bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metalle Ex‐Machina
Authors: Raabe Dierk 
Published: March 2024

ZusammenfassungKünstliche Intelligenz (KI) kann zur Entwicklung von Materialien unter Einbeziehung ihrer Herstellung, Verarbeitung, inneren Strukturdefekte und chemischen Komplexität eingesetzt werden. Heute muss sie aber meist noch mit spärlichen Trainingsdaten zurechtkommen. Hybrid‐Methoden können diese Datenbasis in Verbindung mit aktiv geleiteten Experimenten verbessern. Sie schließen thermodynamische und kinetische Datenbanken, kombinatorische Hochdurchsatzexperimente, Ab‐initio‐Daten und automatisierte Sprachverarbeitung ein. Solche KI‐Methoden für das Materialdesign können auch mit physikalischen Modellen kombiniert werden. Bei allen Ansätzen ist die Identifizierung geeigneter Deskriptoren wichtig, die das gesuchte Material zu finden helfen. Aktuell ist die Verbesserung der Kausalitätsermittlung bei der Materialentwicklung mittels KI ein wichtiges Forschungsfeld. Dies gilt für die effizientere Entdeckung potenziell verheißungsvoller Datenausreißer sowie die Vorhersage außerhalb der Trainingsbereiche der KI.
Understanding local interactions in freestanding flexible poly(vinylidene fluoride)/poly(3,4‐ethyelenedioxythiophene):poly(styrelenesulfonate) films using impedance, Raman, and X‐ray absorption spectroscopy
Authors: Jangra Mandeep , Gupta Mukul , Hussain Shamima 
Published: March 2024

AbstractThe local interaction within poly(vinylidene fluoride)/poly(3,4‐ethyelenedioxythiophene):poly(styrelenesulfonate) (PVDF/PEDOT:PSS) composite films has been explored in this study. Vibrational and impedance spectroscopy were used extensively to investigate the potential interactions within the moieties of PVDF and PEDOT:PSS in the composite. The increased concentration of PEDOT:PSS used as additives enhanced the dielectric constant of the composite films significantly. Both the AC conductivity and the estimated mobility also increased in the composite films with increasing additives. X‐ray absorption spectroscopy gave an insight into the local chain interactions within the polymer composite films. A shift in the C K‐edge toward higher energy confirmed the local interaction of the polymer moieties, suggesting a change in the polymer chain structure due to the possible association of moieties.
Decision‐making for bilateral risk‐reducing mastectomy for an increased lifetime breast cancer risk: A qualitative metasynthesis
Authors: Torrisi Christa , Wareg Nuha K. , Anbari Allison Brandt 
Published: March 2024

AbstractObjectivePrevivor is a term applied to a person with an identified, elevated lifetime cancer risk but without an actual cancer diagnosis. Previvorship entails the selection of risk management strategies. For women with a genetic mutation that increases their predisposition for a breast cancer diagnosis, bilateral risk‐reducing mastectomy (BRRM) is the most effective prevention strategy. However, BRRM can change a woman's breast appearance and function. The purpose of this qualitative metasynthesis (QMS) was to better understand the decision‐making process for BRRM among previvors.MethodsA theory‐generating QMS approach was used to analyze and synthesize qualitative findings. Research reports were considered for inclusion if: (1) women over 18 years of age possessed a genetic mutation increasing lifetime breast cancer risk or a strong family history of breast cancer; (2) the sample was considering, or had completed, BRRM; (3) the results reported qualitative findings. Exclusion criteria were male gender, personal history of breast cancer, and research reports which did not separate findings based on cancer diagnosis and/or risk‐reduction surgery.ResultsA theory and corresponding model emerged, comprised of seven themes addressing the decision‐making process for or against BRRM. While some factors to decision‐making were decisive for surgery, others were more indefinite and contributed to women changing, processing, or suspending their decision‐making for a period of time.ConclusionsRegardless of the decision previvors make about BRRM, physical and psychosocial well‐being should be considered and promoted through shared decision‐making in the clinical setting.
Characteristics and influencing factors of demoralization in patients with lung cancer: A latent class analysis
Authors: Hong Yu Ting , Ye Bi Qin , Lin Jia Ling , Chen Qiu Hong , Zhang Juan , Chen Wei‐Ti , Huang Fei Fei 
Published: March 2024

AbstractObjectiveDemoralization has garnered increasing attention in recent years as a significant psychological distress. This study aims to identify latent classes of demoralization in lung cancer patients using Latent Class Analysis (LCA) from a person‐centered perspective and to explore the factors influencing the latent classes of demoralization.MethodsA cross‐sectional study using convenience sampling was conducted among 567 lung cancer patients in three tertiary hospitals in China. LCA was employed to classify heterogeneous classes of demoralization. Multinomial logistic regression analyses were performed to explore the associations between demographic and clinical characteristics, as well as physical symptoms, resilience, family function, and coping strategies, with class membership in the identified heterogeneous subgroups of lung cancer patients.ResultsThree latent classes of demoralization were identified: the high demoralization group (Class 1, 14.8%), the moderate demoralization‐distress and helplessness group (Class 2, 37.2%), and the low demoralization group (Class 3, 48.0%). In comparison to Class 3, lung cancer patients with hypertension, higher core symptom burden, poorer resilience, dysfunctional family dynamics, and resignation coping were more likely to belong to Class 1 and Class 2.ConclusionsThe demoralization patterns in lung cancer patients were varied. Targeted intervention should be developed based on the characteristics of each class, and timely attention should be paid to high‐risk patients.
Impact of sensory reweighting strategies on postural control using the sensory organization test in older adults with and without fall risks
Authors: Sung Paul , Rowland Phyllis 
Published: March 2024

AbstractBackgroundThe Sensory Organization Test (SOT), an integral part of computerized dynamic posturography, plays a crucial role in evaluating postural stability under various altered sensory conditions. Despite its importance, there have been noted inconsistencies in the results pertaining to equilibrium and sensory system evaluations. This study aimed to compare four sensory analysis scores and equilibrium indices between older adults with and without fall risks.MethodsThe study included 34 participants identified as being at risk of falls and 42 control subjects. To categorize individuals between the two groups, we performed area under the receiver operating characteristic curve analyses. This classification was based on scores from the Modified Falls Efficacy Scale (MFES) and the composite scores obtained from the SOT. In addition, we used the Tampa Scale for Kinesiophobia (TSK) as well as the level of disability.ResultsThe fall risk group demonstrated significantly higher TSK scores (39.39 ± 15.24 for control group vs. 54.65 ± 10.70 for fall risk group; t = −5.09, p = 0.001). The groups demonstrated a significant interaction on the equilibrium index (F = 4.59, p = 0.03), which was lower in the fall risk group in Condition 6 with a moving surface and surround and eyes open (t = 2.29, p = 0.01). The fall risk group demonstrated a higher somatosensory score (t = −1.73, p = 0.04).ConclusionsThe fall risk group had a lower equilibrium index score in Condition six of the SOT, which was useful for identifying deficits in vestibular function to integrate sensory information under challenging conditions for postural adaptation. This strategy suggested that the fall risk group could compensate for their risk of falls by utilizing more effective somatosensory reweighting strategies compared with the control group.
Phenotype versus genotype to optimize cancer dosing in the clinical setting—focus on 5‐fluorouracil and tyrosine kinase inhibitors
Authors: Martin Jennifer H. , Galettis Peter , Flynn Alex , Schneider Jennifer 
Published: March 2024

AbstractCancer medicines often have narrow therapeutic windows; toxicity can be severe and sometimes fatal, but inadequate dose intensity reduces efficacy and survival. Determining the optimal dose for each patient is difficult, with body‐surface area used most commonly for chemotherapy and flat dosing for tyrosine kinase inhibitors, despite accumulating evidence of a wide range of exposures in individual patients with many receiving a suboptimal dose with these strategies. Therapeutic drug monitoring (measuring the drug concentration in a biological fluid, usually plasma) (TDM) is an accepted and well validated method to guide dose adjustments for individual patients to improve this. However, implementing TDM in routine care has been difficult outside a research context. The development of genotyping of various proteins involved in drug elimination and activity has gained prominence, with several but not all Guideline groups recommending dose reductions for particular variant genotypes. However, there is increasing concern that dosing recommendations are based on limited data sets and may lead to unnecessary underdosing and increased cancer mortality. This Review discusses the evidence surrounding genotyping and TDM to guide decisions around best practice.
A comparison of two statistical postprocessing methods for heavy‐precipitation forecasts over India during the summer monsoon
Authors: Angus Michael , Widmann Martin , Orr Andrew , Ashrit Raghavendra , Leckebusch Gregor C. , Mitra Ashis 
Published: March 2024

AbstractAccurate ensemble forecasts of heavy precipitation in India are vital for many applications and essential for early warning of damaging flood events, especially during the monsoon season. In this study we investigate to what extent Quantile Mapping (QM) and Ensemble Model Output Statistics (EMOS) statistical postprocessing reduce errors in precipitation ensemble forecasts over India, in particular for heavy precipitation. Both methods are applied to day‐1 forecasts at 12‐km resolution from the 23‐member National Centre for Medium Range Weather Forecasting (NCMRWF) global ensemble prediction system (NEPS‐G). By construction, QM leads to distributions close to the observed ones, while EMOS optimizes the ensemble spread, and it is not a priori clear which is better suited for practical applications. The methods are therefore compared with respect to several key aspects of the forecasts: local distributions, ensemble spread, and skill for forecasting precipitation amounts and the exceedance of heavy precipitation thresholds. The evaluation includes rank histograms, Continuous Ranked Probability Skill Scores (CRPSS), Brier Skill Scores (BSS), reliability diagrams, and receiver operating characteristic. EMOS performs best not only with respect to correcting under‐ or overdispersive ensembles, but also in terms of forecast skill for precipitation amounts and heavy precipitation events, with positive CRPSS and BSS in most regions (both up to about 0.4 in some areas), while QM in many regions performs worse than the raw forecast. QM performs best with respect to the overall local precipitation distributions. Which aspects of the forecasts are most relevant depends to some extent on how the forecasts are used. If the main criteria are the correction of under‐ or overdispersion, forecast reliability, match between the forecasted distribution for individual days and observations (CRPSS), and the skill in forecasting heavy‐precipitation events (BSS), then EMOS is the better choice for postprocessing NEPS‐G forecasts for short lead times.
Off‐policy reinforcement learning algorithm for robust optimal control of uncertain nonlinear systems
Authors: Amirparast Ali , Kamal Hosseini Sani S. 
Published: March 2024

AbstractIn this article an optimal control scheme is proposed to solve robust control problem for matched and unmatched system. In the proposed optimal approach the value functions are designed such that the obtained optimal control law guarantees asymptotic stability of the uncertain nonlinear system. Since the proposed robust optimal control problem is not straightforward to solve, an off‐policy reinforcement‐learning algorithm based on neural networks approximation is developed to obtain robust optimal control law iteratively. The robust control law for matched uncertain systems can be achieved via proposed off‐policy learning algorithm without requiring exact knowledge of system's dynamics. The advantages of the proposed robust optimal controller are verified by comparative simulations on an uncertain model of a car suspension system and a mathematical nonlinear model.
Dynamic event‐triggered fixed‐time average consensus for general linear multi‐agent systems under switching topologies
Authors: Ning Xiaogang , Li Zonggang , Chen Yinjuan , Du Yajiang 
Published: March 2024

AbstractThis article studies the practical fixed‐time average consensus problem of general linear multi‐agent systems under switching topologies. First, a distributed fixed‐time consensus control protocol based on dynamic event‐triggered mechanism is designed by using the local information exchange between neighboring agents. The protocol introduces an internal dynamic variable and the triggering condition changes in real time based on the dynamic variable obtained online, which can significantly reduce the number of triggering events and effectively decrease the energy consumption of the multi‐agent system. Then, the sufficient conditions for the multi‐agent system to solve the practical fixed‐time average consensus problem are given, and it is proved that there is no Zeno behavior in the system. Furthermore, a self‐triggered control scheme is proposed such that the neighboring agents communicate with each other only when one of them is triggered. In other words, this scheme does not require continuous communication between neighboring agents and thus reduces communication cost of the system. Finally, the simulation results verify the effectiveness of the proposed method.
Dynamic event‐triggered orbit coordination for spacecraft formation via a self‐learning sliding mode control approach
Authors: Jia Qingxian , Gao Junnan , Wu Yunhua , Liao He , Zhang Chengxi , Wu Jin 
Published: March 2024

SummaryThis article investigates the issue of orbit coordination control for a class of multi‐spacecraft formation systems in presence of limited communication and external disturbance. To solve the limitation of communication sources, a dynamic event trigger (DET) mechanism is developed to reduce the communication frequency between the follower spacecrafts. Subsequently, we explore a robust DET mechanism‐based distributed self‐learning sliding mode control design, in which a variable learning intensity‐based iterative learning algorithm is designed to approximate and compensate space perturbation. This approach can guarantee an event triggering sequence without Zeno phenomenon and accurate coordination control for formation configuration simultaneously. Compared with the traditional event‐triggered control and other state‐of‐the‐art approaches, the distributed DET control scheme achieves higher control accuracy of formation configuration meanwhile requires less communication resource. Finally, a series of numerical simulations demonstrate the feasibility and superiority of the event triggered control method.
Robust networked ℒ2$$ {\mathcal{L}}_2 $$‐stable wireless SINR control
Authors: Wigren Torbjörn 
Published: March 2024

AbstractIn the new radio wireless system, use cases for automation, automotive safety and virtual reality will require transmission and reception with very high reliability and very low latency. Radio channel fading and the onset of strong interference combine to make this task hard, which require new methods for mitigation. The alternative studied in this article is to introduce fast signal to interference and noise ratio (SINR) feedback control supported by feed‐forward control from interference estimates, thereby improving the robustness of the networked loop. This challenging nonlinear networked control problem involves delay and coarse control signal quantization. To guarantee that the deployed feedback loop instances are always well‐behaved, the SINR feedback controller is designed to be globally ‐stable using a new loop gain—loop delay product condition, derived from the classical circle criterion. Monte‐Carlo simulations show that the proposed controller is able to reduce the SINR back‐off significantly.
Mix with the crowd? Craft‐based campaigns and the value of distinctiveness in campaign success
Authors: Wolfe Marcus T. , Blaseg Daniel , Patel Pankaj C. , Chan Richard 
Published: March 2024

AbstractResearch SummaryDistinctiveness is an essential element of crafts. Building on optimal distinctiveness theory, we examine the relationship between craft‐based ventures, distinctiveness, and crowdfunding performance. Using a sample of 10,915 craft campaigns and 429,290 non‐craft campaigns, we find that craft‐based campaigns have higher distinctiveness but realize lower success through distinctiveness. Additionally, craft‐based campaigns with a higher risk index have lower distinctiveness, those with higher strategy breadth have higher distinctiveness, and those with lower cognitive complexity have higher distinctiveness. The findings have implications for crafts‐based entrepreneurs in leveraging distinctiveness and the value of lowering perceptions of distinctiveness through elements of strategic entrepreneurship—strategy breadth and cognitive complexity.Managerial SummaryOur study aids craft‐based entrepreneurs in presenting their ventures in crowdfunding contexts. We find that increasing the distinctiveness of craft‐based ventures results in lower crowdfunding campaign performance. Additionally, our results indicate that craft‐based campaigns that have higher risk have lower levels of distinctiveness. Conversely, we find that craft‐based campaigns with higher levels of strategic breadth and lower levels of cognitive complexity exhibit higher levels of distinctiveness. These findings have important implications regarding best practices related to how craft‐based entrepreneurs can best present their ventures within crowdfunding contexts. Specifically, our results indicate that craft‐based ventures can realize better crowdfunding performance via lower levels of distinctiveness within their campaigns.
An Eco‐Friendly Approach for Determination of Lead in Biological Samples after Deep Eutectic Solvent Extraction
Authors: Germer Fabiana Luvizon , Lacerda Elenice Hass Caetano , da Silva Macedo Eduardo , Chaves Eduardo Sidinei 
Published: March 2024

AbstractThe present research proposes investigating deep eutectic solvents for extracting Pb from biological samples for further determination by GF AAS. Among the synthesized solvents, the DES obtained from choline chloride and oxalic acid (ChCl : Ox) in a molar ratio 1 : 1 presented the best lead (Pb) extraction efficiency. Subsequently, it was characterized by Fourier Transform Infrared Spectroscopy (FTIR). For extraction, the optimized conditions were: 40 mg of sample, 400 μL of DES (ChCl : Ox) added, and 30 min at 95±5 °C. The supernatant was diluted, and the Pb was determined by GF AAS. The optimized instrumental conditions for Pb determination were 900 °C and 2100 °C, pyrolysis and atomization temperatures, respectively, using Pd as a chemical modifier. The limits of detection and quantification were 0.04 and 0.12 μg g−1, respectively. The method's accuracy was evaluated by analyzing the certificate reference materials, and good agreement was obtained between the determined and certificate values. The greenness of the proposed method was evaluated by green star and eco‐scale metrics. Thus, the proposed method proved simple, efficient, and eco‐friendly for determining Pb in biological samples.
Molecular Interactions of Sodium Dodecyl Sulphate with a Sulpha Drug and its Nanoaggregates in Aqueous System
Authors: Singh Harpreet , Raj Tilak , Kumar Sood Ashwani , Singh Banipal Tarlok , Singh Gagandeep , Bahadur Indra , Mohammad Faruq 
Published: March 2024

AbstractInteraction study between sulfanilamide (SM) and sodium dodecyl sulfate (SDS) in an aqueous environment has been conducted using electrical conductivity, emission, and absorption spectroscopy techniques. Conductivity measurements were performed over the temperature range of (288.15 to 318.15) K and SM concentrations ranging from (c=0.005 to 0.03) mol ⋅ L−1. Thermodynamic parameters: Gibbs free energy (ΔGom), enthalpy (ΔHom), and entropy (ΔSom) associated with micellization have been calculated. To further investigate the interactions between (SM and SDS), the absorption and emission spectroscopy were employed at premicellar concentrations of SDS. Resulting SM‐SDS conjugate was then utilized to examine its interaction behavior with electrolytes and vitamins commonly found in biofluids namely chlorides and sulfates of sodium, potassium, magnesium, and calcium, along with L‐ascorbic acid (LAA) and nicotinic acid (NA). Moreover, SM drug has been transformed into its nanoaggregates (SMNA). These nanoaggregates have been characterized using dynamic light scattering (DLS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Interactions between SMNA‐SDS conjugates were also studied in the presence of the above‐mentioned electrolytes and vitamins. The findings of this study have been interpreted within the context of the interactions occurring in the solution phase. This research provides valuable insights into the complicated interactions between SM, SDS, electrolytes, and vitamins in aqueous system.
Theoretical, DNA/BSA Binding, Molecular Docking and In Vitro Cytotoxicity Studies of Homoleptic Metal(II) Complexes Derived from 2‐Formylpyridine‐Based Ligands
Authors: Jayathuna Mugamathu Ali , Rajagopal Gopalan , Anand Thiraviyam , Saxena Kartikey , Kalilur Rahiman Aziz 
Published: March 2024

AbstractA new class of homoleptic metal(II) complexes of general formula [M(L1–4)2]2Cl in which L1=1‐([1,1′‐biphenyl]‐4‐yl)‐N‐(2‐((‐pyridin‐2‐ylmethylene)amino)ethyl)methanimine, L2=1‐([1,1′‐biphenyl]‐4‐yl)‐N‐(2‐((‐pyridin‐2‐ylmethylene)amino)phenyl)methanimine, L3=1‐([1,1′‐biphenyl]‐4‐yl)‐N‐(2‐((‐pyridin‐2‐ylmethylene)amino)‐4‐nitrophenyl)methanimine and L4=4‐(([1,1′‐biphenyl]‐4‐ylmethylene)amino)‐3‐((−pyridin‐2‐ylmethylene)amino)benzophenone, and M=Ni(II) (1–4), Cu(II) (5–8) and Zn(II) (9–12) have been synthesized and characterized. The IR spectra reveal the involvement of azomethine and 2‐formylpyridine ring nitrogen atoms in chelation. The UV‐Vis and EPR spectral studies envisage distorted octahedral geometry around metal(II) ion. All the complexes were stable for 72 h in biologically relevant solutions, and copper(II) complexes were reduced to Cu+ center in the presence of ascorbic acid solution. The binding studies of complexes with calf thymus DNA (CT‐DNA) indicate groove mode of binding, and the complexes 3, 7 and 11 containing the 4‐nitrophenyl substituent exhibit the highest binding affinity than the other complexes. Furthermore, the spectral studies also revealed the interaction of complexes with BSA through static mechanism. In vitro cytotoxicity activity of the complexes was screened against human lung adenocarcinoma (A549) and breast adenocarcinoma (MCF‐7) cancerous, and normal murine fibrosarcoma (L929) cell lines. The molecular docking studies of the homoleptic metal(II) complexes show hydrophobic, π–π, σ–π and hydrogen bonding interactions with EGFR/VEGFR2 kinase receptors.