bluuebunny/crossref_metadata_2025 huggingface dataset:
Photodegradation of imidacloprid insecticide using polyethersulfone membranes modified with iron doped cerium oxide
Authors: Malatjie Kgolofelo I. , Moutloali Richard M. , Mishra Ajay K. , Mishra Shivani B. , Nxumalo Edward N.
Published: February 2024

The widespread accumulation of insecticides in water systems is a growing concern. This study reports efficient photodegradation of imidacloprid (IMD) insecticide using polyethersulfone (PES) membranes modified with iron‐doped cerium oxide (Fe‐CeO2). The work focuses on the modification of ultrafiltration polyethersulfone membranes with incremental amounts of Fe‐CeO2 photocatalysts (0.5–2.0 wt.%) using phase inversion method. An increase in Fe‐CeO2 content showed an improvement in surface roughness and porosity of membranes. Pure water flux (PWF) increased from 55.9 L m2 h−1 in M0 (PES) to 77.2 (M1, 0.5% Fe‐CeO2‐PES), 118.0 (M2, 1% Fe‐CeO2‐PES), 128.0 in M3 (1.5 wt.% Fe‐CeO2‐PES) and then decreased to 98.5 L m2 h−1 in M4 (2 wt.% Fe‐CeO2‐PES). This decrease is brought about by the high Fe‐CeO2 content, which minimizes the membranes' surface pores. Fe‐CeO2 photocatalysts are thought to give the membrane both hydrophilic and photocatalytic qualities because of their capacity to absorb light and create radical species that cause the photodegradation of IMD molecules. Consequently, under visible light irradiation, modified membranes demonstrated photocatalytic ability over IMD. Photocatalytic efficiencies of the membranes were found to be 5.2% (M0), 68.9 (M1), 75.8 (M2), 81.8 (M3), and 56.0% (M4), respectively, with M3 membranes showing the highest photocatalytic degradation efficiency and low leaching of metals. The remarkable performance observed by M3 membranes during both water filtration and photocatalytic performance may be an illustration of well dispersed photocatalyst which receives high absorption of light irradiation. Membranes with photocatalytic functionalities are tailored to exploit dual benefits of the membrane filtration and photocatalysis without compromising their original functions. However, maintaining the delicate balance of this phenomenon is still very challenging.
Investigation on the enhancement of solvent‐resistant nanofiltration membrane performance utilizing PDA‐UiO‐66@CNT as an interlayer
Authors: Zhong Zhaohuang , Li Lang , Yu Siwei , Li Xindong , Li Haike , Jia Jianghui , Huang Jiaju , Cai Meng , Huang Wanfu
Published: February 2024

With the growing complexity of separation systems, the application of thin film composite nanofiltration (TFN) membranes in organic solvent separation faces numerous challenges. To augment its solvent stability, an in‐situ constructed dopamine hydrogel doped with UiO‐66@CNT was developed as an intermediate layer on a polyetherimide (PEI) ultrafiltration membrane. Subsequent interfacial polymerization on this interlayer led to the formation of a solvent‐resistant nanofiltration membrane with a vast covalent bond structure, large specific surface area, and enhanced hydrophilicity. Our findings revealed that when the CNT loading in the UiO‐66@CNT composite nanoparticles was 2 wt%, the TFN‐U2C2 membrane exhibited a maximum pure water flux of 126.32 L/(m2·h) and a methanol flux of 45.45 L/(m2·h). The rejection rates for Congo red aqueous and methanol solutions were 96.88% and 92.14%, respectively. The membrane also demonstrated commendable anti‐fouling properties. Remarkably, even after 48 h of immersion in various organic solvents, the membrane retained its morphology and separation efficiency. Compared to the TFN‐U2 membrane without CNT addition, the enhancement in separation performance was considerably significant. Hence, this membrane has significant potential for application in treatment of wastewater containing organic solvents and is promising in related fields.
Simple mechanochemical synthesis, characterization, optical and thermoelectric properties of a nanostructured silver (I) selenide semiconductor
Authors: Achimovičová Marcela , Gáborová Katarína , Girman Vladimír , Dutková Erika , Briančin Jaroslav , Levinský Petr , Puchý Viktor
Published: February 2024

Silver(I) selenide, Ag2Se was very simply and conveniently prepared from Ag and Se powders in a stoichiometric ratio by one‐step mechanochemical synthesis after 10 min of milling in a planetary ball mill. The kinetics of this synthesis and the structural, morphological, optical, and thermoelectric properties of the product were studied. The crystal structure, physical properties, and morphology were characterized by X‐ray diffraction (XRD), specific surface area measurements, particle size distribution analysis, scanning, and transmission electron microscopy. XRD confirmed the orthorhombic crystal structure of naumannite, Ag2Se. The electron microscopy revealed that the nanostructured product consisted of isolated rod‐shaped particles and agglomerated nanoparticles of irregular shape which formed clusters with a size >30 μm. Crystallinity was inspected by selected area diffraction. The optical properties were studied using ultraviolet‐visible and photoluminescence spectroscopy. The determined band gap energy of 1.15 eV was blue‐shifted relative to the bulk Ag2Se. For the densification of mechanochemically synthesized powdered Ag2Se, the spark plasma sintering method was applied to prepare a suitable sample for thermoelectric characterization. High‐temperature thermoelectric properties were evaluated in terms of the potential application of mechanochemically synthesized Ag2Se in energy conversion.
An RBFNN‐based constraint control algorithm for electric vehicle AFS + DYC system with state delays and uncertain parameters
Authors: Zhou Yu , He Youguo , Cai Yingfeng , Yuan Chaochun , Shen Jie , Tian Liwei
Published: February 2024

A novel multi‐input multi‐output adaptive control strategy applied to the combined active front steering (AFS) and direct yaw moment control (DYC) system is proposed in this paper. Studies have been conducted to show the potential for electric vehicles to be affected by time delay, which may appear in states. Aiming to address the state delay, radial basis function neural network (RBFNN) and Lyapunov‐Krakovskii functional‐based AFS and DYC controllers are constructed, which also can process the parameter uncertainties due to the powerful ability of RBFNN to approximate the unknown terms. Meanwhile, the controller is designed to incorporate the barrier Lyapunov function so that the state variables under control, including the sideslip angle and yaw rate, remain in their respective stable ranges while accurately tracking the corresponding desired values. Co‐simulations utilizing Simulink and CarSim are implemented for verifying the effectiveness of the proposed control scheme and comparing it with the traditional control scheme.
Modeling flight delays by an intensity‐based Hawkes process
Authors: Franses Philip Hans , Smeets Carlijn
Published: February 2024

Two key features of airline departure delays are that they cascade and that there can be exceptional peaks. We model these features using an intensity‐based Hawkes process. Our application to all KLM departure delays at Amsterdam Schiphol airport in January 2015 shows that volatility in departure delays is endogenous. We correlate the key parameters of the estimated Hawkes process with daily weather conditions and find that these conditions amplify the self‐exciting feature of departure delays.
A review on statistical and machine learning competing risks methods
Authors: Monterrubio‐Gómez Karla , Constantine‐Cooke Nathan , Vallejos Catalina A.
Published: February 2024

When modeling competing risks (CR) survival data, several techniques have been proposed in both the statistical and machine learning literature. State‐of‐the‐art methods have extended classical approaches with more flexible assumptions that can improve predictive performance, allow high‐dimensional data and missing values, among others. Despite this, modern approaches have not been widely employed in applied settings. This article aims to aid the uptake of such methods by providing a condensed compendium of CR survival methods with a unified notation and interpretation across approaches. We highlight available software and, when possible, demonstrate their usage via reproducible R vignettes. Moreover, we discuss two major concerns that can affect benchmark studies in this context: the choice of performance metrics and reproducibility.
A low‐temperature SPR‐based assay for monoclonal antibody galactosylation and fucosylation assessment using FcγRIIA/B
Authors: Gaudreault Jimmy , Forest‐Nault Catherine , Gilbert Michel , Durocher Yves , Henry Olivier , De Crescenzo Gregory
Published: February 2024

Monoclonal antibodies (MAbs) are powerful therapeutic tools in modern medicine and represent a rapidly expanding multibillion USD market. While bioprocesses are generally well understood and optimized for MAbs, online quality control remains challenging. Notably, N‐glycosylation is a critical quality attribute of MAbs as it affects binding to Fcγ receptors (FcγRs), impacting the efficacy and safety of MAbs. Traditional N‐glycosylation characterization methods are ill‐suited for online monitoring of a bioreactor; in contrast, surface plasmon resonance (SPR) represents a promising avenue, as SPR biosensors can record MAb–FcγR interactions in real‐time and without labeling. In this study, we produced five lots of differentially glycosylated Trastuzumab (TZM) and finely characterized their glycosylation profile by HILIC‐UPLC chromatography. We then compared the interaction kinetics of these MAb lots with four FcγRs including FcγRIIA and FcγRIIB at 5°C and 25°C. When interacting with FcγRIIA/B at low temperature, the differentially glycosylated MAb lots exhibited distinct kinetic behaviors, contrary to room‐temperature experiments. Galactosylated TZM (1) and core fucosylated TZM (2) could be discriminated and even quantified using an analytical technique based on the area under the curve of the signal recorded during the dissociation phase of a SPR sensorgram describing the interaction with FcγRIIA (1) or FcγRII2B (2). Because of the rapidity of the proposed method (<5 min per measurement) and the small sample concentration it requires (as low as 30 nM, exact concentration not required), it could be a valuable process analytical technology for MAb glycosylation monitoring.
Assessment of the competitiveness of food products of Ukraine in the domestic and foreign markets
Authors: Musayeva Nazakat , Tanriverdiyeva Gulnara , Faradjova Dilbar , Mammadova Ulkar
Published: February 2024

This article conducts a comprehensive financial analysis of the competitiveness of confectionery producers in Ukraine within the global confectionery market context. It aims to assess the challenges faced by Ukrainian producers and propose practical strategies to enhance their competitiveness. The research employs various methods, including the construction of a competitive market map and the application of the theory of effective competition. Competitiveness coefficients are calculated to evaluate the performance of key players. A SWOT analysis is conducted to identify strengths and weaknesses, and potential measures for increasing competitiveness are proposed. The global confectionery market has reached $298 billion in 2021, but Ukrainian producers have encountered obstacles, such as the COVID‐19 pandemic, rising production costs and geopolitical conflicts, leading to closures and reduced exports. Roshen emerges as the leader with a 24.7% market share in 2022, although all major companies experienced negative growth rates due to the war. Competitiveness coefficients also position Roshen at the forefront, whilst several other plants demonstrate significant potential. The article's practical significance stems from its data‐driven analysis of competitiveness, providing valuable insights and strategies for managers to improve the production and export capabilities of Ukrainian confectionery producers in the face of global market challenges. Future research could explore sustainable competitive advantages and cost reduction strategies.
Wildest dreams: NIL experts make predictions for 2024
Authors: Stein Callan , Shire Howard J. , Lowe Michael S. , Brolley Christopher M. , DeFilippis Connor B. , Clifford Danielle A. , Zancolli Patrick
Published: February 2024

Looking back, 2023 proved to be yet another important year for the landscape of college sports and name, image, and likeness. As we look ahead to 2024, it's imperative for higher education stakeholders to consider how the landscape will evolve further. Here, we delve into the future of NIL in 2024 and offer some predictions and insights that could define this year of college sports.
Recent Understanding of Water‐Assisted CO2 Hydrogenation to Alcohols
Authors: Vieira Luiz H. , da Silva Alisson H. M. , Santana Cássia S. , Assaf Elisabete M. , Assaf José M. , Gomes Janaina F.
Published: February 2024

Alcohol production from CO2 hydrogenation is a cutting‐edge process in sustainable chemistry that holds vast promise for addressing climate change by recycling and repurposing emissions. Many strategies have been proposed to improve the process efficiency. In‐situ generated, and trace amounts of water added to the feed stream have recently proved to be determinant to promote key reaction steps, increasing alcohol selectivity and yield. Here, we discuss the main findings that led to an atomic‐level understanding of water promotional effects in CO2 hydrogenation to alcohols. H2O and the products resultant from its dissociation (OH and O) can act in different ways, stabilizing intermediates and active sites or participating in the hydrogen transfer mechanisms during the reaction. Gaining insights into the mechanisms underlying water promotion offers a cost‐effective strategy for enhancing alcohol production efficiency.
Diversity Oriented Synthesis of Novel Xanthones Reveal Potent Doxorubicin‐Inspired Analogs
Authors: Meringdal Jonas W. , Bade Leon , Bendas Gerd , Menche Dirk
Published: February 2024

Inspired by potent antiproliferative xanthone natural products and so far limited examples of derived bioactive agents, a structure activity study of architecturally novel types of xanthones is reported. Their preparation was enabled in a short and divergent manner by a modular chlorination in combination with optimized protocols for a polar condensation and a hetero‐cyclization. Application of these procedures allowed for the synthesis of various polyhalogenated representatives (including mixed bromo/chloro xanthones) that were obtained in up to fourfold improved yields as compared to previous procedures. Subsequent Suzuki coupling of either halide enabled access to phenyl‐ and chloro‐bearing xanthones, which may be functionalized at four out of five non‐hydroxylated positions. Antiproliferative assays against breast cancer cell lines revealed potent activities of some of these simplified analogs that are in the range of pharmaceutically used anticancer drug doxorubicin.
Abscopal effect in maxillary sinus cancer: Insights from two case reports and a literature review
Authors: Sakai Akihiro , Ebisumoto Koji , Iijima Hiroaki , Yamauchi Mayu , Maki Daisuke , Fukuzawa Tsuyoshi , Okami Kenji
Published: February 2024

Background

The abscopal effect is a rare phenomenon in which localized radiation therapy triggers tumor reduction in nontargeted areas. Although this phenomenon has been observed in various cancer types, it remains infrequent and not fully understood.

Case

Two patients with maxillary sinus cancer with distant metastases were treated with radiotherapy after immune checkpoint inhibitor (ICI) therapy. The patients demonstrated abscopal effects following ICI therapy and radiotherapy, showing shrinkage in metastatic areas not directly targeted by radiation.

Conclusion

This report was reviewed to examine the synergistic effects of ICI and radiotherapy and to identify optimal strategies to enhance the abscopal effect in clinical practice. It has also touched on various ongoing debates and clinical trials aimed at understanding and exploiting this effect to improve cancer treatment. The exact mechanisms and optimal treatment protocols remain areas for future research.
Mechanistic Inquisition on the Reduction of C17Si(NH2)2 to NH3: A DFT Study
Authors: Sen Sobitri , Bag Arijit , Pal Sourav
Published: February 2024

Activation of molecular nitrogen by silicon‐substituted cyclo[18]carbon and its ability to produce the C17Si‐(NH2)2 derivative, as the precursor of NH3, has been recently reported. This specific acquisition has piqued an interest to investigate the possibility of NH3 formation with further addition of H2 molecules in the gaseous reaction media. The current investigations reported in this article show that two moles of molecular H2 generate two molecules of NH3 and a C17Si‐H2 byproduct from its precursor. The catalyst gets restored by an in situ reaction between some unreacted C17Si‐N2 and the byproduct in the media. This reaction also produces the next C17Si‐(NH)2 adduct, which restarts the catalytic cycle for NH3 production again.
Analytical Workflows for Single‐Cell Multiomic Data Using the BD Rhapsody Platform
Authors: Li Wenyan , Bazaz Sajad Razavi , Mayoh Chelsea , Salomon Robert
Published: February 2024

The conversion of raw sequencing reads to biologically relevant data in high‐throughput single‐cell RNA sequencing experiments is a complex and involved process. Drawing meaning from thousands of individual cells to provide biological insight requires ensuring not only that the data are of the highest quality but also that the signal can be separated from noise. In this article, we describe a detailed analytical workflow, including six pipelines, that allows high‐quality data analysis in single‐cell multiomics. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Image analysis

Basic Protocol 2: Sequencing quality control and generation of a gene expression matrix

Basic Protocol 3: Gene expression matrix data pre‐processing and analysis

Basic Protocol 4: Advanced analysis

Basic Protocol 5: Conversion to flow cytometry standard (FCS) format

Basic Protocol 6: Visualization using graphical interfaces
Developing CSR communication strategies to increase sustainable behaviors from the perspective of spiritual capital
Authors: Lee Ya‐Ching
Published: February 2024

Many companies pursue sustainability and rely on communication to convince consumers of their sustainability efforts. This study examines the impact of corporate sustainable communication strategies from the perspective of spiritual capital. Results indicate that communication framed in strength, personal well‐being, and mobilizability positively affects consumers' trust and sustainable behavior intentions through perceived spirituality. This study also clarifies gender differences. It offers a simple yet rigorous theoretical framework to evaluate sustainable communication strategies. The conceptualization and development of these measures is an important step for future studies that evaluate sustainable communication effects. To our knowledge, this study is the first attempt to explore the dimensions of perceived spirituality and evaluate their roles in sustainable communication. It finally offers practical suggestions for business sustainable communication strategies.
ADB‐HEXINACA—a novel synthetic cannabinoid with a hexyl substituent: phase I metabolism in authentic urine samples, a case report and prevalence on the German market
Authors: Giorgetti Arianna , Zschiesche Annette , Groth Olwen , Haschimi Belal , Scheu Martin , Pelletti Guido , Fais Paolo , Musshoff Frank , Auwärter Volker
Published: February 2024

Synthetic cannabinoid receptor agonists (SCRAs) are one of the largest groups of new psychoactive substances (NPS). Yet, another novel analog started spreading on the NPS market around 2021. Soon after, the substance could be analytically characterized in herbal material as ADB‐HEXINACA, an SCRA containing a hexyl‐substituted tail on the indazole core. Here, we present suitable urinary markers to prove the consumption of this analog, a case report of acute polydrug intoxication and data on its prevalence in Germany. Anticipated phase I metabolites were detected in 12 authentic urine samples that were collected for abstinence control and analyzed by ultra‐performance liquid chromatography coupled to a time‐of‐flight mass spectrometer (UPLC‐qToF‐MS). The results of in vivo samples were confirmed by analysis of in vitro incubates with pooled human liver microsomes (pHLMs). Forensic samples were used to assess the prevalence of ADB‐HEXINACA. Thirty‐two phase I metabolites were detected in the authentic urine samples. The main metabolites resulted from amide hydrolysis in combination with either monohydroxylation or ketone formation at the hexyl moiety (M15 and M26), the monitoring of which is recommended as a proof of consumption. ADB‐HEXINACA was detected in 3.5% of SCRA positive urine samples collected for abstinence control in Freiburg up to December 2022 and in 5.5% of the SCRA positive blood/serum samples. The hexyl substituent of ADB‐HEXINACA allows for the detection of specific urinary biomarkers suggested as analytical targets to confirm its prior intake. ADB‐HEXINACA had a rather low prevalence in Germany, alternating months of higher prevalence with periods of total absence.
Sustaining eastern oak forests: Synergistic effects of fire and topography on vegetation and fuels
Authors: Hutchinson Todd F. , Adams Bryce T. , Dickinson Matthew B. , Heckel Maryjane , Royo Alejandro A. , Thomas‐Van Gundy Melissa A.
Published: February 2024

Across much of the eastern United States, oak forests are undergoing mesophication as shade‐tolerant competitors become more abundant and suppress oak regeneration. Given the historical role of anthropogenic surface fires in promoting oak dominance, prescribed fire has become important in efforts to reverse mesophication and sustain oaks. In 2000 we established the Ohio Hills Fire and Fire Surrogate (FFS) study to examine whether repeated prescribed fire (Fire), mechanical partial harvest (Mech), and their combined application (Mech + Fire) reduced the dominance of subcanopy mesophytic competitors, increased the abundance of large oak–hickory advance regeneration, created a more diverse and productive ground‐layer flora, and produced fuel beds more conducive to prescribed fire, reducing the risk of high‐severity wildfire. Here we report on the ~20‐year effects of treatments on vegetation and fuels and examine the support for interactive effects across a topographic‐moisture and energy gradient. In general, we found that Fire and Mech + Fire treatments tended to reverse mesophication while the Mech‐only treatment did not. The moderate and occasionally high‐intensity fires resulted in effects that were ultimately very similar between the two fire treatments but were modulated by topography with increasing fire severity on drier sites. In particular, we found support for an interaction effect between treatment and topography on forest structure and tree regeneration responses. Fire generally reduced mesophytic tree density in the midstory and sapling strata across all site conditions, while leading to substantial gains in the abundance of large oak–hickory advance regeneration on dry and intermediate landscape positions. Fire also promoted ground‐layer diversity and created compositionally distinct communities across all site conditions, primarily through the increased richness of native perennial herbs. However, the fire had limited effects on fine surface fuel loading and increased the loading of large woody fuels, potentially increasing the risk of high‐severity wildfire during drought conditions. We conclude that two decades of repeated fires, with and without mechanical density reduction, significantly shifted the trajectory of mesophication across most of the landscape, particularly on dry and intermediate sites, highlighting the capacity of a periodic fire regime to sustain eastern oak forests and promote plant diversity but modulated by topography.
Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning
Authors: Sandoval‐Araujo Luis E. , Cusack Claire E. , Ralph‐Nearman Christina , Glatt Sofie , Han Yuchen , Bryan Jeffrey , Hooper Madison A. , Karem Andrew , Levinson Cheri A.
Published: February 2024

Objective

Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two.

Methods

Using an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI.

Results

Model performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%).

Discussion

Model performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered.

Public Significance

There is a growing debate about the differences between anorexia nervosa and atypical anorexia nervosa as their diagnostic differentiation relies on BMI despite being similar otherwise. We aimed to see if machine learning could distinguish between the two disorders and found accurate classification only if BMI was used as a feature. This finding calls into question the need to differentiate between the two disorders.
Integrating context in the examination of pubertal timing effects on disordered eating among Black and Latinx girls
Authors: Anaya Carolina
Published: February 2024

Earlier pubertal onset has been associated with increased disordered eating symptoms in cisgender girls. Although this finding has been replicated across studies of disordered eating, most studies have focused on white samples. The lack of studies is surprising given that early pubertal timing may impact disordered eating risk in Black and Latinx girls differently due to trends of earlier pubertal onset in these groups and increased stressors related to interpersonal and structural racism and economic marginalization. Current methods of examining pubertal timing among Black and Latinx girls may also not fully capture their experience. Contextual factors (e.g., neighborhood and school racial/ethnic composition) may influence how minoritized girls both perceive and are affected by their pubertal timing. Moreover, factors such as ethnic–racial identity development and experiences of discrimination may be important mechanisms explaining the association between pubertal timing and disordered eating risk. This paper aims to provide a brief overview of studies examining pubertal timing and disordered eating risk among Black and Latinx girls in the US and to discuss recommendations for future research that integrate contextual factors in the examination of pubertal timing and its effects.

Public significance

Early pubertal timing has been associated with increased risk of disordered eating symptoms among cisgender girls; however, studies have been limited due to the use of predominantly white samples. The article provides a brief overview of findings related to pubertal timing effects among Black and Latinx girls, discusses considerations for the measurement of pubertal timing, and highlights the need for inclusion of contextual factors in future research.
Synthesis conditions affecting electrochemical and chemical stabilities of Ga‐doped Li7La3Zr2O12 solid electrolyte
Authors: Huang DingYuan , Kamiko Masao , Yagi Shunsuke
Published: February 2024

All‐solid‐state lithium batteries with Li metal anodes and solid‐state electrolytes (SSEs) can achieve higher energy density and enhanced safety compared to the current liquid‐based Li‐ion batteries. Among several SSEs, Li7La3Zr2O12 (LLZO) has attracted attention due to its high Li+ ion conductivity (∼10−3 S cm−1 at room temperature for Ga‐doped LLZO) and good stability in ambient air. However, the challenges of Li penetration and the chemical instability against Li are the primary obstacles to its practical application. This study investigates the effects of the grain size and electronic conductivity of Ga‐doped LLZO on the critical current density (CCD). Using samples with similar interfacial impedances between Ga‐doped LLZO and Li, we demonstrate that a decrease in the grain size of Ga‐doped LLZO lowers the electronic conductivity, leading to a higher CCD. Furthermore, although a previous study suggests that Ga‐doped LLZO might be unsuitable for direct contact with Li, the chemical stability against Li is enhanced in a more compact pellet prepared at a higher cold‐pressing pressure. These results underscore the significance of the sintering conditions and pellet pressing pressure in the synthesis of Ga‐doped LLZO since they ultimately affect the electrochemical and chemical stabilities of the Ga‐doped LLZO solid electrolyte with a Li‐metal anode.
Season‐specific impacts of climate change on canopy‐forming seaweed communities
Authors: Truong Anthony T. , Edwards Matthew S. , Long Jeremy D.
Published: February 2024

Understory assemblages associated with canopy‐forming species such as trees, kelps, and rockweeds should respond strongly to climate stressors due to strong canopy‐understory interactions. Climate change can directly and indirectly modify these assemblages, particularly during more stressful seasons and climate scenarios. However, fully understanding the seasonal impacts of different climate conditions on canopy‐reliant assemblages is difficult due to a continued emphasis on studying single‐species responses to a single future climate scenario during a single season. To examine these emergent effects, we used mesocosm experiments to expose seaweed assemblages associated with the canopy‐forming golden rockweed, Silvetia compressa, to elevated temperature and pCO2 conditions reflecting two projected greenhouse emission scenarios (RCP 2.6 [low] & RCP 4.5 [moderate]). Assemblages were grown in the presence and absence of Silvetia, and in two seasons. Relative to ambient conditions, predicted climate scenarios generally suppressed Silvetia biomass and photosynthetic efficiency. However, these effects varied seasonally—both future scenarios reduced Silvetia biomass in summer, but only the moderate scenario did so in winter. These reductions shifted the assemblage, with more extreme shifts occurring in summer. Contrarily, future scenarios did not shift assemblages within Silvetia Absent treatments, suggesting that climate primarily affected assemblages indirectly through changes in Silvetia. Mesocosm experiments were coupled with a field Silvetia removal experiment to simulate the effects of climate‐mediated Silvetia loss on natural assemblages. Consistent with the mesocosm experiment, Silvetia loss resulted in season‐specific assemblage shifts, with weaker effects observed in winter. Together, our study supports the hypotheses that climate‐mediated changes to canopy‐forming species can indirectly affect the associated assemblage, and that these effects vary seasonally. Such seasonality is important to consider as it may provide periods of recovery when conditions are less stressful, especially if we can reduce the severity of future climate scenarios.
Decomposing diversity into measures of evenness, similarity, and richness
Authors: Chen Bingzhang , Grinfeld Michael
Published: February 2024

It has long been recognized that diversity has many measurable aspects, such as richness, evenness, and similarity among species. However, given a diversity index, it is unclear whether it necessarily can be decomposed into components that reflect these different aspects. Here, we present a scheme to decompose the Leinster and Cobbold diversity index, which subsumes and generalizes many other indices, into the components of richness, evenness and taxonomic similarity. Our approach addresses the problem that in general a vector of equal relative abundances does not maximize diversity. Furthermore, our approach uses all available information to give unbiased estimates of both evenness and similarity.
Species identification through deep learning and geometrical morphology in oaks (Quercus spp.): Pros and cons
Authors: Qi Min , Du Fang K. , Guo Fei , Yin Kangquan , Tang Jijun
Published: February 2024

Plant phenotypic characteristics, especially leaf morphology of leaves, are an important indicator for species identification. However, leaf shape can be extraordinarily complex in some species, such as oaks. The great variation in leaf morphology and difficulty of species identification in oaks have attracted the attention of scientists since Charles Darwin. Recent advances in discrimination technology have provided opportunities to understand leaf morphology variation in oaks. Here, we aimed to compare the accuracy and efficiency of species identification in two closely related deciduous oaks by geometric morphometric method (GMM) and deep learning using preliminary identification of simple sequence repeats (nSSRs) as a prior. A total of 538 Asian deciduous oak trees, 16 Q. aliena and 23 Q. dentata populations, were firstly assigned by nSSRs Bayesian clustering analysis to one of the two species or admixture and this grouping served as a priori identification of these trees. Then we analyzed the shapes of 2328 leaves from the 538 trees in terms of 13 characters (landmarks) by GMM. Finally, we trained and classified 2221 leaf‐scanned images with Xception architecture using deep learning. The two species can be identified by GMM and deep learning using genetic analysis as a priori. Deep learning is the most cost‐efficient method in terms of time‐consuming, while GMM can confirm the admixture individuals' leaf shape. These various methods provide high classification accuracy, highlight the application in plant classification research, and are ready to be applied to other morphology analysis.
Data assimilation experiments inform monitoring needs for near‐term ecological forecasts in a eutrophic reservoir
Authors: Wander Heather L. , Thomas R. Quinn , Moore Tadhg N. , Lofton Mary E. , Breef‐Pilz Adrienne , Carey Cayelan C.
Published: February 2024

Ecosystems around the globe are experiencing changes in both the magnitude and fluctuations of environmental conditions due to land use and climate change. In response, ecologists are increasingly using near‐term, iterative ecological forecasts to predict how ecosystems will change in the future. To date, many near‐term, iterative forecasting systems have been developed using high temporal frequency (minute to hourly resolution) data streams for assimilation. However, this approach may be cost‐prohibitive or impossible for forecasting ecological variables that lack high‐frequency sensors or have high data latency (i.e., a delay before data are available for modeling after collection). To explore the effects of data assimilation frequency on forecast skill, we developed water temperature forecasts for a eutrophic drinking water reservoir and conducted data assimilation experiments by selectively withholding observations to examine the effect of data availability on forecast accuracy. We used in situ sensors, manually collected data, and a calibrated water quality ecosystem model driven by forecasted weather data to generate future water temperature forecasts using Forecasting Lake and Reservoir Ecosystems (FLARE), an open source water quality forecasting system. We tested the effect of daily, weekly, fortnightly, and monthly data assimilation on the skill of 1‐ to 35‐day‐ahead water temperature forecasts. We found that forecast skill varied depending on the season, forecast horizon, depth, and data assimilation frequency, but overall forecast performance was high, with a mean 1‐day‐ahead forecast root mean square error (RMSE) of 0.81°C, mean 7‐day RMSE of 1.15°C, and mean 35‐day RMSE of 1.94°C. Aggregated across the year, daily data assimilation yielded the most skillful forecasts at 1‐ to 7‐day‐ahead horizons, but weekly data assimilation resulted in the most skillful forecasts at 8‐ to 35‐day‐ahead horizons. Within a year, forecasts with weekly data assimilation consistently outperformed forecasts with daily data assimilation after the 8‐day forecast horizon during mixed spring/autumn periods and 5‐ to 14‐day‐ahead horizons during the summer‐stratified period, depending on depth. Our results suggest that lower frequency data (i.e., weekly) may be adequate for developing accurate forecasts in some applications, further enabling the development of forecasts broadly across ecosystems and ecological variables without high‐frequency sensor data.
Filament analysis based on mathematical morphology of surface dielectric barrier discharges in N2/O2 mixtures
Authors: Uemura Takuma , Komuro Atsushi , Ono Ryo
Published: February 2024

In this paper, we measured the electrical potential distribution of surface dielectric barrier discharges (SDBD) caused by alternating voltage in synthetic air and nitrogen using the Pockels effect. It was shown that different potential distributions of filament thickness and length are generated in synthetic air and nitrogen. A filament analysis based on mathematical morphology was performed to quantify the geometric characteristics of the filaments produced in each gas atmosphere. The results show that the discharge filament thickness and the entropy in the filament direction depend on the oxygen ratio and the magnitude of the applied voltage.
Reactivity of Biomass‐Derived Olefins with Elemental Sulfur: Mechanistic Insight
Authors: Kapuge Dona Nawoda L. , Maladeniya Charini P. , Smith Rhett C.
Published: February 2024

Lignocellulosic biomass remains underutilized despite its annual production in gigaton quantities. Sulfur is another vastly underutilized waste product of fossil fuel refining. New mechanistic insight into the reactions of sulfur unveiled since 2020 suggest a rich and hitherto unexplored chemistry between biomass‐derived olefins and elemental sulfur. In this study, four biomass‐derived olefins (eugenol (1), 4‐allyl‐2,6‐dimethoxyphenol (2),o‐eugenol (3), and 2‐allyl‐6‐methylphenol(4)) were reacted with elemental sulfur to elucidate the S−C bond‐forming and other reactivity of these compounds. Each of the compounds was reacted with elemental sulfur in three sulfur : organic reactant ratios (2 : 1, 4 : 1 and 9 : 1) and at two temperatures (180 °C or 230 °C). Product mixtures were characterized using1H NMR spectrometry and GC‐MS analysis. Products resulting from a range of mechanisms were unveiled, including inverse vulcanization, S−Callylic/benzylicbond formation, S−Carylbond formation, intramolecular cyclization, C−C σ‐bond scission, and C−O σ‐bond scission. It is anticipated that the insights from this study will support further synergy between the critical sustainability goals of biomass and sulfur utilization.
Pd‐Catalyzed Synthesis of Aryl Esters Involving Difluorocarbene Transfer Carbonylation
Authors: Wang Lu , Hu Chengxian , Yang Xue , Fu Ying , Du Zhengyin
Published: February 2024

A Pd‐catalyzed three‐component intermolecular reaction between aryl halides, ClCF2COONa and phenols is developed. A series of aryl benzoates were synthesized in up to 84 % yield via difluorocarbene transfer carbonylation. It is devoted to acquiring the targeted products by construction of new C−C, C=O and C−O bonds in a one‐pot, one‐step process. The feature of this method includes the use of readily available starting materials, showing outstanding resistance to spatial obstruction and simple operation procedure with mild reaction conditions. Therefore, this makes the methodology a useful alternative to other schemes typically used for the synthesis of aryl esters.
The relationships between affect dimensions and level of construal
Authors: Efrat‐Treister Dorit , Oreg Shaul , Dover Yaniv
Published: February 2024

The relationship between affect and cognition is a central topic of interest in psychology. In this study, we focus on the relationship of affect valence and activation with construal level. Existing findings are inconsistent. We propose that these inconsistencies may result from the interdependency of affect valence and activation and propose that valence and activation interact in predicting construal level. Specifically, we propose that, overall, valence has a positive effect on construal level, and that activation accentuates the effect of valence. We test our predictions through a text analysis of event descriptions in four data sets: TripAdvisor hotel reviews (N = 330,853); Yelp restaurant reviews (N = 648,974); Amazon Digital Music reviews (N = 1,518,409); and Twitter Negative Emotions database (N = 8,756). Results confirm the predicted V‐shaped relationship between valence and activation, and the moderating effect of activation on the relationship between valence and construal level. We discuss these findings and the inconsistencies across studies.
Space, mortality, and economic growth
Authors: Cupido Kyran , Jevtić Petar , Boonen Tim J.
Published: February 2024

Currently, most academic research involving the mortality modeling of multiple populations mainly focuses on factor‐based approaches. Increasingly, these models are enriched with socio‐economic determinants. Yet these emerging mortality models come with little attention to interpretable spatial model features. Such features could be highly valuable to demographers and old‐age benefit providers in need of a comprehensive understanding of the impact of economic growth on mortality across space. To address this, we propose and investigate a family of models that extend the seminal Li‐Lee factor‐based stochastic mortality modeling framework to include both economic growth, as measured by the real gross domestic product (GDP), and spatial patterns of the contiguous United States mortality. Model selection performed on the introduced new class of spatial models shows that based on the AIC criteria, the introduced spatial lag of GDP with GDP (SLGG) model had the best fit. The out‐of‐sample forecast performance of SLGG model is shown to be more accurate than the well‐known Li–Lee model. When it comes to model implications, a comparison of annuity pricing across space revealed that the SLGG model admits more regional pricing differences compared to the Li‐Lee model.
Electromyography findings in radiation‐induced unilateral tongue immobility
Authors: Harley Randall J. , Johnson Jonas T. , Nilsen Marci L. , Munin Michael C.
Published: February 2024

Background

We used electromyography to characterize hypoglossal nerve function among radiation‐treated head and neck cancer survivors with later onset unilateral tongue immobility.

Methods

Patients with unilateral tongue immobility without evidence of recurrent cancer were seen at a tertiary academic institution between February and September 2021. All patients were at least 2 years post‐treatment with radiation therapy for head and neck squamous cell carcinoma. Participants were under annual surveillance and displayed no evidence of operative injury to the hypoglossal nerve.

Results

The median symptom‐free interval for the 10 patients included in this study was 13.2 years (range 2–25 years). Myokymia alone was present in 3 of 10 patients, fibrillation potentials alone were present in 3 of 10 patients, and 1 subject displayed both fibrillation and myokymia. Three out of 10 patients had normal hypoglossal nerve function.

Discussion

These findings highlight how disparate mechanisms may underlie similar clinical presentations of radiation‐induced neuromuscular dysfunction.
Raising the issue of quality in implementation science reporting in global health: Implications for health planning and practice
Authors: Rose Alexandra L. , Jack Helen E. , Rasheed Muneera A. , Magidson Jessica F.
Published: February 2024

Implementation outcomes, which focus on the barriers to, and facilitators and processes of healthcare delivery, are critical to translating research evidence to health planning and practice and to improving healthcare delivery. This article summarises key quality issues in reporting of implementation science outcomes within global health and describes the ways in which this presents a challenge for shifting health planning and practice across low‐resource health systems. This article also suggests that the wider use of reporting guidelines for implementation outcomes could help address this issue.
Impact of COVID‐19 pandemic on trauma mortality patients: A retrospective observational study in an Iranian level 1 trauma center
Authors: Ayatizadeh Seyyed HamidReza , Borazjani Roham , Fereidooni Reza , Jamali Kazem , Fard Hossein Abdolrahimzadeh , Homaeifar Reza , Shayan Leila , Saadatjoo Zohreh , Paydar Shahram
Published: February 2024

Background and Aims

The COVID‐19 pandemic has reshaped the epidemiology of various clinical conditions, including trauma which is closely tied to social policies. This study examines and compares the characteristics of trauma mortality patients, and their initial prognostic trauma scores, in the pre‐pandemic and pandemic periods.

Methods

We conducted a retrospective observational study involving patients who passed away at a level 1 trauma center from July 23, 2018, to February 19, 2020 (prepandemic), and from February 20, 2020, to September 22, 2021 (pandemic). A subgroup analysis that matched 12 of the same months of the year in the two periods was also done. Patients who arrived deceased or passed away immediately upon arrival were excluded from data analysis. We collected and analyzed demographic and clinical data, employing the Abbreviated Injury Score (AIS), Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and ISS (TRISS) to compare initial prognoses.

Results

Our study encompassed 1128 patients, with 529 in the prepandemic group and 599 in the pandemic group. Demographic characteristics showed no significant differences in the number of patients in the two periods. Motor vehicle accidents remained the predominant injury mechanism in both periods. While the mean ISS increased insignificantly (22.80 vs. 22.91, p = 0.902), the mean RTS decreased (6.32 vs. 5.82), and TRISS increased (23.97% vs. 28.93%) during the pandemic (p < 0.05). Hospital length of stay decreased in the pandemic period (15.57 vs. 12.54 days, p < 0.05). Subgroup analysis revealed increased ISS, decreased RTS, and increased TRISS during the pandemic (p < 0.05).

Conclusion

In conclusion, while overall demographics and injury mechanisms remained virtually unchanged, trauma patients during the pandemic displayed worse estimated clinical prognoses, particularly in physiological trauma scores. The heightened mortality rate was attributed to poorer clinical conditions of patients.