bluuebunny/crossref_metadata_2025 huggingface dataset:
Catalytic properties of trivalent rare-earth oxides with intrinsic surface oxygen vacancy
Authors: Xu Kai , Liu Jin-Cheng , Wang Wei-Wei , Zhou Lu-Lu , Ma Chao , Guan Xuze , Wang Feng Ryan , Li Jun , Jia Chun-Jiang , Yan Chun-Hua
Published: July 2024

Oxygen vacancy (Ov) is an anionic defect widely existed in metal oxide lattice, as exemplified by CeO2, TiO2, and ZnO. As Ov can modify the band structure of solid, it improves the physicochemical properties such as the semiconducting performance and catalytic behaviours. We report here a new type of Ov as an intrinsic part of a perfect crystalline surface. Such non-defect Ov stems from the irregular hexagonal sawtooth-shaped structure in the (111) plane of trivalent rare earth oxides (RE2O3). The materials with such intrinsic Ov structure exhibit excellent performance in ammonia decomposition reaction with surface Ru active sites. Extremely high H2 formation rate has been achieved at ~1 wt% of Ru loading over Sm2O3, Y2O3 and Gd2O3 surface, which is 1.5–20 times higher than reported values in the literature. The discovery of intrinsic Ov suggests great potentials of applying RE oxides in heterogeneous catalysis and surface chemistry.
Acquisition of molecular rolling lubrication by self-curling of graphite nanosheet at cryogenic temperature
Authors: Li Panpan , He Wenhao , Ju Pengfei , Ji Li , Liu Xiaohong , Wu Fan , Lu Zhibin , Li Hongxuan , Chen Lei , Liu Jingzhou , Zhou Huidi , Chen Jianmin
Published: July 2024

Friction as a fundamental physical phenomenon dominates nature and human civilization, among which the achievement of molecular rolling lubrication is desired to bring another breakthrough, like the macroscale design of wheel. Herein, an edge self-curling nanodeformation phenomenon of graphite nanosheets (GNSs) at cryogenic temperature is found, which is then used to promote the formation of graphite nanorollers in friction process towards molecular rolling lubrication. The observation of parallel nanorollers at the friction interface give the experimental evidence for the occurrence of molecular rolling lubrication, and the graphite exhibits abnormal lubrication performance in vacuum with ultra-low friction and wear at macroscale. The molecular rolling lubrication mechanism is elucidated from the electronic interaction perspective. Experiments and theoretical simulations indicate that the driving force of the self-curling is the uneven atomic shrinkage induced stress, and then the shear force promotes the intact nanoroller formation, while the constraint of atomic vibration decreases the dissipation of driving stress and favors the nanoroller formation therein. It will open up a new pathway for controlling friction at microscale and nanostructural manipulation.
A fungal metabolic regulator underlies infectious synergism during Candida albicans-Staphylococcus aureus intra-abdominal co-infection
Authors: Paul Saikat , Todd Olivia A. , Eichelberger Kara R. , Tkaczyk Christine , Sellman Bret R. , Noverr Mairi C. , Cassat James E. , Fidel Paul L. , Peters Brian M.
Published: July 2024

Candida albicans and Staphylococcus aureus are two commonly associated pathogens that cause nosocomial infections with high morbidity and mortality. Our prior and current work using a murine model of polymicrobial intra-abdominal infection (IAI) demonstrates that synergistic lethality is driven by Candida-induced upregulation of functional S. aureus α-toxin leading to polymicrobial sepsis and organ damage. In order to determine the candidal effector(s) mediating enhanced virulence, an unbiased screen of C. albicans transcription factor mutants was undertaken revealing that zcf13Δ/Δ fails to drive augmented α-toxin or lethal synergism during co-infection. A combination of transcriptional and phenotypic profiling approaches shows that ZCF13 regulates genes involved in pentose metabolism, including RBK1 and HGT7 that contribute to fungal ribose catabolism and uptake, respectively. Subsequent experiments reveal that ribose inhibits the staphylococcal agr quorum sensing system and concomitantly represses toxicity. Unlike wild-type C. albicans, zcf13Δ/Δ did not effectively utilize ribose during co-culture or co-infection leading to exogenous ribose accumulation and agr repression. Forced expression of RBK1 and HGT7 in the zcf13Δ/Δ mutant fully restores pathogenicity during co-infection. Collectively, our results detail the interwoven complexities of cross-kingdom interactions and highlight how intermicrobial metabolism impacts polymicrobial disease pathogenesis with devastating consequences for the host.
Two-dimensional bilayer ice in coexistence with three-dimensional ice without confinement
Authors: Jiang Jing , Lai Yuanming , Sheng Daichao , Tang Guihua , Zhang Mingyi , Niu Dong , Yu Fan
Published: July 2024

Icing plays an important role in various physical-chemical process. Although the formation of two-dimensional ice requires nanoscale confinement, two-dimensional bilayer ice in coexistence with three-dimensional ice without confinement remains poorly understood. Here, a critical value of a surface energy parameter is identified to characterize the liquid-solid interface interaction, above which two-dimensional and three-dimensional coexisting ice can surprisingly form on the surface. The two-dimensional ice growth mechanisms could be revealed by capturing the growth and merged of the metastable edge structures. The phase diagram about temperature and pressure vs energy parameters is predicted to distinguish liquid water, two-dimensional ice and three-dimensional ice. Furthermore, the deicing characteristics of coexisting ice demonstrate that the ice adhesion strength is linearly related to the ratio of ice-surface interaction energy to ice temperature. In addition, for gas-solid phase transition, the phase diagram about temperature and energy parameters is predicted to distinguish gas, liquid water, two-dimensional ice and three-dimensional ice. This work gives a perspective for studying the singular structure and dynamics of ice in nanoscale and provides a guide for future experimental realization of the coexisting ice.
Regioselective fluorination of allenes enabled by I(I)/I(III) catalysis
Authors: Wang Zi-Xuan , Xu Yameng , Gilmour Ryan
Published: July 2024

The prominence and versatility of propargylic fluorides in medicinal chemistry, coupled with the potency of F/H and F/OH bioisosterism, has created a powerful impetus to develop efficient methods to facilitate their construction. Motivated by the well-established conversion of propargylic alcohols to allenes, an operationally simple, organocatalysis-based strategy to process these abundant unsaturated precursors to propargylic fluorides would be highly enabling: this would consolidate the bioisosteric relationship that connects propargylic alcohols and fluorides. Herein, we describe a highly regioselective fluorination of unactivated allenes based on I(I)/I(III) catalysis in the presence of an inexpensive HF source that serves a dual role as both nucleophile and Brønsted acid activator. This strategy enables a variety of secondary and tertiary propargylic fluorides to be prepared: these motifs are prevalent across the bioactive small molecule spectrum. Facile product derivatisation, concise synthesis of multi-vicinal fluorinated products together with preliminary validation of enantioselective catalysis are disclosed. The expansive potential of this platform is also demonstrated through the highly regioselective organocatalytic oxidation, chlorination and arylation of allenes. It is envisaged that the transformation will find application in molecular design and accelerate the exploration of organofluorine chemical space.
Fully nonlinear neuromorphic computing with linear wave scattering
Authors: Wanjura Clara C. , Marquardt Florian
Published: July 2024

The increasing size of neural networks for deep learning applications and their energy consumption create a need for alternative neuromorphic approaches, for example, using optics. Current proposals and implementations rely on physical nonlinearities or optoelectronic conversion to realize the required nonlinear activation function. However, there are considerable challenges with these approaches related to power levels, control, energy efficiency and delays. Here we present a scheme for a neuromorphic system that relies on linear wave scattering and yet achieves nonlinear processing with high expressivity. The key idea is to encode the input in physical parameters that affect the scattering processes. Moreover, we show that gradients needed for training can be directly measured in scattering experiments. We propose an implementation using integrated photonics based on racetrack resonators, which achieves high connectivity with a minimal number of waveguide crossings. Our work introduces an easily implementable approach to neuromorphic computing that can be widely applied in existing state-of-the-art scalable platforms, such as optics, microwave and electrical circuits.
Effects of metronome walking on long-term attractor divergence and correlation structure of gait: a validation study in older people
Authors: Piergiovanni Sophia , Terrier Philippe
Published: July 2024

This study investigates the effects of metronome walking on gait dynamics in older adults, focusing on long-range correlation structures and long-range attractor divergence (assessed by maximum Lyapunov exponents). Sixty older adults participated in indoor walking tests with and without metronome cues. Gait parameters were recorded using two triaxial accelerometers attached to the lumbar region and to the foot. We analyzed logarithmic divergence of lumbar acceleration using Rosenstein’s algorithm and scaling exponents for stride intervals from foot accelerometers using detrended fluctuation analysis (DFA). Results indicated a concomitant reduction in long-term divergence exponents and scaling exponents during metronome walking, while short-term divergence remained largely unchanged. Furthermore, long-term divergence exponents and scaling exponents were significantly correlated. Reliability analysis revealed moderate intrasession consistency for long-term divergence exponents, but poor reliability for scaling exponents. Our results suggest that long-term divergence exponents could effectively replace scaling exponents for unsupervised gait quality assessment in older adults. This approach may improve the assessment of attentional involvement in gait control and enhance fall risk assessment.
Non-invasive VOCs detection to monitor the gut microbiota metabolism in-vitro
Authors: Dell’Olio Andrea , Rubert Josep , Capozzi Vittorio , Tonezzer Matteo , Betta Emanuela , Fogliano Vincenzo , Biasioli Franco
Published: July 2024

This work implemented a non-invasive volatile organic compounds (VOCs) monitoring approach to study how food components are metabolised by the gut microbiota in-vitro. The fermentability of a model food matrix rich in dietary fibre (oat bran), and a pure prebiotic (inulin), added to a minimal gut medium was compared by looking at global changes in the volatilome. The substrates were incubated with a stabilised human faecal inoculum over a 24-h period, and VOCs were monitored without interfering with biological processes. The fermentation was performed in nitrogen-filled vials, with controlled temperature, and tracked by automated headspace-solid-phase microextraction coupled with gas chromatography–mass spectrometry. To understand the molecular patterns over time, we applied a multivariate longitudinal statistical framework: repeated measurements—ANOVA simultaneous component analysis. The methodology was able to discriminate the studied groups by looking at VOCs temporal profiles. The volatilome showed a time-dependency that was more distinct after 12 h. Short to medium-chain fatty acids showed increased peak intensities, mainly for oat bran and for inulin, but with different kinetics. At the same time, alcohols, aldehydes, and esters showed distinct trends with discriminatory power. The proposed approach can be applied to study the intertwined pathways of gut microbiota food components interaction in-vitro.
Apolipoprotein E polymorphisms and female fertility in a transgenic mouse model of Alzheimer’s disease
Authors: Medegan Fagla Bani , York Jason , Christensen Amy , Dela Rosa Cielo , Balu Deebika , Pike Christian J. , Tai Leon M. , Buhimschi Irina A.
Published: July 2024

Apolipoprotein E (APOE) is a major cholesterol carrier responsible for lipid transport and injury repair in the brain. The human APOE gene (h-APOE) has 3 naturally occurring alleles: ε3, the common allele; ε4, which increases Alzheimer’s disease (AD) risk up to 15-fold; and ε2, the rare allele which protects against AD. Although APOE4 has negative effects on neurocognition in old age, its persistence in the population suggests a survival advantage. We investigated the relationship between APOE genotypes and fertility in EFAD mice, a transgenic mouse model expressing h-APOE. We show that APOE4 transgenic mice had the highest level of reproductive performance, followed by APOE3 and APOE2. Intriguingly, APOE3 pregnancies had more fetal resorptions and reduced fetal weights relative to APOE4 pregnancies. In conclusion, APOE genotypes impact fertility and pregnancy outcomes in female mice, in concordance with findings in human populations. These mouse models may help elucidate how h-APOE4 promotes reproductive fitness at the cost of AD in later life.
Disease burden of stroke and its subtypes attributable to low dietary fiber in China, 1990–2019
Authors: Jin Shuai , Xie Lang , Wang Junwen , Xia Kaide , Zhang Haiwang
Published: July 2024

This study aimed to assess the current status and changing trends of the disease burden of stroke and its subtypes due to low dietary fiber intake in China from 1990 to 2019. In cases of stroke and its subtypes attributable to low dietary fiber, deaths, disability-adjusted life-years (DALYs), age-standardized mortality rates (ASMR), age-standardized DALYs rates (ASDR), and percentage change were used to assess disease burden. Data were obtained from the 2019 global burden of disease study. Trends were assessed using Joinpoint regression and age-period-cohort analysis. Between 1990 and 2019, there was a declining trend in stroke and its subtypes, ASDR and ASMR, as well as the corresponding number of deaths and DALYs, due to low dietary fiber intake in China. Subarachnoid hemorrhage (SH) showed the greatest decrease, followed by intracerebral hemorrhage (IH) and ischemic stroke (IS). Local drift curves showed a U-shaped distribution of stroke, IS, and IH DALYs across the whole group and sex-based groups. For mortality, the overall and male trends were similar to those for DALYs, whereas female stroke, IH, and IS showed an upward trend. The DALYs for stroke and IH showed a clear bimodal distribution, IS showed an increasing risk with age. For mortality, the SH subtype showed a decreasing trend, whereas other subtypes showed an increasing risk with age. Both the period and cohort rates of stroke DALYs and motality due to low dietary fiber have declined. Males had a higher risk of DALYs and mortality associated with low fiber levels. The burden of stroke and its subtypes associated with a low-fiber diet in China has been declining over the past 30 years, with different patterns of change for different stroke subtypes and a higher burden for males, highlighting the differential impact of fiber intake on stroke and its subtypes.
A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning
Authors: Zakeri Mostafa , Atef Amirhossein , Aziznia Mohammad , Jafari Azadeh
Published: July 2024

Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population. Their development can be attributed to various factors, presentations, and treatment approaches. The importance of selecting the appropriate treatment becomes evident upon diagnosis, as the severity of the disease guides the course of action. Cerebral aneurysms are particularly vulnerable in the circle of Willis and pose a significant concern due to the potential for rupture, which can lead to irreversible consequences, including fatality. The primary objective of this study is to predict the rupture status of cerebral aneurysms. To achieve this, we leverage a comprehensive dataset that incorporates clinical and morphological data extracted from 3D real geometries of previous patients. The aim of this research is to provide valuable insights that can help make informed decisions during the treatment process and potentially save the lives of future patients. Diagnosing and predicting aneurysm rupture based solely on brain scans is a significant challenge with limited reliability, even for experienced physicians. However, by employing statistical methods and machine learning techniques, we can assist physicians in making more confident predictions regarding rupture likelihood and selecting appropriate treatment strategies. To achieve this, we used 5 classification machine learning algorithms and trained them on a substantial database comprising 708 cerebral aneurysms. The dataset comprised 3 clinical features and 35 morphological parameters, including 8 novel morphological features introduced for the first time in this study. Our models demonstrated exceptional performance in predicting cerebral aneurysm rupture, with accuracy ranging from 0.76 to 0.82 and precision score from 0.79 to 0.83 for the test dataset. As the data are sensitive and the condition is critical, recall is prioritized as the more crucial parameter over accuracy and precision, and our models achieved outstanding recall score ranging from 0.85 to 0.92. Overall, the best model was Support Vector Machin with an accuracy and precision of 0.82, recall of 0.92 for the testing dataset and the area under curve of 0.84. The ellipticity index, size ratio, and shape irregularity are pivotal features in predicting aneurysm rupture, respectively, contributing significantly to our understanding of this complex condition. Among the multitude of parameters under investigation, these are particularly important. In this study, the ideal roundness parameter was introduced as a novel consideration and ranked fifth among all 38 parameters. Neck circumference and outlet numbers from the new parameters were also deemed significant contributors.
Predictive value of inflammatory prognostic index for contrast-induced nephropathy in patients undergoing coronary angiography and/or percutaneous coronary intervention
Authors: Jiang Yan , Luo Baolin , Chen Yaqin , Peng Yanchun , Lu Wen , Chen Liangwan , Lin Yanjuan
Published: July 2024

The purpose of this study was to investigate the relationship between Inflammatory Prognostic Index (IPI) levels and Contrast-Induced Nephropathy (CIN) risk and postoperative clinical outcomes in patients undergoing coronary angiography (CAG) and/or percutaneous coronary intervention (PCI). A total of 3,340 consecutive patients who underwent CAG and/or PCI between May 2017 and December 2022 were enrolled in this study. Based on their baseline IPI levels, patients were categorized into four groups. Clinical characteristics and postoperative outcomes were compared among these groups. In-hospital outcomes focused on CIN risk, repeated revascularization, major bleeding, and major adverse cardiovascular events (MACEs), while the long-term outcome examined the all-cause readmission rate. Quartile analysis found a significant link between IPI levels and CIN risk, notably in the highest quartile (P < 0.001). Even after adjusting for baseline factors, this association remained significant, with an adjusted Odds Ratio (aOR) of 2.33 (95%CI 1.50–3.64; P = 0.001). Notably, baseline IPI level emerged as an independent predictor of severe arrhythmia, with aOR of 0.50 (95%CI 0.35–0.69; P < 0.001), particularly driven by the highest quartile. Furthermore, a significant correlation between IPI and acute myocardial infarction was observed (P < 0.001), which remained significant post-adjustment. For patients undergoing CAG and/or PCI, baseline IPI levels can independently predict clinical prognosis. As a comprehensive inflammation indicator, IPI effectively identifies high-risk patients post-procedure. This study underscores IPI's potential to assist medical professionals in making more precise clinical decisions, ultimately reducing mortality and readmission rates linked to cardiovascular disease (CVD).
An efficient, reliable and valid assessment for affective states during online learning
Authors: Siu Oi-ling , Lui Kelvin F. H. , Huang Yi , Ng Ting Kin , Yeung Wai Lan Victoria
Published: July 2024

The current study aims to develop an efficient, reliable and valid assessment, the affective states for online learning scale (ASOLS), for measuring learners’ affective states during online learning using a sample of 173 young learners. The assessment consists of 15 items which assess five affective states, including concentration, motivation, perseverance, engagement, and self-initiative. To improve efficiency, five items (one for each affective state) are randomly selected and presented every 30 min during online learning. In addition, 14 among the participants were further invited to perform on-site online learning, and their affective states were validated by observations conducted by two psychologists. The ASOLS was found to be reliable and valid, with high internal consistency reliabilities and good construct, convergent and criterion validity. Confirmatory factor analyses showed that the hypothesized five-factor structure demonstrated a satisfactory fit to the data. Moreover, engagement was found to be positively associated with learning performance. Our findings suggest that the ASOLS provides a useful tool for teachers to identify students in upper primary and junior secondary schools with deficits in affective states and offer appropriate remedy or support. It can also be used to evaluate the effectiveness of interventions aimed at enhancing students’ affective states during online learning.
A score and nine years of irbesartan
Authors: Ochsenbein Philippe , Bonin Michel , Fadaei-Tirani Farzaneh , Lemée Marie-Hélène , Kieffer Jérôme , Görl Daniel , El-Hajji Mohamed , Schenk-Joß Kurt
Published: July 2024

Irbesartan exists as tautomers A and B in diverse solvent mixtures. Homogeneous nucleation gives (pseudo)polymorphs with layer-wise or columnar growth. The desmotropes present different habits, thermal expansions, stabilities and phase transitions.
Development of problem-solving skills supported by metacognitive scaffolding: insights from students’ written work
Authors: Vo Kimberly , Sarkar Mahbub , White Paul J. , Yuriev Elizabeth
Published: July 2024

Despite problem solving being a core skill in chemistry, students often struggle to solve chemistry problems. This difficulty may arise from students trying to solve problems through memorising algorithms. Goldilocks Help serves as a problem-solving scaffold that supports students through structured problem solving and its elements, such as planning and evaluation. In this study, we investigated how first-year chemistry students solved problems, when taught with Goldilocks Help, and whether their problem-solving success and approaches changed over the course of one semester. The data comprised of student written problem-solving work, and was analysed using frequency analysis and grouped based on the problem-solving success and the extent of the demonstrated problem-solving elements. Throughout the course of semester, students exhibited increasingly consistent demonstration of structured problem solving. Nonetheless, they encountered difficulties in fully demonstrating such aspects of problem solving as understanding and evaluating concepts, which demand critical thinking and a firm grasp of chemistry principles. Overall, the study indicated progress in successful and structured problem solving, with a growing proportion of students demonstrating an exploratory approach as time progressed. These findings imply the need for incorporation of metacognitive problem-solving scaffolding, exposure to expert solutions, reflective assignments, and rubric-based feedback into wide teaching practice. Further research is required to extend the exploration of the effectiveness of metacognitive scaffolding, in particular via think-aloud interviews, which should help identify productive and unproductive uses of the problem-solving elements.
A portable label-free electrochemical DNA biosensor for rapid detection of Salmonella Typhi
Authors: Zambry Nor Syafirah , Awang Mohd Syafiq , Hamzah Hairul Hisham , Mohamad Ahmad Najib , Khalid Muhammad Fazli , Khim Beh Khi , Bustami Yazmin , Jamaluddin Nurul Fauzani , Ibrahim Fatimah , Aziah Ismail , Abd Manaf Asrulnizam
Published: July 2024

The graphical representation depicts a novel method of detecting Salmonella Typhi using a portable label-free electrochemical DNA biosensor-based printed circuit board gold electrode (PCBGE).
Advances in liquid organic hydrogen carriers: developing efficient dehydrogenation strategies
Authors: Tan Ruike , Ji Qing , Ling Yanni , Li Lu
Published: July 2024

In pursuit of global carbon neutrality, countries are intensifying their efforts to harness clean energy sources.
In situ fabrication of fully negatively-charged layer-by-layer nanofilms on a living cell surface
Authors: Zhang Zhuying , Zeng Jinfeng , Matsusaki Michiya
Published: July 2024

Biocompatible fully negatively-charged layer-by-layer nanofilms driven by Cu-free click reaction were assembled directly on the living cell surface.
On the variation of cluster core characteristics by an endohedral atom. Shape variation in 8-ce [EAu4(PPh3)4]2+ (E = N, P, As, Sb) clusters
Authors: Guajardo-Maturana Raul , MacLeod Carey Desmond , Rodríguez-Kessler Peter L. , Muñoz-Castro Alvaro
Published: July 2024

Atomically precise gold superatoms have attracted interest owing to their suitable use as building blocks for cluster-assembled materials, favoring ordered structures with advanced properties.
Ultrafast electron shuttling suppresses the energy transfer process in Mn-doped CsPbCl3 nanocrystals
Authors: Debnath Tushar
Published: July 2024

We show that ultrafast electron shuttling to surface-adsorbed 4-nitro phenol molecules from Mn-doped CsPbCl3 nanocrystals sets a complete restriction to the exciton scattering and a three-order slower exciton-to-dopant energy transfer process.
Mechanism of charge accumulation in potassium poly(heptazine imide)
Authors: Seo Goichiro , Hayakawa Ryoma , Wakayama Yutaka , Ohnuki Ryosuke , Yoshioka Shinya , Kanai Kaname
Published: July 2024

Energy diagram for a comprehensive understanding of charge accumulation, a critical phenomenon in dark photocatalysis.
Construction of a novel S-scheme AgVO3/CaIn2S4 heterostructure for efficient photodegradation of tetracycline hydrochloride
Authors: Zhang Lina , Li Xiaodong , Xu Haifeng , Zhang Wei , Yin Xiaotong , Tian Yuxin , Wang Qiushi , Ma Jinwen
Published: July 2024

CaIn2S4 nanoparticles are deposited onto the surface of AgVO3 to form an S-scheme heterojunction, enabling effective photocatalytic degradation of TCH.
Correction: A chelated borinium cation
Authors: Major Christopher , Lough Alan , Stephan Douglas W.
Published: July 2024

Correction for ‘A chelated borinium cation’ by Christopher Major et al., Dalton Trans., 2024, 53, 10075–10078, https://doi.org/10.1039/D4DT01242A.
Multi-channel dilution analysis
Authors: Jones Willis B. , Huff Robbie M. , Richardson Adam L. , Dessoffy Taylor , Lewis Sophie M. , Eddy Alexandria , Crossman Abigail J. , Jones Bradley T.
Published: July 2024

Multi-channel dilution analysis is a novel calibration method that automatically prepares dilutions of a standard solution as it travels to an analytical instrument.
Facile construction of iron-based MIL-101@MIL-53 Z-scheme heterojunction for the efficient removal of tetracycline hydrochloride
Authors: Zhang Xia , Chu Jialong , Zhang Yifang , Li Fei , Wang Chen , Li Tiemei , Fan Jing
Published: July 2024

In situ formation of an iron-based MIL-101@MIL-53 Z-scheme heterojunction promoted the separation of photogenerated carriers. Superoxide radical was the main active substance for tetracycline degradation.
In situgreen synthesis of copper-loaded chitin/hydroxyapatite hydrogels for efficient catalytic reduction of 4-nitrophenol
Authors: Feng Tao , Chen Yinyu , Wu Si , Wang Shuai
Published: July 2024

In this study, thein situreduction of Ch/HA hydrogel with adsorbed Cu2+was used for the efficient catalytic reduction of 4-nitrophenol, which provides a new idea for the reuse of water treatment agents and the reduction of secondary pollution.
High-performance flexible photodetectors based on CdTe/MoS2 heterojunction
Authors: Yang Shuo , Liu Yunjie , Wu Yupeng , Guo Fuhai , Zhang Mingcong , Zhu Xinru , Xu Ruqing , Hao Lanzhong
Published: July 2024

High-quality flexible photodetector devices based on CdTe/MoS2 were prepared by mechanical stripping, demonstrating high photodetectivity and great mechanical stability with a slight photocurrent variation after 200 periodic strain cycles.
Hydrogen production catalysed by atomically precise metal clusters
Authors: Song Tongxin , Cai Xiao , Zhu Yan
Published: July 2024

Atomically precise metal clusters for electrocatalytic and photocatalytic H2 production are systematically summarized, which is expected to provide new insights into the design of high-performance H2 production catalysts.
Patchy stereocomplex micelles as efficient compatibilizers for polymer blends
Authors: Schaller Roman , Schmidt Marius , Schweimer Kristian , Schmalz Holger
Published: July 2024

Patchy spherical micelles prepared via stereocomplex-driven self-assembly are applied as efficient compatibilizers for highly immiscible polystyrene/poly(tert-butyl methacrylate) blends.
Nanotechnology in food packaging materials: role and application of nanoparticles
Authors: Herrera-Rivera Maria del Rosario , Torres-Arellanes Sandra P. , Cortés-Martínez Carlos Inocencio , Navarro-Ibarra Diana C. , Hernández-Sánchez Laura , Solis-Pomar Francisco , Pérez-Tijerina Eduardo , Román-Doval Ramón
Published: July 2024

Global concerns about food security, driven by rising demand, have prompted the exploration of nanotechnology as a solution to enhance food supply.
AZGs: a new family of cytokinin transporters
Authors: Tessi Tomas M. , Maurino Veronica G.
Published: July 2024

Cytokinins (CKs) are phytohormones structurally similar to purines that play important roles in various aspects of plant physiology and development. The local and long-distance distribution of CKs is very important to control their action throughout the plant body. Over the past decade, several novel CK transporters have been described, many of which have been linked to a physiological function rather than simply their ability to transport the hormone in vitro. Purine permeases, equilibrative nucleotide transporters and ATP-binding cassette transporters are involved in the local and long-range distribution of CK. In addition, members of the Arabidopsis AZA-GUANINE RESISTANT (AZG) protein family, AZG1 and AZG2, have recently been shown to mediate CK uptake at the plasma membrane and endoplasmic reticulum. Despite sharing ∼50% homology, AZG1 and AZG2 have unique transport mechanisms, tissue-specific expression patterns, and subcellular localizations that underlie their distinct physiological functions. AZG2 is expressed in a small group of cells in the overlying tissue around the lateral root primordia, where its expression is induced by auxins and it is involved in the regulation of lateral root growth. AZG1 is ubiquitously expressed, with high levels in the division zone of the root apical meristem. Here, it binds and stabilises the auxin efflux carrier PIN1, thereby shaping root architecture, particularly under salt stress. This review highlights the latest findings on the protein properties, transport mechanisms and cellular functions of this new family of CK transporters and discusses perspectives for future research in this field.
Assessing the Language Abilities of Preterm-Born Children: An Examination of Standardized Testing and Language Sample Analysis
Authors: Coughlan Sarah , Quigley Jean , Nixon Elizabeth
Published: July 2024

Purpose:

To understand how best to assess the language abilities of preterm-born children, this study: (a) compared preterm- and term-born children's language skills using standardized testing and language sample analysis (LSA), (b) investigated how executive function skills and the language sampling context respectively affect standardized test and LSA scores, and (c) examined the pattern of associations between standardized test and LSA scores among preterm-/term-born groups.

Method:

Twenty-five term-born and 23 preterm-born 2-year-old singletons were administered the language scales of the Bayley Scales of Infant and Toddler Development–Third Edition (receptive communication, expressive communication, language composite scores). Parent–child free-play recordings were used to quantify the (para)linguistic features of the children's speech. Executive function was measured via parent report.

Results:

The preterm-born group obtained significantly lower scores than the term-born group on all Bayley language measures (though differences were not consistently observed when using cutoff scores). Few preterm–term differences in LSA measures were found. The preterm–term differences in Bayley scores were not explained by between-group differences in executive function. Some preterm–term differences in LSA scores were moderated by the language sampling context. The preterm- and term-born groups exhibited different patterns of Bayley–LSA correlations.

Conclusions:

Preterm language difficulties were more apparent on standardized test than LSA scores. Nonetheless, the Bayley–LSA correlations indicate that poor test performance (linked with preterm birth) is associated with functional communication difficulties. The discussion outlines the complementary utility of standardized tests and LSA while acknowledging the limited utility of cutoff scores and the confounding influence of the language sampling context.

Supplemental Material:

https://doi.org/10.23641/asha.26142661
Links Among Attention-Deficit/Hyperactivity Disorder Symptoms and Psycholinguistic Abilities Are Different for Children With and Without Developmental Language Disorder
Authors: Redmond Sean M. , Ash Andrea C. , Li Haojia , Zhang Yue
Published: July 2024

Purpose:

Both developmental language disorder (DLD) and attention-deficit/hyperactivity disorder (ADHD) represent relatively common and chronic neurodevelopmental conditions associated with increased risk for poor academic and interpersonal outcomes. Reports of common co-occurrence suggest these neurodevelopmental disruptions might also be linked. Most of the data available on the issue have been based on case–control studies vulnerable to ascertainment and other biases.

Method:

Seventy-eight children, representing four neurodevelopmental profiles (DLD, ADHD, co-occurring ADHD + DLD, and neurotypical development), were administered a battery of psycholinguistic tests. Parents provided standardized ratings of the severity of their children's inattention, hyperactivity/impulsivity, and executive function symptoms. Examiners were blinded to children's clinical status. Group differences, correlations, and best subset regression analyses were used to examine potential impacts of children's ADHD symptoms on their psycholinguistic abilities.

Results:

For children with DLD, significant links between their ADHD symptoms and psycholinguistic abilities were limited to the contributions of elevated hyperactivity/impulsivity symptoms to lower pragmatic abilities. For children without DLD, inattention symptoms contributed to lower levels of performance in pragmatic, sentence recall, receptive vocabulary, and narrative abilities.

Discussion:

Links among children's ADHD symptoms and their psycholinguistic abilities were different for children with and without DLD. Implications for the provision of clinical services are discussed.
Retracted: The Relationship Between Oral and Written Language in Narrative Production by Arabic-Speaking Children: Fundamental Skills and Influences
Authors: Kawar Khaloob
Published: July 2024

Notice of Retraction:

https://doi.org/10.1044/2024_Nov2024ASHA

Purpose:

This study aims to investigate the relationship between oral and written language skills in narrative production among Arabic-speaking children, focusing on cognitive and linguistic abilities. It examines the differences in narrative parameters between oral and written narratives and explores the associations between these parameters and cognitive and linguistic skills.

Method:

The research involved 237 sixth-grade Arabic-speaking students from low–socioeconomic status schools in Israel. Each participant was instructed to orally tell a narrative and to write another narrative based on two sets of six sequential pictures. Various narrative features were analyzed, including word count for length, type–token ratio (TTR) for lexical diversity, mean length of utterance (MLU) for morphosyntax, and number of episodes for macrostructure. Cognitive linguistic measures, including Raven's Progressive Matrices, reading comprehension (RC), and morphological awareness (MA) were also assessed.

Results:

The study found significant differences between oral and written narratives regarding lexical diversity and macrostructure. Participants exhibited significantly higher TTR in written narratives compared to oral narratives, whereas the number of episodes was significantly higher in oral narratives than in written ones. However, no significant differences were observed in narrative length or MLU. Moreover, the study identified significant predictors for various aspects of written narratives, particularly MA and RC, which significantly predicted TTR, MLU, and macrostructure. Additionally, the inclusion of word count in oral narratives significantly enhanced the explained variance for narrative length and macrostructure in written language.

Conclusions:

The results highlight the importance of the oral–written interface in both micro- and macrostructure representations in both oral and written modalities. They suggest that cognitive and linguistic skills, such as MA and RC, play a crucial role in narrative production. The findings have implications for educational practices and literacy outcomes in the Arab world, enhancing the understanding of the challenges and strategies involved in written language production among Arabic-speaking children.
Existence of optimal virtual element weights for mmWave FMCW MIMO radar based heart rate estimation
Authors: Gilles Yowel Massala Mboyi , Han Jung‐Hoon
Published: July 2024

Measuring heart rate is a critical component of assessing cardiac health and detecting potential heart diseases at an early stage. Various sensors, including electrocardiogram and photoplethysmograph, are commonly employed for this purpose. However, these conventional methods necessitate direct contact with the patient's skin which may be impractical or uncomfortable in situations involving patients with skin diseases or burn injuries. To address these limitations, a concerted effort has been to develop non‐contact methods leveraging frequency‐modulated continuous‐wave multiple‐input multiple‐output radar systems. Recent studies have illustrated the sensitivity of the phase component of received signals to micro‐motion, presenting a promising avenue for effective heart rate estimation. However, existing literature predominantly focuses on single‐antenna setups, overlooking the potential benefits offered by multiple‐input multiple‐output systems, which provide diverse channels with varying precision levels. This correspondence introduces a novel phase extraction model grounded in the argument of the analytic signal derived from both in‐phase and quadrature channels. Furthermore, leveraging the normal equation, we establish the feasibility of optimizing weights assigned to individual virtual antennas to achieve a robust approximation of ground truth data.
An equivalent and simplified approach for acoustic noise prediction in a PM synchronous motor based on the semi‐analytical‐FEM model
Authors: Saki Armin , Kiyoumarsi Arash , Ariaei Alireza
Published: July 2024

The vibration and acoustic noise of a permanent‐magnet synchronous motor are analysed and evaluated. Acoustic noise sound levels, their prominent frequencies, and the noisiest motor speed range are predicted. According to many resources, the radial vibration of the stator system due to the magnetic attraction between rotor permanent magnets and stator iron teeth is the main reason for the acoustic noise propagation of the PMSMs. The dominant orders of the spatial circumferential harmonics of the radial magnetic forces (RMFs) have been investigated and compared. The complete and complicated mechanical components, materials, and harmonics of the magnetic forces of the motor and their interaction are simplified and equalised to a vibration model, which consists of the interaction between the stator system and the dominant harmonic orders of the RMFs. Based on this approach, the simplest and most adequate semi‐analytical‐FEM model for noise prediction in PMSMs is proposed. This model, in addition to simplification, clarifies the role of the main mechanical and electromagnetic origins of noise generation. The acoustic noise prediction, using the proposed method has been compared with the experimental results. There is a proper agreement between the analytical, the FEM, and measurement results.
Psitrum: An open source simulator for universal quantum computers
Authors: Alghadeer Mohammed , Aldawsari Eid , Selvarajan Raja , Alutaibi Khaled , Kais Sabre , Alharbi Fahhad H.
Published: July 2024

Quantum computing is a radical new paradigm for a technology that is capable to revolutionise information processing. Simulators of universal quantum computer are important for understanding the basic principles and operations of the current noisy intermediate‐scale quantum processors, and for building in future fault‐tolerant quantum computers. As next‐generation quantum technologies continue to advance, it is crucial to address the impact on education and training in quantum physics. The emergence of new industries driven by progress in quantum computing and simulation will create a demand for a specialised quantum workforce. In response to these challenges, the authors present Psitrum, an open‐source simulator for universal quantum computers. Psitrum serves as a powerful educational and research tool, enabling a diverse range of stakeholders to understand the fundamental principles and operations of quantum systems. By offering a comprehensive platform for emulating and debugging quantum algorithms through quantum circuits, Psitrum aids in the exploration and analysis of various quantum applications using both MATLAB and MATLAB application programming interface to use the software on other platforms. Psitrum software and source codes are fully available at GitHub.
A resilience‐oriented restoration framework for multi‐area active distribution network following a disaster
Authors: Beiranvandi Hekmat , Samanfar Amin , Doostizadeh Meysam , Saki Reza
Published: July 2024

A disaster disrupts energy trading between the distribution network (DN) and autonomous areas in the multi‐area active distribution network (MA‐ADN). Since these areas are self‐interested agents, the energy transaction cost between them should be considered when determining the grid restoration scheme. In this regard, a new three‐level resilience‐oriented restoration (TLROR) framework is proposed to optimally schedule available tie‐lines, and distributed energy resources (DERs) in the MA‐ADN, considering the autonomy and privacy of their ownership. In the first level of the proposed TLROR, an electrical price vector (EPV) is created with the contribution of different areas. In the second level, each area should calculate the amount of imported active and reactive power from the DN through its tie branches and save it in the transactive power list (TPL). Finally, at the third level, the transactive energy market is cleared by the DN operator considering economic issues and operating limits. The proposed method provides energy transactions between independent agents to enhance MA‐ADN resiliency, with the least information sharing, and privacy preserving. The effectiveness of the proposed method is verified using the modified IEEE 33‐bus MA‐ADN and a part of the DN in the Pol‐e Dokhtar in the Lorestan province of Iran.
Coupled vertical double quantum dots at single-hole occupancy
Authors: Ivlev Alexander S. , Tidjani Hanifa , Oosterhout Stefan D. , Sammak Amir , Scappucci Giordano , Veldhorst Menno
Published: July 2024

Gate-defined quantum dots define an attractive platform for quantum computation and have been used to confine individual charges in a planar array. Here, we demonstrate control over vertical double quantum dots confined in a strained germanium double quantum well. We sense individual charge transitions with a single-hole transistor. The vertical separation between the quantum wells provides a sufficient difference in capacitive coupling to distinguish quantum dots located in the top and bottom quantum wells. Tuning the vertical double quantum dot to the (1,1) charge state confines a single-hole in each quantum well beneath a single plunger gate. By simultaneously accumulating holes under two neighboring plunger gates, we are able to tune to the (1,1,1,1) charge state. These results motivate quantum dot systems that exploit the third dimension, opening new opportunities for quantum simulation and quantum computing.
Ground state energy of Bogoliubov energy functional in the high density limit
Authors: Mokrzański Norbert , Pałuba Bartosz
Published: July 2024

We consider the Bogoliubov energy functional proposed by Napiórkowski, Reuvers and Solovej and analize it in the high density regime. We derive a two term asymptotic expansion of the ground state energy.
A comparison of models for predicting the maximum spreading factor in droplet impingement
Authors: Yu Wenlong , Li Bo , Lin Shuyu , Wang Wenhao , Chen Shuo , Cao Damin , Zhao Jiayi
Published: July 2024

The maximum spreading factor during droplet impact on a dry surface is a pivotal parameter of a range of applications, including inkjet printing, anti-icing, and micro-droplet transportation. It is determined by a combination of the inertial force, viscous force, surface tension, and fluid–solid interaction. There are currently a series of qualitative and quantitative prediction models for the maximum spreading factor rooted in both momentum and energy conservation. However, the performance of these models on consistent experimental samples remains ambiguous. In this work, a comprehensive set of 785 experimental samples spanning the last four decades is compiled. These samples encompass Weber numbers ranging from 0.038 to 2447.7 and Reynolds numbers from 9 to 34 339. A prediction model is introduced that employs a neural network, which achieves an average relative error of less than 16.6% with a standard error of 0.018 08 when applied to the test set. Following this, a fair comparison is presented of the accuracy, generality, and stability of different prediction models. Although the neural network model provides superior accuracy and generality, its stability is weaker than that of Scheller's We-Re-dependent formula, chiefly due to the absence of physical constraints. Subsequently, a physics-informed prediction model is introduced by considering a physical loss term. This model demonstrates comprehensive enhancements compared to the original neural network, and the average relative and standard errors for this model are reduce to 13.6% and 0.010 59, respectively. This novel model should allow for the rapid and precise prediction of the maximum spreading factor across a broad range of parameters for various applications.