Inner Mongolia University

Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learning algorithms are Convolutional and Deep Neural Networks (CNNs and DNNs), which are known to be both computationally and memory intensive. A number of neural network accelerators have been recently proposed which can offer high computational capacity/area ratio, but which remain hampered by memory accesses. However, unlike the memory wall faced by processors on general-purpose workloads, the CNNs and DNNs memory footprint, while large, is not beyond the capability of the on chip storage of a multi-chip system. This property, combined with the CNN/DNN algorithmic characteristics, can lead to high internal bandwidth and low external communications, which can in turn enable high-degree parallelism at a reasonable area cost. In this article, we introduce a custom multi-chip machine-learning architecture along those lines. We show that, on a subset of the largest known neural network layers, it is possible to achieve a speedup of 450.65x over a GPU, and reduce the energy by 150.31x on average for a 64-chip system. We implement the node down to the place and route at 28nm, containing a combination of custom storage and computational units, with industry-grade interconnects.

Binary transition metal oxides (BTMOs) possess higher reversible capacity, better structural stability and electronic conductivity, and have been widely studied to be novel electrode materials for supercapacitors.

Abstract Demonstrated here is the correlation between atomic configuration induced electronic density of single‐atom Co active sites and oxygen reduction reaction (ORR) performance by combining density‐functional theory (DFT) calculations and electrochemical analysis. Guided by DFT calculations, a MOF‐derived Co single‐atom catalyst with the optimal Co 1 ‐N 3 PS active moiety incorporated in a hollow carbon polyhedron (Co 1 ‐N 3 PS/HC) was designed and synthesized. Co 1 ‐N 3 PS/HC exhibits outstanding alkaline ORR activity with a half‐wave potential of 0.920 V and superior ORR kinetics with record‐level kinetic current density and an ultralow Tafel slope of 31 mV dec −1 , exceeding that of Pt/C and almost all non‐precious ORR electrocatalysts. In acidic media the ORR kinetics of Co 1 ‐N 3 PS/HC still surpasses that of Pt/C. This work offers atomic‐level insight into the relationship between electronic density of the active site and catalytic properties, promoting rational design of efficient catalysts.

Together with the evolution of digital health care, the wearable electronics field has evolved rapidly during the past few years and is expected to be expanded even further within the first few years of the next decade. As the next stage of wearables is predicted to move toward integrated wearables, nanomaterials and nanocomposites are in the spotlight of the search for novel concepts for integration. In addition, the conversion of current devices and attachment-based wearables into integrated technology may involve a significant size reduction while retaining their functional capabilities. Nanomaterial-based wearable sensors have already marked their presence with a significant distinction while nanomaterial-based wearable actuators are still at their embryonic stage. This review looks into the contribution of nanomaterials and nanocomposites to wearable technology with a focus on wearable sensors and actuators.

Cadmium (Cd) is a heavy metal that has received considerable concern environmentally and occupationally. Cd has a long biological half-life mainly due to its low rate of excretion from the body. Thus, prolonged exposure to Cd will cause toxic effect due to its accumulation over time in a variety of tissues, including kidneys, liver, central nervous system (CNS), and peripheral neuronal systems. Cd can be uptaken from the nasal mucosa or olfactory pathways into the peripheral and central neurons; for the latter, Cd can increase the blood brain barrier (BBB) permeability. However, mechanisms underlying Cd neurotoxicity remain not completely understood. Effect of Cd neurotransmitter, oxidative damage, interaction with other metals such as cobalt and zinc, estrogen-like, effect and epigenetic modification may all be the underlying mechanisms. Here, we review the in vitro and in vivo evidence of neurotoxic effects of Cd. The available finding indicates the neurotoxic effects of Cd that was associated with both biochemical changes of the cell and functional changes of central nervous system, suggesting that neurotoxic effects may play a role in the systemic toxic effects of the exposure to Cd, particularly the long-term exposure.

Shedding light: Nitroaromatic compounds on gold nanoparticles (3 wt %) supported on ZrO2 can be reduced directly to the corresponding azo compounds when illuminated with visible light or ultraviolet light at 40 °C (see picture). The process occurs with high selectivity and at ambient temperature and pressure, and enables the selection of intermediates that are unstable in thermal reactions. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

The two-dimensional (2D) magnet, a long-standing missing member in the family of 2D functional materials, is promising for next-generation information technology. The recent experimental discovery of 2D magnetic ordering in CrI3, Cr2Ge2Te6, VSe2, and Fe3GeTe2 has stimulated intense research activities to expand the scope of 2D magnets. This review covers the essential progress on 2D magnets, with an emphasis on the current understanding of the magnetic exchange interaction, the databases of 2D magnets, and the modification strategies for modulation of magnetism. We will address a large number of 2D intrinsic magnetic materials, including binary transition metal halogenides; chalogenides; carbides; nitrides; oxides; borides; silicides; MXene; ternary transition metal compounds CrXTe3, MPX3, Fe-Ge-Te, MBi2Te4, and MXY (M = transition metal; X = O, S, Se, Te, N; Y = Cl, Br, I); f-state magnets; p-state magnets; and organic magnets. Their electronic structure, magnetic moment, Curie temperature, and magnetic anisotropy energy will be presented. According to the specific 2D magnets, the underlying direct, superexchange, double exchange, super-superexchange, extended superexchange, and multi-intermediate double exchange interactions will be described. In addition, we will also highlight the effective strategies to manipulate the interatomic exchange mechanism to improve the Curie temperature of 2D magnets, such as chemical functionalization, isoelectronic substitution, alloying, strain engineering, defect engineering, applying electronic/magnetic field, interlayer coupling, carrier doping, optical controlling, and intercalation. We hope this review will contribute to understanding the magnetic exchange interaction of existing 2D magnets, developing unprecedented 2D magnets with desired properties, and offering new perspectives in this rapidly expanding field.

Microbial induced calcite precipitation (MICP) is one of the potential methods for improvement of engineering properties of soil. A laboratory study was conducted to investigate the influence of various factors on engineering properties of MICP-treated soil catalyzed by bacteria and ureases. Some of these factors include bacteria concentration, urease concentration, cementation media concentration, reaction time, type of sand, and curing conditions. The experiments of MICP catalyzed by Sporosarcina pasteurii and urease were conducted in similar conditions. The soil samples were prepared with full contact flexible molds (FCFMs). The results of unconfined compression test show that the experimental factors (bacteria/urease concentration, cementation media concentration, reaction time, and type of sand) have a significant impact on the MICP process and engineering properties of sand treated by both bacteria and urease, whereas the curing conditions has a small effect. The unconfined compression strength (approximately 1.76–2.04 MPa) of bacteria treated samples is almost 5× (approximately 0.33–0.43 MPa) that of urease treated samples under similar urease activity. The MICP process catalyzed by bacteria is much more effective than the process catalyzed by urease in terms of engineering soil properties improvement.

Abstract High‐entropy oxides (HEOs), which incorporate multiple‐principal cations into single‐phase crystals and interact with diverse metal ions, extend the border for available compositions and unprecedented properties. Herein, a high‐entropy‐stabilized (Ca 0.2 Sr 0.2 Ba 0.2 La 0.2 Pb 0.2 )TiO 3 perovskite is reported, and the effective absorption bandwidth (90% absorption) improves almost two times than that of BaTiO 3 . The results demonstrate that the regulation of entropy configuration can yield significant grain boundaries, oxygen defects, and an ultradense distorted lattice. These characteristics give rise to strong interfacial and defect‐induced polarizations, thus synergistically contributing to the dielectric attenuation performance. Moreover, the large strains derived from the strong lattice distortions in the high‐entropy perovskite offer varied transport for electron carriers. The high‐entropy‐enhanced positive/negative charges accumulation around grain boundaries and strain‐concentrated location, quantitatively validated by electron holography, results in unusual dielectric polarization loss. This study opens up an effective avenue for designing strong microwave absorption materials to satisfy the increasingly demanding requirements of advanced and integrated electronics. This work also offers a paradigm for improving other interesting properties for HEOs through entropy engineering.

Significance Estimates of nutrient allocation in different plant tissues and the relationships between the nutrient contents and photosynthetic capacity are critical to predicting ecosystem carbon sequestration under global change. Here, we provide an assessment of large-scale patterns of community-level nitrogen and phosphorus concentrations in different plant tissues and then examine how nutrient allocations are coupled with plant productivity. The results show that nutrient concentrations in leaves are less responsive to abiotic environments than those in woody stems and roots (stable leaf nutrient concentration hypothesis); the relationships between vegetation primary productivity and leaf nutrient contents are stronger when less nutrients are allocated to the woody tissues (productivity–nutrient allocation hypothesis) and are stronger in deciduous than in evergreen vegetation (productivity–leaf lifespan hypothesis).

Although great progress has been made in artificial enzyme engineering, their catalytic performance is far from satisfactory as alternatives of natural enzymes. Here, we report a novel and efficient strategy to access high-performance nanozymes via direct atomization of platinum nanoparticles (Pt NPs) into single atoms by reversing the thermal sintering process. Atomization of Pt NPs into single atoms makes metal catalytic sites fully exposed and results in engineerable structural and electronic properties, thereby leading to dramatically enhanced enzymatic performance. As expected, the as-prepared thermally stable Pt single-atom nanozyme (PtTS-SAzyme) exhibited remarkable peroxidase-like catalytic activity and kinetics, far exceeding the Pt nanoparticle nanozyme. The following density functional theory calculations revealed that the engineered P and S atoms not only promote the atomization process from Pt NPs into PtTS-SAzyme but also endow single-atom Pt catalytic sites with a unique electronic structure owing to the electron donation of P atoms, as well as the electron acceptance of N and S atoms, which simultaneously contribute to the substantial enhancement of the enzyme-like catalytic performance of PtTS-SAzyme. This work demonstrates that thermal atomization of the metal nanoparticle-based nanozymes into single-atom nanozymes is an effective strategy for engineering high-performance nanozymes, which opens up a new way to rationally design and optimize artificial enzymes to mimic natural enzymes.

Current blood-based approach for gout diagnosis can be of low sensitivity and hysteretic. Here via a 68-member cohort of 33 healthy and 35 diseased individuals, we reported that the intestinal microbiota of gout patients are highly distinct from healthy individuals in both organismal and functional structures. In gout, Bacteroides caccae and Bacteroides xylanisolvens are enriched yet Faecalibacterium prausnitzii and Bifidobacterium pseudocatenulatum depleted. The established reference microbial gene catalogue for gout revealed disorder in purine degradation and butyric acid biosynthesis in gout patients. In an additional 15-member validation-group, a diagnosis model via 17 gout-associated bacteria reached 88.9% accuracy, higher than the blood-uric-acid based approach. Intestinal microbiota of gout are more similar to those of type-2 diabetes than to liver cirrhosis, whereas depletion of Faecalibacterium prausnitzii and reduced butyrate biosynthesis are shared in each of the metabolic syndromes. Thus the Microbial Index of Gout was proposed as a novel, sensitive and non-invasive strategy for diagnosing gout via fecal microbiota.

Microbial contamination arising from pathogens poses serious threats to human health and in recent decades has presented an unprecedented challenge to antibacterial research. Of the various antibacterial agents that effectively kill pathogens, halogen-based antibacterial compounds have been successful in eliminating harmful pathogen-associated diseases and are becoming the most popular disinfectants. As a significant subcategory of halogen antibacterial agents, N-halamines have drawn increasing research interest into their chemistry and practical applications. N-Halamines have many advantages over other antibacterial agents, including effectiveness against a broad spectrum of microorganisms, long-term physicochemical stability, high structural durability, and the regenerability of their functional groups, with corresponding renewal of their antibacterial properties. This review examines recent progress and research trends in both theoretical and experimental studies of N-halamines, with the aim of providing a systematic and comprehensive survey and assessment of the significant advances in our understanding of antibacterial N-halamines. This review serves as a practical guide to developing N-halamines through both broad and in-depth basic research and offers suggestions for their potential future applications.

Ecosystem structure, functioning and stability have been a focus of ecological and environmental sciences during the past two decades. The mechanisms underlying their relationship, however, are not well understood. Based on comprehensive studies in Inner Mongolia grassland, here we show that species-level stoichiometric homoeostasis was consistently positively correlated with dominance and stability on both 2-year and 27-year temporal scales and across a 1200-km spatial transect. At the community level, stoichiometric homoeostasis was also positively correlated with ecosystem function and stability in most cases. Thus, homoeostatic species tend to have high and stable biomass; and ecosystems dominated by more homoeostatic species have higher productivity and greater stability. By modulating organism responses to key environmental drivers, stoichiometric homoeostasis appears to be a major mechanism responsible for the structure, functioning and stability of grassland ecosystems.

Soil salinization is among the most critical threats to agriculture and food security. Excess of salts adversely affects soil structure and fertility, plant growth, crop yield, and microorganisms. It is caused by natural processes, such as dry climates and low precipitations, high evaporation rate, poor waterlogging, and human factors, such as inappropriate irrigation practices, poor drainage systems, and excessive use of fertilizers. The growing extremization of climate with prolonged drought conditions is worsening the phenomenon. Nature-based solutions (NBS), combined with precision or conservation agriculture, represent a sustainable response, and offer benefits through revitalizing ecosystem services. This perspective explores NBS that can be adopted, along with their challenges and implementation limitations. We also argue that NBS could not be enough to combat hunger in the world's most vulnerable regions and fully achieve the Sustainable Development Goal - Zero Hunger (SDG2). We therefore discuss their possible combination with salt-tolerant crops based on bioengineering.

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health.

Craniofrontonasal syndrome (CFNS) is an X-linked developmental disorder that shows paradoxically greater severity in heterozygous females than in hemizygous males. Females have frontonasal dysplasia and coronal craniosynostosis (fusion of the coronal sutures); in males, hypertelorism is the only typical manifestation. Here, we show that the classical female CFNS phenotype is caused by heterozygous loss-of-function mutations in EFNB1, which encodes a member of the ephrin family of transmembrane ligands for Eph receptor tyrosine kinases. In mice, the orthologous Efnb1 gene is expressed in the frontonasal neural crest and demarcates the position of the future coronal suture. Although EFNB1 is X-inactivated, we did not observe markedly skewed X-inactivation in either blood or cranial periosteum from females with CFNS, indicating that lack of ephrin-B1 does not compromise cell viability in these tissues. We propose that in heterozygous females, patchwork loss of ephrin-B1 disturbs tissue boundary formation at the developing coronal suture, whereas in males deficient in ephrin-B1, an alternative mechanism maintains the normal boundary. This is the only known mutation in the ephrin/Eph receptor signaling system in humans and provides clues to the biogenesis of craniosynostosis.

Background: Although draft genomes are available for most agronomically important plant species, the majority are incomplete, highly fragmented, and often riddled with assembly and scaffolding errors. These assembly issues hinder advances in tool development for functional genomics and systems biology. Findings: Here we utilized a robust, cost-effective approach to produce high-quality reference genomes. We report a near-complete genome of diploid woodland strawberry (Fragaria vesca) using single-molecule real-time sequencing from Pacific Biosciences (PacBio). This assembly has a contig N50 length of ∼7.9 million base pairs (Mb), representing a ∼300-fold improvement of the previous version. The vast majority (>99.8%) of the assembly was anchored to 7 pseudomolecules using 2 sets of optical maps from Bionano Genomics. We obtained ∼24.96 Mb of sequence not present in the previous version of the F. vesca genome and produced an improved annotation that includes 1496 new genes. Comparative syntenic analyses uncovered numerous, large-scale scaffolding errors present in each chromosome in the previously published version of the F. vesca genome. Conclusions: Our results highlight the need to improve existing short-read based reference genomes. Furthermore, we demonstrate how genome quality impacts commonly used analyses for addressing both fundamental and applied biological questions.

Methanol–water reforming is a promising solution for H2 production/transportation in stationary and mobile hydrogen applications. Developing inexpensive catalysts with sufficiently high activity, selectivity, and stability remains challenging. In this paper, nickel-supported over face-centered cubic (fcc) phase α-MoC has been discovered to exhibit extraordinary hydrogen production activity in the aqueous-phase methanol reforming reaction. Under optimized condition, the hydrogen production rate of 2% Ni/α-MoC is about 6 times higher than that of conventional noble metal 2% Pt/Al2O3 catalyst. We demonstrate that Ni is atomically dispersed over α-MoC via carbon bridge bonds, forming a Ni1–Cx motif on the carbide surface. Such Ni1–Cx motifs can effectively stabilize the isolated Ni1 sites over the α-MoC substrate, rendering maximized active site density and high structural stability. In addition, the synergy between Ni1–Cx motif and α-MoC produces an active interfacial structure for water dissociation, methanol activation, and successive reforming processes with compatible activity.

Abstract An important area of computer vision is real-time object tracking, which is now widely used in intelligent transportation and smart industry technologies. Although the correlation filter object tracking methods have a good real-time tracking effect, it still faces many challenges such as scale variation, occlusion, and boundary effects. Many scholars have continuously improved existing methods for better efficiency and tracking performance in some aspects. To provide a comprehensive understanding of the background, key technologies and algorithms of single object tracking, this article focuses on the correlation filter-based object tracking algorithms. Specifically, the background and current advancement of the object tracking methodologies, as well as the presentation of the main datasets are introduced. All kinds of methods are summarized to present tracking results in various vision problems, and a visual tracking method based on reliability is observed.