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Abstract Developing devices with a wide-temperature range persistent photoconductivity (PPC) and ultra-low power consumption remains a significant challenge for optical synaptic devices used in neuromorphic computing. By harnessing the PPC properties in materials, it can achieve optical storage and neuromorphic computing, surpassing the von Neuman architecture-based systems. However, previous research implemented PPC required additional gate voltages and low temperatures, which need additional energy consumption and PPC cannot be achieved across a wide temperature range. Here, we fabricated a simple heterojunctions using zinc(II)-meso-tetraphenyl porphyrin (ZnTPP) and single-walled carbon nanotubes (SWCNTs). By leveraging the strong binding energy at the heterojunction interface and the unique band structure, the heterojunction achieved PPC over an exceptionally wide temperature range (77 K-400 K). Remarkably, it demonstrated nonvolatile storage for up to 2×104 s, without additional gate voltage. The minimum energy consumption for each synaptic event is as low as 6.5 aJ. Furthermore, we successfully demonstrate the feasibility to manufacture a flexible wafer-scale array utilizing this heterojunction. We applied it to autonomous driving under extreme temperatures and achieved as a high impressive accuracy rate as 94.5%. This tunable and stable wide-temperature PPC capability holds promise for ultra-low-power neuromorphic computing.

Developing and excavating new agrochemicals with highly active and safe is an important tactic for protecting crop health and food safety. In this paper, to discover the new bactericide candidates, we designed, prepared a new type of 1,2,3,4-tetrahydro-β-carboline (THC) derivatives and evaluated the in vitro and in vivo bioactivities against the Xanthomonas oryzae pv. oryzae (Xoo), Xanthomonas axonopodis pv. citri (Xac), and Pseudomonas syringae pv. actinidiae (Psa). The in vitro bioassay results exhibited that most title molecules possessed good activity toward the three plant pathogenic bacteria, the compound A17 showed the most active against Xoo and Xac with EC50 values of 7.27 and 4.89 mg mL–1 respectively, and compound A8 exhibited the best inhibitory activity against Psa with EC50 value of 4.87 mg mL–1. Pot experiments showed that compound A17 exhibited excellent in vivo antibacterial activities to manage rice bacterial leaf blight and citrus bacterial canker, with protective efficiencies of 52.67 and 79.79% at 200 mg mL–1, respectively. Meanwhile, compound A8 showed good control efficiency (84.31%) against kiwifruit bacterial canker at 200 mg mL–1. Antibacterial mechanism suggested that these compounds could interfere with the balance of the redox system, damage the cell membrane, and induce the apoptosis of Xoo cells. Taken together, our study revealed that tetrahydro-β-carboline derivatives could be a promising candidate model for novel broad-spectrum bactericides.

Abstract Quantum spin liquids (QSLs) are in a quantum disordered state that is highly entangled and has fractional excitations. As a highly sought-after state of matter, QSLs were predicted to host spinon excitations and to arise in frustrated spin systems with large quantum fluctuations. Here we report on the experimental observation and theoretical modeling of QSL signatures in monolayer 1T-NbSe2, which is a newly emerging two-dimensional material that exhibits both charge-density-wave (CDW) and correlated insulating behaviors. By using scanning tunneling microscopy and spectroscopy (STM/STS), we confirm the presence of spin fluctuations in monolayer 1T-NbSe2 by observing the Kondo resonance as monolayer 1T-NbSe2 interacts with metallic monolayer 1H-NbSe2. Subsequent STM/STS imaging of monolayer 1T-NbSe2 at the Hubbard band energy further reveals a long-wavelength charge modulation, in agreement with the spinon modulation expected for QSLs. By depositing manganese-phthalocyanine (MnPc) molecules with spin S = 3/2 onto monolayer 1T-NbSe2, new STS resonance peaks emerge at the Hubbard band edges of monolayer 1T-NbSe2. This observation is consistent with the spinon Kondo effect induced by a S = 3/2 magnetic impurity embedded in a QSL. Taken together, these experimental observations indicate that monolayer 1T-NbSe2 is a new promising QSL material.

Abstract Patients with brain cancers including medulloblastoma lack treatments that are effective long‐term and without side effects. In this study, a multifunctional fluoropolymer‐engineered iron oxide nanoparticle gene‐therapeutic platform is presented to overcome these challenges. The fluoropolymers are designed and synthesized to incorporate various properties including robust anchoring moieties for efficient surface coating, cationic components to facilitate short interference RNA (siRNA) binding, and a fluorinated tail to ensure stability in serum. The blood‐brain barrier (BBB) tailored system demonstrates enhanced BBB penetration, facilitates delivery of functionally active siRNA to medulloblastoma cells, and delivers a significant, almost complete block in protein expression within an in vitro extracellular acidic environment (pH 6.7) – as favored by most cancer cells. In vivo, it effectively crosses an intact BBB, provides contrast for magnetic resonance imaging (MRI), and delivers siRNA capable of slowing tumor growth without causing signs of toxicity – meaning it possesses a safe theranostic function. The pioneering methodology applied shows significant promise in the advancement of brain and tumor microenvironment‐focused MRI‐siRNA theranostics for the better treatment and diagnosis of medulloblastoma.

Abstract Objective To investigate the mechanism of ultrasound microbubbles (UTMB) promoting stem cells homing to fibrotic liver. Methods Bone marrow derived mesenchymal stem cells (BMSCs) were divided into 5 groups with or without ultrasound microbubbles and continuously irradiated with ultrasound conditions of frequency 1 MHZ and output power 0.6 W/cm2 for different times, and then injected into a mouse model of liver fibrosis through the tail vein with or without ultrasound microbubbles, with sound intensity. The effect of ultrasound microbubbles on MSC expression of CXC chemokine receptor 4 (CXCR4) and homing fibrotic liver was evaluated by flow cytometry (FCM), western blot (WB) and immunohistochemistry (IHC) analysis. Results The level of CXCR4 expression was significantly higher in the ultrasound microbubble group than in the non-intervention group (P

Abstract Visualizing rapid biological dynamics like neuronal signaling and microvascular flow is crucial yet challenging due to photon noise and motion artifacts. Here we present a deep learning framework for enhancing the spatiotemporal relations of optical microscopy data. Our approach leverages correlations of mirrored perspectives from conjugated scan paths, training a model to suppress noise and motion blur by restoring degraded spatial features. Quantitative validation on vibrational calcium imaging validates significant gains in spatiotemporal correlation (2.2×), signal-to-noise ratio (9–12 dB), structural similarity (6.6×), and motion tolerance compared to raw data. We further apply the framework to diverse in vivo experiments from mouse cerebral hemodynamics to zebrafish cardiac dynamics. This approach enables the clear visualization of the rapid nutrient flow (30 mm/s) in microcirculation and the systolic and diastolic processes of heartbeat (2.7 cycle/s), as well as cellular and vascular structure in deep cortex. Unlike techniques relying on temporal correlations, learning inherent spatial priors avoids motion-induced artifacts. This self-supervised strategy flexibly enhances live microscopy under photon-limited and motion-prone regimes.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is characterized by rapid progression and poor prognosis. Understanding the genetic mechanisms that affect cancer properties and reprogram tumor immune microenvironment will develop new strategies to maximize the benefits for cancer therapies. Methods Gene signatures and biological processes associated with advanced cancer and unfavorable outcome were profiled using bulk RNA sequencing and spatial transcriptome sequencing, Caprin-1 was identified as an oncogenesis to expedite pancreatic cancer growth by activating autophagy. The mechanism of Caprin-1 inducing autophagy activation was further explored in vitro and in vivo. In addition, higher level of Caprin-1 was found to manipulate immune responses and inflammatory-related pathways. The immune profiles associated with increased levels of Caprin-1 were identified in human PDAC samples. The roles of CD4+T cells, CD8+T cells and tumor associated macrophages (TAMs) on clinical outcomes prediction were investigated. Results Caprin-1 was significantly upregulated in advanced PDAC and correlated with poor prognosis. Caprin-1 interacted with both ULK1 and STK38, and manipulated ULK1 phosphorylation which activated autophagy and exerted pro-tumorigenic phenotypes. Additionally, the infiltrated CD4+T cells and tumor associated macrophages (TAMs) were increased in Caprin-1High tissues. The extensive CD4+T cells determined poor clinical outcome in Caprin-1high patients, arguing that highly expressed Caprin-1 may assist cancer cells to escape from immune surveillance. Conclusions Our findings establish causal links between the upregulated expression of Caprin-1 and autophagy activation, which may manipulate immune responses in PDAC development. Our study provides insights into considering Caprin-1 as potential therapeutic target for PDAC treatment.

A rapid, simple, effective, and green method for the determination of betaine and trigonelline from Lycium chinense Mill. (LCM) and the quantification of the trigonelline in coffee was proposed and validated by matrix-assisted laser desorption ionization time-of-flight mass spectrometric (MALDI-TOF MS) detection. Due to without chromatographic separation, the method greatly shortened the detection time. The detection of betaine and trigonelline concentration showed good linearity in the range of 1–100 μg/mL and 0.01–100 μg/mL, with correlation coefficients r2 = 0.9962 and 0.9946, respectively. The good reproducibility and reliability of the method were demonstrated by excellent intraday and interday precisions with RSD

Agriculture is the foundation of the national economy, and the issue of food security is the cornerstone of national development. Heilongjiang province is China’s largest commercial grain base. How to achieve the sustainable agricultural development of Heilongjiang province under the problem of food security is of great significance. This article takes the five aspects of population system, social system, economic system, resource system, and environmental system, with a total of 29 secondary indicators as the basis for evaluation, the sustainable development and coordination of agriculture in Heilongjiang from 2005 to 2018 were evaluated by using entropy method and coupling degree model. The evaluation results showed that development methods of extensive agriculture greatly increased the grain output of Heilongjiang province from 2005 to 2007, but the level of sustainable agricultural development continued to decline, and there were also threats to the long-term development of food security. Although the sustainable level had been continuously improved since 2007, the whole system is still in the stage of low-level coupling and serious maladjustment. From the results of each subsystem, the coordination degree of population-environment system continues to decline, and the coordination degree of resource-environment system fluctuates in the low-level coordination state, which indicates that there is an obvious development in coordination among subsystems in Heilongjiang province, which restricts comprehensive and coordinated development of agricultural system. Based on the empirical analysis, this article takes Heilongjiang province as an example, and puts forward suggestions for sustainable agricultural development from the perspective of ensuring food security.

Abstract Cancer remains a global health challenge, demanding early detection and accurate diagnosis for improved patient outcomes. An intelligent paradigm is introduced that elevates label‐free nonlinear optical imaging with contrastive patch‐wise learning, yielding stain‐free nonlinear optical computational histology (NOCH). NOCH enables swift, precise diagnostic analysis of fresh tissues, reducing patient anxiety and healthcare costs. Nonlinear modalities are evaluated, including stimulated Raman scattering and multiphoton imaging, for their ability to enhance tumor microenvironment sensitivity, pathological analysis, and cancer examination. Quantitative analysis confirmed that NOCH images accurately reproduce nuclear morphometric features across different cancer stages. Key diagnostic features, such as nuclear morphology, size, and nuclear‐cytoplasmic contrast, are well preserved. NOCH models also demonstrate promising generalization when applied to other pathological tissues. The study unites label‐free nonlinear optical imaging with histopathology using contrastive learning to establish stain‐free computational histology. NOCH provides a rapid, non‐invasive, and precise approach to surgical pathology, holding immense potential for revolutionizing cancer diagnosis and surgical interventions.

Abstract Hypertriglyceridemic pancreatitis (HTGP) is featured by higher incidence of complications and poor clinical outcomes. Gut microbiota dysbiosis is associated with pancreatic injury in HTGP and the mechanism remains unclear. Here, we observe lower diversity of gut microbiota and absence of beneficial bacteria in HTGP patients. In a fecal microbiota transplantation mouse model, the colonization of gut microbiota from HTGP patients recruits neutrophils and increases neutrophil extracellular traps (NETs) formation that exacerbates pancreatic injury and systemic inflammation. We find that decreased abundance of Bacteroides uniformis in gut microbiota impairs taurine production and increases IL-17 release in colon that triggers NETs formation. Moreover, Bacteroides uniformis or taurine inhibits the activation of NF-κB and IL-17 signaling pathways in neutrophils which harness NETs and alleviate pancreatic injury. Our findings establish roles of endogenous Bacteroides uniformis-derived metabolic and inflammatory products on suppressing NETs release, which provides potential insights of ameliorating HTGP through gut microbiota modulation.

Myocardial ischemia-reperfusion (MI/R) injury is common in patients who undergo revascularization therapy for myocardial infarction, often leading to cardiac dysfunction. Carbon monoxide (CO) has emerged as a therapeutic molecule due to its beneficial properties such as anti-inflammatory, anti-apoptotic, and mitochondrial biogenesis-promoting properties. However, its clinical application is limited due to uncontrolled release, potential toxicity, and poor targeting efficiency. To address these limitations, a peroxynitrite (ONOO−)-triggered CO donor (PCOD585) is utilized to generate a poly (lactic-co-glycolic acid) (PLGA)-based, biomimetic CO nanogenerator (M/PCOD@PLGA) that is coated with the macrophage membrane, which could target to the ischemic area and neutralize proinflammatory cytokines. In the ischemic area, local produced ONOO− triggers the continuous release of CO from M/PCOD@PLGA, which efficiently ameliorates MI/R injury by clearing harmful ONOO−, attenuating the inflammatory response, inhibiting cardiomyocyte apoptosis, and promoting mitochondrial biogenesis. This study provides a novel insight into the safe therapeutic use of CO for MI/R injury by utilizing a novel CO donor combined with biomimetic technology. The M/PCOD@PLGA nanogenerator offers targeted delivery of CO to the ischemic area, minimizing potential toxicity and enhancing therapeutic efficacy.

Sequence alignment is a critical factor in the variant analysis of genomic research. Since the FM (Ferrainas–Manzini) index was developed, it has proven to be a model in a compact format with efficient pattern matching and high-speed query searching, which has attracted much research interest in the field of sequence alignment. Such characteristics make it a convenient tool for handling large-scale sequence alignment projects executed with a small memory. In bioinformatics, the massive success of next-generation sequencing technology has led to an exponential growth in genomic data, presenting a computational challenge for sequence alignment. In addition, the use of a heterogeneous computing system, composed of various types of nodes, is prevalent in the field of HPC (high-performance computing), which presents a promising solution for sequence alignment. However, conventional methodologies in short-read alignment are limited in performance on current heterogeneous computing infrastructures. Therefore, we developed a parallel sequence alignment to investigate the applicability of this approach in NUMA-based (Non-Uniform Memory Access) heterogeneous architectures against traditional alignment algorithms. This proposed work combines the LF (longest-first) distribution policy with the EP (enhanced partitioning) strategy for effective load balancing and efficient parallelization among heterogeneous architectures. The newly proposed LF-EP-based FM aligner shows excellent efficiency and a significant improvement over NUMA-based heterogeneous computing platforms. We provide significantly improved performance over several popular FM aligners in many dimensions such as read length, sequence number, sequence distance, alignment speedup, and result quality. These resultant evaluation metrics cover the quality assessment, complexity analysis, and speedup evaluation of our approach. Utilizing the capabilities of NUMA-based heterogeneous computing architectures, our approach effectively provides a convenient solution for large-scale short-read alignment in the heterogeneous system.

Abstract Advanced atomic tracking techniques play a critical role in characterizing structural evolution, elucidating fundamental mechanisms of exotic phenomena and tailoring delicate properties. Thermally driven structural modulation in 2D crystals, such as the charge density wave (CDW), often leads to intriguing quantum properties, making them a valuable platform for exploring fundamental physics and potential device applications. However, despite their significance, experimental studies addressing atomic tracking of thermally‐driven structural evolution in 2D crystals have been limited. Herein, we utilize high‐accuracy variable‐temperature atomic tracking measurements with scanning tunneling microscopy (STM) to directly observe a series of structural transitions in a model 2D crystal, namely NbSe2. With the atomic tracking technique, we confirm the existence of the universal thermally‐driven CDW transition hysteresis between the heating and cooling cycles. This transition hysteresis, characterized by a constant temperature offset, represents a new phenomenon of structural evolution. Our findings provide a feasible method to track CDW transitions at the atomic scale in 2D crystals, significantly contributing to a better understanding and the potential modulation of these materials' functions in nanodevices.

The economic improvements of a queueing system with two types of customers achieved by service decomposition are examined. The service process for a Type 2 customer can be split into two phases: a basic service and an additional service. The basic service rate is equal to that of the Type 1 customer. Additional services can be viewed as orders stored in inventory and processed when the server is idle. Once a new customer arrives during idle time, the server will provide a basic service to the customer upon his/her arrival. That is, customers have preemptive priority for orders stored in inventory. We obtain a two-dimensional unbounded Markov process and apply the multivariate generating function to derive the stationary probability of the proposed model as well as some performance measures. The condition under which performing service decomposition can improve economic efficiency is also obtained. Both the optimal inventory capacity and the minimum system cost are obtained numerically. Numerical experiments demonstrate the impact of optimal inventory setting on economic improvement efficiency. Finally, simulation experiments prove the correctness of our theoretical analysis.

Abstract Imaging biomolecules in real space is crucial for gaining a comprehensive understanding of the properties and functions of biological systems at the most fundamental level. Among the various imaging techniques available for biomolecules and their assembled nanostructures, scanning probe microscopy (SPM) provides a powerful and nondestructive imaging option. SPM is unique in visualizing intrinsically disordered biomolecules at the nanometer scale (e.g., glycans). This review highlights recent achievements in studying biomolecules using SPM technique, focusing on DNA bases, amino acids, proteins, and glycans. The atomic‐level analysis of biomolecules made possible by SPM allows for a more accurate definition of the local structure–property relationship. High‐resolution SPM imaging of single biomolecules offers a new way to study basic processes of life at the molecular level.

This is a paper in the field of mineral processing engineering. Application of ultra-fine grinding technology to treat phosphate ore can change the physical and chemical properties of phosphate containing minerals in phosphate ore, thus improving the dissolution and release of phosphorus in phosphate ore, so that it can be used as phosphate fertilizer. As an ultra-fine grinding equipment, the feasibility of using stirred mill to treat phosphate ore and the research on the influence of process parameters on grinding effect are not perfect. A phosphate ore in Hebei Province was wet ground by a vertical stirring mill in this paper.The particle size distribution of the ground product was detected by NKT6100-D laser particle size analyzer.The effect of grinding process parameters on the particle size composition of product and the content of newly formed particles was explored, and the product particle size was parametrically analyzed by R-R equation to determine the more appropriate operating process parameters. The results showed that under the conditions of agitator speed of 550 r/min, grinding concentration of 65%, filling rate of 60%, feed to ball ratio of 0.5 and grinding time of 30 min, the available phosphorus content and phosphorus solubility in citric acid of 8.75% and 74.03%, particle characteristic parameter b of 0.371 and uniformity coefficient n of 1.426 were obtained. It can be seen that it is feasible to use a vertical stirring mill for ultra-fine grinding of phosphate ore.

This paper considers a two-stage tandem queuing system with ordinary customers and priority customers. Upon arrival, ordinary customers are individually served in the first stage, then move to the second stage and receive clearing service. Priority customers can bypass the first stage and proceed directly to the second stage for clearing service. The second stage has N service seats. All customers currently in the second stage are served simultaneously (i.e., clearing service). Once there are N customers in the second stage, the first stage will be blocked, and newly arriving priority customers will balk and leave without joining. We first formulate a two-dimensional Markov chain to analyze this queuing system and derive the stability condition. Subsequently, the stationary distribution of the system is derived using the matrix-analytic method and spectral expansion technique. Furthermore, analytical expressions for the mean queue length, mean sojourn time, and other performance measures are presented. Finally, some numerical examples are provided to illustrate the effects of various parameters, offering valuable insights for designing such two-stage tandem queuing systems.

Long waiting times and crowded services are the current medical situation in China. Especially in hierarchic healthcare systems, as high-quality medical resources are mainly concentrated in comprehensive hospitals, patients are too concentrated in these hospitals, which leads to overcrowding. This paper constructs a game-theoretical queueing model to analyze the strategic queueing behavior of patients. In such hospitals, patients are divided into first-visit and referred patients, and the hospitals provide patients with two service phases of “diagnosis” and “treatment”. We first obtain the expected sojourn time. By defining the patience level of patients, the queueing behavior of patients in equilibrium is studied. The results suggest that as long as the patients with low patience levels join the queue, the patients with high patience levels also join the queue. As more patients arrive at the hospitals, the queueing behavior of patients with high patience levels may have a negative effect on that of patients with low patience levels. The numerical results also show that the equilibrium behavior deviates from a socially optimal solution; therefore, to reach maximal social welfare, the social planner should adopt some regulatory policies to control the arrival rates of patients.

The Tsiolkovsky crater is located on the farside of the Moon. It formed in the late Imbrian epoch and was filled with a large area of mare basalts. Multisource remote sensing data are used to interpret the geological features of the Tsiolkovsky area. Compared with previous studies, new remote sensing data and a chronological model based on crater size–frequency distribution are used to further refine the stratigraphic units and determine the absolute ages of the mare basalt units. The evolution of volcanic activity in this crater is discussed. The results are as follows: Abundances of major elements, Th, and silicate minerals suggest that the mare basalt in the crater floor is not a uniform unit but rather nine units with different compositions. The nine basalt units are divided into two episodes of volcanic activity: The first occurred at 3.5–3.7 Ga, when highly evolved lava erupted at the crater floor at a large scale; the second occurred at ~3.4 Ga, when a small area of more primitive lava extended to the northern portion of the crater floor.

Abstract Background Tetramates or tetramic acid-containing compounds (TACs) are a group of bioactive natural products featuring a pyrrolidine-2,4-dione ring acknowledged being closed via Dieckmann cyclization. The cariogenic Streptococcus mutans strains bearing a muc biosynthetic gene cluster (BGC) can synthesize mutanocyclin (MUC), a 3-acetylated TAC that can inhibit both leukocyte chemotaxis and filamentous development in Candida albicans. Some strains can also accumulate reutericyclins (RTCs), the intermediates of MUC biosynthesis with antibacterial activities. However, the formation mechanism of the pyrrolidine-2,4-dione ring of MUC and the distribution of muc-like BGCs along with their ecological functions has not been explored extensively. Results We demonstrated that a key intermediate of MUC biosynthesis, M-307, is installed by a hybrid nonribosomal peptide synthetase-polyketide synthase assembly line and its pyrrolidine-2,4-dione ring is closed via an unprecedented lactam bond formation style. Subsequent C-3 acetylation will convert M-307 to RTCs, which is then hydrolyzed by a deacylase, MucF, to remove the N-1 fatty acyl appendage to generate MUC. Distribution analysis showed that the muc-like BGCs distribute predominantly in human-associated bacteria. Interestingly, most of the muc-like BGCs possessing a mucF gene were isolated from human or livestock directly, indicating their involvement in alleviating the host’s immune attacks by synthesizing MUC; while those BGCs lacking mucF gene distribute mainly in bacteria from fermented products, suggesting that they tend to synthesize RTCs to compete with neighboring bacteria. It is noteworthy that many bacteria in the same habitats (e.g., the oral cavity) lack the muc-like BGC, but possess functional MucF homologues to “detoxify” RTCs to MUC, including several competitive bacteria of S. mutans. We also comparably studied the distribution of TAS1, a fungal enzyme responsible for the production of phytotoxic tenuazonic acids (TeAs), a class of 3-acetylated TACs with similar structure but distinct biosynthetic mechanism to MUC, and found that it mainly exists in plants or crops. Conclusions The in vivo and in vitro experiments revealed that the pyrrolidine-2,4-dione ring of MUC is closed via lactam bond formation, which may be adopted by many TACs without 3-acyl decorations. Besides, we found that muc-like BGCs are widespread in human-associated bacteria and their shapes and main products can be influenced by the habitat environment and vice versa. By comparing with TeAs, we provided thought-provoking insights into how ecological and evolutionary forces drive bacteria and fungi to construct a common 3-acetylated pyrrolidine-2,4-dione core through different routes, and how the biosynthetic processes are delicately controlled to generate diverse 3-acetylated TACs for environmental adaptation. Video Abstract

Fractional‐order vector vortex beams (VVBs) have recently been demonstrated as new carriers of fractional‐strength optical vortices. However, the inherent mechanism of the new vortex beams, formed by the combination of both unstable states, to propagate stably in free space requires clarification. In this study, this scientific problem is solved by revealing the physical essence of propagable fractional‐strength optical vortices in free space. Therefore, three new viewpoints regarding these unique vortex beams are proposed: Abbe's diffraction limit, the phase evolution of the vortex beam, and the binary time vector property of phase. First, due to Abbe's diffraction limit, the inherent polarization modes are intertwined, thereby maintaining the entire unique vortex beam in free space. In the second case, the phase evolution of the vortex beam is the physical cause for the polarization rotation of fractional‐order VVBs. Third, the phase is not merely a scalar attribute of the light beam and demonstrates a binary time vector property. This study provides entirely different physical viewpoints on the phase of the vortex beam and Abbe's diffraction limit, which may deepen the knowledge on the behavior of light beams in classical optics.

IntroductionAinaxiang (Blumea balsamifera (Linn.) DC.) is cultivated for the extraction of (-)-borneol and other pharmaceutical raw materials due to its abundant volatile oil. However, there is limited knowledge regarding the structural basis and composition of volatile oil accumulation in fresh B. balsamifera leaves.MethodsTo address this problem, we compare the fresh leaves’ morphology, microstructure, and volatile metabonomic at different development stages, orderly defined from the recently unfolded young stage (S1) to the senescent stage (S4).Results and discussionDistinct differences were observed in the macro-appearance and microstructure at each stage, particularly in the B. balsamifera glandular trichomes (BbGTs) distribution. This specialized structure may be responsible for the accumulation of volatile matter. 213 metabolites were identified through metabolomic analysis, which exhibited spatiotemporal accumulation patterns among different stages. Notably, (-)-borneol was enriched at S1, while 10 key odor metabolites associated with the characteristic balsamic, borneol, fresh, and camphor aromas of B. balsamifera were enriched in S1 and S2. Ultra-microstructural examination revealed the involvement of chloroplasts, mitochondria, endoplasmic reticulum, and vacuoles in the synthesizing, transporting, and storing essential oils. These findings confirm that BbGTs serve as the secretory structures in B. balsamifera, with the population and morphology of BbGTs potentially serving as biomarkers for (-)-borneol accumulation. Overall, young B. balsamifera leaves with dense BbGTs represent a rich (-)-borneol source, while mesophyll cells contribute to volatile oil accumulation. These findings reveal the essential oil accumulation characteristics in B. balsamifera, providing a foundation for further understanding.

BackgroundDue to the lower reliability of laboratory tests, skin diseases are more suitable for diagnosis with AI models. There are limited AI dermatology diagnostic models combining images and text; few of these are for Asian populations, and few cover the most common types of diseases.MethodsLeveraging a dataset sourced from Asia comprising over 200,000 images and 220,000 medical records, we explored a deep learning-based system for Dual-channel images and extracted text for the diagnosis of skin diseases model DIET-AI to diagnose 31 skin diseases, which covers the majority of common skin diseases. From 1 September to 1 December 2021, we prospectively collected images from 6,043 cases and medical records from 15 hospitals in seven provinces in China. Then the performance of DIET-AI was compared with that of six doctors of different seniorities in the clinical dataset.ResultsThe average performance of DIET-AI in 31 diseases was not less than that of all the doctors of different seniorities. By comparing the area under the curve, sensitivity, and specificity, we demonstrate that the DIET-AI model is effective in clinical scenarios. In addition, medical records affect the performance of DIET-AI and physicians to varying degrees.ConclusionThis is the largest dermatological dataset for the Chinese demographic. For the first time, we built a Dual-channel image classification model on a non-cancer dermatitis dataset with both images and medical records and achieved comparable diagnostic performance to senior doctors about common skin diseases. It provides references for exploring the feasibility and performance evaluation of DIET-AI in clinical use afterward.

Graphene is one of the most well-known two-dimensional (2D) materials that has attracted significant interest due to its unique electrical and optical properties. Being a van der Waals substrate, the fabrication of few-layered graphene by stacking a pre-defined number of graphene monolayers is essential in the field. The thickness can influence the interface interaction and therefore tune the surface electronic properties. In the study, we demonstrate a bottom-up synthesis of pre-defined few-layer graphene on SiC substrate using the thermal decomposition method and carefully characterize its thickness by the non-damageable synchrotron-radiation-based X-ray photo-electron spectroscopy (SR-XPS). By varying the photon energy, we acquire different probe depths, resulting in the different intensity ratios of graphene to SiC substrate, which is then used to estimate the thickness of the few-layer graphene. Our calculation demonstrates that the thermal decomposition method in the study can repeatedly fabricate graphene samples with expected thickness. We further compare the obtained few-layer graphene to the single-layer graphene and HOPG using the scanning tunneling microscopy (STM) technique. Our work provides accurate methods for fabricating and characterizing pre-defined few-layer graphene, providing essential knowledge in future graphene-based thin film electronics.

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. The carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China’s future carbon quota allocation will gradually transition from free allocation to auction allocation, and the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism, constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model, systematically researches the power generation structure under different auction ratios with the time scale of months, and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions. The results of the study show that after comprehensively comparing the total economic cost, renewable energy development, and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

Acute pancreatitis (AP) is a common acute abdomen disease characterized by the pathological activation of digestive enzymes and the self-digestion of pancreatic acinar cells. Secondary infection and sepsis are independent prognosticators for AP progression and increased mortality. Accumulating anatomical and epidemiological evidence suggests that the dysbiosis of gut microbiota affects the etiology and severity of AP through intestinal barrier disruption, local or systemic inflammatory response, bacterial translocation, and the regulatory role of microbial metabolites in AP patients and animal models. Recent studies discussing the interactions between gut microbiota and the pancreas have opened new scopes for AP, and new therapeutic interventions that target the bacteria community have received substantial attention. This review concentrates on the alterations of gut microbiota and its roles in modulating gut–pancreas axis in AP. The potential therapies of targeting microbes as well as the major challenges of applying those interventions are explored. We expect to understand the roles of microbes in AP diagnosis and treatment.

Fiber-optic biosensors have garnered significant attention and witnessed rapid development in recent years owing to their remarkable attributes such as high sensitivity, immunity to electromagnetic interference, and real-time monitoring. They have emerged as a potential tool in the realm of biomarker detection for low-concentration and small molecules. In this paper, a portable and cost-effective optical fiber biosensor based on surface plasmon resonance for the early detection of breast cancer is demonstrated. By utilizing the aptamer human epidermal growth factor receptor 2 (HER2) as a specific biomarker for breast cancer, the presence of the HER2 protein can be detected through an antigen-antibody binding technique. The detection method was accomplished by modifying a layer of HER2 aptamer on the flat surface of a gold-coated D-shaped polymer optical fiber (core/cladding diameter 120/490 μm), of which the residual thickness after side-polishing was about 245 μm, the thickness of the coated gold layer was 50 nm, and the initial wavelength in pure water was around 1200 nm. For low-concentration detection of the HER2 protein, the device exhibited a wavelength shift of ~1.37 nm with a concentration of 1 μg/mL (e.g., 5.5 nM), which corresponded to a limit of detection of ~5.28 nM. Notably, the response time of the biosensor was measured to be as fast as 5 s. The proposed biosensor exhibits the potential for early detection of HER2 protein in initial cancer serum and offers a pathway to early prevention of breast cancer.

Abstract Monolayer transition metal dichalcogenides (TMDs) can host exotic phenomena such as correlated insulating and charge‐density‐wave (CDW) phases. Such properties are strongly dependent on the precise atomic arrangements. Strain, as an effective tuning parameter in atomic arrangements, has been widely used for tailoring material's structures and related properties, yet to date, a convincing demonstration of strain‐induced dedicate phase transition at nanometer scale in monolayer TMDs has been lacking. Here, a strain engineering technique is developed to controllably introduce out‐of‐plane atomic deformations in monolayer CDW material 1T‐NbSe2. The scanning tunneling microscopy and spectroscopy (STM and STS) measurements, accompanied by first‐principles calculations, demonstrate that the CDW phase of 1T‐NbSe2 can survive under both tensile and compressive strains even up to 5%. Moreover, significant strain‐induced phase transitions are observed, i.e., tensile (compressive) strains can drive 1T‐NbSe2 from an intrinsic‐correlated insulator into a band insulator (metal). Furthermore, experimental evidence of the multiple electronic phase coexistence at the nanoscale is provided. The results shed new lights on the strain engineering of correlated insulator and useful for design and development of strain‐related nanodevices.

Abstract Background The ketogenic diet (KD) has anti-tumor and anti-diabetic effects in addition to its anti-epileptic role. It could also improve cardiac function and attenuate neurological insult. However, the effect of KD on blood perfusion or tissue recovery after ischemia remains largely unknown. Thus, we observed blood flow and ischemic tissue recovery following hind limb ischemia (HLI) in mice. Methods C57 mice were fed with either a KD or normal diet (ND) for 2 weeks, before inducing hind limb ischemia, blood perfusion of ischemic limb tissue was observed at 0, 7, and 21 days post operation. Results KD not only decreased blood perfusion of ischemic limb tissue but also delayed muscle recovery after ischemia, induced muscle atrophy of non-ischemic tissue compared to mice fed with ND. Furthermore, KD delayed wound healing at the surgical site and aggravated inflammation of the ischemic tissue. At the cellular level, KD altered the metabolic status of limb tissue by decreasing glucose and ketone body utilization while increasing fatty acid oxidation. Following ischemia, glycolysis, ketolysis, and fatty acid utilization in limb tissue were all further reduced by KD, while ketogenesis was mildly increased post KD in this mice model. Conclusion The KD may cause impaired tissue recovery after ischemia and possible muscle atrophy under a prolonged diet. Our results hint that patients with limb ischemia should avoid ketogenic diet.

Abstract Background The association between prothrombin time-international normalized ratio (PT-INR) and long-term prognosis among patients with coronary artery disease (CAD) without atrial fibrillation or anticoagulant therapy was still unclear. We analyzed the association of PT-INR levels and long-term mortality in a large cohort of CAD patients without atrial fibrillation or using of anticoagulant drugs. Methods We obtained data from 44,662 patients who were diagnosed with CAD and had follow-up information from January 2008 to December 2018. The patients were divided into 4 groups (Quartile 1: PT-INR ≤ 0.96; Quartile2: 0.96 1.06). The main endpoint was long-term all-cause death. Kaplan–Meier curve analysis and Cox proportional hazards models were used to investigate the association between quartiles of PT-INR levels and long-term all-cause mortality. Results During a median follow-up of 5.25 years, 5613 (12.57%) patients died. We observed a non-linear shaped association between PT-INR levels and long-term all-cause mortality. Patients in high PT-INR level (Quartile4: PT-INR > 1.06) showed a significantly higher long-term mortality than other groups (Quartile2 or 3 or 4), (Compared with Quartile 1, Quartile 2 [0.96 1.06], aHR = 1.33, 95% CI 1.22–1.45, P

Abstract OPTN is an autophagy receptor involved in autophagic degradation. Here we studied the role of OPTN in attenuating the neurotoxicity induced by mutated Tau protein. We constructed recombinant adeno-associated viruses with OPTN and Tau-P301L genes, respectively. Through virus coinfection on neuronal cell line HT22 in vitro and Kunming mice in vivo, we found that autophagy- and apoptosis-associated genes are altered by Tau-P301L at both mRNA and protein levels, which are restored by OPTN expression. Functionally, OPTN suppresses apoptosis and enhances cellular viability in Tau-P301L expressing HT22 cells, and increases learning and memory in Tau-P301L expressing mice, respectively. Last, we found that OPTN reduces the p-Tau levels in vitro and in vivo. Our results reveal the function of OPTN in lowering the p-Tau level and the expressions of apoptosis genes, and increasing the expressions of autophagic genes, indicating a beneficial role of OPTN in Tau pathology.

ObjectiveShip capsizing induced by pure loss of stability is an important issue for research on the second-generation intact stability criteria proposed by IMO. MethodsA CFD solver based on the viscous theory is developed in combination with the dynamic overset approach and feedback controller for ship maneuver behavior, thereby simulating the course-keeping of a free-running ship with rudders and propellers in stern quartering waves. 6-DOFs motions are predicted for the ship under pure loss of stability with stability failure mode and capsizing assessment. ResultsThe results indicate that large amplitude roll motion occurs with the continuous loss of stability, and the extreme roll eventually leads to the ship capsizing. The yaw angle increases significantly with the variation in roll angle, which indicates that the rudder deflection is unable to control the ship's course effectively, resulting in the broaching phenomenon. Conclusions The results of this study demonstrate that the CFD approach can accurately simulate the stability failure mode and capsizing of a ship, providing references for research on the second-generation intact stability criteria, and technical support for the development of direct stability assessment under pure loss of stability.

Abstract Background Eukaryotic translation elongation factors 1 δ (EEF1D), has garnered much attention with regards to their role in the drug resistance of cancers. In this paper, we investigated the effects and mechanisms of increasing the sensitivity of ovarian cancer cells to cisplatin or cis-dichlorodiammine platinum (DDP) by knockdown and knockout of EEF1D gene in cellular and animal models. Methods The EEF1D gene was knocked-down or -out by siRNA or CRISPR/Cas9 respectively in human ovarian cancer cell SKOV3, DDP-resistant subline SKOV3/DDP, and EEF1D gene in human primary ovarian cancer cell from 5 ovarian cancer patients with progressive disease/stable disease (PD/SD) was transiently knocked down by siRNA interference. The mice model bearing xenografted tumor was established with subcutaneous inoculation of SKOV3/DDP. Results The results show that reducing or removing EEF1D gene expression significantly increased the sensitivity of human ovarian cancer cells to DDP in inhibiting viability and inducing apoptosis in vitro and in vivo, and also boosted DDP to inhibit xenografted tumor growth. Interfering with EEF1D gene expression in mice xenografted tumor significantly affected the levels of OPTN, p-Akt, Bcl-2, Bax, cleaved caspase-3 and ERCC1 compared to DDP treated mice alone, and had less effect on PI3K, Akt and caspase-3. Conclusions The knocking down or out EEF1D gene expression could enhance the sensitivity of ovarian cancer cells to DDP partially, which may be achieved via inactivating the PI3K/AKT signaling pathway, thus inducing cell apoptosis and decreasing repairment of DNA damage. Our study provides a novel therapeutic strategy for the treatment of ovarian cancer.

It is well known that microorganisms are abundant in sponges, which make up 50%-60% of the host biomass. Moreover, mounting evidence suggests that bacteria, fungi, and cyanobacteria, all associated with sponges, are the true creators of the bioactive compounds identified from sponges. The discovery of 774 structurally active compounds from 1998 to 2017 presents a good overview of natural product resources in sponge-associated microorganisms. During the last 5 years, many new molecules, including peptides, polyketides, alkaloids, and terpenes, have been identified from sponge-associated microorganisms through various mining strategies, exhibiting a wide range of biological activities, such as anti-microbial, anti-cancer, enzyme inhibition, and antioxidant properties. In this paper, 140 compounds produced by sponge-associated microorganisms from 2017 to 2022 are systematically discussed in terms of their structures, biological activities, and strain sources, as well as the mining strategies, which not only further updates the natural product library of sponge-associated microorganisms but also provides a new guideline for exploring the “dark matter” in sponges.

Hepatocellular carcinoma (HCC) is considered a classic inflammation-associated tumor that usually originates from chronic hepatitis, where an intense and chronic inflammatory response leads to the accumulation of mutations and eventually carcinogenesis under conditions of persistent liver injury. In recent years, immunotherapy for HCC has continued to evolve, as the liver is naturally filled with a large variety of immune cells, making hepatocellular carcinoma a more complex inflammatory microenvironment unlike other tumors. With a better understanding of the specific inflammatory microenvironment of HCC, there is an opportunity to try new therapeutic strategies for HCC immunotherapy. In this paper, we review the immunotherapy of primary liver cancer in terms of the correlation between ICI drugs, ACT therapy and the inflammatory microenvironment of HCC, summarize and discuss the progress and difficulties of immunotherapy of liver cancer, and provide more scientific guidance for immunotherapy of primary liver cancer.

Abstract Pancreatic ductal adenocarcinoma (PDAC) presents with high mortality and short overall survival. Cancer‐associated fibroblasts (CAFs) act as refuge for cancer cells in PDAC. Mechanisms of intracelluar communication between CAFs and cancer cells need to be explored. Long noncoding RNAs (lncRNAs) are involved in the modulation of oncogenesis and tumor progression of PDAC; however, specific lncRNAs and their mechanism of action have not been clarified clearly in tumoral microenvironment. This work aims to identify novel lncRNAs involved in cellular interaction between cancer cells and CAFs in PDAC. To this end, differentially expressed lncRNAs between long‐term and short‐term survival PDAC patients are screened. Lnc‐FSD2‐31:1 is found to be significantly increased in long‐term survival patients. This work then discovers that tumor‐derived lnc‐FSD2‐31:1 restrains CAFs activation via miR‐4736 transported by extracellular vesicles (EVs) in vitro and in vivo. Mechanistically, EVs‐derived miR‐4736 suppresses autophagy and contributes to CAFs activation by targeting ATG7. Furthermore, blocking miR‐4736 suppresses tumor growth in genetically engineered KPC (LSL‐KrasG12D/+, LSL‐Trp53R172H/+, and Pdx‐1‐Cre) mouse model of PDAC. This study demonstrates that intratumoral lnc‐FSD2‐31:1 modulates autophagy in CAFs resulting in their activation through EVs‐derived miR‐4736. Targeting miR‐4736 may be a potential biomarker and therapeutic target for PDAC.

In recent years, there has been a growing fascination with suspended two-dimensional (2D) materials, owing to their excellent mechanical, optical, and electronic characteristics. This surge of interest stems from the remarkable properties exhibited by these materials when they are isolated in a two-dimensional counterpart. Nanofabrication technologies provide a new platform to further explore the properties of 2D materials by suspending them to reduce the influence of substrates. In recent years, many scientists have discovered the feasibility of using suspended membranes of 2D materials in various fields, including optoelectronics and photonics. This review summarizes the recent progress in the fabrication, characterization, and applications of suspended 2D materials, focusing on critical properties such as optical and electronic properties, strain engineering, and thermal properties. This area has the potential to lead to new technologies and applications in a wide range of innovative fields.

The prediction of drug–target interaction (DTI) is crucial to drug discovery. Although the interactions between the drug and target can be accurately verified by traditional biochemical experiments, the determination of DTI through biochemical experiments is a time-consuming, laborious, and expensive process. Therefore, we propose a learning-based framework named BG-DTI for drug–target interaction prediction. Our model combines two main approaches based on biological features and heterogeneous networks to identify interactions between drugs and targets. First, we extract original features from the sequence to encode each drug and target. Later, we further consider the relationships among various biological entities by constructing drug–drug similarity networks and target–target similarity networks. Furthermore, a graph convolutional network and a graph attention network in the graph representation learning module help us learn the features representation of drugs and targets. After obtaining the features from graph representation learning modules, these features are combined into fusion descriptors for drug–target pairs. Finally, we send the fusion descriptors and labels to a random forest classifier for predicting DTI. The evaluation results show that BG-DTI achieves an average AUC of 0.938 and an average AUPR of 0.930, which is better than those of five existing state-of-the-art methods. We believe that BG-DTI can facilitate the development of drug discovery or drug repurposing.

Abstract Flexible organic materials that exhibit dynamic ultralong room temperature phosphorescence (DURTP) via photoactivation have attracted increasing research interest for their fascinating functions of reversibly writing-reading-erasing graphic information in the form of a long afterglow. However, due to the existence of a nonnegligible activation threshold for the initial exposure dose, the display mode of these materials has thus far been limited to binary patterns. By resorting to halogen element doping of carbon dots (CDs) to enhance intersystem crossing and reduce the activation threshold, we were able to produce, for the first time, a transparent, flexible, and fully programmable DURTP composite film with a reliable grayscale display capacity. Examples of promising applications in UV photography and highly confidential steganography were constructed, partially demonstrating the broad future applications of this material as a programmable platform with a high optical information density.

Atomically precise boundaries of two-dimensional crystals can play host to novel electronic properties. Here, the authors identify distinct one dimensional electronic states corresponding to different atomically sharp edge terminations of monolayer 1H-NbSe2 and, as a result, the intrinsic charge density wave in the material is reconstructed into a stripe ordering near the crystal edge.

Abstract Background In the present research, challenges arose when many reports have been published on the poisoning of humans due to the ingestion of crops of Crataegus plants contaminated with cyanobacterial toxins. The discovery of several poisonings around agricultural zones prompted us to study the toxic compounds in a strain of Neowestiellopsis which is the most abundant in the agricultural zones of Kermanshah province of Iran, using a polyphasic approach. Molecular procedure was followed to study these strains deeply. Material and methods To elucidate their systematic position, besides the 16S rRNA gene, the analyses of molecular toxicity markers, namely nos, mcy G, mcy D and internal transcribed spacer (ITS), were also used. Results Based on the results, for the first time, we record the presence of a gene cluster coding for the biosynthesis of a bioactive compound (Nostopeptolides) that is very rare in this family and the presence of toxic compounds (microcystin), which might account for the poisoning of humans. Conclusions This case is the first observation of a toxic soil strain from the genus Neowestiellopsis from agricultural fields in Iran.

Single-layer NbSe2 has a charge density wave with two degenerate domains, related by mirror reflection. Here, using scanning tunneling microscopy, the authors observe the time-dependent movement of domain walls, and demonstrate reversible switching between the two domain types using a voltage pulse from the microscope tip.

A self-alignment attention-guided residual-in-residual dense generative adversarial networks architecture closes the gap between speed, field of view, and image quality of label-free nonlinear optical microscopes which are notoriously slow.

Introduction:Alpiniae oxyphyllae Fructus (AOF) has been abundantly utilized for the treatment of diarrhea, dyspepsia, kidney asthenia, and abdominal pain in China. AOF is effective for treating AD in clinical trials, but its exact mode of action is yet unknown.Methods: In this study, metabolomics was combined to ascertain the alterations in plasma metabolism in APP/PS1 transgenic mice, the therapy of AOF on model mice, and the dynamic variations in 15 bile acids (BAs) concentration.Results: 31 differential biomarkers were finally identified in APP/PS1 group vs. the WT group. The levels of 16 metabolites like sphinganine (Sa), lyso PE (20:2), lysoPC (17:0), glycocholic acid (GCA), deoxycholicacid (DCA) were increased in APP/PS1 group, and those of 15 metabolites like phytosphingosine, cer (d18:0/14:0), and fumaric acid were reduced in APP/PS1 group. After AOF treatment, 29 of the 31 differential metabolites showed a tendency to be back-regulated, and 15 metabolites were significantly back-regulated, including sphinganine (Sa), lyso PE (20:2), glycocholic acid (GCA), deoxycholic acid (DCA). The relationship between BAs level and AD had been received increasing attention in recent years, and we also found notable differences between DCA and GCA in different groups. Therefore, a BAs-targeted metabonomic way was established to determine the level of 15 bile acids in different groups. The consequence demonstrated that primary BAs (CA, CDCA) declined in APP/PS1 model mice. After 3 months of AOF administration, CA and CDCA levels showed an upward trend. Conjugated primary bile acids (TCA, GCA, TCDCA, GCDCA), and secondary bile acids (DCA, LCA, GDCA, TDCA, TLCA GLCA) ascended in APP/PS1 group. After 3 months of AOF treatment, the levels of most BAs decreased to varying degrees. Notably, the metabolic performance of DCA and GCA in different groups was consistent with the predictions of untargeted metabolomics, validating the correctness of untargeted metabolomics.Discussion: According to metabolic pathways of regulated metabolites, it was prompted that AOF ameliorated the symptom of AD mice probably by regulating bile acids metabolism. This study offers a solid foundation for further research into the AOF mechanism for the therapy of AD.

As a fundamental task in power system operations, transmission-constrained unit commitment (TCUC) decides ON/OFF state (i.e., commitment) and scheduled generation for each unit. Generally, TCUC is formulated as a mixed-integer linear programming (MILP) and must be resolved within a limited time window. However, due to the NP-hard property of MILP and the increasing complexity of power systems, solving the TCUC within a limited time is computationally challenging. Regarding the computation challenge, the availability of historical TCUC data and the development of the machine learning (ML) community are potentially helpful. To this end, this paper designs an ML-aided framework that can leverage historical data in enabling computation improvement of TCUC. In the offline stage, ML models are trained to predict the commitments based on historical TCUC data. In the online stage, the commitments are quickly predicted using the well-trained ML. Furthermore, a feasibility checking process is conducted to ensure the commitment feasibility. As a result, only a reduced TCUC with fewer binary variables needs to be solved, leading to computation acceleration. Case studies on an IEEE 24-bus and a practical 5655-bus system show the effectiveness of the presented framework.

Reducing circuit redundancy represents a priority for the scalability of parallel computing hardware. Here, the authors report the realization of pixel processing units consisting of single 2D WSe2 transistors implementing electrically-switchable logic functions. This strategy enables the fabrication of an image processing array with ~16% transistor consumption compared to traditional circuits.

The properties of mesoporous nanomaterials have been exploited for several applications, including drug delivery and NIR-II photoacoustic imaging. Here, the authors design monodispersed semimetallic mesoporous antimony nanospheres with photothermal conversion efficiency in the second near-infrared range and drug loading capacity, showing their potential for cancer photothermal/chemo therapy.

This paper considers a retrial G-queue with collisions, transmission errors, and a finite number of sources, where service and repair time are both general distributions. The number of sources (terminals) is finite and a source cannot generate new requests until the channel (server) finishes its work, i.e., the rate at which new primary requests are generated varies inversely with the number of data frame (customer) in the system. A collision occurs when service requests arrive at a busy channel, and transmission errors prevent data frames from leaving the system after completing service. Two types of arrivals are considered. Negative customers will break down the system in the busy state and remove the customer under service. The application of our model is indicated, with a particular emphasis on communication networks such as the local-area networks (LAN) with CSMA/CD protocol. Recursive formulas have been derived to calculate the stationary joint distributions and the Laplace transform of reliability function by applying the discrete transformations method along with the supplementary variables technique (SVT). Furthermore, the comparative performance and reliability analysis have been conducted numerically. Numerical examples are provided to investigate the sensitivity of different parameters on performance measures and reliability indicators.