conor , Commins Seán , Moral Rafael A.
Published: September 2024

Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigation tasks. Frontal theta oscillations are thought to play an important role in spatial navigation and memory. Electroencephalography (EEG) datasets are very complex, making any changes in the neural signal related to behaviour difficult to interpret. However, multiple analytical methods are available to examine complex data structures, especially machine learning-based techniques. These methods have shown high classification performance, and their combination with feature engineering enhances their capability. This paper proposes using hidden Markov and linear mixed effects models to extract features from EEG data. Based on the engineered features obtained from frontal theta EEG data during a spatial navigation task in two key trials (first, last) and between two conditions (learner and non-learner), we analysed the performance of six machine learning methods on classifying learner and non-learner participants. We also analysed how different standardisation methods used to pre-process the EEG data contribute to classification performance. We compared the classification performance of each trial with data gathered from the same subjects, including solely coordinate-based features, such as idle time and average speed. We found that more machine learning methods perform better classification using coordinate-based data. However, only deep neural networks achieved an area under the ROC curve higher than 80% using the theta EEG data alone. Our findings suggest that standardising the theta EEG data and using deep neural networks enhances the classification of learner and non-learner subjects in a spatial learning task.
Normativität und Rekonstruktion
Authors: Franz Julia , Kubisch Sonja , Unterkofler Ursula
Published: September 2024

In der sozialarbeitswissenschaftlichen Professionalisierungsforschung sind Forschende mit verschiedenen normativen Fragen konfrontiert. Dies betrifft sowohl die Praxis Sozialer Arbeit, die von expliziten Normen und impliziten Wertorientierungen durchdrungen ist, als auch den Diskurs über Profession und Professionalität, der selbst normativ aufgeladen ist, wie auch die Prinzipien rekonstruktiver Sozialforschung, zu denen eine amoralische Analysehaltung zählt. Die Herausforderung besteht darin, normative Aspekte in der Forschungspraxis zu erkennen, zu reflektieren und eine offene Forschungshaltung zu bewahren. In diesem Beitrag werden das Zusammenspiel verschiedener Aspekte von Normativität und die daraus resultierenden Spannungen näher betrachtet, und zwar mit einem Fokus auf rekonstruktiven Forschungsverfahren, mit denen die Strukturlogik professionellen Handelns empirisch untersucht wird. Anknüpfend an Überlegungen zum „sozialpädagogischen Blick“ der Forschung werden Normativität und rekonstruktive Forschung ins Verhältnis gesetzt. Die Autorinnen beziehen sich auf eigene empirisch-rekonstruktive Analysen und zeigen anhand eines empirischen Beispiels auf, welche normativen Fragen sich in der Forschung der Sozialen Arbeit zur Professionalisierung stellen. Sie konkretisieren so den „forschenden Blick Sozialer Arbeit“.
Multi-omics-based Machine Learning for the Subtype Classification of Breast Cancer
Authors: Hassan Asmaa M. , Naeem Safaa M. , Eldosoky Mohamed A. A. , Mabrouk Mai S.
Published: September 2024

Cancer is a complicated disease that produces deregulatory changes in cellular activities (such as proteins). Data from these levels must be integrated into multi-omics analyses to better understand cancer and its progression. Deep learning approaches have recently helped with multi-omics analysis of cancer data. Breast cancer is a prevalent form of cancer among women, resulting from a multitude of clinical, lifestyle, social, and economic factors. The goal of this study was to predict breast cancer using several machine learning methods. We applied the architecture for mono-omics data analysis of the Cancer Genome Atlas Breast Cancer datasets in our analytical investigation. The following classifiers were used: random forest, partial least squares, Naive Bayes, decision trees, neural networks, and Lasso regularization. They were used and evaluated using the area under the curve metric. The random forest classifier and the Lasso regularization classifier achieved the highest area under the curve values of 0.99 each. These areas under the curve values were obtained using the mono-omics data employed in this investigation. The random forest and Lasso regularization classifiers achieved the maximum prediction accuracy, showing that they are appropriate for this problem. For all mono-omics classification models used in this paper, random forest and Lasso regression offer the best results for all metrics (precision, recall, and F1 score). The integration of various risk factors in breast cancer prediction modeling can aid in early diagnosis and treatment, utilizing data collection, storage, and intelligent systems for disease management. The integration of diverse risk factors in breast cancer prediction modeling holds promise for early diagnosis and treatment. Leveraging data collection, storage, and intelligent systems can further enhance disease management strategies, ultimately contributing to improved patient outcomes.
Simulation methods for local microstructure evolution-cooling and time–temperature transformation behavior in heat treatment of tool steels
Authors: Schuppener Jannik , Benito Santiago , Weber Sebastian
Published: September 2024

This paper presents the development of a simulative workflow capable of predicting microstructural evolution during heat treatment processes. It represents a meaningful advance in this field by extending existing simulation models previously published by the authors. In this previous work, the software solutions MatCalc®, MATLAB®, and Abaqus FEA® were coupled to calculate several local microstructural properties: the carbide content, the type, the distribution, and the chemical composition of the matrix. In addition, the model could determine the proportions of microstructural components such as martensite and retained austenite within the matrix. The hardening treatment was simplified by assuming a fast quenching, leading to complete martensitic phase transformation. However, this assumption may not be valid for larger components, leaving room for optimization. Therefore, the simulation model in this publication has been successfully extended to include local solution-state dependent time–temperature transformation behavior. In addition, an automated microstructure simulation of the entire component is now possible. As an application example, two tool geometries of different sizes were simulated with an identical furnace heat treatment. The same furnace temperature (T = 1050 °C) and the same holding time (t = 60 min) were simulated with a slow air cooling (Tair = 25 °C). The austenitizing temperature and holding time were chosen to dissolve a sufficient amount of carbides during austenitization, and the slow cooling rates were chosen to form diffusion controlled phases such as bainite or pearlite. To validate the simulation model, the simulated time–temperature sequences were reproduced experimentally in a quenching dilatometer. The resulting real microstructures were compared with the simulated ones.
First Red List of Ecosystems assessment of a tropical glacier ecosystem to diagnose the pathways towards imminent collapse
Authors: Ferrer-Paris José R. , Llambí Luis D. , Melfo Alejandra , Keith David A.
Published: September 2024

Tropical glaciers are rapidly disappearing, particularly in isolated mountain peaks below 5,000 m elevation. These glaciers are fundamental substrates for unique cryogenic ecosystems in high tropical environments where the ice, melting water and rocky substrate sustain microbiological communities and other meso- and macro-biota. This study uses the Red List of Ecosystems guidelines to diagnose the collapse of the tropical glacier ecosystem of the Cordillera de Mérida, Venezuela. We undertook the assessment with existing estimates of glacier ice extent, indirect historical estimates of ice mass balance and global mechanistic models of future ice mass balance. We complemented these with additional statistical analysis of trends and bioclimatic suitability modelling to calculate and predict rates of decline and relative severity of degradation in selected ecosystem indicators. The evidence suggests an extreme risk of collapse (Critically Endangered) because of a prolonged and acute reduction in ice extent and changes in climatic conditions that are leading to the complete loss of ice mass. The ice substrate has declined 90% in the last 20 years, and observed acceleration of the rate of decline suggests it will probably disappear within the next 5 years. Loss of ice substrate will trigger an immediate loss of supraglacial, englacial and subglacial biotic compartments and initiate a decades-long succession of forefield vegetation. However, ongoing inventories of native biota and monitoring of ecosystem transitions can provide valuable insights and lessons for other ecosystems facing similar risks. The Red List of Ecosystems assessment protocol provides a useful framework for comparative analysis of cryogenic ecosystems.
Anticoagulation in embolic acute limb ischaemia-an observational	study
Authors: Patil Aishan , Williams Dean T. , Gomati Ayoub , Nagy John
Published: September 2024

Summary: The management of embolic acute limb ischaemia commonly involves determining aetiology and performing emergency invasive procedures. This detailed study aimed to determine the impact of manipulation of anticoagulation in the aetiology of emboli in acute limb ischaemia and determine the efficacy of primary anticoagulation therapy vs. invasive interventions. Material and methods: Data collection was conducted at a single institution on a cohort of patients presenting consecutively with embolic acute limb ischaemia over one year. Two groups were compared, one receiving anticoagulation as primary therapy with those undergoing invasive treatment as the internal comparison group. Results: A likely haematological causation was identified in 22 of 38 presentations, related to interruption of anticoagulation in cardiac conditions, the majority atrial fibrillation (n=12), or hypercoagulable states (n=10). Limb salvage was pursued in 36 patients employing anticoagulation (n=19) or surgical embolectomy (n=17) as the primary therapy in upper and lower limbs (n=17 vs n=19 respectively). Despite delays often well beyond six hours and a range of ischaemic severity in both groups, 35 of 36 patients achieved full or substantive restoration of function with improved perfusion. Regarding anatomical distribution of arterial disease and therapy, three patients with multi-level disease proceeded to embolectomy following anticoagulation. Embolectomy was undertaken most often for proximal emboli and more profound paralysis. Conclusions: Anticoagulation and coagulopathy are commonly implicated in the aetiology of arterial emboli, with omission of effective anticoagulation in atrial fibrillation being associated in almost 1/3 of presentations. Whilst more profound limb paralysis and proximal or multi-level disease tended to be managed surgically, primary anticoagulation therapy alone or with a secondary embolectomy was effective across the spectrum of ischaemia severity and despite significant delays beyond guideline recommendations.
Messung von akut situativen Risiko- und Schutzfaktoren und ihre Relevanz für die Beurteilung positiver und negativer Vollzugsverhalten
Authors: Yoon Dahlnym , Rücknagel Stefanie , Kilic Senem , Wunsch Lea Victoria
Published: September 2024

Zusammenfassung: Standardisierte Messungen von Risiko- und Schutzfaktoren bei Straftätern sind als Mindestanforderungen an die Kriminalprognose vorgesehen. Die prognostisch relevanten Risiko- und Schutzfaktoren sind in der Regel sogenannte Trait-Risikofaktoren, und es liegen wenige Instrumente vor, die die Beurteilung von State-Situation-Faktoren erlauben. Zudem sind die meisten Instrumente nicht für eine interdisziplinäre Arbeit geeignet, da sie hohe Qualifikationen der/die Anwender_innen voraussetzen. Im Vergleich zur mittel- und längerfristigen Rückfallprognose sind im Haftverlauf mehrere aversive Verhaltensweisen denkbar, die per se einen Rückfall oder ein rückfallnahes Verhalten darstellen könnten (z. B. Gewalt, Substanzmissbrauch), gleichzeitig gibt es auch welche, die im Rahmen der Behandlung eine wichtige Rolle spielen, allerdings nicht zwangsläufig prognostisch relevant sein müssen (z. B. Vernachlässigung, Viktimisierung). Eine genauere Differenzierung solcher Verhaltensweisen und Kategorisierung dieser in deliktnahes (Offense-Analogue Behavior), deliktersetzendes (Offense-Replacement Behavior) oder deliktirrelevantes Verhalten (Offense-Irrelevant Behavior) sowie die relevanten kurzeitigen Einflussfaktoren könnten für die Prüfung der Lockerungseignung hilfreich sein und mittel-/längerfristige Kriminalprognose ergänzen.
Momentary Associations Between Positive Coping and Nonsuicidal Self-Injury Risk Among Individuals With Problematic Alcohol Use
Authors: Ammerman Brooke A. , O’Brien Connor , Park Yeonsoo , Jacobucci Ross
Published: September 2024

Abstract: Background: The use of positive coping skills has demonstrated protective effects with regard to Nonsuicidal Self-Injury (NSSI) engagement; however, cross-sectional evidence suggests that the presence of comorbid conditions, such as alcohol use disorders, may negate these benefits. Aims: The current study leverages ecological momentary assessment (EMA) to examine the between-person and within-person relationships between positive coping strategies and NSSI risk among individuals with problematic alcohol use. Method: Undergraduate students ( n = 56) completed a 21-day EMA protocol, in which they completed four surveys per day asking about their use of several positive coping strategies and NSSI risk. Results: Socializing was the only coping strategy to demonstrate a protective effect on NSSI risk. Alternatively, the coping strategies of finding perspective, positive thinking, and sitting with feelings until they pass all increased risk for NSSI. Limitations: The current study was underpowered to disentangle relationships with urges to engage in NSSI and NSSI behaviors. Conclusion: The results suggest that using coping skills that may present physical barriers to engaging in NSSI may be effective for reducing momentary NSSI risk.
Using Satellite Observations of Lightning and Precipitation to Diagnose the Behavior of Deep Convection in Tropical Cyclones Traversing the Midlatitudes
Authors: Heuscher Lena , Gatlin Patrick , Petersen Walter A.
Published: September 2024

This study uses a unique combination of geostationary and low‐Earth orbiting satellite‐based lightning and precipitation observations, respectively, to examine the evolution of deep convection during the tropical cyclone (TC) lifecycle. The study spans the 2018–2021 Atlantic Basin hurricane seasons and is unique as it provides the first known analysis of total lightning (intra‐cloud and cloud‐to‐ground) observed in TCs through their extratropical transition and post‐tropical cyclone (PTC) phases. We consider the TC lifecycle stage, geographic location (e.g., land, coast, and ocean), shear strength, and quadrant relative to the storm motion and environmental shear vectors. Total lightning maxima are found in the forward right quadrant relative to storm motion and downshear of the TC center, consistent with previous studies using mainly cloud‐to‐ground lightning. Increasing environmental shear focuses the lightning maxima to the downshear right quadrant with respect to the shear vector in tropical storm phases. Vertical profiles of radar reflectivity from the Global Precipitation Measurement mission show that super‐electrically active convective precipitation features (>75 flashes) within the PTC phase of TCs have deeper mixed phase depths and higher reflectivity at −10°C than other phases, indicating the presence of more intense convection. Differences in the net convective behavior observed throughout TC evolution manifest in both the TC‐scale frequency of lightning‐producing cells and the intensity variations amongst individual convective cells. The combination of continuous lightning observations and precipitation snapshots improves our understanding of convective‐scale processes in TCs, especially in PTC phases, as they traverse the tropics and mid‐latitudes.
2D Magnetotelluric Inversion Using Linear Finite Element Methods and a Discretize‐Last Strategy With First and Second–Order Anisotropic Regularization
Authors: Codd Andrea , Gross Lutz , Kerr Janelle
Published: September 2024

We present a new inversion scheme for 2D magnetotelluric data. In contrast to established approaches, it is based on a mesh‐free formulation of the Quasi‐Newton Broyden–Fletcher–Goldfarb–Shanno (BFGS) iteration which uses the cost function gradient to implicitly construct approximations of the Hessian inverse to update the unknown conductivity. We introduce conventional first–order regularization as well as second–order regularization where inversions based on the latter are more appropriate for sparse data and can be read as maximum likelihood estimation of the unknown conductivity. We apply first–order finite element method (FEM) discretizations of the inversion scheme, forward and adjoint problems, where the latter is required for the construction of the cost function gradients. We allow for unstructured first–order triangular meshes supporting an enhanced ground level resolution including topographical features and coarsening at the far field leading to significant reduction in computational costs from using structured mesh. Formulating the inversion iteration in continuous form prior to discretization eliminates bias due to local refinements in the mesh and gives way for computationally efficient sparse matrix techniques in the implementation. A keystone in the new scheme is the multi‐grid approximation of the Hessian of the regularizations to construct efficient preconditioning for the inversion iteration. The method is applied to the Commeni4 benchmark and two field data sets. Tests show that for both first and second–order regularization an anisotropic approach is important to address the vast differences in horizontal and vertical spatial scale which in conventional approaches is implicitly introduced through the elongated shape of grid cells.
A Systematic Review of Meta‐Surface Based Antennas for Thz Applications
Authors: Sharma Nipun , Kaur Amrit
Published: September 2024

The growing demand for advanced wireless communication, high‐resolution imaging, and innovative medical applications in the Terahertz (THz) frequency range has driven remarkable developments in meta‐surface‐based antennas. This comprehensive review delves into the cutting‐edge advancements, novel designs, and practical applications of meta‐surfaces in the THz spectrum. The review begins by exploring the materials employed in meta‐surfaces and their crucial role in achieving efficient THz operation. It delves into the realm of polarization diversity, revealing innovative approaches to harnessing the potential of meta‐surfaces for polarization control and conversion. A key area of focus is beam‐steering technology, with a thorough investigation into beam‐steering techniques that have significant implications for enhancing wireless communication, high‐resolution imaging, and the internet of things. The paper highlights the potential of these techniques in addressing real‐world challenges and advancing THz technology. Furthermore, this review provides an in‐depth examination of the innovative antenna designs tailored for THz applications, shedding light on their characteristics and benefits. It also explores the exciting possibilities of THz technology within the medical field, including precise bio sensing and cancer cell detection.
Extracellular vesicles containing GAS6 protect the liver from ischemia-reperfusion injury by enhancing macrophage efferocytosis via MerTK-ERK-COX2 signaling
Authors: Miao Longyu , Yu Chaoqun , Guan Ge , Luan Xiaoyu , Jin Xiaoshuang , Pan Meiqi , Yang Yuzhen , Yan Jiaoyang , Chen Peng , Di Guohu
Published: September 2024

Hepatic ischemia-reperfusion injury (HIRI) is a significant issue during liver transplantation and surgery, contributing to the liver failure or even mortality. Although extracellular vesicles derived from mesenchymal stem cells (MSC-EVs) have shown substantial potentials in cell replacement therapy of various organ ischemia reperfusion injuries (IRIs), the precise mechanisms remain unclear. In this study, we demonstrate that systemic MSC-EVs administration is predominantly absorbed by macrophages, and verified that it could significantly reduce the liver injury and inflammatory response in mice suffering from HIRI. Furthermore, treatment with MSC-EVs induces macrophage polarization toward an anti-inflammatory phenotype. Mechanistically, proteomic profiling reveals an enrichment of growth arrest-specific 6 (GAS6) in MSC-EVs, significantly promoting the activation of myeloid-epithelial-reproductive tyrosine kinase/extracellular regulated protein kinases/cyclooxygenase 2 (MerTK/ERK/COX2) signaling pathway in macrophages and further enhancing their efferocytosis efficiency. Knockdown of GAS6 via lentiviral transfection or inhibition of MerTK using UNC2025 (a MerTK small molecule inhibitor) partially eliminates the protective effects of MSC-EVs on macrophage efferocytosis and liver injury. Overall, our findings support that MSC-EVs enriched GAS6 execute an anti-inflammation effect, highlighting that treatment based on the modulation of macrophage function by MSC-EVs as a promising approach in IRI.
Post-functionalization of alternating π-conjugated copolymers containing fluorene moieties via anodic chlorination using AlCl3
Authors: Kurioka Tomoyuki , Tomita Ikuyoshi , Inagi Shinsuke
Published: September 2024

Fluorene (Fl) derivatives are representative emitting motifs; thus, they are often installed into alternating π-conjugated copolymers (P(Fl-Ar)) as soluble polymeric emitters. Many researchers have focused on modifying the combined arylene units in P(Fl-Ar) derivatives to tune their optoelectronic properties; however, P(Fl-Ar) derivatives that contain fluorene units with functional groups at their sp2 carbons remain limited. Here, we synthesize P(Fl-Ar) derivatives comprising sp2-chlorinated fluorene units via anodic chlorination using aluminum chloride (AlCl3). The introduced chlorine atoms affect the optoelectronic properties of the pristine P(Fl-Ar) derivatives. Compared with the precursor P(Fl-Ar) derivatives, chlorinated P(Fl-Ar) derivatives exhibit longer maximum emission wavelengths.
Subclinical impairment of the left atrium is associated with MRI-based lung volume but not with parameters from pulmonary function testing
Authors: Wintergerst Charlotte , Lorbeer Roberto , Mujaj Blerim , Bulwer Bernard E. , Rospleszcz Susanne , Askani Esther , Schulz Holger , Karrasch Stefan , Peters Annette , Schlett Christopher L. , Bamberg Fabian , von Krüchten Ricarda
Published: September 2024

Left atrial (LA) physiology and hemodynamics are intimately connected to cardiac and lung function in health and disease. This study examined the relationship between MRI-based left atrial (LA) size and function with MRI-based lung volume and pulmonary function testing (PFT) parameters in the population-based KORA study cohort of 400 participants without overt cardiovascular disease. MRI quantification assessed LA size/function in sequences with and without ECG synchronization, alongside lung volume. Regression analysis explored the relationship of LA with MRI lung volume and PFT parameters. Among 378 participants (average age 56.3 ± 9.2 years; 42.3% women), non-gated LA size averaged 16.8 cm2, while maximal and minimal LA size from gated measurements were 19.6 cm2 and 11.9 cm2 respectively. The average MRI-derived lung volume was 4.0 L, with PFT showing a total lung capacity of 6.2 L, residual lung volume of 2.1 L, and forced vital capacity of 4.1 L. Multivariate regression analysis, adjusted for age, gender, and cardiovascular risk factors, revealed an inverse association between maximum LA size, non-gated LA, and LA area fraction with lung volume (ß = − 0.03, p = 0.006; ß = − 0.03, p = 0.021; ß = − 0.01, p = 0.012), with no significant association with PFT parameters. This suggests that MRI-based assessment may offer greater sensitivity in detecting subclinical LA impairment than PFT.
Adherence to non-pharmaceutical interventions following COVID-19 vaccination: a federated cohort study
Authors: Rader Benjamin , Sehgal Neil K. R. , Michelman Julie , Mellem Stefan , Schultheiss Marinanicole D. , Hoddes Tom , MacFarlane Jamie , Clark Geoff , O’Banion Shawn , Eastham Paul , Tuli Gaurav , Taylor James A. , Brownstein John S.
Published: September 2024

In pandemic mitigation, strategies such as social distancing and mask-wearing are vital to prevent disease resurgence. Yet, monitoring adherence is challenging, as individuals might be reluctant to share behavioral data with public health authorities. To address this challenge and demonstrate a framework for conducting observational research with sensitive data in a privacy-conscious manner, we employ a privacy-centric epidemiological study design: the federated cohort. This approach leverages recent computational advances to allow for distributed participants to contribute to a prospective, observational research study while maintaining full control of their data. We apply this strategy here to explore pandemic intervention adherence patterns. Participants (n = 3808) were enrolled in our federated cohort via the “Google Health Studies” mobile application. Participants completed weekly surveys and contributed empirically measured mobility data from their Android devices between November 2020 to August 2021. Using federated analytics, differential privacy, and secure aggregation, we analyzed data in five 6-week periods, encompassing the pre- and post-vaccination phases. Our results showed that participants largely utilized non-pharmaceutical intervention strategies until they were fully vaccinated against COVID-19, except for individuals without plans to become vaccinated. Furthermore, this project offers a blueprint for conducting a federated cohort study and engaging in privacy-preserving research during a public health emergency.
O-GlcNAcylation mediates Wnt-stimulated bone formation by rewiring aerobic glycolysis
Authors: You Chengjia , Shen Fangyuan , Yang Puying , Cui Jingyao , Ren Qiaoyue , Liu Moyu , Hu Yujie , Li Boer , Ye Ling , Shi Yu
Published: September 2024

Wnt signaling is an important target for anabolic therapies in osteoporosis. A sclerostin-neutralizing antibody (Scl-Ab), that blocks the Wnt signaling inhibitor (sclerostin), has been shown to promote bone mass in animal models and clinical studies. However, the cellular mechanisms by which Wnt signaling promotes osteogenesis remain to be further investigated. O-GlcNAcylation, a dynamic post-translational modification of proteins, controls multiple critical biological processes including transcription, translation, and cell fate determination. Here, we report that Wnt3a either induces O-GlcNAcylation rapidly via the Ca2+-PKA-Gfat1 axis, or increases it in a Wnt-β-catenin-dependent manner following prolonged stimulation. Importantly, we find O-GlcNAcylation indispensable for osteoblastogenesis both in vivo and in vitro. Genetic ablation of O-GlcNAcylation in the osteoblast-lineage diminishes bone formation and delays bone fracture healing in response to Wnt stimulation in vivo. Mechanistically, Wnt3a induces O-GlcNAcylation at Serine 174 of PDK1 to stabilize the protein, resulting in increased glycolysis and osteogenesis. These findings highlight O-GlcNAcylation as an important mechanism regulating Wnt-induced glucose metabolism and bone anabolism.
Synthesis, crystal structure analysis, computational modelling and evaluation of anti-cervical cancer activity of novel 1,5-dicyclooctyl thiocarbohydrazone
Authors: Shukla Soni , Trivedi Prince , Johnson Delna , Sharma Pulkit , Jha Abhinav , Khan Habiba , Thiruvenkatam Vijay , Banerjee Monisha , Bishnoi Abha
Published: September 2024

Thiocarbazones as bioactive and pharmaceutical intermediates exhibiting diverse biological and pharmacological activities.
Controlling nanocluster growth through nanoconfinement: the effect of the number and nature of metal–organic framework functionalities
Authors: King James , Lin Zhipeng , Zanca Federica , Luo Hui , Zhang Linda , Cullen Patrick , Danaie Mohsen , Hirscher Michael , Meloni Simone , Elena Alin M. , Szilágyi Petra Á.
Published: September 2024

Synthesis of active nanoclusters through confinement in pores of functional frameworks is an attractive approach as it allows for geometry control and potential surface-chemistry modification simultaneously.
Latest progress and challenges associated with lithium-ion semi-solid flow batteries: a critical review
Authors: He Man , Zhou Xuelong , Liu Jiapeng
Published: September 2024

A critical review of research progress in lithium-ion semi-solid flow batteries (Li-SSFBs) in aqueous and non-aqueous systems.
Elucidation of the exchange interaction in photoexcited three-spin systems – a second-order perturbational approach
Authors: Franz Michael , Neese Frank , Richert Sabine
Published: September 2024

This work focusses on calculating exchange couplings in multi-spin systems, where a difference-dedicated perturbation theory method is developed that uses the possibility of state-averaging in preceeding CASSCF calculations to improve the accuracy.
PEDOT-based stretchable optoelectronic materials and devices for bioelectronic interfaces
Authors: Li Weizhen , Li Yiming , Song Ziyu , Wang Yi-Xuan , Hu Wenping
Published: September 2024

This review summarized the strategies and mechanisms for improving the conductivity, mechanical properties and stability of PEDOT:PSS, as well as the reliable micropatterning technologies and optoelectronic devices applied at bio-interfaces.
Protein Complexations and Amyloid Fibrilization as Novel Approaches to Improve Techno-Functionality of Plant-Based proteins
Authors: Khan Zakir Showkat , Mandliya Shubham , Suri Shweta , Bhinder Seerat , Choudhary Pintu , Mandal Shreya , Chandla Narender Kumar , Kar Koyel , Toker Ömer Said , Smaoui Slim , Bhat Mohmad Sayeed , Mishra Hari Niwas , Sodhi Navdeep Singh , Dhillon Bhavnita , Aijaz Thameed
Published: September 2024

Proteins play a critical role in human diet and nutrition. Plant proteins hold immense potential in the development of sustainable, ethical, and low-cost future foods to achieve food security. Designing...
Fish scale utilized biogenic synthesis of CuO nanoparticles: effect of calcination temperature on structural properties and antibacterial activity
Authors: Chowdhury Fariha , Bin Mobarak Mashrafi , Hakim Mahmuda , Uddin Md. Najem , Hossain Md. Sahadat , Akhter Umme Sarmeen , Islam Dipa , Ahmed Samina , Das Harinarayan
Published: September 2024

Fish scale utilized biogenic synthesis of CuO nanoparticles for antibacterial application.
Atypical hydrogenation selectivity of platinum by reactive environment modulation
Authors: Cazemier Jurjen , Zaarour Moussa , Komaty Sarah , Lavrik Polina , Aguilar Tapia Antonio , Veeranmaril Sudheesh Kumar , Hazemann Jean-Louis , Ruiz-Martinez Javier
Published: September 2024

Non-polar reactive environment maintained by Silicalite-1 pore walls and toluene solvent favors CC versus CO hydrogenation over confined Pt particle of Pt@S-1 giving rise to excellent selectivity.
Pd-catalyzed S-glycosylation of cysteine-containing peptides at room temperature
Authors: Shen Linhua , Le Bideau Franck , Chen Gong , Messaoudi Samir
Published: September 2024

This study reports the synthesis of thioglycopeptides via a Pd-catalyzed coupling of cysteine-containing peptides with iodoglycals. A variety of cysteine-containing peptides and other thiol nucleophiles including thiosugars and thiophenols were used.
Lipid lateral diffusion: mechanisms and modulators
Authors: Sharma V. K. , Srinivasan H. , Gupta J. , Mitra S.
Published: September 2024

Various models of lipid lateral diffusion which gives distinct shapes of quasielastic neutron scattering spectra: ballistic motion – Gaussian, continuous/jump diffusion – Lorentzian, and confined diffusion – combined elastic and Lorentzian.
Traveling waves at the surface of active liquid crystals
Authors: Gulati Paarth , Caballero Fernando , Kolvin Itamar , You Zhihong , Marchetti M. Cristina
Published: September 2024

The interface of an active liquid crystal can support travelling waves. We derive dispersion relations from a linear theory and compute the dynamical structure factor from continuum simulations.
Phase behavior of polymer dispersed liquid crystals, comparison between mean-field theory, and coarse-grained molecular dynamics simulations
Authors: Fall William S. , Kolli Hima Bindu , Mukherjee Biswaroop , Chakrabarti Buddhapriya
Published: September 2024

We report a simulation methodology to quantitatively predict the thermodynamic behaviour (phase diagrams) of polymer mixtures, that exhibit phases with broken orientational symmetry.
Comprehensive compensation method for co‐phase power supply in electrified railways based on V/v transformer and electromagnetic single‐phase var compensator
Authors: Yan Xiangwu , Wu Weilin , Shao Chen , Peng Weifeng
Published: September 2024

To solve the problem of negative‐sequence and reactive power in electrified railway, this paper proposes a comprehensive compensation method based on V/v transformer and electromagnetic single‐phase var compensator (ESVC) for co‐phase power supply. First, based on the principles of static var generator and single‐phase rotary phase shifting transformer, the topology and model of ESVC have been established, and the compensation mechanism has been analysed. Second, the topological structure and mathematical model of co‐phase power comprehensive compensation device (CPCD) are put forward based on the principles of V/v transformer and ESVC, and the operation mode of CPCD in multiple scenarios is designed. Then the strategy of CPCD with double closed loop control is analysed: corresponding compensation mode is selected according to negative‐sequence unbalance degree and expected power factor value. In this strategy, the compensated current output by ESVC is taken as the quantity of external loop control, and the rotation angle of ESVC is taken as the quantity of internal loop control to realize double‐closed loop control of CPCD. Finally, the comprehensive CPCD compensation model is built on the simulation platform and validated the accuracy of the mathematical model and the effectiveness of the control strategy.
Investigating the relative accuracy of GPS, GSM and CDR data for inferring spatiotemporal travel trajectories
Authors: Zannat Khatun E. , Choudhury Charisma F. , Hess Stephane , Watling David
Published: September 2024

The potential of passively generated big data sources in transport modelling is well‐recognised. However, assessing their accuracy and suitability for policymaking remains challenging due to the lack of ground‐truth (GT) data for validation. This study evaluates the accuracy of inferring human mobility patterns from global positioning system (GPS), call detail records (CDR), and global system for mobile communication (GSM) data. Using outputs from an agent‐based simulation platform (MATSim) as ‘synthetic GT’ (SGT), synthetic GPS, CDR, and GSM data were generated, considering their positional disturbances and conventional spatiotemporal resolutions. Mobility information, including activity location, departure time, and trajectory distance, derived from the synthetic data, was compared with SGT to evaluate the accuracy of passive trajectory data at both disaggregate and aggregate levels. The results indicated a higher accuracy of GPS data in identifying stay locations at high resolution. But, GSM data at a lower resolution effectively accounted for over 80% of the variability in stay locations. Comparisons of departure time distribution and travel distance revealed higher measurement errors in GSM and CDR data than in GPS data. The proposed simulation‐based accuracy assessment framework will aid transport planners select the most suitable data for specific analyses and understand the potential margin of error involved.
The accessibility of public electric vehicle (EV) charging infrastructure: Evidence from the cities of Nottingham and Frankfurt
Authors: Arslangulova Botakoz , Galanakis Kostas
Published: September 2024

The distribution of public electric vehicle (EV) charging infrastructure is a widespread approach for promoting EV adoption and decarbonising transportation. A significant amount of literature explores the distribution of EV charging points at a country scale, but there is a lack of studies focusing on a district scale. This study aims to contribute to this gap by gaining insights into the distribution of EV charging points per district within cities, such as Nottingham and Frankfurt. The study investigates the current distribution of EV charging points across 38 postcode districts in Frankfurt and 9 postcode districts in Nottingham, using geographical data analysis and a linear regression approach. The following factors in response to the number of EV charging points per postcode district (ZIP code) are examined: the percentage of apartment buildings/floor area ratio, the availability of amenities, population, charging capacity (kW), area size, strategic approaches, including policy goals and principles. The results reveal disparities in access to EV charging infrastructure across districts and underscore the importance of expanding EV charging networks not only in districts located near urban centres or those with high availability of amenities but also ensuring that users without home charging options are not left behind.
A high gain quasi Z‐source based full‐bridge isolated DC‐DC converter with extendable structure for grid‐tied/standalone PV system
Authors: Nallaiya Gounder Kanagaraj , Murugesan Ramasamy , Madhaiyan Vijayakumar , Aldosari Obaid
Published: September 2024

A multi‐input single‐output converter that is based on the impedance network and the standard isolated converters is presented. The topology is named quasi Z‐source full‐bridge isolated converter (qZSFBIC). The proposed topology helps to integrate various renewable power generation systems with a common three‐phase grid‐connected inverter. It was also capable of providing isolation between the input and output circuits in addition to the boost function. The integration of multiple energy sources is achieved using fewer components than conventional converters. As a result, it achieves greater conversion efficiency and has improved circuit characteristics. It offers a larger voltage control range as compared to the conventional ZSC and enhances the input‐output voltage transformation ratio. To determine whether or not the suggested converter is technically feasible, the circuit architecture, operating principle, control mechanism, and simulation results are presented. An improved proportional resonant‐second order general integrator (IPR‐SOGI) has been utilized to provide a gating signal for the voltage source inverter. The 1.5 kW, 400 V, 50 Hz model is designed to authenticate the proposed scheme with qZSFBIC. The results showed that the proposed converter offered double the time of boosting than the conventional ZSC converter and the conversion efficiency is around 89%.
A probabilistic approach for optimal integration of EVs and RES using artificial hummingbird algorithm in distribution network
Authors: Bilal Mohd , Gupta Saket , Bokoro Pitshou N. , Sharma Gulshan
Published: September 2024

The adoption of electric vehicles (EVs) is crucial for reducing pollution from traditional automobiles. Strategic placement of electric vehicle charging stations (EVCS) is needed to meet demand while minimizing impacts on the electrical grid. This article outlines a practical method to identify optimal EVCS locations within the IEEE 69 bus system. The transition to EVs affects the electrical distribution network, requiring consideration of voltage regulation, power loss, stability, reliability, and energy loss costs when deploying EVCS. To manage increased energy demands, the article recommends integrating solar distributed generation (SDG) units at strategic points in the network, creating a self‐sustaining system. The study explores the resilience of the distribution system with EVCS and SDGs through eight case studies (CS), examining EVCS deployment scenarios with and without SDG integration. The impact of slow and fast EV charging on system objectives is also analysed. The artificial hummingbird algorithm is used to solve the allocation problem, with results compared to other optimization methods. Notably, active power loss decreased from 224.67 kW (CS1) to 53.35 kW (CS8), and reactive power loss was reduced by 71.4% in CS8 compared to CS1.
Study on photovoltaic primary frequency control strategy at different time scales
Authors: Wang Lei , Zhang Runtao , Zang Qian , Cheng Ziwei , Su Can , Li Zhiwei , Zhang Hao
Published: September 2024

During the participation of photovoltaics in grid frequency regulation, different frequency regulation tasks are required at different time scales. The grid demands that photovoltaics (PVs) improve steady‐state frequency when facing short‐term load fluctuations, while also enhancing frequency response to long‐term environmental and load changes. Therefore, this study takes different time scales as the starting point. First, a two‐stage PV grid‐connected inverter generation system model is established, and an overall control strategy is proposed. Next, for short‐term time scales, a virtual inertia strategy based on direct current (DC) voltage droop control is proposed to utilize the energy storage effect of DC capacitors to suppress frequency fluctuations. For long‐term time scales, a strategy for controlling the variable reactive power reserve capacity is proposed to address the inadequacy of frequency regulation caused by traditional fixed de‐rating rate strategies and redundant standby power. Finally, the effectiveness of the proposed strategies is verified through model validation in MATLAB/Simulink. Simulation results demonstrate the effectiveness of the strategies at different time scales, aiding in improving grid frequency response.
Coordinated planning of thermal power, wind power, and photovoltaic generator units considering capacity electricity price
Authors: Xu Ye , Liu Wenxia , Yang Benhao
Published: September 2024

With the implementation of China's carbon reduction policies, the role of thermal power units will transition to a regulating power source. Hence, the electricity market fails to accurately reflect the capacity value of thermal power units, resulting in potential future losses for these units. Therefore, it is imperative to establish a rational capacity compensation mechanism that guarantees the revenue of thermal power units and offers effective investment and construction signals. Therefore, this paper proposes a capacity compensation mechanism for thermal power units based on effective capacity. To achieve this, a two‐layer power source planning model is established. At the upper level of the model, the installed capacity and capacity price of various types of power sources are optimized, while minimizing the operating costs of the planning horizon year under constraints such as annual net profit of units. The lower level focuses on the operation of typical days, optimizing the output of various types of units. Through case analysis, it can be concluded that the proposed model can achieve coordinated planning of capacity and capacity prices for various types of units, effectively ensuring the economic efficiency of the system while safeguarding the revenue of each unit.
Process deviation detection method for dry‐type air‐core reactor based on power factor frequency characteristics
Authors: Wang Yonghong , Ge Xingyu , Zhuang Yu , Meng Zihe , Zhao Chunming
Published: September 2024

To address the problem that the process deviation of dry‐type air‐core reactors cannot be effectively detected, electrical parameters of reactor are numerically analysed at different frequencies. A new method of process deviation detection by the power factor frequency characteristic is proposed. Considering on‐site power frequency interference, a harmonic analysis method is proposed, which is based on the integer multiple of the power frequency cycle, to calculate the power factor. The results show that the resistance loss remains relatively constant at power frequency and gradually increases at higher frequencies with the number of deviation turns increases. The eddy current loss remains basically unchanged at different turn deviations and frequencies. The change laws of resistance loss and the resistance loss power factor are the same. In a double logarithmic coordinate system, resistance loss power factor changes from linear to non‐linear. The non‐linearity degree can be used to detect the process deviation. The test results are consistent with the theory, and the correctness of the detection method is verified.
Are light curve classification metrics good proxies for SN Ia cosmological constraining power?
Authors: Malz Alex I. , Dai Mi , Ponder Kara A. , Ishida Emille E. O. , Gonzalez-Gaitain Santiago , Durgesh Rupesh , Krone-Martins Alberto , de Souza Rafael S. , Kennamer Noble , Sreejith Sreevarsha , Galbany Lluís ,   The LSST Dark Energy Science Collaboration (DESC),   The Cosmostatistics Initiative (COIN)
Published: September 2024

Context. When selecting a light curve classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process.

Aims. This study tests the assumption that light curve classification metrics are an appropriate proxy for cosmology metrics.

Methods. We emulated photometric SN Ia cosmology light curve samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates.

Results. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter.

Conclusions. Based on these findings, we discourage any exclusive reliance on light curve classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.