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Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disorder caused by the expansion of GGC trinucleotide repeats in NOTCH2NLC gene. Despite identifying uN2CpolyG, a toxic polyglycine (polyG) protein translated by expanded GGC repeats, the exact pathogenic mechanisms of NIID remain unclear. In this study, we investigated the role of polyG by expressing various forms of NOTCH2NLC in mice: the wild-type, the expanded form with 100 GGC repeats (either translating or not translating into uN2CpolyG), and the mutated form that encodes a pure polyG without GGC-repeat RNA and the C-terminal stretch (uN2CpolyG-dCT). Both uN2CpolyG and uN2CpolyG-dCT induced the formation of inclusions composed by filamentous materials and resulted in neurodegenerative phenotypes in mice, including impaired motor and cognitive performance, shortened lifespan, and pathologic lesions such as white-matter lesions, microgliosis, and astrogliosis. In contrast, expressing GGC-repeat RNA alone was non-pathogenic. Through bulk and single-nuclei RNA sequencing, we identified common molecular signatures linked to the expression of uN2CpolyG and uN2CpolyG-dCT, particularly the upregulation of inflammation and microglia markers, and the downregulation of immediate early genes and splicing factors. Importantly, microglia-mediated inflammation was visualized in NIID patients using positron emission tomography, correlating with levels of white-matter atrophy. Furthermore, microglia ablation ameliorated neurodegenerative phenotypes and transcriptional alterations in uN2CpolyG-expressing mice but did not affect polyG inclusions. Together, these results demonstrate that polyG is crucial for the pathogenesis of NIID and highlight the significant role of microglia in polyG-induced neurodegeneration. [ABSTRACT FROM AUTHOR]

BACKGROUND: Early weaning is prone to damage intestinal barrier function, resulting in diarrhea, whereas rutin, as a natural flavonoid with multiple biological functions, shows potential in piglets. Therefore, the effects of dietary rutin on growth, antidiarrheal, barrier function, antioxidant status and cecal microbiota of weaned piglets were investigated with the control group (CON) (basal diet) and Rutin (basal diet+500 mg kg−1 rutin) groups fed for 14 days. RESULTS: The results showed that dietary 500 mg kg−1 rutin significantly decreased diarrhea index, serum diamine oxidase activity and total aerobic bacterial population in mesenteric lymph nodes, whereas it significantly increased the gain‐to‐feed ratio (G:F) and serum growth hormone content, jejunal villus height and villus height to crypt depth ratio, and also enhanced jejunal claudin‐1 and zonula occludens‐1 mRNA and protein expression. Meanwhile, dietary rutin significantly decreased inflammation‐associated mRNA expression, malondialdehyde (MDA) content, swollen mitochondrial number and mitochondrial area in the jejunum, whereas it increased the total superoxide dismutase (T‐SOD) and glutathione peroxidase activities and activated the Nrf2 signaling pathway. Moreover, dietary rutin significantly increased Firmicutes abundance and decreased Campylobacterota abundance, which were closely associated with the decreased diarrhea index and MDA content or increased Claudin‐1 expression and T‐SOD activity. CONCLUSION: Dietary 500 mg kg−1 rutin increased G:F by improving intestinal morphology, and alleviated diarrhea by enhancing intestinal barrier, which might be associated with the enhanced antioxidant capacity via activating the Nrf2/Keap1 signaling pathway and the improved cecal microbial composition in weaned piglets. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Background: Progression of non-target lesions (NTLs) after stenting has been reported and is associated with the triggering of an inflammatory response. The perivascular fat attenuation index (FAI) may be used as a novel imaging biomarker for the direct quantification of coronary inflammation. Objectives: To investigate whether FAI values can help identify changes in inflammation status in patients undergoing stent implantation, especially in NTLs. Methods: Patients who underwent pre- and post-stenting coronary computed tomography angiography (CCTA) examination between January 2015 and February 2021 were consecutively enrolled. The pre- and post-stenting FAIs of the full coronary arteries were compared in both the non- and stent-implanted coronary arteries. Moreover, local FAI values were measured and compared between the NTLs and target lesions in the stent implantations. We also compared changes in plaque type and volume in NTLs before and after stenting. Results: A total of 89 patients (mean age 61 years; male 59) were enrolled. The perivascular FAI values in the full coronary arteries decreased after stenting in both the non- and stent-implanted coronary arteries, similar to those in the target lesions. Conversely, the perivascular FAI values in the NTLs increased after stenting (p < 0.05). In addition, the plaque volumes significantly increased in the NTLs after stenting, regardless of whether they were non-calcified, mixed, or calcified (p < 0.05). Conclusion: Perivascular FAI values and plaque volumes increased in the NTLs after stenting. Perivascular FAI can be a promising imaging biomarker for monitoring coronary inflammation after stenting and facilitate long-term monitoring in clinical settings. Clinical relevance statement: Perivascular fat attenuation index, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in non-target lesions and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment. Key Points: • Perivascular fat attenuation index (FAI) values and plaque volumes increased in the non-target lesions (NTLs) after stenting, suggesting potential focal inflammation progression after stenting. However, stenting along with anti-inflammatory treatment ameliorated inflammation in the full coronary arteries. • Perivascular FAI, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in NTLs and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment. [ABSTRACT FROM AUTHOR]

Salidroside, a principal bioactive component of Rhodiola crenulata, is neuroprotective across a wide time window in stroke models. We investigated whether salidroside induced neurogenesis after cerebral ischemia and aimed to identify its primary molecular targets. Rats, subjected to transient 2 h of middle cerebral artery occlusion (MCAO), received intraperitoneal vehicle or salidroside ± intracerebroventricular HSC70 inhibitor VER155008 or TrkB inhibitor ANA‐12 for up to 7 days. MRI, behavioural tests, immunofluorescent staining and western blotting measured effects of salidroside. Reverse virtual docking and enzymatic assays assessed interaction of salidroside with purified recombinant HSC70. Salidroside dose‐dependently decreased cerebral infarct volumes and neurological deficits, with maximal effects by 50 mg/kg/day. This dose also improved performance in beam balance and Morris water maze tests. Salidroside significantly increased BrdU+/nestin+, BrdU+/DCX+, BrdU+/NeuN+, BrdU−/NeuN+ and BDNF+ cells in the peri‐infarct cortex, with less effect in striatum and no significant effect in the subventricular zone. Salidroside was predicted to bind with HSC70. Salidroside dose‐dependently increased HSC70 ATPase and HSC70‐dependent luciferase activities, but it did not activate HSP70. HSC70 immunoreactivity concentrated in the peri‐infarct cortex and was unchanged by salidroside. However, VER155008 prevented salidroside‐dependent increases of neurogenesis, BrdU−/NeuN+ cells and BDNF+ cells in peri‐infarct cortex. Salidroside also increased BDNF protein and p‐TrkB/TrkB ratio in ischemic brain, changes prevented by VER155008 and ANA‐12, respectively. Additionally, ANA‐12 blocked salidroside‐dependent neurogenesis and increased BrdU−/NeuN+ cells in the peri‐infarct cortex. Salidroside directly activates HSC70, thereby stimulating neurogenesis and neuroprotection via BDNF/TrkB signalling after MCAO. Salidroside and similar activators of HSC70 might provide clinical therapies for ischemic stroke. [ABSTRACT FROM AUTHOR]

Background: Fragile X-associated tremor/ataxia syndrome (FXTAS) is a neurodegenerative disorder caused by CGG repeat expansion of FMR1 gene. Both FXTAS and neuronal intranuclear inclusion disease (NIID) belong to polyglycine diseases and present similar clinical, radiological, and pathological features, making it difficult to distinguish these diseases. Reversible encephalitis-like attacks are often observed in NIID. It is unclear whether they are presented in FXTAS and can be used for differential diagnosis of NIID and FXTAS. Case presentation: A 63-year-old Chinese male with late-onset gait disturbance, cognitive decline, and reversible attacks of fever, consciousness impairment, dizziness, vomiting, and urinary incontinence underwent neurological assessment and examinations, including laboratory tests, electroencephalogram test, imaging, skin biopsy, and genetic test. Brain MRI showed T2 hyperintensities in middle cerebellar peduncle and cerebrum, in addition to cerebellar atrophy and DWI hyperintensities along the corticomedullary junction. Lesions in the brainstem were observed. Skin biopsy showed p62-positive intranuclear inclusions. The possibilities of hypoglycemia, lactic acidosis, epileptic seizures, and cerebrovascular attacks were excluded. Genetic analysis revealed CGG repeat expansion in FMR1 gene, and the number of repeats was 111. The patient was finally diagnosed as FXTAS. He received supportive treatment as well as symptomatic treatment during hospitalization. His encephalitic symptoms were completely relieved within one week. Conclusions: This is a detailed report of a case of FXTAS with reversible encephalitis-like episodes. This report provides new information for the possible and rare features of FXTAS, highlighting that encephalitis-like episodes are common in polyglycine diseases and unable to be used for differential diagnosis. [ABSTRACT FROM AUTHOR]

In order to achieve fast and accurate detection of Gannan navel orange fruits with different ripeness levels in a natural environment under all-weather scenarios and then to realise automated harvesting of Gannan navel oranges, this paper proposes a YOLOv5-NMM (YOLOv5 with Navel orange Measure Model) object detection model based on the improvement in the original YOLOv5 model. Based on the changes in the phenotypic characteristics of navel oranges and the Chinese national standard GB/T 21488-2008, the maturity of Gannan navel oranges is tested. And it addresses and improves the problems of occlusion, dense distribution, small target size, rainy days, and light changes in the detection of navel orange fruits. Firstly, a new detection head of 160 × 160 feature maps is constructed in the detection layer to improve the multi-scale target detection layer of YOLOv5 and to increase the detection accuracy of the different maturity levels of Gannan navel oranges of small sizes. Secondly, a convolutional block attention module is incorporated in its backbone layer to capture the correlations between features in different dimensions to improve the perceptual ability of the model. Then, the weighted bidirectional feature pyramid network structure is integrated into the Neck layer to improve the fusion efficiency of the network on the feature maps and reduce the amount of computation. Lastly, in order to reduce the loss of the target of the Gannan Navel Orange due to occlusion and overlapping, the detection frame is used to remove redundancy using the Soft-NMS algorithm to remove redundant candidate frames. The results show that the accuracy rate, recall rate, and average accuracy of the improved YOLOv5-NMM model are 93.2%, 89.6%, and 94.2%, respectively, and the number of parameters is only 7.2 M. Compared with the mainstream network models, such as Faster R-CNN, YOLOv3, the original model of YOLOv5, and YOLOv7-tiny, it is superior in terms of the accuracy rate, recall rate, and average accuracy mean, and also performs well in terms of the detection rate and memory occupation. This study shows that the YOLOv5-NMM model can effectively identify and detect the ripeness of Gannan navel oranges in natural environments, which provides an effective exploration of the automated harvesting of Gannan navel orange fruits. [ABSTRACT FROM AUTHOR]

Organic afterglow is a fascinating phenomenon with exceptional applications. However, it encounters challenges such as low intensity and efficiency, and typically requires UV-light excitation and facile intersystem crossing (ISC) due to its spin-forbidden nature. Here, we develop a novel strategy that bypasses the conventional ISC pathway by promoting singlet-triplet transition through the synergistic effects of the intra/intermolecular heavy-atom effect in aromatic crystals, enabling the direct population of triplet excited states from the ground state. The resulting materials exhibit a bright organic afterglow with a remarkably enhanced quantum efficiency of up to 5.81%, and a significantly increased organic afterglow lifetime of up to 157 microseconds under visible light. Moreover, given the high-efficiency visible-light excitable organic afterglow emission, the potential application is demonstrated in lifetime-resolved, color-encoded, and excitation wavelength-dependent pattern encryption. This work demonstrates the importance of the direct population method in enhancing the organic afterglow performance and red-shifting the excitation wavelength, and provides crucial insights for advancing organic optoelectronic technologies that involve triplet states. [ABSTRACT FROM AUTHOR]

In this study, the flexural bearing behavior of corroded reinforced concrete (RC) beams reinforced with U-type Textile Reinforced Concrete (TRC) was investigated using a four-point bending loading method. Nine test beams were produced: one original beam, three RC beams with corrosion alone, and five corroded beams strengthened with U-type TRC. The analysis focuses on assessing the impacts of the steel corrosion degree and the number of textile layers on various aspects of the bending behavior, such as failure modes, bearing capacity, and load displacement curves, in U-type TRC-strengthened corroded beams. The experimental results revealed three distinct failure modes in the U-type TRC-strengthened corroded beams. TRC effectively enhanced the bearing capacity. With sufficient textile layers, it can be restored to the level of the original RC beams. Moreover, in the cases of severe corrosion in RC beams, the bearing capacity increased more significantly. The TRC also enhanced the ductility. Finally, a calculation equation for the ultimate bearing capacity of U-type TRC-strengthened corroded beams was presented and validated, demonstrating consistent alignment with the experimental data. [ABSTRACT FROM AUTHOR]

In the face of complex scenarios, the information insufficiency of classification tasks dominated by a single modality has led to a bottleneck in classification performance. The joint application of multimodal remote sensing data for surface observation tasks has garnered widespread attention. However, issues such as sample differences between modalities and the lack of correlation in physical features have limited the performance of classification tasks. Establishing effective interaction between multimodal data has become another significant challenge. To fully integrate heterogeneous information from multiple modalities and enhance classification performance, this paper proposes a dual-branch cross-Transformer feature fusion network aimed at joint land cover classification of hyperspectral imagery (HSI) and Light Detection and Ranging (LiDAR) data. The core idea is to leverage the potential of convolutional operators to represent spatial features, combined with the advantages of the Transformer architecture in learning remote dependencies. The framework employs an improved self-attention mechanism to aggregate features within each modality, highlighting the spectral information of HSI and the spatial (elevation) information of LiDAR. The feature fusion module based on cross-attention integrates deep features from two modalities, achieving complementary information through cross-modal attention. The classification task is performed using jointly obtained spectral and spatial features. Experiments were conducted on three multi-source remote sensing classification datasets, demonstrating the effectiveness of the proposed model compared to existing methods. [ABSTRACT FROM AUTHOR]

The use of plastic bags in the long-term contact with food may cause certain harm to human health due to the production process of plastic bags and the use of plasticizers such as BPA. Therefore, the analysis and research methods of BPA and other harmful substances are receiving extensive attention. Molecularly imprinted polymers have attracted much attention for their high selectivity, while magnetic metal–organic frameworks (MOFs) have been widely used for their excellent adsorption potential. However, the current methods of synthesizing these polymers typically require many steps and are time-consuming. Additionally, these methods involve the use of large amounts of solvents, which are not environmentally friendly and sustainable. This study proposed an easy, convenient, quick, and green method for synthesizing magnetic copper MOF molecularly imprinted polymers (MCMMIPs) using a one-pot technique to overcome these challenges. The resulting MCMMIPs exhibited excellent magnetic separation ability (20 emu/g), a large specific surface area (289.4 m2/g), and a well-defined imprinted cavity. MCMMIPs have been successfully applied to the extraction of BPA in plastic bags with a detection limit of 1.01 µg/kg and recoveries ranging from 72.1% to 102.85%. More importantly, the detection method proposed based on the material has been successfully applied to the detection of BPA in plastic bags, with a good detection effect. [ABSTRACT FROM AUTHOR]

To investigate the long-term effects of dietary zinc oxide nanoparticle (Nano-ZnO, 20–40 nm) on the relative organ weight, liver function, deposition, and absorption of trace minerals in intrauterine growth retardation (IUGR) pigs, piglets were allocated to NBW (6 normal birth weight piglets fed basal diets), IUGR (6 IUGR piglets fed basal diets) and IUGR+NZ (6 IUGR piglets fed basal diets + 600 mg Zn/kg from Nano-ZnO) groups at weaning (21 days of age), which were sampled at 163 days of age. There were no noteworthy changes in the relative weight of organs, hepatic histomorphology, serum alkaline phosphatase, glutamic pyruvic transaminase and glutamic oxalacetic transaminase activities, and Mn, Cu, and Fe concentrations in leg muscle, the liver, the tibia, and feces among the IUGR, NBW, and IUGR+NZ groups (P>0.05), and no intact Nano-ZnO in the jejunum, liver, and muscle was observed, while dietary Nano-ZnO increased the Zn concentrations in the tibia, the liver, serum, and feces (P<0.05) and mRNA expression of metallothionein (MT) 1A, MT2A, solute carrier family 39 member (ZIP) 4, ZIP14, ZIP8, divalent metal transporter 1, solute carrier family 30 member (ZnT) 1, ZnT4 and metal regulatory transcription factor 1, and ZIP8 protein expression in jejunal mucosa (P<0.05). Immunohistochemistry showed that dietary Nano-ZnO increased the relative optical density of ZIP8 (mainly expressed in cells of brush border) and MT2A (mainly expressed in villus lamina propria and gland/crypt) (P<0.05). In conclusion, long-term dietary Nano-ZnO showed no obvious side effects on the development of the major organs, liver function, and metabolism of Cu, Fe, and Mn in IUGR pigs, while it increased the Zn absorption and deposition via enhancing the expression of transporters (MT, ZIP, and ZnT families) in the jejunum, rather than via endocytosis as the form of intact nanoparticles. [ABSTRACT FROM AUTHOR]

Predicting the biological properties of molecules is crucial in computer-aided drug development, yet it's often impeded by data scarcity and imbalance in many practical applications. Existing approaches are based on self-supervised learning or 3D data and using an increasing number of parameters to improve performance. These approaches may not take full advantage of established chemical knowledge and could inadvertently introduce noise into the respective model. In this study, we introduce a more elegant transformer-based framework with focused attention for molecular representation (TransFoxMol) to improve the understanding of artificial intelligence (AI) of molecular structure property relationships. TransFoxMol incorporates a multi-scale 2D molecular environment into a graph neural network + Transformer module and uses prior chemical maps to obtain a more focused attention landscape compared to that obtained using existing approaches. Experimental results show that TransFoxMol achieves state-of-the-art performance on MoleculeNet benchmarks and surpasses the performance of baselines that use self-supervised learning or geometry-enhanced strategies on small-scale datasets. Subsequent analyses indicate that TransFoxMol's predictions are highly interpretable and the clever use of chemical knowledge enables AI to perceive molecules in a simple but rational way, enhancing performance. [ABSTRACT FROM AUTHOR]

Valence tuning of transition metal oxides is an effective approach to design high‐performance catalysts, particularly for the oxygen evolution reaction (OER) that underpins solar/electric water splitting and metal‐air batteries. Recently, high‐valence oxides (HVOs) are reported to show superior OER performance, in association with the fundamental dynamics of charge transfer and the evolution of the intermediates. Particularly considered are the adsorbate evolution mechanism (AEM) and the lattice oxygen‐mediated mechanism (LOM). High‐valence states enhance the OER performance mainly by optimizing the eg‐orbital filling, promoting the charge transfer between the metal d band and oxygen p band. Moreover, HVOs usually show an elevated O 2p band, which triggers the lattice oxygen as the redox center and enacts the efficient LOM pathway to break the "scaling" limitation of AEM. In addition, oxygen vacancies, induced by the overall charge‐neutrality, also promote the direct oxygen coupling in LOM. However, the synthesis of HVOs suffers from relatively large thermodynamic barrier, which makes their preparation difficult. Hence, the synthesis strategies of the HVOs are discussed to guide further design of the HVO electrocatalysts. Finally, further challenges and perspectives are outlined for potential applications in energy conversion and storage. [ABSTRACT FROM AUTHOR]

The current work reveals the influence of loading parameters on the crack growth behavior of a Zr/Ti/steel composite plate with a crack normal to the interface by using an experiment and the finite element method. The Chaboche model was first used to study cyclic plastic evolution in composite materials. The results reveal that an increase in Fmax, Fm, and Fa can promote da/dN; meanwhile, an increase in R will reduce da/dN. The plastic strain accumulation results indicate that Fm mainly contributes to the tensile strain and compressive stress after the first cycle. Additionally, Fa increases the stress range and compression stress and greatly improves the plastic strain accumulation degree in subsequent loading cycles. The Fmax can significantly increase the stress amplitude and plastic strain accumulation level. When R increases, the plastic strain accumulation increases a little, but the stress amplitude and compression stress decrease greatly. Furthermore, it is also found that the elastic–plastic mismatch also affects the plastic evolution, that is, strengthening or weakening the effect of the loading parameters. [ABSTRACT FROM AUTHOR]

Nowadays, interactive recommendation systems (IRS) play a significant role in our daily life. Recently, reinforcement learning has shown great potential in solving challenging tasks in IRS, since it can focus on long-term profit and can capture the dynamic preference of users. However, existing RL methods for IRS have two typical deficiencies. First, most state representation models use left-to-right recurrent neural networks to capture the user dynamics, which usually fail to handle the long and noisy sequential data in real life. Second, an IRS always needs to handle millions of items, leading to a large discrete action space in RL settings, which has not been fully addressed by the inefficient existing works. To bridge these deficiencies, in this paper, we propose attention-based tree recommendation (ATRec), an efficient tree-structured policy with attention-based state representation for IRS. ATRec uses an attention-based state representation model to effectively capture the user's dynamic preference hidden in the long and noisy sequence of behaviors. Moreover, to improve the learning efficiency, we propose an efficient tree-structured policy representation method, in which a complete tree is devised to represent the policy, and a novel parameter-sharing strategy is introduced. Extensive experiments are conducted on three real-world datasets and the results show the proposed ATRec obtains 42.3% improvement over some of the state of the arts methods in the hit rate and 21.4% improvement in the mean reciprocal rank of the top 30 ranked items. Additionally, the learning and decision efficiency can also be improved at an average of 35.5%. [ABSTRACT FROM AUTHOR]

Mixed mode fracture is a widely studied topic, while the coupling effects of mixed mode cracking are unclear. In this paper, elastic fracture behaviors and the coupling effects of the mixed mode cracks are studied in detail based on the finite element method, experimental study and linear elastic fracture mechanics. Results show that there always exist II-III coupling effects at the crack tips of mixed mode cracks, which have many effects on the crack tip field and crack propagation behavior. It is found that a mode II component at the tip of a mixed mode crack is the main reason for crack deflection, while the mode III components show no effect. For any mixed mode crack, mode II components at the crack tip can be divided as that by mode II loading which causes plane crack propagation, and by the coupling effect which causes spatial crack propagation. On this basis, a new fracture criterion suitable for any mixed mode crack is proposed, combined with the coupling effect and the linear elastic superposition principle. The research in this paper provides a solution to the problem of an II-III coupling effect in mixed mode fracture research and further promotes the development of fracture mechanics. [ABSTRACT FROM AUTHOR]

Crime analysis is important for social security management. With the advance of crowd sensing techniques, abundant multisource crowd sensed data could be used for crime analysis. The occurrence of crimes usually has some patterns in terms of temporal and spatial aspects. Investigating the spatio-temporal correlation of crimes could provide more useful cues for crime analysis and help discover underlying crime patterns. In this paper, we conduct a spatio-temporal study to understand urban crimes leveraging multisource crowd sensed data, including crime data, meteorological data, POI distribution, and taxi trips. Specifically, we first present monthly temporal trends and spatial distribution of crimes. We then investigate the spatio-temporal correlation using meteorological data (e.g., weather conditions and air temperature) and POI distribution and taxi trips. It is found that taxi trips and air temperature have a strong correlation with the crime, and some POI categories have a valuable correlation with the crime, e.g., College & University. We also find that Overcast days would witness more crime than other weather conditions. [ABSTRACT FROM AUTHOR]

Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∼30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a 'snapshot' introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation. [ABSTRACT FROM AUTHOR]

A new type of magnetic zinc metal–organic framework molecularly imprinted polymer (MZMMIP) was created by a crystal growth method, combined with molecular imprinting technology. The material was designed to solve the problems associated with metal–organic frameworks, which have the disadvantages of small pore size and low selectivity in the detection field. MZMMIPs were characterized by SEM, XRD, FTIR, TGA, BET, etc. The results showed that MZMMIPs achieved good crystalline form, excellent magnetic separation ability, rich pore structure, and large specific surface area (602.4 m2/g). Furthermore, the results of the adsorption experiment show that the crystal growth method with molecular imprint technology not only improved the MZMMIP adsorption capacity (64 mg/g) and microporous aperture, but also accelerated its adsorption (3 min) and elution rate (10 min) on the target product. With the introduction of molecular imprinting technology, MZMMIPs show a suitable adsorption selective performance (selection factor is 1.6) in the adsorption performance test of structural and nonstructural analogs of pyrene. MZMMIPs display good stability and reusability (the adsorption capacity of MZMMIPs decreased by only 21.8% after 10 elution times). The detection method in the study was successfully implemented for the determination of pyrene in vegetable oil, and achieved an excellent detection effect. The detection limit of MZMMIPs to pyrene is 0.11 µg/kg. The recovery ranged from 93.34 to 95.92%. [ABSTRACT FROM AUTHOR]

As nano-zinc oxide (Nano-ZnO), a new type of nanomaterial, has antioxidant and intestinal protection effects, we hypothesized that dietary Nano-ZnO could modulate poor meat quality, oxidative stress and disturbed gut microbiota in the finishing pig model of naturally occurring intrauterine growth retardation (IUGR). A total of 6 normal-born weight (NBW) and 12 IUGR piglets were selected based on birth weight. The pigs in the NBW group received a basal diet, and IUGR pigs were randomly divided into two groups and treated with basal diet and 600 mg/kg Nano-ZnO-supplemented diet. Dietary Nano-ZnO ameliorated IUGR-associated declined meat quality by lowering the drip loss48h, cooking loss, shearing force and MyHc IIx mRNA expression, and raising the redness (a*), peak area ratio of immobilized water (P22), sarcomere length and MyHc Ia mRNA expression. Nano-ZnO activated the nuclear factor erythroid 2-related factor 2-glutamyl cysteine ligase (Nrf2-GCL) signaling pathway by promoting the nuclear translocation of Nrf2, increasing the GCL activities, and mRNA and protein expression of its catalytic/modify subunit (GCLC/GCLM), thereby attenuating the IUGR-associated muscle oxidative injury. Additionally, the composition of IUGR pigs' cecal microbiota was altered by Nano-ZnO, as seen by changes in Shannon and Simpson indexes, the enhanced UCG-005, hoa5-07d05 gut group and Rikenellaceae RC9 gut group abundance. The UCG-005 and hoa5-07d05 gut group abundance were correlated with indicators that reflected the meat quality traits and antioxidant properties. In conclusion, Nano-ZnO improved the IUGR-impaired meat quality by altering water holding capacity, water distribution and the ultrastructure of muscle, activating the Nrf2-GCL signaling pathway to alleviate oxidative status and regulating the cecal microbial composition. [ABSTRACT FROM AUTHOR]

We demonstrate that the conductivity of graphene on thin-film polymer substrates can be accurately determined by reflection-mode air-plasma-based THz time-domain spectroscopy (THz-TDS). The phase uncertainty issue associated with reflection measurements is discussed, and our implementation is validated by convincing agreement with graphene electrical properties extracted from more conventional transmission-mode measurements. Both the reflection and transmission THz-TDS measurements reveal strong non-linear and instantaneous conductivity depletion across an ultra-broad bandwidth (1–9 THz) under relatively high incident THz electrical field strengths (up to 1050 kV/cm). [ABSTRACT FROM AUTHOR]

Aqueous zinc-ion batteries (AZIBs) are promising for large-scale energy storage systems due to their high safety, large capacity, cost-effectiveness, and environmental friendliness. However, their commercialization is currently hindered by several challenging issues, including cathode degradation and zinc dendrite growth. Recently, metal-organic frameworks (MOFs) and their derivatives have gained significant attention and are widely used in AZIBs due to their highly porous structures, large specific surface area, and ability to design frameworks for Zn2+ shuttle. Based on preceding contributions, this review aims to generalize two design principles for MOF-based materials in AZIBs: cathode preparation and anode protection. For cathode preparation, we mainly introduce novel MOF-based electrode materials such as pure MOFs, porous carbon materials, metal oxides, and their compounds, focusing on the analysis of the specific capacity of AZIBs. For anode protection, we systematically analyze MOF-based materials used as 3D Zn architecture, solid electrolyte interfaces, novel separators, and solid-state electrolytes, highlighting the improvement in the cyclic stability of Zn anodes. Finally, we propose the future development of MOF-based materials in AZIBs. Our work can give some clues for raising the practical application level of aqueous ZIBs. [ABSTRACT FROM AUTHOR]

Nitrofurazone (NF) is a kind of synthetic antibiotic with teratogenic and carcinogenic properties, which is often residual in animal food, so it is of great significance to detect it with high selectivity and rapid. In this study, a molecularly imprinted electrochemical sensor was constructed by electropolymerization for the high-specificity, high sensitivity,and rapid detection of NF in milk. By sequentially modifying reduced graphene oxide (RGO) and gold nanoparticles (AuNPs) on the glassy carbon electrode, the effective surface area and electron transfer ability of the electrode are improved, the double amplification of the electrical signal is realized, and the sensitivity and stability of the sensor are improved. A molecularly imprinted polymer (MIP) is polymerized on the surface of the modified electrode by using NF as a target molecule and o-phenylenediamine (o–PD) as a functional monomer to improve the specific detection ability of the sensor for NF. The experimental conditions (the number of turns of depositing RGO, the thickness of the MIP, the elution time, and the adsorption time) were optimized to attain the best detection performance of the sensor. Differential pulse voltammetry (DPV) was used to detect NF by redox probe ([Fe(CN)6]3−/4−). The constructed sensor exhibited an admirable linear relationship between 5 and 1000 nmol L−1 (R2 = 0.9968) and the detection limit was 0.18 nmol L−1 (S/N = 3). Compared to the non-imprinted sensor, the imprinting factor was found to be 3.09. In addition, the sensor also showed excellent repeatability (RSD = 1.17%) and stability, and also showed a good recovery rate in actual sample detection (99.06–101.46%), which is expected to be applied to the detection of other harmful substances in food. [ABSTRACT FROM AUTHOR]

BACKGROUND: This study was conducted to investigate the effect of dietary rutin on the meat quality, antioxidant status and mitochondrial structure and function in the breast muscle of heat‐stressed broilers. A total of 192 male broilers were randomly assigned into three groups and treated with normal control (CON), heat stress (34 °C, HS), and HS with 500 mg kg−1 rutin supplementation (HS + Rutin), respectively. RESULTS: Dietary rutin significantly reversed HS‐induced decrease in body weight, average daily feed intake, average daily gain, and feed efficiency. Rutin supplementation attenuated HS‐induced impaired meat quality by decreasing the lightness, drip loss at 24 and 48 h, the peak time of free water (T22) and the peak area ratio of free water (P22), and increasing the pH24h and peak area ratio of immobilized water (P21). Rutin supplementation promoted superoxide dismutase, glutathione peroxidase activities and total antioxidant capacity, and decreased malondialdehyde levels compared with the HS group. Moreover, rutin attenuated HS‐induced mitochondrial damage by increasing the mitochondrial DNA copy number and improving mitochondrial morphology. Dietary rutin significantly increased mitochondrial biogenesis‐related mRNA (proliferator‐activated γ receptor coactivator‐1α [PGC‐1α], nuclear respiratory factor 1 [NRF1], and mitochondrial transcription factor A [TFAM]) expression via the AMP‐activated protein kinase (AMPK) signaling pathway. HS significantly increased mitophagy‐related genes and proteins (Parkin, PTEN‐induced putative kinase 1 [PINK1], microtubule associated protein light chain 3‐II [LC3‐II]) expression, and dietary rutin significantly reversed these alterations. CONCLUSION: Dietary rutin attenuated the HS‐induced decline in meat quality and antioxidant capacity of broilers, which may be related to inhibition of the AMPK/PINK1–Parkin signaling pathway to attenuate mitochondrial damage. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

A method is presented to manipulate the final morphology of roll‐to‐roll slot‐die coated poly(3‐hexylthiophene) (P3HT) by optically exciting the p‐type polymer in solution while coating. These results provide a comprehensive picture of the entire knowledge chain, from demonstrating how to apply the authors' method to a fundamental understanding of the changes in morphology and physical properties induced by exciting P3HT while coating. By combining results from density functional theory and molecular dynamics simulations with a variety of X‐ray experiments, absorption spectroscopy, and THz spectroscopy, the relationship between morphology and physical properties of the thin film is demonstrated. Specifically, in P3HT films excited with light during deposition, changes in crystallinity and texture with more face‐on orientation and increased out‐of‐plane charge mobility are observed. [ABSTRACT FROM AUTHOR]

Accurate long-term runoff forecasting is crucial for managing and allocating water resources. Due to the complexity and variability of natural runoff, the most difficult problems currently faced by long-term runoff forecasting are the difficulty of model construction, poor prediction accuracy, and time intensive forecasting processes. Therefore, this study proposes a hybrid long-term runoff forecasting framework that uses the antecedent inflow and specific meteorological factors as the inputs, is modeled by ensemble empirical mode decomposition (EEMD) coupled with an artificial neural network (ANN), and computed by a parallel algorithm. First, the framework can transform monthly inflow and meteorological series into stationary signals via EEMD to more comprehensively explore the relationships of the input factors through the ANN. Second, the selected meteorological factors that are closely related to inflow formation can be filtered out by the single correlation coefficient method, which contributes to reducing coupling between input factors, and increases the accuracy of the prediction models. Finally, a multicore parallel algorithm that is easily accessed everywhere and that fully utilizes multiple calculation resources while flexibly contending with various optimization requirements will improve forecasting efficiency. The Xiaowan Hydropower Station (XW) is selected as the study area, and the final results of the study show that (1) the addition of targeted meteorological factors does indeed greatly enhance the performance of the prediction models; (2) the five criteria for evaluating the prediction accuracy show that the EEMD-ANN model is far superior to the prediction performance from the ordinary ANN model when run under the same input conditions; and (3) the optimization time of the 32-core model can be reduced by as much as 25 times, which significantly saves time during the forecast process. [ABSTRACT FROM AUTHOR]

We report on studies of the dwell fatigue crack growth (FCG) behavior of commercial pure titanium (CP-Ti) TA2 weld joints at 25 °C and 200 °C. Taking into account the effects of load ratio and dwell temperature, the impact of dwell on FCG behavior and the associated fracture mechanism are clearly demonstrated. Meanwhile, in order to illustrate creep–fatigue interaction, finite element simulations are also performed to analyze the evolution of stress and strain field near the crack tip. The results show that with the increase in dwell temperature, the FCG rate is increased. Furthermore, the effect of dwell on FCG behavior is more pronounced at higher load ratios. Finite element simulation results indicate that dwell induces creep stress relaxation and leads to an increase in the equivalent plastic strain near the crack tip. With the increase of dwell temperature and load ratio, the more pronounced creep deformation may lead to a creep-dominated FCG behavior. As consistent with the above analysis, the examination of the fracture surface reveals that more cavities and secondary cracks may be observed because of the increased creep deformation at the higher dwell temperature and load ratio. [ABSTRACT FROM AUTHOR]

The hydropower unit commitment (HUC) is often indirectly considered by combining individual units in a hydropower plant into a plant-based generator to alleviate the dimensional difficulty in short-term hydropower scheduling of cascaded reservoirs. This work presents three procedures to combine operating zones of units in a hydropower plant into the plant-based operating zones, including an exhaustive method (M01) that enumerates all the possible combinations, a discrete method (M03) that investigates discrete values to see if they are in an operating zone, and a bound oriented method (M04) that explores new operating zones with an optimization solver. The procedures are compared with a previous one (M02) that merges the operating zones of a unit one by one in order. The experiments of the methods in 11 case studies involving a variety of hydropower plants reveal that the second method (M02) should always be recommended due to its strength, which is even more prominent than any other methods in dealing with large-scale problems, and errors occur when using interpolation to estimate the plant-based operating zones at a water head between two sampling water heads. [ABSTRACT FROM AUTHOR]

This study investigated the effects of different doses of rutin on the growth performance, immunity, intestinal barrier, and antioxidant capacity of broilers. A total of two hundred and fifty-six 1-day-old male broilers were divided into 4 groups and fed basal diets supplemented with 0 (control group), 250, 500 and 1,000 mg rutin/kg, respectively, for 42 days. In the starter period (days 1–21) and whole trial period (days 1–42), broilers fed diets containing 500 mg rutin/kg had significantly (p < 0.05) higher average daily feed intake, body weight and average daily gain and better feed conversion ratio. Dietary 500 mg rutin/kg increased the villus height, villus height to crypt depth ratio and villus area, while reducing the B cell lymphoma 2 associated X mRNA expression (p < 0.05). Dietary 500 mg rutin/kg increased the level of IgA in serum and decreased serum tumour necrosis factor-α (TNF-α) content, and the nuclear factor kappa-B, interleukin-2 and TNF-α mRNA expression in jejunal mucosa (p < 0.05). Simultaneously, 500 and 1,000 mg rutin/kg significantly decreased serum diamine oxidase activity, D-lactic acid and lipopolysaccharide concentration, increased activities of total superoxide dismutase and total antioxidant capacity in jejunal mucosa (p < 0.05), and upregulated mRNA expressions of genes related to intestinal barrier and antioxidant capacity in jejunal mucosa (p < 0.05). These findings indicate that dietary rutin, especially at 500 mg/kg, improves broilers' growth performance, intestinal barrier function, immunity, and antioxidant capability, which may be related to the nuclear factor erythroid-2-related factor 2 (Nrf2) pathway. Dietary rutin improved growth performance, jejunal morphology, and intestinal barrier function. Dietary rutin enhanced the immunity via inhibiting NF-κB, and improved antioxidant capacity via activating Nrf2/HO-1 pathway in broilers. The optimal dose of rutin was 500 mg/kg in broiler diet. [ABSTRACT FROM AUTHOR]

Dietary zinc oxide nanoparticle (ZnO NP) possessing multiple biological activities might be a potential substitute for the combination of ZnSO4 and antibiotic growth promoter in broiler diets. Therefore, this study was conducted to investigate the efficacy of dietary ZnO NP as a substitute to the combination of ZnSO4 and xanthomycin for growth, antioxidant capacity, immunity, intestinal barrier and liver function in broilers. Arbor Acres chicks (n = 320) were assigned to 5 treatments with 8 replicates. Birds received a basal diet supplemented with 80 mg/kg ZnSO4 plus 5 mg/kg xanthomycin (ZnSO4 + Xanthomycin) or 0 (negative control, NC), 40, 80, and 160 mg/kg ZnO NP for 42 days. The average daily gain, average daily feed intake and feed-to-gain ratio showed dose-dependent increases with the increasing level of dietary ZnO NP during the 21–42 day and 1–42 day stages. The final body weight (42 d) and serum concentrations of insulin-like growth factor 1 and growth hormone increased linearly with the increasing level of dietary ZnO NP. In addition, 80 mg/kg ZnO NP increased the serum concentrations of IgA, IgG, IgM, andinterleukin-10 and peroxidase activity, the jejunal mucosal villus height, villus width and goblet cell numbers. Dietary 80 or 160 mg/kg ZnO NP significantly altered mRNA abundances of genes related to antioxidant status, intestinal barrier and immunity in the jejunal mucosa. These results indicated that dietary supplementation with 40–160 mg/kg ZnO NP caused no obvious negative effects on liver function, but effectively improved growth performance, intestinal barrier function, immunity and antioxidant capacity. Dietary 40–160 mg/kg zinc oxide nanoparticle (ZnO NP) improved growth performance and enhanced immunity of broilers without obvious negative effects on liver function. Dietary 40–160 mg/kg ZnO NP improved intestinal barrier and intestinal morphology, and enhanced antioxidant capacity via Nrf2/HO-1 pathway. Doses of 40–80 mg/kg ZnO NP were suggested to alternate the combination of 80 mg/kg ZnSO4 and 5 mg/kg xanthomycin in diets of broilers. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by dysfunction of the upper and lower motor neurons resulting in muscle weakness and wasting. Recently, several studies on ALS patients and ALS animal models indicated that intramuscular toxicity played a role in ALS disease progression; however, the mechanisms driving this are unknown. In this study, we explored the possible dysfunction of lipid metabolism in myocytes associated with ALS. Initially, skeletal muscle from 41 ALS patients, as well as 53 non-ALS control subjects, was investigated, and we identified that lipid droplet accumulation in the muscle fibers of ALS patients was significantly increased, especially in patients with FUS mutations. A myoblast (C2C12) cell line expressing mutant FUS (FUS-K510Q) was able to induce lipid droplet accumulation and mitochondrial dysfunction. Consistently, transgenic flies expressing FUS-K510Q under a muscle-specific driver showed elevated triglyceride levels in the flight muscles, as well as locomotor defects. Biochemical analysis of C2C12 cells and fly muscle tissues showed upregulation of PLIN2, and downregulation of ATGL and CPT1A, indicating inhibition of lipolysis and fatty acid β-oxidation in muscle cells with FUS mutations. Our study provided a potential explanation for the pathogenesis associated with lipid droplets accumulating in skeletal muscle in ALS. Our data also suggested that disordered lipid metabolism and mitochondrial dysfunction play a crucial role in intramuscular toxicity in ALS. [ABSTRACT FROM AUTHOR]

A monthly hydropower scheduling determines the monthly flows, storage, and power generation of each reservoir/hydropower plant over a planning horizon to maximize the total revenue or minimize the total operational cost. The problem is typically a complex and nonlinear optimization that involves equality and inequality constraints including the water balance, hydraulic coupling between cascaded hydropower plants, bounds on the reservoir storage, etc. This work applied the Zoutendijk algorithm for the first time to a medium/long-term hydropower scheduling of cascaded reservoirs, where the generating discharge capacity is handled with an iterative procedure, while the other head-related nonlinear constraints are represented with exponential functions fitting to discrete points. The procedure starts at an initial feasible solution, from which it finds a feasible improving direction, along which a better feasible solution is sought with a one-dimensional search. The results demonstrate that the Zoutendijk algorithm, when applied to six cascaded hydropower reservoirs on the Lancang River, worked very well in maximizing the hydropower production while ensuring the highest firm power output to be secured. [ABSTRACT FROM AUTHOR]

The influence of pre-strain on the fatigue crack growth behavior of Zr702/TA2/Q345R composite plate is studied by experiments and the finite element method. The crack perpendicular to the interface and the through-wall crack are considered at the same time. For the crack perpendicular to the interface, the monotonic plastic zone and cyclic plastic zone at the crack tip are used to study the influence of pre-strain on the plastic zone. Furthermore, the influence of pre-strain on the evolution of the plastic damage at the crack tip is analyzed in detail by studying the variation in the initial plastic energy and equivalent plastic strain. For the through-wall crack, the effect of pre-strain on the propagation behavior of cracks on both sides and the whole crack is studied systematically. The results show that the strengthening of the cracks on the Zr702 side is significantly higher than that on the Q345R side, so the inhibitory effect of pre-strain on the whole crack of the through-wall specimen is mainly due to the increase in the resistance to crack growth on the Zr702 side. [ABSTRACT FROM AUTHOR]

This paper introduces an efficient and flexible 3D FFT framework for state-of-the-art multi-GPU distributed-memory systems. In contrast to the traditional pure MPI implementation, the multi-GPU distributed-memory systems can be exploited by employing a hybrid multi-GPU programming model that combines MPI with OpenMP to achieve effective communication. An asynchronous strategy that creates multiple streams and threads to reduce blocking time is adopted to accelerate intra-node communication. Furthermore, we combine our scheme with the GPU-Aware MPI implementation to perform GPU-GPU data transfers without CPU involvement. We also optimize the local FFT and transpose by creating fast parallel kernels to accelerate the total transform. Results show that our framework outperforms the state-of-the-art distributed 3D FFT library, being up to achieve 2× faster in a single node and 1.65× faster using two nodes. [ABSTRACT FROM AUTHOR]

Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein–protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biological functions. Understanding PPIs reveals how cells behave and operate, such as the antigen recognition and signal transduction in the immune system. In the past decades, many computational methods have been developed to predict PPIs automatically, requiring less time and resources than experimental techniques. In this paper, we present a comparative study of various graph neural networks for protein–protein interaction prediction. Five network models are analyzed and compared, including neural networks (NN), graph convolutional neural networks (GCN), graph attention networks (GAT), hyperbolic neural networks (HNN), and hyperbolic graph convolutions (HGCN). By utilizing the protein sequence information, all of these models can predict the interaction between proteins. Fourteen PPI datasets are extracted and utilized to compare the prediction performance of all these methods. The experimental results show that hyperbolic graph neural networks tend to have a better performance than the other methods on the protein-related datasets. [ABSTRACT FROM AUTHOR]

Metaverse is the future of the Internet and integrates a variety of information technologies. It leads future education trends and brings profound changes to education. On the basis of analysis of the development trend of smart education and the connotation and action mechanism of edu-metaverse in the view of metaverse, this paper structures the smart education ecosystem, builds the scenario and modular smart learning space of three education scenarios of resource collaborative interaction, virtuality-reality integration experience, and ubiquitous spatial inquiry by using the six core technologies, and forms the new education mode of virtuality-reality symbiosis, trans-spatial fusion, and collaborative inquiry. Then, it verifies the application effect by AHP. Finally, it creates the smart education ecosystem of "four ecology integration"—resource ecology, interaction ecology, space ecology, and collaboration ecology, which accelerates the organic integration of metaverse and smart education and provides theoretical basis and reference for the new application of future education. [ABSTRACT FROM AUTHOR]

Background: Familial episodic pain syndrome type 3 (FEPS3) is an inherited disorder characterized by the early-childhood onset of severe episodic pain that primarily affects the distal extremities. As skin biopsy has revealed a reduction in intraepidermal nerve fiber density and degeneration of the unmyelinated axons, it remains unclear whether FEPS3 patients have pathological changes in the peripheral nerve. Methods: The clinical features of patients with FEPS3 were summarized in a large autosomal dominant family. Sural nerve biopsies were conducted in two patients. Whole exome sequencing (WES) was performed in the index patient. Sanger sequencing was used to analyze family co-segregation. Results: Fourteen members exhibited typical and uniform clinical phenotypes characterized by length-dependent and age-dependent severe episodic pain affecting the distal extremities, which can be relieved with anti-inflammatory medicine. The WES revealed a heterozygous mutation c.665G > A (p.R222H) in the SCN11A gene, which was co-segregated with the clinical phenotype in this family. A sural biopsy in patient V:1, who was experiencing episodic pain at 16 years old, showed normal structure, while the sural nerve in patient IV:1, whose pain attack had completely diminished at 42 years old, displayed a decrease of the density of unmyelinated axons with the axonal degeneration. Conclusions: The clinical phenotype of FEPS3 showed distinctive characteristics that likely arise from dysfunctional nociceptive neurons that lack detectable pathological alterations in the nerve fibers. Nevertheless, long-term dysfunction of the Nav1.9 channel may cause degeneration of the unmyelinated fibers in FEPS3 patient with pain remission. [ABSTRACT FROM AUTHOR]

With the expansion of wind power grid integration, the challenges of sharp fluctuations and high uncertainty in preparing the power grid day-ahead plan and short-term dispatching are magnified. These challenges can be overcome through accurate short-term wind power process prediction based on mining historical operation data and taking full advantage of meteorological forecast information. In this paper, adopting the ERA5 reanalysis dataset as input, a short-term wind power prediction framework is proposed, combining light gradient boosting machine (LightGBM), mutual information coefficient (MIC) and nonparametric regression. Primarily, the reanalysis data of ERA5 provide more meteorological information for the framework, which can help improve the model input features. Furthermore, MIC can identify effective feature subsets from massive feature sets that significantly affect the output, enabling concise understanding of the output. Moreover, LightGBM is a prediction method with a stronger ability of goodness-of-fit, which can fully mine the effective information of wind power historical operation data to improve the prediction accuracy. Eventually, nonparametric regression expands the process prediction to interval prediction, which significantly improves the utility of the prediction results. To quantitatively analyze the prediction results, five evaluation criteria are used, namely, the Pearson correlation coefficient (CORR), the root mean square error (RMSE), the mean absolute error (MAE), the index of agreement (IA) and Kling–Gupta efficiency (KGE). Compared with support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost) models, the present framework can make full use of meteorological information and effectively improve the prediction accuracy, and the generated output prediction interval can also be used to promote the safe operation of power systems. [ABSTRACT FROM AUTHOR]

Broad bean fermentation is of vital importance in PixianDouban (PXDB) production, as well as a key process for microorganisms to degrade protein, which lays the foundation for the formation of PXDB flavor. In this study, two fungi and bacteria were screened, and their morphology, molecular biology, growth, and enzyme production characteristics were analyzed, and then they were applied to the broad bean fermentation simulation system. The protein, peptide, amino acid, amino nitrogen, and sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE) in the system were evaluated. The results showed that the four microorganisms were Aspergillus oryzae, Aspergillus jensenii, Staphylococcus gallinarum, and Enterobacter hormaeche. Aspergillus oryzae had the highest protease activity at pH 7.0, while the other three strains had better enzyme activity stability under neutral acidic conditions. And the total protein (F1 and F2 were 18.32 g/100 g, 19.15 g/100 g, respectively), peptides (11.79 ± 0.04 mg/g and 12.06 ± 0.04 mg/g), and amino acids (55.12 ± 2.78 mg/g and 54.11 ± 1.97 mg/g) of the fungus experimental groups (F) were higher than the bacterial experimental groups (B). In addition, the enzyme system produced by fungi exhibited a stronger ability for albumin (20 kDa) and glutenin (<30 kDa) deterioration in neutral conditions, while the bacterial enzyme system was more efficient in degrading albumin (<30 kDa) and glutenin (20–30 kDa) in acidic conditions, as indicated by SDS‐PAGE. These findings showed that both bacteria and fungi played an important role in the degradation of protein in different fermentation stages of broad bean fermentation. Practical applications: There is a lack of comprehensive understanding of the protein composition and protein degradation mechanism of broad beans in the fermentation stage of PXDB. This research work explored the differences in the degradation of PXDB fermented protein by different microorganisms, and provided a theoretical basis for optimizing the production of PXDB and improving the quality of PXDB. [ABSTRACT FROM AUTHOR]

Ultrathin inorganic nanosheets (e.g., 2D nanomaterials, thin films, etc.) have attracted tremendous research interest because of their unique properties and promising applications. However, because of their ultrathin thickness (<100 nm) and low flexural rigidity, it is difficult to manufacture low‐dimensional structures using these nanosheets. In this work, the observation of an intriguing elasto‐capillary unfolding phenomenon is first reported which occurs on a variety of freestanding inorganic nanosheets floating on a liquid surface. Through theoretical modeling and experiments, it is demonstrated that one can easily unfold, re‐roll, and transport different kinds of nanosheets by tuning the interfacial properties of the liquid. As a result, one can assemble nanosheets on the liquid surface into small structures (e.g., heterogeneous scrolls, optical resonators) and/or transfer them out of the liquid surface onto other surfaces for the manufacturing of flexible devices. The outcome of this research paves the way for nano‐manufacturing of low‐dimensional structures with ultrathin inorganic nanosheets. [ABSTRACT FROM AUTHOR]

Objectives: Benzbromarone and febuxostat use different mechanisms to reduce serum urate. However, the effectiveness of benzbromarone versus febuxostat in reducing serum urate in gouty patients classified with different types of hyperuricaemia remains unclear. Method: In this retrospective study from January 1, 2018, to September 30, 2020, subjects were identified if they were newly treated with benzbromarone 25 mg daily or febuxostat 20 mg daily. The subjects were classified into four types according to their 24-h urinary uric acid and fractional excretion of uric acid. The baseline data and follow-up information after 28 ± 3 days of treatment were collected. Results: Seventy-three subjects with gout were finally enrolled. Among them, 50 were treated with benzbromarone. The percent changes in serum urate from the baseline were − 33.71 ± 13.59% and − 29.45 ± 10.62% in the benzbromarone and febuxostat group, respectively, without a significant difference between the groups (P = 0.188). No differences were found between the groups in subjects classified as the renal underexcretion type, combined type, or "normal" type. In patients with eGFR ≥ 70 mL/min/1.73 m2, the rate of serum urate lowering was higher in those treated with benzbromarone than in those treated with febuxostat. Febuxostat treatment significantly lowered serum creatinine from the baseline (P = 0.001). Conclusions: Benzbromarone 25 mg daily and febuxostat 20 mg daily may have comparable effectiveness in lowering the serum urate among different types of hyperuricaemia. Benzbromarone was more effective than febuxostat in lowering serum urate in subjects with eGFR ≥ 70 mL/min/1.73 m2, while febuxostat had a renal protective effect. Key Points • Benzbromarone 25 mg daily and febuxostat 20 mg daily may have comparable effectiveness in lowering the serum urate in patients with different types of hyperuricaemia. • Benzbromarone 25 mg daily was more effective than febuxostat 20 mg daily in lowering serum urate in subjects with eGFR ≥ 70 mL/min/1.73 m2. • Febuxostat had a renal protective effect after about 1 month treatment. [ABSTRACT FROM AUTHOR]

Mineral hydrogels have caught a lot of attention for their strong competency as artificial skin-like materials. Nonetheless, it remains a great difficulty in fulfilling in one hydrogel system a range of key functionalities that are needed for practical artificial skin applications, i.e., to be biocompatible, strain-sensitive, ion-conductive, elastic and robust, anti-swelling, and anti-freezing. Here we present a such type of versatile hydrogel that is not only capable to deliver all the above-mentioned key functionalities but also highly stable. This novel hydrogel is constructed by introducing a gelatinous and amorphous multi-ionic biomineral (denoted as Mg-ACCP, containing Mg2+, Ca2+, CO32−, and PO43−) into the network of biocompatible polyvinyl alcohol (PVA) and sodium alginate (SA). The presence of Mg2+ and PO43− in this hydrogel helps prohibit the crystallization of the biominerals, leading to significantly improved stability. The hydrogel thus obtained delivers excellent mechanical performance due to the chelation between the mineral ions and the organic matrix, and high sensitivity even to subtle pressure and strain applied, such as slight finger bending and gentle tapping. Furthermore, the novel hydrogel features high ionic conductivity, high resistance to swelling, and extraordinary anti-freezing property, holding great promise for applications in different practical scenarios, particularly in aqueous or cold environments. [ABSTRACT FROM AUTHOR]

In order to conduct a data-driven load forecasting modeling and its application in optimal control of air-conditioning system, this study used a hotel's central air conditioning system as the research object. Based on the data of the hotel energy management system, the load-forecasting model of the central air conditioning system based on support vector regression (SVR) was established by MATLAB. Based on the working principle of a chiller, chilled water pump, cooling water pump, and cooling tower, the energy consumption models were established, respectively. Finally, based on the load-forecasting results and the equipment energy consumption model, the energy consumption optimization objective function of the hotel water system was established, the objective function was solved to optimize the operating parameters of the water system at different load rates, the operation control strategy for each piece of equipment was obtained, and the energy-saving analysis was carried out. The results show that in the range of a load rate of 25~90%, the optimization strategy has an energy-saving effect, and the system's energy-saving rate is the highest when the load rate is 25.4%. The average energy-saving rate of the system is 12.4%. [ABSTRACT FROM AUTHOR]

Fabrication of single-crystalline metal-organic framework (MOF) hollow nanostructures with two-dimensional (2D) morphologies is a challenging task. Herein, twin-like MOF nanobricks, a quasi-hollow 2D architecture, with multi-metal nodes and replaceable organic ligands, are uniformly and firmly grown on conductive Ni foam through a generic one-pot approach. The formation process of twin-like MOF nanobricks mainly includes selective epitaxial growth of Fe-rich MOF layer and simultaneously dissolution of the pre-formed Ni-rich metal-organic frameworks (MOFs), all of which can be ascribed to a special self-templated mechanism. The fantastic structural merits of twin-like MOF nanobrick arrays, featuring highly exposed active sites, remarkable electrical conductivity, and hierarchical porosities, enable this material for efficient electrocatalysis. Using bimetallic NiFe-MOFs grown on Ni foam as an example, the resultant twin-like nanobrick arrays can be directly utilized as three-dimensional (3D) integrated electrode for high-performance water oxidation in 1 M KOH with a low overpotential, fast reaction kinetics (28.5 mV·dec−1), and superb stability. Interestingly, the unstable NiFe-MOFs were served as an oxygen evolution reaction (OER) pre-catalyst and the single-crystalline NiFe-MOF precursor can be in-situ topochemically regulated into porous and low-crystalline NiFeOx nanosheets during the OER process. This work extends the hollowing strategy to fabricate hollow MOFs with 2D architectures and highlights their direct utilization for advanced electrocatalysis. [ABSTRACT FROM AUTHOR]

Crime risk prediction is helpful for urban safety and citizens’ life quality. However, existing crime studies focused on coarse-grained prediction, and usually failed to capture the dynamics of urban crimes. The key challenge is data sparsity, since that 1) not all crimes have been recorded, and 2) crimes usually occur with low frequency. In this paper, we propose an effective framework to predict fine-grained and dynamic crime risks in each road using heterogeneous urban data. First, to address the issue of unreported crimes, we propose a cross-aggregation soft-impute (CASI) method to deal with possible unreported crimes. Then, we use a novel crime risk measurement to capture the crime dynamics from the perspective of influence propagation, taking into consideration of both time-varying and location-varying risk propagation. Based on the dynamically calculated crime risks, we design contextual features (i.e., POI distributions, taxi mobility, demographic features) from various urban data sources, and propose a zero-inflated negative binomial regression (ZINBR) model to predict future crime risks in roads. The experiments using the real-world data from New York City show that our framework can accurately predict road crime risks, and outperform other baseline methods. [ABSTRACT FROM AUTHOR]

Crime has been a complex social problem worldwide, impacting numerous individuals in both property and psychology, and affecting public safety as well. To prevent and avoid crime is of great importance for urban authorities and citizens. Crime prediction using various urban sensing data provides a promising paradigm to cope with this challenging problem. However, previous studies on crime prediction mainly focus on coarse-grained prediction at the region level, which fail in fine-grained road-level crime inference due to data sparsity problems. This article proposes a road-level framework for fine-grained crime risk inference leveraging heterogeneous open data. We first extract a set of features from relevant external datasets and historical crime records, i.e., temporal, spatial, and recurrence crime features. We then establish a spatio-temporal crime pattern using spatio-temporal features, and further infer road-level crime risk incorporating with recurrence crime features. The framework not only considers a useful spatio-temporal pattern but also considers a unique crime near-repeat phenomenon, which helps address the data sparsity. We further present an application crime risk-aware route recommendation to demonstrate the effectiveness of our framework. This application cannot be solved well with coarse-grained (e.g., region-level) crime risk results since it is inconvenient for people to travel while avoiding large regions with potential crime risks. Experiments with the real-world datasets from New York City show that our framework accurately infers road-level crime risk and outperforms other baseline methods. [ABSTRACT FROM AUTHOR]