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Water-soluble fluorescent probes for conveniently and rapidly monitoring the hazardous uranyl ions (UO 2 2+) in nuclear wastewater are crucial for public nuclear security. Herein, we demonstrated a water-soluble CdSe/CdS/ZnS QDs probe by substituting hydrophilic dodecyl sodium sulfate (SDS) ligands for the original hydrophobic oleic acid ligands toward the rapid and accurate detection of trace UO 2 2+ in aqueous environments. From this simple ligand exchange mothed, the as-prepared QDs probe exhibited a narrow full width at half maximum (FWHM) of 53 nm with an emission peak at 666 nm. Benefiting from dynamic and static fluorescence quenching interaction, this probe represented a high sensitivity (a detect limit of 15.4 nM), a high selectivity with comparison of presettable eight metal ions), a high environmental stability (a recovery rate of 81–94 %) and a rapid inspection ability (on the order of a few minutes). Therefore, this work provided a new approach for the determination of UO 2 2+ in aqueous environments and then for the assurance of public nuclear security. [Display omitted] [ABSTRACT FROM AUTHOR]

BACKGROUND: Peanut is a significant source of nutrition and a valuable oilseed crop. It is also a serious allergy source, which poses a threat to 1.1% of the population. This study aimed to screen lactic acid bacteria (LAB) with the capacity to alleviate peanut allergenicity and exhibit anti‐allergic properties. RESULT: The results show that LAB can make use of substances in peanuts to reduce the pH of peanut milk from 6.603 to 3.593–4.500 by acid production and that it can utilize the protein in peanuts to reduce the allergenic content (especially Ara h 1) and improve biological activity in peanut pulp. The content of Ara h 1 peanut‐sensitizing protein was reduced by 74.65% after fermentation. The protein extracted from fermented peanut pulp is more readily digestible by gastrointestinal juices. The inhibitory activity assay of hyaluronidase (an enzyme with strong correlation to allergy) increased from 46.65% to a maximum of 90.57% to reveal that LAB fermentation of peanut pulp exhibited a robust anti‐allergic response. CONCLUSION: The strains identified in this study exhibited the ability to mitigate peanut allergenicity partially and to possess potential anti‐allergic properties. Lactobacillus plantarum P1 and Lactobacillus salivarius C24 were identified as the most promising strains and were selected for further research. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Highly tunable localized surface plasmon (LSP) resonances in metal nanostructures are of great importance for manipulating light waves and enhancing light–matter interactions at the nanoscale. Here, a new type of plasmonic resonators based on hollow elliptical nanotubes, which can generate highly tunable LSP resonances in the visible frequencies, are reported. High‐quality hollow gold (Au) elliptical nanotubes with fine controllable size and morphology are experimentally fabricated. Dark‐field scattering measurements reveal the presence of multiple plasmon resonances including longitudinal Fabry–Pérot resonances and transverse hybridized LSP resonances due to rotational symmetry breaking. Upon varying the ellipticity, the hybridized LSP resonances exhibit continuously spectral evolution behaviors, such as the hybridized modes shifting and crossing. The experimental results show good agreement with the rigorous electromagnetic modeling and Raman spectroscopic measurements. The hollow anisotropic geometries provide highly tunable plasmonic responses together with homogeneous field distributions and high surface‐to‐volume ratio, which hold great potential for practical applications in sensing, nonlinear optics, surface‐enhanced spectroscopies, and bio‐medicine. [ABSTRACT FROM AUTHOR]

Why do people often fail to find new ideas creative? The literature indicates people fail to find creativity due to ideas having characteristics that are incongruent with people's existing perspectives. The current paper identifies a second reason stemming from the need for evaluators to understand what ideas are before determining if those ideas meet evaluation criteria. We propose that to find creativity in early phase ambiguous ideas, people's existing perspectives may not be helpful. People may need to engage in a process of perspective change by searching for and finding alternative fruitful interpretations. Three studies provide evidence that people tended to evaluate ideas as more creative if they spontaneously experienced (Study 1) or were induced to experience (Study 2) a change in perspective when evaluating them. Further, if people were induced not to experience a perspective change, ideas were perceived as less creative (Study 3). These findings add to theory by revealing new aspects of the process of evaluating early phase ideas. They also support practice by identifying why spending more time searching for and potentially finding fruitful interpretations of early phase ideas might help evaluators find creativity, and thereby support rather than squelch innovation. The current research identifies a gap in the prior creativity literature on evaluation, which has focused primarily on how people evaluate later phase ideas. We observe that, unlike later phase ideas, early phase ideas may lead evaluators to undertake an additional, initial stage in the idea evaluation process. Early phase ideas are often ambiguous, abstract, and difficult to communicate, which can mean evaluators might need to interpret these ideas in new ways before rendering judgments. As a result, people may experience variation in the process of evaluating early phase ideas. We show that this variation helps explain creativity assessments. During later phase idea evaluation, the creativity literature notes that evaluators use their existing perspectives to determine if ideas are useful via convergent thinking. In contrast, during early phase idea evaluation when ideas are ambiguous, evaluators' existing perspectives may not help them make sense of ideas, resulting in their viewing these ideas as bizarre and so not creative. It is also possible for evaluators to assimilate ideas into existing perspectives, thereby viewing these ideas as trivial and so not creative. Further still, evaluators may engage in a process of perspective change by searching for (i.e., divergent thinking) and finding (i.e., convergent thinking) a fruitful new perspective with which to appreciate ideas, thereby finding creativity. Our findings suggest that recognizing early phase new ideas as creative can involve a similar kind of thinking as generating creative ideas, namely a perspective change process of seeking out and finding alternative perspectives. Therefore, the evaluation of early phase creative ideas, much like the generation of creative ideas, can be a cognitively effortful activity. An additional implication is that the process people enact during idea evaluation, separate from any characteristics of the ideas themselves, influences how creative those ideas appear to be. Taken together, the results from the current study advance our understanding of why recognizing creative ideas can be hard, what might help, and why thinking about creativity as a process of changing perspectives can be useful. [ABSTRACT FROM AUTHOR]

Vehicle classification is widely used in intelligent transportation and smart cities. However, the good performance of vehicle classification often depends on a large number of labeling data, which leads to the high cost of manual labeling. How to use a small number of labeled samples with rich features to achieve good classification performance is a challenge in vehicle classification. To solve these problems, we propose a deep active learning framework called Feature Fusion Spatial Pyramid Pooling and Re -parameterization Visual Geometry Group (FFSPP-RepVGG). The framework is mainly divided into two parts: query strategy and feature extraction module. Specifically, the query strategy uses Feature Fusion (FF) to calculate the loss, thus defining uncertainty and being able to select more valuable samples for labeling training. The feature extraction module uses Spatial Pyramid Pooling and Re -parameterization Visual Geometry Group (SPP-RepVGG) model, which can extract more reliable image features. It can reduce the cost of data labeling and have better performance at the same time. The experimental results on the BIT-Vehicle data set and the car-10 data set show that the FFSPP-RepVGG framework has superior performance than that of the comparison models. [ABSTRACT FROM AUTHOR]

The development of efficient, durable and economical catalysts based on non-precious metals for the controllable and fast hydrogen evolution from chemical hydrogen storage materials is highly desirable for the hydrogen economy. Herein, we introduce an advanced catalytic system by in situ encapsulating cobalt phosphide (CoP) nanoparticles into a quasi-metal–organic framework (quasi-Co-MOF-74) through a smart pyrolysis method. The designed synergic structure of CoP@quasi-Co-MOF-74 facilitates the efficient adsorption and activation of reactants, and achieves superior catalytic activity for the dehydrogenation of ammonia borane (AB). The extremely high hydrogen generation rate (HGR) of 9790 mL min−1 gcat−1 achieved by this catalytic system is 13.1, 4.4, and 46.5 times higher than that of quasi-Co-MOF-74, CoP, and CoP@C counterparts, respectively. Furthermore, CoP@quasi-Co-MOF-74 also delivers a high turnover frequency (TOF) of 55.9 min−1 and a low activation energy of 38.22 kJ mol−1 for the catalytic hydrolysis of AB, which compares favorably to most of the previously reported transition metal phosphide and cobalt-based catalysts. [ABSTRACT FROM AUTHOR]

Compared with visible fluorescence carbon dots (CDs), the multi-emission (visible and near infrared) fluorescence CDs based platform (V-N Platform) with blood-brain barrier penetration, real-time brain imaging and drug loading capacities, is of great significance. Herein, a novel type of multi-emission fluorescence CDs (GT) was created to penetrate BBB for brain imaging and local drug delivery, which was synthesized by hydrothermal method, using endogenous l -tryptophan and d -glucose. The capability for in vitro imaging was verified through the experiments on cell imaging. Moreover, the ability of in vivo imaging, especially for brain imaging, was confirmed by experiments in mice and zebrafish. In addition, the in vitro and in vivo experiments preliminarily confirmed its potential to act as a drug delivery platform. This V-N Platform (GT) will be expected to have a significant impact on the researches for CDs and the theranostics of brain diseases. A novel kind of multi-emission fluorescence carbon dots (GT) was created with NIR fluorescence to act as the "V-N Platform", using endogenous nutrients. With the BBB-penetrating ability and drug loading potential, GT could be expected to with the potential of theranostics for brain diseases. [Display omitted] • GT CDs was synthesized using two endogenous nutrients (d -glucose and l -tryptophan) as the precursor by hydrothermal method. • The retained bio-activity of d -glucose and l -tryptophan enabled GT to cross the BBB effectively. • Carbonization endowed GT with multi-emission fluorescence, especially the NIR fluorescence. • GT could be used as fluorescent probe at multi-level,especially the brain imaging in real-time. • Nanoscale ensured GT as a drug carrier for loading drugs with various polarity. [ABSTRACT FROM AUTHOR]

Trepanation skulls have been found clustered in the Gan‐Qing region of northwestern China, where the trepanation also demonstrated more signs of healing than those from other areas. In this study, two skulls belonging to the pre‐Qiang people from the Mapai cemetery in the late Neolithic period in the Gan‐Qing region with trepanation were observed using ultra‐depth electron microscopy and CT imaging. Moreover, trepanation experiments were conducted to test different tools and tool combinations to investigate the trepanation technique used by the pre‐Qiang people. Results demonstrated that the trepanation openings with signs of healing were the work of experienced trepanation practitioners, most likely for therapeutic purposes. Our experiments also demonstrated that different tools need to be used to generate similar perforations, suggesting a mature trepanation procedure by the pre‐Qiang people. Although it seems clear that the two individuals in this study underwent neurosurgical operations, it is impossible to determine why that surgery was performed. The trepanation phenomenon of the Gan‐Qing region enriches our knowledge of lifestyles, health status, and primitive yet then advanced medical techniques and healthcare. [ABSTRACT FROM AUTHOR]

• Carbon offset potentials of rooftop PV in 31 provinces in China are assessed. • Beijing possesses the highest carbon offset potential while Tibet has the lowest. • Most provinces are projected to have shrinking carbon offset potential. • Targeted policies are needed for rooftop PV development in different areas. As a promising tool for mitigating carbon emission, rooftop photovoltaics have attracted worldwide attention. This study examines the carbon offset potential of rooftop photovoltaics in 31 provinces in China. The future trends of carbon offset potentials over the lifetime of rooftop photovoltaic systems are investigated. The findings reveal that the carbon offset potentials vary significantly across different regions in China due to the combined effects of variations in climate conditions and the energy mix for electricity generation. The northern regions possess significantly higher carbon offset potentials than the southwestern areas. In 2021, the annual total carbon offset potential ranged from the lowest at −2.0 kg CO 2 /m2 in Tibet to the highest at 169.3 kg CO 2 /m2 in Beijing. The projected future trends indicate that Beijing and Tibet will respectively maintain their highest and lowest carbon offset potential rankings. Most provinces are projected to witness decreasing carbon offset potentials. In terms of the carbon offset potential over the lifetime of rooftop photovoltaics, the northern regions − Beijing, Tianjin and Inner Mongolia − rank the top three. Not only can these findings serve as reference for developing targeted policies for carbon mitigation in China, the methodology of this study can also be applied in other places to determine their carbon offset potentials of rooftop photovoltaics. [ABSTRACT FROM AUTHOR]

As the reach of science content in traditional media declines, many institutions and scientists are turning to YouTube as a powerful tool for communicating directly with non-expert publics. They do so with little empirical social science research guiding their efforts. This study explores how video characteristics and social endorsement cues provided by audience members might influence user engagement with online science videos. Shorter videos are more likely to be viewed. Social endorsement cues significantly relate to variations in user engagement, with likes having a consistent positive association with all types of engagement. Implications for science communication through YouTube are discussed. [ABSTRACT FROM AUTHOR]

Porous carbon nanostructures are promising supports for stabilizing the highly dispersed metal nanoparticles and facilitating the mass transfer during the reaction, which are critical to achieve the high efficiency of hydrogen generation from sodium borohydride dehydrogenation. Herein, the catalytically active porous architectures are simply prepared by using 2-methylimidazole and melamine as reactive sources. The structural and compositional characterizations reveal the coexistence of metallic cobalt and N -doped carbon in porous architectures. Electron microscopy observations indicate that the synthesized products are smartly constructed from the carbon nanosheets with densely dispersed Co nanoparticles. Due to the notable structural features, the prepared Co@NC-600 sample presents the highly efficient activity for catalytic hydrolysis of NaBH 4 with a hydrogen generation rate of 2574 mL min−1 g cat −1 and an activation energy of 47.6 kJ mol−1. The catalytically active metallic Co and suitable support-effect of N -doped carbon are responsible for catalytic dehydrogenation. [Display omitted] • A scalable and simple strategy is developed to prepare Co@NC catalysts. • Highly homogeneous dispersion of Co nanoparticles onto NC nanosheets is achieved. • Co@NC catalyst presents highly activity for catalytic NaBH 4 hydrolysis. • The optimal catalyst shows the hydrogen generation rate of 2574 mL min−1 g cat −1. [ABSTRACT FROM AUTHOR]

Bone defect in the mandible due to developmental defects, trauma, or diseases is common. However, large scale of mandibular bone atrophy induced by long‐term pressure is rare. This study reported a mandibular anomaly, possibly a secondary lesion, from a Bronze Age adult male excavated from the Dunping cemetery during the Eastern Zhou Dynasty (770–256 BCE), Zhang County, Gansu Province, China. The defect presents as an absence of bone mass at the angle of inferior lingual aspect of the mandibular corpus, incorporating the gonial angle of the mandible on the left side. Overall profile of the defect was assessed using morphological observations of the mandible, accompanied by computed tomography (CT) imaging and panoramic dental X‐ray images of the jaws used to assist with the diagnosis. There were no signs of trauma, osteogenic neoplasms, or osteolytic lesions. Pressure resorption, a Stafne defect, was postulated as the primary cause of bone atrophy due to a long‐term lesion of the neighboring submandibular gland, namely, chronic sialadenitis or a benign neoplasm pleomorphic adenoma. This is for the first reported case of a mandible anomaly as such identified from ancient China. This reporting enriches the knowledge of long‐term effects of pressure resorption in the human mandible. [ABSTRACT FROM AUTHOR]

Traditional surface polishing methods are no longer able to meet the ultra-precision requirements of the high-tech industry for the inner surface of the pipe, but magnetorheological polishing technology is very suitable due to its advantages of high precision, fast controllability and good deposition stability. However, there is even less investigation on the microforce analysis, chaining mechanism and micromodeling methods of magnetorheological polishing fluid (MRPF), and the polishing mechanism of MRPF has not been explored yet. As a step to completely develop the magnetorheological polishing (MRP) technique, this paper proposed the simulation method of MRPF based on particle dynamics, and the shear stress model of magnetorheological fluid (MRF) is optimized under the action of the magnetic field after performing the chain simulation. On the basis of the optimized shear stress model and the hexagonal close-packed structure of MRF, the holding mechanism of polishing abrasive particles is explored for the MRPF and the corresponding holding models are proposed. Then, the shear yield stress models and material removal model are also established for the inner surface polishing, respectively. Eventually, the above theoretical analysis and related models have been verified though the polishing experiment of the titanium alloy pipe. [ABSTRACT FROM AUTHOR]

Plant essential oils (EO) are increasingly used as food preservatives due to their antibacterial and antioxidant activities. For such applications, EO are commonly microencapsulated to overcome their poor stability, low solubility and dominant aromas. But, typically, individual EO act against only a narrow range of bacterial species. Therefore, in this study, we aimed to develop a microencapsulated preservative using a combination of three EO and to determine its anti-bacterial action against three common food contaminants, viz. Escherichia coli , Salmonella and Staphylococcus aureus , and one, usually, beneficial species, viz. Lactoplantibacillus plantarum. The EO of cinnamon (Cinnamomum cassia), peppermint (Mentha haplocalyx) and lemon (Citrus limon) were combined in the proportions, 1.0 : 1.8: 2.4, respectively and were encapsulated in gelatin-chitosan by spray drying. The particle size, zeta potential, moisture content, and encapsulation rate of the essential oil microcapsules (EOM) were measured. With increasing EOM exposure time, the concentrations of E. coli , Salmonella , S. aureus and L. plantarum decreased by 3, 3, 4, and 5 orders of magnitude, respectively. Cell apoptosis accompanied loss of membrane integrity and permeability, inhibition of lactate dehydrogenase activity and disruption of organic acid metabolism. Gram-positive bacteria (S. aureus and L. plantarum) were more susceptible to those effects of EOM than Gram-negative bacteria (E. coli and Salmonella). It also demonstrates that in applications as preservatives for probiotic foods requiring live L. plantarum , EOM comprising cinnamon, peppermint or lemon EO should be avoided. [Display omitted] • Microcapsules comprised cinnamon, peppermint and lemon essential oil. • Gelatin/chitosan encapsulated the essential oil. • The microcapsules exhibited good physicochemical and antibacterial properties. • Antibacterial assessment included Lactobacillus plantarum and other bacteria. [ABSTRACT FROM AUTHOR]

SNAREs (soluble N‐ethylmaleimide‐sensitive factor attachment protein receptors) facilitate docking and fusion of vesicles with their target membranes, playing a crucial role in vesicle trafficking and exocytosis. However, the spatial assembly and roles of plasma membrane (PM)‐associated SNAREs in phytopathogen development and pathogenicity are not clearly understood. In this study, we analysed the roles and molecular mechanisms of PM‐associated SNARE complexes in the banana Fusarium wilt fungus Fusarium oxysporum f. sp. cubense tropical race 4 (FocTR4). Our findings demonstrate that FocSso1 is important for the fungal growth, conidiation, host penetration and colonization. Mechanistically, FocSso1 regulates protein secretion by mediating vesicle docking and fusion with the PM and hyphal apex. Interestingly, a FocSso1–FocSec9–FocSnc1 complex was observed to assemble not only at the fungal PM but also on the growing hyphal apex, facilitating exocytosis. FocSso2, a paralogue of FocSso1, was also found to form a ternary SNARE complex with FocSec9 and FocSnc1, but it mainly localizes to the PM in old hyphae. The functional analysis of this protein demonstrated that it is dispensable for the fungal growth but necessary for host penetration and colonization. The other subunits, FocSec9 and FocSnc1, are involved in the fungal development and facilitate host penetration. Furthermore, FocSso1 and FocSnc1 are functionally interdependent, as loss of FocSso1 leads to mis‐sorting and degradation of FocSnc1 in the vacuole and vice versa. Overall, this study provides insight into the formation of two spatially and functionally distinct PM SNARE complexes and their involvement in vesicle exocytosis to regulate development and pathogenicity of FocTR4. [ABSTRACT FROM AUTHOR]

[Display omitted] • CoP x -implanted N-doped carbon dodecahedrons are rationally designed and constructed. • CoP x @NC/PMS system exhibits excellent catalytic activity for TC degradation. • Non-radical pathway dominates CoP x @NC/PMS system for TC degradation. • This is the first time to demonstrate the charge imbalance strategy for PMS activation. Development of a new catalytic system with synergistic multiple active sites to effectively promote the activation of peroxymonosulfate (PMS) is crucial for the control of emerging organic pollutants in water, but it is still challenging. Herein, we explore robust CoP x -implanted porous N-doped carbon frameworks (CoP x @NC) to effectively activate PMS and eliminate tetracycline (TC). The cobalt phosphides in CoP x @NC spontaneously create the distinctive charge imbalance to form asymmetrically charged Coδ+ and Pδ− as dual active sites to efficiently enhance catalytic activity, while the positively polarized carbon induced by neighboring electronegative N atoms in CoP x @NC contributes to high catalytic efficiency in parallel. As an advanced catalyst, CoP x @NC displays excellent catalytic performances in PMS activation toward efficient TC degradation with an improved rate constant of 0.137 min−1 and a favorable k-value of 1.43 μmol s−1 g−1. Mechanistic analysis clearly unveils that the non-radical pathway (singlet oxygen 1O 2 and direct electron transfer) in CoP x @NC/PMS system dominantly governs the TC degradation along with cooperative radical (SO 4 ·− and ·OH) pathway. This study enriches the charge imbalance strategy for catalyst design and highlights a new catalytic platform to activate PMS for efficient pollutant degradation in water. [ABSTRACT FROM AUTHOR]

Using data from a nationally representative survey of U.S. adults, this study explores how trust in key actors to responsibly manage artificial intelligence (AI) develops among members of the U.S. population and how trust, along with other key factors, shapes public attitudes toward AI. Greater trust is linked to stronger support for AI, both directly and indirectly (through risk and benefit perceptions). Furthermore, the strength or direction of the link between trust and support—as well as media diets and trust—differs significantly for liberals and conservatives, suggesting that Americans are indeed beginning to process AI-related information through a political lens. [ABSTRACT FROM AUTHOR]

• A new type of cross-laminated bamboo and timber, consisting of flattened bamboo boards and fast-growing timber was prepared. • The effect of the number of layers of the flattened bamboo board on the engineering performance of CLBT was investigated. • A finite element model based on the Tsai-Wu failure criterion was used to predicting the bending performance of CLBT. Bamboo-wood composites are effective for utilizing the mechanical properties of bamboo and fast-growing wood resources. Investigation the application of flattened bamboo in engineering structures provides added value to bamboo resources. This paper analyzes the flatwise bending and shear properties of cross-laminated bamboo and timber (CLBT) panels consisting of flattened bamboo boards and Chinese fir lumber. A three-layer cross-laminated timber (CLT) panel made from Chinese fir lumber was used for comparison. The mechanical properties of the CLBT and CLT panels in the major strength direction were obtained through experimental tests, and theoretical and finite element models were developed to predict the panels' bending stiffness and strength. The calculated values were compared with the experimental data. The results showed that the failure modes of the three groups of CLBT panels were similar to those of the CLT panel and were predominantly rolling shear and bonding delamination. The bending strength and modulus of the CLBT were higher than that of the CLT. Increasing the number of layers of the flattened bamboo board improved the maximum bending moment and bending stiffness of the CLBT. The bending stiffness and strength of the CLBT/CLT obtained from the finite element model were in better agreement with the static test values than the theoretical model values. The results of this study provie new information for future engineering applications and the structural design of CLBT. [ABSTRACT FROM AUTHOR]

Today, in the construction of smart city, the development of self-driving technology plays the key role. The explosion of convolutional neural network (CNN) technology has made it possible to utilize end-to-end tasks with images. However, today's CNN has deeper, more accurate characteristics. If we do not improve the calculation method to reduce the number of network parameters, this feature makes it very difficult for us to run neural network computing in small devices. In this paper, we further optimize the network computing methods based on MobileNets to reduce number of network parameters. At the same time, in the network structure, we add BatchNormalization and Swish activation function. We designed our own network in the end-to-end prediction for steering angle in the self-driving car task. From the final simulation results, our neural network's storage space can be reduced and the execution speed of neural network can be improved while maintaining the accuracy of the neural network. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ni nanoparticles-loaded porous N-doped carbon are rationally constructed. • Efficient hydrogenation reduction of Cr(VI) in Ni@NC/FA system is realized. • Experimental identification of H species in FA-mediated Cr(VI) reduction is performed. • Ni–H ads * and ·H radical species in Ni@NC/FA system contribute to Cr(VI) reduction. • Cr(VI) reduction mechanism in Ni@NC/FA system is preferentially proposed. Catalytic hydrogenation via formic acid (FA) activation is an important way for the control of Cr(VI)-contaminated water. In the present study, three-dimensional porous N-doped carbon nanostructures loaded with quasi-spherical Ni nanoparticles (Ni@NC) are rationally prepared by a facile carbonization strategy and developed as a robust catalyst to effectively activate FA for hydrogenation reduction conversion of Cr(VI) to Cr(III). Such carbon nanostructures with large specific surface areas and abundant mesopores not only protect the anchored Ni nanoparticles from poisoning, but also coordinate with Ni nanoparticles to diversify active sites, significantly promoting Cr(VI) reduction efficiency. The optimal Ni@NC catalyst presents the excellent activity for catalytic FA activation and achieves high-efficiency Cr(VI) reduction, delivering the enhanced rate constant of 0.059 min−1 and favorable k-value of 3.15 μmol s−1 g−1, attributing to collaborative cooperation of high-electron-density Ni sites and self-polarized NC. More importantly, the Ni@NC catalyst exhibits robust tolerance of coexisting ions and good reusability for Cr(VI) reduction in acidic environment. Spectroscopic analysis and electrochemical evaluation unveil the critical role of the surface-bonded Ni–H ads * species and hydrogen radicals (·H) in-situ generated in Ni@NC/FA system for hydrogenation reduction of Cr(VI). [ABSTRACT FROM AUTHOR]

A major challenge in applying Model Predictive Control (MPC) to building automation and control (BAC) is the development of a simplified mathematical model of the building for real-time control with fast response times. However, building models are highly complex due to nonlinearities in heat and mass transfer processes of the building itself and the accompanying air-conditioning and mechanical ventilation systems. This paper proposes a method to develop an integrated state-space model (SSM) for indoor air temperature, radiant temperature, humidity and Predicted Mean Vote (PMV) index suitable for fast real-time multiple objectives optimization. Using the model, a multi-objective MPC controller is developed and its performance is evaluated through a case study on the BCA SkyLab test bed facility in Singapore. The runtime of the MPC controller is less than 0.1 s per optimization, which is suitable for real-time BAC applications. Compared to the conventional ON/OFF control, the MPC controller can achieve up to 19.4% energy savings while keeping the PMV index within the acceptable comfort range. When the MPC controller is adjusted to be thermal-comfort-dominant that achieves a neutral PMV index at most office hours, the system can still bring about 6% in energy savings as compared to the conventional ON/OFF control. [ABSTRACT FROM AUTHOR]

Given a set of facilities and a set of users, a reverse nearest neighbors (RNN) query retrieves every user $u$ for which the query facility $q$ is its closest facility. Since $q$ is the closest facility to $u$ , the user $u$ is said to be influenced by $q$ . In this paper, we propose a relaxed definition of influence where a user $u$ is said to be influenced by not only its closest facility but also every other facility that is almost as close to $u$ as its closest facility is. Based on this definition of influence, we propose reverse approximate nearest neighbors (RANN) queries. Formally, given a value $x>1$ , an RANN query $q$ returns every user $u$ for which $dist(u,q) \leq x\times NNDist(u)$ where $NNDist(u)$ denotes the distance between a user $u$ and its nearest facility, i.e., $q$ is an approximate nearest neighbor of $u$ . In this paper, we study both snapshot and continuous versions of RANN queries. In a snapshot RANN query, the underlying data sets do not change and the results of a query are to be computed only once. In the continuous version, the users continuously change their locations and the results of RANN queries are to be continuously monitored. Based on effective pruning techniques and several non-trivial observations, we propose efficient RANN query processing algorithms for both the snapshot and continuous RANN queries. We conduct extensive experiments on both real and synthetic data sets and demonstrate that our algorithm for both snapshot and continuous queries are significantly better than the competitors. [ABSTRACT FROM PUBLISHER]

Two-dimensional (2D) Ruddlesden-Popper hybrid organic-inorganic perovskites are the most promising candidates for highly efficient optoelectronic devices due to their remarkable exciton characteristics, adjustable band structure and long-term environmental stability. However, excitons emission behavior of 2D Ruddlesden-Popper perovskites is still unclear. Here we theoretically-experimentally decoupled the excitons behavior in 2D Ruddlesden-Popper PEA 2 PbI 4 nanosheets. Theoretically, the Elliott theory was used to separate exciton and band edge absorptions of PEA 2 PbI 4 nanosheets and determine an exciton binding energy of about 274 meV. Experimentally, spectral-dependent photoluminescence lifetime and excitation powder density-dependent photoluminescence spectra revealed that a distinct photoluminescence tail emission should be derived from localized excitons with lower emission energy than free excitons. Further, the luminescent component of the free excitons and localized excitons with their corresponding densities of states was theoretically decoupled by line-shape analysis of PEA 2 PbI 4 nanosheets photoluminescence spectra, which is consistent with the experimental results demonstrating the existence of localized excitons. Hence, our work provides understanding on the exciton behavior and luminescence mechanism of 2D Ruddlesden-Popper perovskites, which would benefit the prediction of high-performance excitonic devices based on 2D Ruddlesden-Popper perovskites. • Excitons behavior in 2D Ruddlesden-Popper PEA 2 PbI 4 nanosheets was decoupled. • A band tail state emission derived from localized excitons. • The luminescent component of the free excitons and localized excitons was separated. [ABSTRACT FROM AUTHOR]

This study examined the effectiveness of using comics to communicate scientific information on COVID-19 vaccine safety to Black Americans. Although the effects of comics on interest, recall, and information sharing intention were not significant compared to expository texts and infographics, comics featuring abstract, racially ambiguous characters facilitated greater learning among participants with lower knowledge of COVID-19 vaccines, as opposed to comics with realistic representations of Black individuals. Furthermore, the effects of comics varied depending on individuals' interest in comic reading. These findings highlight the potential of comics in science communication, but their design and target audience should be carefully considered. [ABSTRACT FROM AUTHOR]

• An MPC framework for space heating system with PCM-based active latent heat storage. • A linear, high-fidelity active latent heat storage model for fast building control. • Highly dynamic electricity prices considered for demand-responsive building control. • The MPC approach reduces electricity costs for space heating by 53.2% to 122.7% • A good synergy between the MPC approach and active latent heat storage is observed. Active latent heat storage (ALHS) involving phase-change materials constitutes a promising energy-efficient solution for building energy management (BEM) by reshaping building energy demands without occupant comfort degradation. Current BEM systems based on conventional reactive control lack the level of control delicacy required to exploit the full potential of ALHS for BEM under certain conditions, such as highly dynamic electricity prices. This study proposes a smart model predictive control (MPC) approach for BEM to minimize the energy cost while maintaining the indoor climate by fully applying ALHS. More specifically, a reduced-order, high-fidelity state-space model (SSM) of ALHS is proposed for fast building control. An MPC framework considering highly dynamic electricity prices and ALHS dynamics is developed based on the proposed ALHS SSM integrated with a building SSM. A case study entailing a set of simulations is designed based on a single-family house with a space heating system, including an ALHS, ground source heat pump, and radiator. The proposed MPC approach, compared to conventional reactive control, enables substantial reductions in the electricity cost (ranging from 53.2% to 122.7% depending on the MPC settings and ALHS capacity), even financial gains under certain scenarios. Further analysis reveals that coupling ALHS with MPC is critical to ensure that ALHS adoption is economically convincing: while conventional reactive control of an ALHS-equipped building increases the electricity cost, an MPC-enabled building could reduce the electricity cost by 45.1% due to ALHS adoption. The proposed MPC approach also exhibits promising feasibility for real-world BEM applications. [ABSTRACT FROM AUTHOR]

• Edge-oriented MoS 2 nanosheets deposited on layered Ti 3 C 2 is achieved. • MoS 2 /Ti 3 C 2 exhibits the excellent performance for 4-NP and MB reduction. • MoS 2 /Ti 3 C 2 shows promising as cost-effective, efficient and reusable catalyst. • Charge transfer between MoS 2 and Ti 3 C 2 is demonstrated and favorable for catalysis reaction. [Display omitted] In this work, we report a simple one-step hydrothermal synthesis strategy for depositing edge-rich MoS 2 nanosheets on conductive layered Ti 3 C 2 MXene, and demonstrate the formed MoS 2 /Ti 3 C 2 heterostructure has significant active site exposure and effective charge carrier flow. The resulting MoS 2 /Ti 3 C 2 exhibits enhanced activity and excellent stability for the catalytic reduction of 4-nitrophenol (4-NP). The optimal MoS 2 /Ti 3 C 2 catalyst displays a high pseudo-first-order rate constant of 0.61 min−1, a conversion efficiency of 96.2% within 5 min and almost unchanged activity after six consecutive reaction cycles, which is better than the pristine MoS 2 nanosheets. Moreover, the MoS 2 /Ti 3 C 2 catalyst achieves a pseudo-first-order rate constant as high as 0.779 min−1 for the catalytic reduction of methylene blue (MB). This study opens up new opportunities for the design and development of cost-effective, efficient and reusable alternatives to noble metal catalysts based on molybdenum disulfide for environmental applications. [ABSTRACT FROM AUTHOR]

• A machine learning-based model predictive control with instantaneous linearization. • The instantaneous linearization linearizes the machine learning models recurrently. • The proposed control is implemented in an office for air-conditioning control. • The proposed control achieves 26% energy savings with better thermal comfort. • The proposed control is 70 times faster than nonlinear model predictive control. Machine-learning (ML) –based building models have been gaining popularity in constructing model predictive control (MPC) for building energy management applications. However, ML-based building models are usually nonlinear so to capture the building dynamics, leading to high computation load for MPC, prohibiting its application for real-time building control. This study proposes a ML-based MPC with an instantaneous linearization (IL) scheme, which employs real-time building operation data to linearize the nonlinear ML-based building model for constructing a linear MPC at each control interval. The proposed ML-based MPC with IL system is implemented to control an air conditioning system in an office of a general hospital building located in Singapore for experimental evaluation of its control performance. The ML-based MPC with IL is compared to a ML-based MPC that directly uses a nonlinear ML-based building model and the original reactive-control-based thermostat of the office. Results show that the ML-based MPC with IL significantly reduced the computation time (by more than 70 times) as compared to the ML-based MPC while retained most of the advantages of the ML-based MPC. The ML-based MPC with IL and the ML-based MPC achieved 31.6% and 26.0% reductions, respectively, in cooling energy consumption as compared to the original thermostat. Meanwhile, both the MPC systems significantly improved indoor thermal comfort for the office as compared to the original thermostat. The study demonstrated that using IL for ML-based MPC could substantially improve computation efficiency with no obvious performance degradation in terms of thermal comfort and energy saving. [ABSTRACT FROM AUTHOR]

• A model predictive control for coordinated control of multiple building services. • A hybrid model for predicting indoor visual comfort and lighting power. • The model predictive control is experimentally implemented in a test facility. • The model predictive control reduced 15.1–20.7% of building energy consumption. Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting the building's overall energy inefficiency and occupant comfort. A model predictive control (MPC) system that features a multi-objective MPC scheme to enable coordinated control of multiple building services for overall optimized energy efficiency, indoor thermal and visual comfort, as well as a hybrid model for predicting indoor visual comfort and lighting power is proposed. The MPC system was implemented in a test facility having two identical, side-by-side experimental cells to facilitate comparison with a building management system (BMS) employing conventional reactive feedback control. The MPC system coordinated the control of the ACMV, dynamic façade and automated dimmable lighting systems in one cell while the BMS controlled the building services in the other cell in a conventional manner. The MPC side achieved 15.1–20.7% electricity consumption reduction, as compared to the BMS side. Simultaneously, the MPC system improved indoor thermal comfort by maintaining the room within the comfortable range (−0.5 < predicted mean vote < 0.5) for 98.3% of the time, up from 91.8% of the time on the BMS side. Visual comfort, measured by indoor daylight glare probability (DGP) and horizontal illuminance level at work plane height, was maintained for the entire test period on the MPC side, improving from having visual comfort for 94.5% and 85.7% of the time, respectively, on the BMS side. [ABSTRACT FROM AUTHOR]

Efficient and controllable release of hydrogen from solid hydrogen storage materials is a promising way to produce hydrogen safely and on-demand. The development of economical, highly active, easily recyclable catalysts is critical for practical applications, which remains a great challenging. Herein, the easily controllable and cost-effective corrosion strategy is ingeniously developed to simply prepare ultralow-content ruthenium coupled with nickel hydroxide on nickel foam (Ru–Ni–NF). After experiencing the spontaneous oxidation-reduction reactions between the reactive NF and Ru3+, ultrafine Ru nanoparticles decorated nickel hydroxide nanosheets are in situ intimately grown on porous NF networks. The optimal Ru–Ni–NF catalyst exhibits the excellent performance for catalytic hydrolysis of ammonia borane with a high turnover frequency (TOF) of 539.6 mol H2 mol Ru −1 min−1 at 298 K and a low apparent activation energy of 36.4 kJ mol−1, due to the synergistic effect between Ru nanoparticles and nickel hydroxide nanosheets. Furthermore, the Ru–Ni–NF catalyst possesses easy separation and outstanding durability, which is superior to powdered catalysts. This study provides a facile and economical strategy for the preparation of ultralow-content noble metal supported metal foam-type catalysts for dehydrogenation of ammonia borane. • A cost-effective corrosion strategy is ingeniously developed to prepare Ru–Ni–NF. • Ultralow-content ruthenium coupled with nickel hydroxide on NF is achieved. • Ru–Ni–NF catalyst displays highly activity for catalytic hydrolysis of ammonia borane. • The optimal catalyst shows a high TOF value of 539.6 mol H2 mol Ru −1 min−1 at 298 K. • The Ru–Ni–NF catalyst possesses easy separation and outstanding durability. [ABSTRACT FROM AUTHOR]

Objective: The goal of the present study was to investigate the correlation between serum 25-hydroxyvitamin D [25(OH)D] levels and disease remission in Takayasu arteritis (TAK) patients. Methods: This retrospective study included 59 patients in the study group and 80 patients in the validation cohort with TAK. After 6 months of therapy, patients were re-evaluated, and serum 25(OH)D levels were compared before and after treatment. Correlations between changes in 25(OH)D levels and changes in disease activity scores (NIH, ITAS2010, ITAS.A) were analyzed. Additionally, a predictive cut-off value for disease remission was determined. Results: After 6 months of therapy, serum 25(OH)D levels in TAK patients significantly increased compared to baseline [(18.33 ± 7.25)µg/L vs (11.77 ± 4.14) µg/L] (P < 0.001). Positive correlations were observed between the increasing changes in the 25(OH)D level and the decreasing changes in the reduced NIH, ITAS2010, and ITAS.A scores (r = 0.455, P < 0.001; r = 0.495, P < 0.001; and r = 0.352 P = 0.006, respectively). A change of 8.45 µg/L in 25(OH)D level was identified as the predictive cut-off value for TAK remission (sensitivity 54.1%, specificity 90.9%, area under the curve = 0.741). Similarly for patients with normal baseline ESR, sensitivity is 68.0%, specificity is 92.3%, and area under the curve is 0.831, and for patients with normal baseline CRP, sensitivity is 58.3%, specificity is 90.0%, and area under the curve is 0.748. Validation in an additional 80 patients demonstrated a higher remission rate in those with a 25(OH)D level change > 8.45 µg/L. Conclusion: Serum 25(OH)D levels significantly increased after treatment in TAK patients, and an increase of ≥ 8.45 µg/L was predictive of disease remission, especially in individuals with normal baseline ESR and/or CRP levels. Key Points • Following treatment, there was a significant increase in serum 25(OH)D levels among TAK patients. • The elevated changes in 25(OH)D levels before and after treatment demonstrated a positive correlation with the reduction in disease activity scores. • In patients with TAK before and after treatment, an elevation in serum 25(OH)D levels exceeding 8.45 µg/L serves as an indicator for disease remission, particularly prominent in individuals with normal baseline ESR and/or CRP levels. [ABSTRACT FROM AUTHOR]

• Proposed an approximate model predictive control for building energy management. • The proposed control is based on a dynamic feedback machine learning model. • The proposed control is experimentally implemented in two test buildings. • The proposed control achieves up to 52% reduction of cooling energy. • The proposed control is more than 100% faster than common model predictive control. The adoption of model predictive control (MPC) for building automation and control applications is challenged by the high hardware and software requirements to solve its optimization problem. This study proposes an approximate MPC that mimics the dynamic behaviours of MPC using the recurrent neural network with a structure of nonlinear autoregressive network with exogenous inputs. The approximate MPC is developed by learning from the measured operation data of buildings controlled by MPC, therefore it can produce MPC-like control for buildings without needing to solve the optimization problem, significantly reducing the computation load as compared to MPC. The proposed approximate MPC is implemented in two testbeds, an office and a lecture theatre, to control the air-conditioning systems. The control performance of the approximate MPC is compared to MPC as well as the original reactive control of the two testbeds. The approximate MPC retained most of the energy and thermal comfort performance of MPC in both testbeds. For the office, the MPC and approximate MPC reduced 58.5% and 51.6% of cooling energy consumption, respectively, as compared to the original control. For the lecture theatre, the MPC and approximate MPC reduced 36.7% and 36.2% of cooling energy consumption, respectively, as compared to the original control. Meanwhile, both approximate MPC and MPC significantly improved indoor thermal comfort in the two testbeds as compared to their original control. Despite having minor degradation in control performance the approximate MPC was more than 100 times faster than MPC in generating optimal control commands in each time step. [ABSTRACT FROM AUTHOR]

This article links the redevelopment of urban villages in China to the discourse on incremental housing schemes. Urban villages, due to the less regulated and more informal aspect of China's rapid urbanisation, house a large share of the migrant population. Current urban village redevelopment debates focus on state-initiated redevelopment, which involves large-scale demolitions and has become the norm in Beijing. The aim of this article is to make visible an alternative, village-initiated approach to redevelopment that is managed by the local village committee and that allows for incrementality and flexibility in a long-term transformation. This research traces the redevelopment process and subsequent transformation of Maquanying village over a period of more than 20 years. It focuses on the related decision-making and negotiation processes, and on socio-spatial changes during this time. In the context of the debate on incremental housing, the Maquanying approach can be understood as a locally initiated sites-and-services scheme within the Chinese environment. Both indigenous villagers and migrants are included and compared with other urban villages, higher standards of housing are delivered. The article argues that the redevelopment principles and strategies embedded in this approach can be transferred to other urban villages in China. [ABSTRACT FROM AUTHOR]

• A multi-objective model predictive control for real-time building control. • A continuous building model adaption scheme using machine learning. • A hybrid optimizer to solve the nonlinear multi-objective optimization problem. • Experimental evaluation of control performance in an office and a lecture theatre. • The model predictive control achieves 36–58% energy savings in the two testbeds. A model predictive control system with adaptive machine-learning-based building models for building automation and control applications is proposed. The system features an adaptive machine-learning-based building dynamics modelling scheme that updates the building model regularly using online building operation data through a dynamic artificial neural network with a nonlinear autoregressive exogenous structure. The system also employs a multi-objective function that could optimize both energy efficiency and indoor thermal comfort, two often contradicting demands. The proposed model predictive control system is implemented to control the air-conditioning and mechanical ventilation systems in two single-zone testbeds, an office and a lecture theatre, located in Singapore for experimental evaluation of its control performance. The model predictive control system is compared against the original reactive control system (thermostat in the office and building management system in the lecture theatre) in each testbed. The model predictive control system reduces 58.5% cooling thermal energy consumption in the office and 36.7% cooling electricity consumption in the lecture theatre, as compared to their respective original control. Meanwhile, the indoor thermal comfort in both testbeds is also greatly improved by the model predictive control system. Developing a model predictive control system using machine-learning-based building dynamics models could largely cut down the model construction time to days as compared to its counterpart using physics-based models, which usually take months to construct. However, the machine-learning-based modelling approach could be challenged by lack of building operational data necessary for model training in case of model predictive control development before the building has become operational. [ABSTRACT FROM AUTHOR]

• A MPC for an air-conditioning system with dedicated outdoor air system is developed. • The MPC employs a linear building model to optimise energy use and indoor comfort. • The system is demonstrated experimentally in a lecture theatre for real-time control. • The MPC system achieves 20% energy saving while greatly improves indoor environment. Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separate sensible and latent cooling (SSLC) systems. However, a sophisticated control technique is needed to coordinate the control of multiple cooling coils in such systems. This paper presents a novel model predictive control (MPC) developed for a DOAS-assisted SSLC system. The MPC adopts a linear state-space model that captures building thermodynamics, thermal comfort and ACMV for building response prediction and optimization. Subsequently, a multi-objective cost function is employed to optimize energy use and thermal comfort while fulfilling constraints of predicted mean vote (PMV) (-0.5, 0.5) and relative humidity (0%, 65%) in buildings. The performance of the MPC for controlling a conventional single-coil air-handling unit (AHU) system and a DOAS-assisted SSLC system is experimentally investigated and compared to a conventional feedback-control-based building management system (BMS). The MPC system achieved 18% and 20% electricity savings for the single-coil AHU and DOAS-assisted SSLC, respectively, as compared to the BMS controlled single-coil AHU. Furthermore, indoor thermal comfort is significantly improved, compared to the BMS. DOAS-assisted SSLC is shown to be advantageous compared to single-coil AHU to achieve better indoor environment in terms of thermal comfort and humidity, when both systems are controlled by MPC. [ABSTRACT FROM AUTHOR]

Active chilled beams (ACB) are gaining popularity worldwide as a potentially energy-efficient air-conditioning technology for buildings. However, the control of ACB system is challenging, as it needs to handle multiple cooling coils and the relatively slow response to cooling load dynamics. This paper reports the implementation of a model predictive control (MPC) system for an ACB system, which employs a linear white-box building model for building energy and indoor condition predictions. A multiple-objectives function is employed in the MPC controller to optimize the energy efficiency in air-conditioning system and indoor thermal comfort while fulfilling the constraints of indoor comfort range (−0.5 < PMV < 0.5). The MPC controller was implemented in the BCA SkyLab test facility in Singapore. The control characteristics and performance of the MPC controller in controlling a conventional fan coil unit (FCU) and an ACB system were investigated experimentally. A conventional feedback control based building management system (BMS) originally installed in the SkyLab test facility was employed as a reference for comparison with the MPC controller. Compared to the original BMS, the MPC controller achieved 14.7% and 20% electricity savings for the conventional FCU and ACB systems, respectively. The MPC controller also kept the indoor PMV within acceptable thermal comfort range at all time. This study demonstrated the real-time multi-objectives optimization capability of the MPC controller in enhancing the performance of ACMV systems. [ABSTRACT FROM AUTHOR]

Background: Cancer cells undergo global reprogramming of cellular metabolism to satisfy demands of energy and biomass during proliferation and metastasis. Computational modeling of genome-scale metabolic models is an effective approach for designing new therapeutics targeting dysregulated cancer metabolism by identifying metabolic enzymes crucial for satisfying metabolic goals of cancer cells, but nearly all previous studies neglect the existence of metabolic demands other than biomass synthesis and trade-offs between these contradicting metabolic demands. It is thus necessary to develop computational models covering multiple metabolic objectives to study cancer metabolism and identify novel metabolic targets. Methods: We developed a multi-objective optimization model for cancer cell metabolism at genome-scale and an integrated, data-driven workflow for analyzing the Pareto optimality of this model in achieving multiple metabolic goals and identifying metabolic enzymes crucial for maintaining cancer-associated metabolic phenotypes. Using this workflow, we constructed cell line-specific models for a panel of cancer cell lines and identified lists of metabolic targets promoting or suppressing cancer cell proliferation or the Warburg Effect. The targets were then validated using knockdown and over-expression experiments in cultured cancer cell lines. Results: We found that the multi-objective optimization model correctly predicted phenotypes including cell growth rates, essentiality of metabolic genes and cell line specific sensitivities to metabolic perturbations. To our surprise, metabolic enzymes promoting proliferation substantially overlapped with those suppressing the Warburg Effect, suggesting that simply targeting the overlapping enzymes may lead to complicated outcomes. We also identified lists of metabolic enzymes important for maintaining rapid proliferation or high Warburg Effect while having little effect on the other. The importance of these enzymes in cancer metabolism predicted by the model was validated by their association with cancer patient survival and knockdown and overexpression experiments in a variety of cancer cell lines. Conclusions: These results confirm this multi-objective optimization model as a novel and effective approach for studying trade-off between metabolic demands of cancer cells and identifying cancer-associated metabolic vulnerabilities, and suggest novel metabolic targets for cancer treatment. [ABSTRACT FROM AUTHOR]

Love as an important part of human emotion has been depicted in literature, folklore, and art since ancient China. However, in archaeological settings, direct skeletal evidence for love is rare. A joint burial from North Wei Dynasty (386–534 CE) was reported, in which skeletons of an adult male and an adult female were found placed in loving embrace posture with a ring in situ on the left ring finger of the female, displaying the desire for eternal love of the couple, and the respect to their love by people who buried them as well. It is likely that the wife sacrificed herself to be buried with her dead husband, though other scenarios could not be ruled out. The free expression and active pursuit of love in Chinese culture became prominent during the first millennium. This funerary practice might have been influenced by the customs from the Western Regions and beyond through the Silk Roads and the Sinicization and assimilation of the Xianbei people. This discovery is a unique display of human emotion of love in a burial, offering a rare glimpse people's views towards love, life, death, and afterlife in northern China during a time of intense cultural and ethnic exchange. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence-based algorithms for the curation of news content by social media platforms like Facebook and Twitter has upended the gatekeeping role long held by traditional news outlets. This has caused some US policymakers to argue that platforms are skewing news diets against them, and such claims are beginning to take hold among some voters. In a nationally representative survey experiment, we explore whether traditional models of media bias perceptions extend to beliefs about algorithmic news bias. We find that partisan cues effectively shape individuals' attitudes about algorithmic news bias but have asymmetrical effects. Specifically, whereas in-group directional partisan cues stimulate bias perceptions for members of both parties, Democrats, but not Republicans, also respond to out-group cues. We conclude with a discussion about the implications for the formation of attitudes about new technologies and the potential for polarization. [ABSTRACT FROM AUTHOR]

IRF1 is a tumor suppressor gene in colon cancer. This study aimed to explore the potential regulation of IRF1 on the ferroptosis of colon cancer and the mechanisms underlying its regulation of GPX4 transcription. IRF1 interacting transcription factors regulating GPX4 transcription were predicted and validated. The role of the IRF1/SPI1-GPX4 axis on the ferroptosis of colon cancer cells was explored. Results showed that IRF1 overexpression reduced GPX4 transcription, increased reactive oxygen species (ROS) and lipid ROS accumulation, and enhanced erastin-induced colon cancer cell growth in vitro and in vivo. SPI1 could directly bind to the GPX4 promoter (−414 to −409) and activate its transcription. IRF1 could bind to SPI1 and suppress its transcriptional activating effects on GPX4 expression. SPI1 overexpression reduced ROS and lipid ROS accumulation and increased colon cancer cell viability and colony formation upon erastin induction. These trends were reversed by IRF1 overexpression. In conclusion, this study revealed a novel oncogenic mechanism of SPI1 by reducing erastin-induced ferroptosis in colon cancer. IRF1 interacts with SPI1 and suppresses its transcriptional activating effect on GPX4 expression. Through this mechanism, IRF1 can enhance erastin-induced ferroptosis of colon cancer. The IRF1/SPI1-GPX4 axis might play a crucial role in modulating ferroptosis in colon cancer and might serve as a potential therapeutic target in the future. [ABSTRACT FROM AUTHOR]

Thoracic aortic aneurysm and dissection (TAAD) is a life-threatening cardiovascular disease with severe extracellular matrix (ECM) remodeling that lacks efficient early stage diagnosis and nonsurgical therapy. A disintegrin and metalloproteinase with thrombospondin motif 7 (ADAMTS-7) is recognized as a novel locus for human coronary artery atherosclerosis. Previous work by us and others showed that ADAMTS-7 promoted atherosclerosis, postinjury neointima formation, and vascular calcification. However, whether ADAMTS-7 is involved in TAAD pathogenesis is unknown. We aimed to explore the alterations in ADAMTS-7 expression in human and mouse TAAD, and investigate the role of ADAMTS-7 in TAAD formation. A case–control study of TAAD patients (N = 86) and healthy participants (N = 88) was performed. The plasma ADAMTS-7 levels were markedly increased in TAAD patients within 24 h and peaked in 7 days. A TAAD mouse model was induced with 0.5% β-aminopropionitrile (BAPN) in drinking water. ELISA analysis of mouse plasma, Western blotting, and immunohistochemical staining of aorta showed an increase in ADAMTS-7 in the early stage of TAAD. Moreover, ADAMTS-7-deficient mice exhibited significantly attenuated TAAD formation and TAAD rupture-related mortality in both male and female mice, which was accompanied by reduced artery dilation and inhibited elastin degradation. ADAMTS-7 deficiency caused repressed inflammatory response and complement system activation during TAAD formation. An increase in plasma ADAMTS-7 is a novel biomarker for human TAAD. ADAMTS-7 deficiency attenuates BAPN-induced murine TAAD. ADAMTS-7 is a potential novel target for TAAD diagnosis and therapy. Key messages: A case-control study revealed increased plasma ADAMTS-7 is a risk factor for TAAD. ADAMTS-7 was elevated in plasma and aorta at early stage of mouse TAAD. ADAMTS-7 knockout attenuated mouse TAAD formation and mortality in both sexes. [ABSTRACT FROM AUTHOR]

Background: The metalloprotease ADAMTS-7 (a disintegrin and metalloproteinase with thrombospondin type 1 motif 7) is a novel locus associated with human coronary atherosclerosis. ADAMTS-7 deletion protects against atherosclerosis and vascular restenosis in rodents. Methods: We designed 3 potential vaccines consisting of distinct B cell epitopic peptides derived from ADAMTS-7 and conjugated with the carrier protein KLH (keyhole limpet hemocyanin) as well as aluminum hydroxide as an adjuvant. Arterial ligation or wire injury was used to induce neointima in mice, whereas ApoE -/- and LDLR -/- (LDLR [low-density lipoprotein receptor]) mice fed a high-fat diet were applied to assess atherosclerosis. In addition, coronary stent implantation was performed on vaccine-immunized Bama miniature pigs, followed by optical coherence tomography to evaluate coronary intimal hyperplasia. Results: A vaccine, ATS7vac, was screened out from 3 candidates to effectively inhibit intimal thickening in murine carotid artery ligation models after vaccination. As well, immunization with ATS7vac alleviated neointima formation in murine wire injury models and mitigated atherosclerotic lesions in both hyperlipidemic ApoE -/- and LDLR -/- mice without lowering lipid levels. Preclinically, ATS7vac markedly impeded intimal hyperplasia in swine stented coronary arteries, but without significant immune-related organ injuries. Mechanistically, ATS7vac vaccination produced specific antibodies against ADAMTS-7, which markedly repressed ADAMTS-7–mediated COMP (cartilage oligomeric matrix protein) and TSP-1 (thrombospondin-1) degradation and subsequently inhibited vascular smooth muscle cell migration but promoted re-endothelialization. Conclusions: ATS7vac is a novel atherosclerosis vaccine that also alleviates in-stent restenosis. The application of ATS7vac would be a complementary therapeutic avenue to the current lipid-lowering strategy for atherosclerotic disease. [ABSTRACT FROM AUTHOR]

As a biometric trait, finger vein pattern-based technology is highly effective for personal identification with high security. In this paper, we presented the design of a personal identification system based on near infrared (NIR) finger vein image. In this paper, we introduced an observation model of finger vein imaging, upon which a self-adaptive illuminance control algorithm is proposed and integrated into image acquisition hardware. According to the distribution of pixel intensity of the acquired image, the proposed algorithm could automatically adjust the illuminance distribution of lighting: increase the illuminance of lighting, under which the thicker part of finger body is presented and decrease the illuminance of lighting, under which the thinner part of finger body is presented. With this adaptation, the whole finger body could be illuminated appropriately according to its thickness distribution, and the overexposure and underexposure are avoided effectively. An NIR finger vein image database containing 2040 images is established and published in this paper. In the image preprocessing stage, Gabor filters are used to enhance captured raw finger vein images. In our experiment, the identification performance of our system is evaluated using the recognition rate and the margin distribution. A sparse representation-based algorithm is used to calculate the recognition rate and provide data for margin analysis. The results prove the effectiveness of the proposed illuminance control algorithm and the whole system in finger vein-based personal identification. [ABSTRACT FROM AUTHOR]

[Display omitted] • Co-vacancy rich Co 3 O 4 is synthesized by using layered cobalt glycerate as a precursor. • V co -Co 3 O 4 exhibits outstanding catalytic activity for the hydrolysis of ammonia borane. • V co -Co 3 O 4 yields a high hydrogen production rate of 934 mL min−1 g Cat -1. • V co -Co 3 O 4 shows a low activation energy of 32.65 kJ mol−1 for catalytic hydrolysis. Development of efficient and economical non-precious metal catalysts for dehydrogenation of ammonia borane is an important way to store and release hydrogen. Vacancy-engineered defective catalysts with modulated electronic structure allow ideal adsorption and dissociation of reactant molecules for the optimized catalytic activity. In this study, we report a facile synthesis of cobalt-defective Co 3 O 4 (V Co -Co 3 O 4) nanocatalyst by the calcination of layered cobalt glycerate as a key precursor. The stacked cobalt-oxygen sheets and interlayer bound glycerate anions in a layered structure are favorable for introducing cation vacancy during calcination process. The obtained V co -Co 3 O 4 exhibits outstanding catalytic activity for the hydrolysis of ammonia borane, along with a high hydrogen production rate of 934 mL min−1 g Cat -1 and a low activation energy of 32.65 kJ mol−1. The catalytic performance of the V Co -Co 3 O 4 catalyst can be well maintained for consecutive five cycles. The current study establishes a new example of cation vacancy strategy to facilitate the hydrolysis of ammonia borane for hydrogen generation. [ABSTRACT FROM AUTHOR]

The dual-emission ZAISe/ZnS@BSA@MMV QDs were developed via phase transfer and biomimetic strategy for multi-levels imaging. [Display omitted] • The dual-emission QDs with the exciton mission and defect emission was obtained for the first. • The fluorescence tunability of the dual-emission QDs was investigated. • As-prepared QDs could conduct for the noninvasive diagnosis of atherosclerosis. In vitro or in vivo fluorescence imaging based on quantum dots (QDs) has shown promise for the noninvasive diagnosis of atherosclerosis. However, simultaneous in vitro and in vivo imaging remains challenging due to the limitation of the current synthesis method of dual-emission QDs (dual-emitting hybrid QDs, and broad-spectrum emitting QDs). Herein, we fabricate a dual-emission (visible region and near-infrared region emission) QDs (ZAISe/ZnS) via the "bottom to up" method of a quaternary inorganic compound for the foam cells and atherosclerosis plaque imaging simultaneously without the intricate size modulation and the strict optical filter requirements. The oil-soluble ZAISe/ZnS is further encapsulated with bovine serum albumin (BSA) to realize phase transfer and ultimately possess the inflammation-targeting properties via biomimetic treatment with MMV (macrophage-derived micro-vesicle). The results first indicate that the as-constructed ZAISe/ZnS@BSA@MMV could accurately locate the foam cells and conduct long-term imaging of the atherosclerotic plaque, which provides a new strategy for the early and noninvasive diagnosis of atherosclerosis. [ABSTRACT FROM AUTHOR]

Silver nanoparticles (AgNPs) have a wide adjustable absorption range. However, it is highly difficult to synthesize AgNPs with NIR absorption and act as an agent for photodynamic therapy (PDT) and photothermal therapy (PTT). Herein, we have fabricated an integrated agent (Ag@Cu) with broad NIR absorption, which alleviated hypoxia and enhanced reactive oxygen species (ROS), resulting in the improvement of PDT efficacy. The obtained Ag@Cu exhibited relatively mild PTT to alleviate hypoxia by accelerating blood flow in the tumor microenvironment and making more oxygenated hemoglobin reach the tumor microenvironment to provide oxygen, which enhanced the efficiency of PDT. The metal ions-mediated inorganic nanoparticle assembly approach of introducing Cu2+ achieved efficient chemodynamic therapy (CDT), amplifying the intracellular oxidative stress to further enhance the effects of PDT. Significantly, adenosine triphosphate (ATP) and excess glutathione (GSH) in tumor cells can also be depleted by copper ions, enhancing the efficacy of ROS-mediated therapy. Therefore, fabricating functional nanomaterials by highly efficient self-assembly strategies that introduce functional metal ions is a favorable method for multimodal tumor treatment. [ABSTRACT FROM AUTHOR]

Nuclear accidents and decommissioning in the nuclear industry would release a large number of radioactive aerosols which endangers the natural environment and the health of workers. Therefore, there is an urgent need for environment-friendly aerosol suppressants to control and handle environmental pollution problems caused by radioactive aerosols. In this paper, sodium alginate (SA), a type of polyphenol material (TP), and alkyl glycosides (APGs) were selected as the components of the compound aerosol suppressant and the optimal proportion was generated via the method of D-optimal mixture design. Furthermore, the cesium aerosol sedimentation effect of the optimized compound aerosol suppressants was evaluated via sedimentation efficiency, the change in particle concentration cumulative concentration fraction of the cesium aerosol sedimentation process. The results showed that the aerosol sedimentation efficiency was 99.82% which was much higher than nature settlement, 18.6% and water spraying sedimentation, 43.3%. Moreover, after spraying the compound suppressant, it displayed a good effect on settling the cesium aerosol particles with a diameter of less than 1 µm, as the concentration of particles was reduced from 55.49% to 44.53%. Finally, the sedimentation mechanism of the compound aerosol suppressant and cesium aerosol particles, such as the coagulation effect, was analyzed using the particle size distribution. [ABSTRACT FROM AUTHOR]

Polychlorinated biphenyls (PCBs) are endocrine-disrupting chemicals that have been associated with various adverse health conditions. Herein we explored the associations of PCBs with dyslipidemia and further assessed the modification effect of genetic susceptibility and lifestyle factors. Six serum PCBs (PCB-28, 101, 118, 138, 153, 180) were determined in 3845 participants from the Wuhan-Zhuhai cohort. Dyslipidemia, including hyper-total cholesterol (HyperTC), hyper-triglyceride (HyperTG), hyper-low density lipoprotein cholesterol (HyperLDL-C), and hypo-high density lipoprotein cholesterol (HypoHDL-C) were determined, and lipid-specific polygenic risk scores (PRS) and healthy lifestyle score were constructed. We found that all six PCB congeners were positively associated with the prevalence of dyslipidemias, and ΣPCB level was associated with HyperTC, HyperTG, and HyperLDL-C in dose-response manners. Compared with the lowest tertiles of ΣPCB, the odds ratios (95% confidence intervals) in the highest tertiles were 1.490 (1.258, 1.765) for HyperTC, 1.957 (1.623, 2.365) for HyperTG, and 1.569 (1.316, 1.873) for HyperLDL-C, respectively. Compared with those with low ΣPCB, healthy lifestyle, and low genetic risk, participants with high ΣPCB, unfavorable lifestyle, and high genetic risk had the highest odds of HyperTC, HyperTG, and HyperLDL-C. Our study provided evidence that high PCB exposure exacerbated the association of genetic risk and unhealthy lifestyle with dyslipidemia. [Display omitted] ● Total and specific PCBs exposure were associated with increased prevalence of dyslipidemias. ● Individuals with higher genetic risk, higher PCB exposure, and unhealthier lifestyle have higher risk of dyslipidemia. ● High PCB exposure exacerbated the association of genetic risk and unhealthy lifestyle with dyslipidemia. [ABSTRACT FROM AUTHOR]

The structural stability of a network reflects the ability of the network to maintain a sustainable service. As the leave of some users will significantly break network stability, it is critical to discover these key users for defending network stability. The model of k-core, a maximal subgraph where each vertex has at least k neighbors in the subgraph, is often used to measure the stability of a network. Besides, the coreness of a vertex, the largest k such that the k-core contains the vertex, is validated as the "best practice" for measuring the engagement of the vertex. In this paper, we propose and study the collapsed coreness problem: finding b vertices (users) s.t. the deletion of these vertices leads to the largest coreness loss (the total decrease of coreness from every vertex). We prove that the problem is NP-hard and hard to approximate. We show that the collapsed coreness is more effective and challenging than the existing models. An efficient greedy algorithm is proposed with powerful pruning rules. The algorithm is adapted to find the key users within a given time limit. Extensive experiments on 12 real-life graphs demonstrate the effectiveness of our model and the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]