bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of shear rate on orientation of cellulosic nanofibers and nanocrystals in poly(butylene adipate‐co‐terephthalate) based composites
Authors: Keskes Mariam , Desse Melinda , Carrot Christian , Jaziri Mohamed 
Published: September 2024

AbstractPoly(butylene adipate‐co‐terephthalate) with or without thermoplastic starch is often used as a biodegradable matrix in composites reinforced with 5 and 10 wt% of either microfibrillated cellulose or cellulose nanocrystals. If dispersion of the fillers is well studied, their orientation in melt blended composites requires further understanding. In this study, the effect of a controlled shear rate on the orientation of the filler was investigated to understand how shear rate affects orientation and how orientation affects mechanical properties of the composites. To this end, composites prepared by melt mixing and then compressed were taken as a reference state of low orientation. On the contrary, to orient the fillers, extrusion through a slit die with a determined shear rate was carried out. Results of tensile tests, microscopic observations, atomic force microscopy and dynamic mechanical analysis in the melt showed that orientation of fillers in the flow axis was possible for shear rates higher than 13 s−1. The orientated samples presented enhanced mechanical properties in the elastic domain as opposed to unoriented samples. In general, orientation of fillers leads to uniaxial stiffness at lower filler content with much better ductility. However, this was observed only on samples for which the percolation of the filler was not obtained in the unoriented state, otherwise, orientation proved to be detrimental to the elastic mechanical properties because of the rupture in the formed network.Highlights
Orientation can be controlled during processing.
Sufficient shear rate is required.
Orientation improves mechanical properties.
Orientation might have a negative effect on rigidity in case of existing network.
A review on the ductility design method of fiber‐reinforced polymer bar and future prospects
Authors: Xu Yunbo , Zhang Yu , Zhu Haitang , Gao Danying , Qin Daotian , Zhao Liangping 
Published: September 2024

AbstractIn this paper, the ductility design methods of fiber‐reinforced polymer (FRP) bars were reviewed. It was observed that the graded fracture theory was typically used as the ductility design method of hybrid fiber‐reinforced polymer (HFRP) bar. However, the ductile HFRP bar designed based on the graded fracture theory had the inherent defects of low modulus of elasticity, high yield strain, and post‐yielded sudden drop in stress, which prevented its large‐scale application in civil engineering. In order to eliminate these deficiencies, the authors proposed a novel design concept for a single‐type FRP bar. This novel single‐type FRP bar consisted of highly aligned discontinuous fiber and continuous fiber. The failure mode of this discontinuous/continuous single‐type FRP bar was different from that of the ductile HFRP bar designed based on the graded fracture theory of composite. The tensile ductility of discontinuous/continuous single‐type FRP bar originated from the debonding and stable pull‐out of the discontinuous fiber layer under increasing load. As a result, the post‐yielded sudden drop in stress can be removed for the ductile HFRP bar designed based on the graded fracture theory of composite. In addition, the yield strain can be controlled by adjusting the length of discontinuous fiber layer. In addition, the design configuration, innovative production process, and corresponding theoretical calculations of this novel single‐type FRP bar will be presented in the future.Highlights
The ductility design methods of fiber‐reinforced polymer bars were reviewed.
Deficiencies of ductile HFRP bar composed of continuous fibers were reported.
A novel discontinuous/continuous single‐type FRP bar was foreseen.
Compression molding of ethylene–octene copolymer‐toughened polypropylene/graphene surfaces with actively controlled shape‐morphing microarchitectures induced by friction and wear
Authors: He Jiayi , Wu Weiting , Xu Jinhua , Ding Sha , Zhang Xin , Zhang Jingjing , Lei Caihong , Chen Anfu , Huang Lijia 
Published: September 2024

AbstractSuperhydrophobic microarchitectured polyolefin surfaces are currently used intensively in various industrial applications. However, the deployment of products made of these materials into practical application is typically constrained by their inferior dry sliding behaviors, which stem from their limited strength and toughness. To obtain reinforced and toughened superhydrophobic microstructured surfaces that can be easy to demold and overcome friction in the workplace, elastomeric ethylene–octene copolymer (POE) and rigid graphene (GP) were introduced into the polypropylene (PP) matrix to prepare microstructured PP/POE/GP surfaces by compression molding. The elongation at break is significantly improved by 2000% and reached up to 520.33%. The contact angle (CA) of the microstructured PP/POE/GP surface increases to 154.4°. They exhibit superhydrophobic and low adhesion characteristic, that is, lotus effect. The enhanced toughness of PP/POE/GP composites reduces wear debris and damage to microarchitecture during the abrasion process. Even after the microstructured PP/POE/GP surfaces were worn after a distance length of 3000 mm, they still exhibited superhydrophobic, but high adhesion characteristic, that is, petal effect. The controlled shape‐morphing microarchitectures formed on the microstructured PP/POE/GP surface abraded after 1000 mm, possessing wetting stability during droplet impacting.Highlights
The elongation at break of composites was improved by 2000% through adding POE.
The composite microstructure deforms to consume energy during abrasion and POE reinforces this energy dissipation process.
POE improves fracture toughness and wetting stability of composites.
Compatibility of Linehan's biosocial theory and the DSM‐5 Alternative Model of Personality Disorders for borderline personality disorder
Authors: Livingston Nicholas R. , Stanton Kasey 
Published: September 2024

AbstractBorderline personality disorder (BPD) is characterized by affective, interpersonal, and identity instability, as well as marked impulsivity. There is evidence that BPD may be best operationalized dimensionally using models such as the Alternative Model for Personality Disorders (AMPD) described in Section III of the Diagnostic and Statistical Manual for Mental Disorders (DSM). Moreover, biosocial theory is a well‐known etiological theory of BPD emphasizing emotion dysregulation, inherited impulsivity, and development within invalidating contexts as key etiological mechanisms. Given that current research and clinical efforts for BPD are informed by both nosology and etiology, this narrative review examined how well biosocial theory (a) aligns with AMPD conceptualizations, (b) accounts for psychiatric comorbidity, and (c) accounts for heterogeneity in BPD presentation. Findings suggested that tenets of biosocial theory align well with Criteria A and B of the AMPD; however, biosocial theory focuses narrowly on roles of emotion dysregulation, impulsivity, and invalidating contexts, and empirical support is lacking in some ways for several etiological explanations proposed by biosocial theory. Additionally, although biosocial theory captures empirically supported features of BPD and emphasizes high‐risk subgroups, the theory may not account for lower‐risk subgroups. Finally, the theory accounts for diagnostic co‐occurrence via the central role of emotion dysregulation, but biosocial theory may not be specific to BPD and may broadly apply to a range of psychopathology. Based on the literature reviewed, implications for future research and clinical efforts are highlighted.
High‐strength antifreezing flexible conductive polyvinyl alcohol hydrogel sensors co‐reinforced with silk porous mesh fabric and silk nanofibers
Authors: Zhuge Chengyao , Wang Yaping , Qian Qian , Li Shunyang , Lu Wangyang , Li Nan 
Published: September 2024

AbstractHydrogel‐based flexible strain sensors have an enormous potential for applications in wearable electronics, but currently, realizing excellent mechanical properties and electrical conductivity of sensors is difficult. In this work, polyvinyl alcohol (PVA) hydrogels were augmented with positively charged silk nanofibers (PCSNF) and PEDOT:PSS, and the resultant PVA‐PEDOT:PSS‐PCSNF hydrogel fabric showed remarkable mechanical properties (4.38 MPa) and elevated electrical conductivity. The presence of ethylene glycol (EG) in the hydrogel fabric imparts antifreezing properties and sustains electrical conductivity even at frigid temperatures (−18°C). In addition, EG contributes to the improvement of the electrical conductivity of PEDOT:PSS. This PVA‐PEDOT:PSS‐PCSNF hydrogel fabric can be used as a precise and reliable strain sensor for detecting diverse human motions and facial expressions. Significantly, the PVA‐PEDOT:PSS‐PCSNF hydrogel fabric strain sensor exhibits a gauge factor of 1.02 and exceptional durability, withstanding 400 elbow bends. This study introduces an innovative method for creating high‐performance and resilient hydrogel‐based flexible sensors.
Exploring edible bird nest's potential in mitigating Wi‐Fi's impact on male reproductive health
Authors: Maluin Sofwatul Mokhtarah , Jaffar Farah Hanan Fathihah , Osman Khairul , Zulkefli Aini Farzana , Mat Ros Mohd Farisyam , Ibrahim Siti Fatimah 
Published: September 2024

AbstractPurposeThis study aimed to evaluate the protective effects of edible bird nest (EBN) against the detrimental impact of Wi‐Fi on male reproductive health. Specifically, it examines whether EBN can mitigate Wi‐Fi‐induced changes in male reproductive hormones, estrogen receptors (ER), spermatogenesis, and sperm parameters.MethodsThirty‐six adult male rats were divided into six groups (n = 6): Control, Control EBN, Control E2, Wi‐Fi, Wi‐Fi+EBN, and Wi‐Fi+E2. Control EBN and Wi‐Fi+EBN groups received 250 mg/kg/day EBN, while Control E2 and Wi‐Fi+E2 groups received 12 μg/kg/day E2 for 10 days. Wi‐Fi exposure and EBN supplementation lasted eight weeks. Assessments included organ weight, hormone levels (FSH, LH, testosterone, and E2), ERα/ERβ mRNA and protein expression, spermatogenic markers (c‐KIT and SCF), and sperm quality.ResultsWi‐Fi exposure led to decreased FSH, testosterone, ERα mRNA, and sperm quality (concentration, motility, and viability). EBN supplementation restored serum FSH and testosterone levels, increased serum LH levels, and the testosterone/E2 ratio, and normalized mRNA ERα expression. Additionally, EBN increased sperm concentration in Wi‐Fi‐exposed rats without affecting motility or viability.ConclusionsEBN plays a crucial role in regulating male reproductive hormones and spermatogenesis, leading to improved sperm concentration. This could notably benefit men experiencing oligospermia due to excessive Wi‐Fi exposure.
Data transformations cause altered edaphic‐climatic controls and reduced predictability on soil carbon decomposition rates
Authors: Xiang Daifeng , Wang Gangsheng , Lv Zehao , Li Wanyu , Tian Jing 
Published: September 2024

AbstractData transformation of the reference soil organic matter (SOM) decomposition rates (kref), often derived as turnover times or in alternative formats, is commonly used to develop ecological models for projecting the persistence of SOM. However, the effects of reciprocal or logarithmic transformation of kref on model performance and edaphic‐climatic patterns remain uncertain. Here, we convert published kref values into reciprocal or logarithmic formats and establish machine learning models between the transformed kref and edaphic‐climatic predictors. We show that models trained with the transformed kref exhibit a 11.6%−68.4% reduction in performance upon re‐conversion to kref compared to those trained with the original kref. The variable importance analysis identifies distinct key predictors governing the original kref and its transformed counterparts. This suggests that data transformation alters the relative significance of predictors without necessarily improving kref prediction performance. Consequently, our study underscores the importance of directly focusing on the original values rather than alternative representations when dissecting a given variable's patterns and mechanisms in ecological modeling.
International collaborative study on measuring protein solubility index for legumes, oilseeds, cereals, and related products
Authors: Liu Keshun , Seegers Susan , Hojilla‐Evangelista Mila P. , Pallares Pallares Andrea , Wu Xin 
Published: September 2024

AbstractProtein quality affects nutritional value and functional properties of protein products. It is important to assess protein quality accurately and cost‐effectively. Recently, a new indicator for protein quality, protein solubility index (PSI), was developed (JAOCS, 2022; 99, 855–871). The new method, featuring 5 mM NaOH extraction with magnetic stirring and simultaneous running of multiple samples, was proposed as AOCS method Ba 15‐2023. As part of the AOCS method approval process, a collaborative study was conducted to evaluate its performance. It involved 16 laboratories from 10 countries to measure PSI of the 12 selected samples plus a blind duplicate, including soybeans, pulses, cereals, and their processed products (flours, concentrates and isolates). After rigorous statistical analysis to remove a few outliers, several precision parameters were calculated. Repeatability relative standard deviations (RSDr) ranged 0.6%–11.4%, with 10 samples having RSDr ≤ 5%. Reproducibility RSDR ranged 2.6%–15.7%. The five samples with RSDR ≥ 10% corresponded to protein isolates or those with the lowest N content or the lowest PSI. The study demonstrated robust performance of the proposed AOCS method. A few collaborators carried out additional experiments to address some aspects of the method, leading to further improvement. The results of the present study were presented to the AOCS Uniform Methods Committee for evaluation. Once the method is adopted as the Official Method for measuring PSI in various protein products, it is poised to serve as a unified index for protein quality with respect to both nutritional value and functional properties.
Cocatalyst Embedded Ce‐BDC‐CeO2 S‐Scheme Heterojunction Hollowed‐Out Octahedrons With Rich Defects for Efficient CO2 Photoreduction
Authors: Li Wenpeng , Chen Yajie , Zhang Jiajia , Zeng Fanze , Bao Jinyu , Liu Lu , Tian Guohui 
Published: September 2024

AbstractConstructing heterojunction photocatalysts with optimized architecture and components is an effective strategy for enhancing CO2 photoreduction by promoting photogenerated carrier separation, visible light absorption, and CO2 adsorption. Herein, defect‐rich photocatalysts (Ni2P@Ce‐BDC‐CeO2 HOOs) with S‐scheme heterojunction and hollowed‐out octahedral architecture are prepared by decomposing Ce‐BDC octahedrons embedded with Ni2P nanoparticles and subsequent lactic acid etching for CO2 photoreduction. The hollowed‐out octahedral architecture with multistage pores (micropores, mesopores, and macropores) and oxygen vacancy defects are simultaneously produced during the preparation process. The S‐scheme heterojunction boosts the quick transfer and separation of photoinduced charges. The formed hollowed‐out multi‐stage pore structure is favorable for the adsorption and diffusion of CO2 molecules and gaseous products. As expected, the optimized photocatalyst exhibits excellent performance, producing CO with a yield of 61.6 µmol h−1 g−1, which is four times higher than that of the original Ce‐BDC octahedrons. The X‐ray photoelectron spectroscopy, scanning Kelvin probe, and electron spin resonance spectroscopy characterizations confirm the S‐schematic charge‐transfer route. The key intermediate species during the CO2 photoreduction process are detected by in situ Fourier transform infrared spectroscopy to support the proposed mechanism for CO2 photoreduction. This work presents a synthetic strategy for excellent catalysts with potential prospects in photocatalytic applications.
A New Class of Mechano‐Responsive Polyurethane Via Anthracene ‐TAD Diels‐Alder (DA) Click Chemistry
Authors: Chakraborty Swadhin , Choudhury Soumyadip , Singha Nikhil K. 
Published: September 2024

AbstractSmart or stimuli‐responsive polymers have garnered significant interest in the scientific community due to their response to different stimuli like pH, temperature, light, mechanical force, etc. Mechanophoric polymer is an intriguing class of smart polymers that respond to external mechanical force by producing fluorescent moieties and can be utilized for damage detection and stress‐sensing assessment. In recent reports on mechanophoric polymers, different mechanophoric motifs such as spiropyran, rhodamine, coumarin, etc. are explored. This investigation reports a new kind of mechanophoric polyurethane (PU) adduct based on Diels‐Alder (DA) click chemistry. Here, an anthracene(An)‐end capped tri‐armed urethane system is synthesized, followed by a DA reaction using bis‐(1,2,4‐triazoline‐3,5‐dione) (bis‐TAD) derivative. The incorporation of bis‐TAD in the urethane system renders the anthracene inactive (“turn‐off”) by dismantling its conjugation as a result of a successful DA reaction. The soft PU translated into a harder material through bis‐TAD linkages between polymer chains as evident from nanoindentation (NINT) analysis. The resulting material reverts back to its fluorescent “turned‐on” mode owing to a force‐accelerated retro‐Diels‐Alder (r‐DA) reaction. Besides the mechanophoric attributes, the material demonstrates self‐healing behavior examined by microscopic investigations. This innovative approach can be a potential route to design responsive polymers with dynamic functionalities for advanced material applications.
Quantum‐Sized Co Nanoparticles with Rich Vacancies Enabled the Uniform Deposition of Lithium Metal and Fast Polysulfide Conversion
Authors: Rong Jinsheng , Zhang Jiangjiang , Wang Wenxin , Miao Junqian , Chen Lanli , Cui Shiqiang 
Published: September 2024

AbstractThe notorious polysulfide shuttling and uncontrollable Li‐dendrite growth are the main obstacles to the marketization of Li‐S batteries. Herein, a dual‐functional material consisting of vacancy‐rich quantum‐sized Co nanodots anchored on a mesoporous carbon layer (v‐Co/meso‐C) is proposed. This material exposes more active sites to improve its reaction performance and simultaneously realizes excellent lithiophilicity and sulfiphilicity characteristics in Li‐S electrochemistry. As Li metal deposition hosts, v‐Co/meso‐C shows small nucleation overpotential, low polarization, and ultra‐long cycling stability in both half and symmetric cells, as confirmed by experimental studies. On the S cathode side, experimental and theoretical calculations demonstrate that v‐Co/meso‐C enhances the adsorption of polysulfides and boosts their catalytic conversion rate. This, in turn, suppresses the shuttle effect of polysulfides and improves sulfur utilization efficiency. Finally, a shuttle‐free and dendrite‐free v‐Co/meso‐C@Li//v‐Co/meso‐C@S full cell is fabricated, exhibiting excellent rate performance (739 mAh g−1 at 5.0 C) and good cyclability (capacity decay rate is 0.033% and 0.035% per cycle at 2.0 and 5.0 C, respectively). Even a pouch cell with high sulfur loading (5.5 mg cm−2) and lean electrolyte/sulfur (4.8 µL mg−1) can still work 50 cycles with 80% capacity retention rate. This study shows far‐reaching implications in the design of dendrite‐free, shuttle‐free Li‐S batteries.
The fourth industrial revolution and the future of work: Reasons to worry and policies to consider
Authors: Goldsmith Arthur H. , Casey James F. 
Published: September 2024

AbstractA striking feature of the contemporary U.S. economy is the widespread adoption of technologies associated with the 4th Industrial Revolution (IR) including sensors, industrial robotics, artificial intelligence, and machine learning. Empirical work investigating the labor market impacts of 4th IR technological advances reveals they are skill‐biased, primarily advancing job opportunities for those with high levels of formal of education, unlike prior industrial revolutions that were skill neutral. This paper explains how the 4th IR has fostered job polarization, greater technological unemployment, and increasing wage inequality. Moreover, we delineate why these developments are worrisome and likely to expand over time. We assert that policy intervention to promote reinstatement of technologically unemployed persons is warranted, because displacement of labor caused by automation creates negative externalities. Consequently, we provide an example of how tax policies could be used to curtail technological unemployment—without creating hurdles for the adoption of 4th IR innovations. We advance and describe a new, innovative way, for fiscal policy to foster employment opportunities for those at greatest risk of job loss through automation. The initiative entails government subsidies to promote the provision and acquisition of skill certificates that employers view as complementary with 4th Industrial Revolution Technologies.
Prediction of wind pressures on supertall buildings based on proper orthogonal decomposition and machine learning
Authors: Huang Jia‐Xing , Li Qiu‐Sheng , Han Xu‐Liang 
Published: September 2024

AbstractDetailed wind pressure information plays a critical role in the accurate estimation of wind loads on high‐rise buildings, especially for complex‐shaped supertall buildings. However, owing to the limited internal space of a scaled building model and the capacity of data‐acquisition devices, it is often difficult to acquire the wind pressures at all positions of interest on the entire model in wind tunnel testing. To this end, a novel approach that combines the proper orthogonal decomposition (POD) and machine learning (ML) is presented in this paper for the prediction of wind pressure time series (WPTS) on supertall building models in wind tunnel testing. In this approach, the prediction of WPTS is converted into the estimation of several main eigenmodes and mean wind pressures by combining the POD with ML. This strategy can effectively reduce the computational effort compared to the direct prediction of WPTS. A combined ML model consisting of the Gaussian process regression (GPR), decision tree regression (DTR), and random forest (RF) (i.e., POD‐GPR‐DTR‐RF model) is utilized for the prediction of eigenmodes and mean wind pressures. Wind pressure records from a wind tunnel experiment of a 600‐m‐high building are employed to verify the accuracy and effectiveness of the presented approach. The results show that the combined ML model (i.e., POD‐GPR‐DTR‐RF model) developed based on the proposed approach performs satisfactorily in the prediction of WPTS and outperforms the conventional method that combines POD with backpropagation neural network model (i.e., POD‐BPNN model), demonstrating that the proposed approach is an effective tool for prediction of WPTS on supertall buildings.