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To improving citizen’s living quality and management efficiency, the construction of smart cities is critical on the agenda. Smart cities are highly dependent on multiple innovative technologies. City Information Modelling (CIM) is a promising approach that meets the implementation requirements of sustainable smart cities through various technology integrations. Therefore, this paper extracted 99 articles from the Web of Science core collection database from 2012 to 2022 for bibliometric analysis and investigated the research themes on the current development of CIM from theory, technology, and application perspectives. Based on the results of the holistic framework of each domain, existing problems and further development directions are proposed to govern the sustainable smart cities based on CIM. According to the findings, CIM, as a tool to aid decision-making for planning and managing sustainable smart cities, greatly promotes city development in the direction of intelligence and sustainability.

Abstract Breast reconstruction is essential for improving the appearance of patients after cancer surgery. Traditional breast prostheses are not appropriate for those undergoing partial resections and cannot detect and treat locoregional recurrence. Personalized shape prostheses that can smartly sense tumor relapse and deliver therapeutics are needed. A 3D‐printed prosthesis that contains a therapeutic hydrogel is developed. The hydrogel, which is fabricated by crosslinking the polyvinyl alcohol with N1‐(4‐boronobenzyl)‐N3‐(4‐boronophenyl)‐N1, N1, N3, N3‐tetramethylpropane‐1,3‐diaminium, is responsive to reactive oxygen species (ROS) in the tumor microenvironment. Specifically, RSL3, a ferroptosis inducer that is loaded in hydrogels, can trigger tumor ferroptosis. Intriguingly, RSL3 encapsulated in the ROS‐responsive hydrogel exerts antitumor effects by increasing the numbers of tumor‐infiltrated CD4+ T cells, CD8+ T cells, and M1 macrophages while reducing the number of M2 macrophages. Therefore, this new prosthesis not only allows personalized shape reconstruction, but also detects and inhibits tumor recurrence. This combination of aesthetic appearance and therapeutic function can be very beneficial for breast cancer patients undergoing surgery.

To enhance the application of building information modeling (BIM) in schedule management for engineering projects, improve spatial planning capabilities, and minimize subjective factors in schedule preparation, this paper presents a framework and method for automatic construction schedule planning based on BIM and data-driven approaches under multi-dimensional spatial resource constraints. The method includes data acquisition, construction process reasoning, time parameter calculation, and schedule generation and scheduling. Initially, the construction data from the BIM model and manual input are imported into the reasoning system to establish the logical relationships of the construction process. Construction time parameters and spatial resource requirements are then automatically calculated using MySQL. Subsequently, the spatial layout and resource allocation data exported from the BIM model are compared to assess whether the space meets the project requirements. Finally, a construction schedule that satisfies the space constraints is generated. The method was validated through a case study, demonstrating its effectiveness in automatic schedule planning under human-computer interaction. This study introduces an innovative approach that considers spatial conflicts in the automatic scheduling process, improving planning efficiency and reducing the risk of spatial conflicts on construction sites.

Pregabalin is a prescription medicine that has recently been approved for individuals who suffer from fibromyalgia, neuropathic pain, anxiety disorder, or epilepsy. Pregabalin has the side effects of dizziness, sleepiness, and angioedema. Pregabalin-induced rhabdomyolysis has been rarely reported, with only four reports to date. We report two cases of rhabdomyolysis after pregabalin treatment. A man aged older than 90 years presented with exhaustion, muscle aches, and a high serum creatine kinase concentration after taking 75 mg of pregabalin on the first day of treatment. A woman in her 90s with long-term use of pregabalin presented with considerably elevated serum creatine kinase concentrations. Both patients had a long history of taking statins. Pregabalin therapy was stopped, high-volume intravenous fluids were administered, and serum electrolytes were frequently checked. Alkalinisation was performed with excellent outcomes. The Naranjo Adverse Drug Reaction scale and previous research suggest an association between pregabalin and rhabdomyolysis. Clinicians should be alert to the possibility of rhabdomyolysis occurring with the use of pregabalin, especially when taking statins.

Background Oxidative stress plays a principal role in the pathogenesis of white matter hyperintensities (WMHs). The induction of heme oxygenase‐1 (HO‐1) gene in the brain represents 1 of the pivotal mechanisms to counteract the noxious effects of reactive oxygen species, and the transcriptional modulation of HO‐1 induction depends on the length of a GT‐repeat (GT)n in the promoter region. We investigated whether the HO‐1 gene (GT)n polymorphism is associated with the risk of WMHs. Methods and Results A total of 849 subjects from the memory clinic were consecutively enrolled, and the HO‐1 (GT)n genotype was determined. WMHs were assessed with the Fazekas scale and further divided into periventricular WMHs and deep WMHs (DWMHs). Allelic HO‐1 (GT)n polymorphisms were classified as short (≤24 (GT)n), median (25≤[GT]n

High-entropy oxides (HEOs) have received significant attention because of their tunable mechanical properties and wide range of functional applications. However, the conventional method used for sintering HEOs requires prolonged processing time, which results in excessive grain growth, thereby compromising their performance. Here, an ultrafast high-temperature sintering (UHS) strategy was adopted, and rock-salt composite (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)O was selected as model materials. Experimental parameters were tuned to illustrate the influence of applied current and soaking time on the densification process and resulting grain size. Additionally, the electrochemical performance of UHS-synthesized microparticles as anode materials in lithium-ion batteries was investigated. The results show that the ultrafast heating rate results in fine grains with a diameter of ~6–8 μm and density of 95%, which are much smaller and similar to those obtained using the conventional sintering method (25 μm and 96%). Moreover, the high surface area and reactivity of the microparticles, as well as their sluggish diffusion effect and structural stability, contribute to outstanding performance with high capacity (336 mA·h/g at 1 A/g) and ultralong cyclability (1000 cycles). This novel technique offers valuable insights into the densification process of HEOs and other materials and can thus broaden their application range.

The tassel state in maize hybridization fields not only reflects the growth stage of the maize but also reflects the performance of the detasseling operation. Existing tassel detection models are primarily used to identify mature tassels with obvious features, making it difficult to accurately identify small tassels or detasseled plants. This study presents a novel approach that utilizes unmanned aerial vehicles (UAVs) and deep learning techniques to accurately identify and assess tassel states, before and after manually detasseling in maize hybridization fields. The proposed method suggests that a specific tassel annotation and data augmentation strategy is valuable for substantial enhancing the quality of the tassel training data. This study also evaluates mainstream object detection models and proposes a series of highly accurate tassel detection models based on tassel categories with strong data adaptability. In addition, a strategy for blocking large UAV images, as well as improving tassel detection accuracy, is proposed to balance UAV image acquisition and computational cost. The experimental results demonstrate that the proposed method can accurately identify and classify tassels at various stages of detasseling. The tassel detection model optimized with the enhanced data achieves an average precision of 94.5% across all categories. An optimal model combination that uses blocking strategies for different development stages can improve the tassel detection accuracy to 98%. This could be useful in addressing the issue of missed tassel detections in maize hybridization fields. The data annotation strategy and image blocking strategy may also have broad applications in object detection and recognition in other agricultural scenarios.

Abstract Myocardial fibrosis post myocardial infarction (MI) is characterized by abnormal extracellular matrix (ECM) deposition and cardiac dysfunction could finally develop into serious heart disease, like heart failure. Lots of regulating factors involved in this pathological process have been reported while the specific mediators and underlying mechanisms remain to need to be further investigated. As part of the NAP1 family, Nucleosome assembly protein 1 like 1 (NAP1L1) is expressed in a wide variety of tissues. Here, we report that NAP1L1 is a significant regulator of cardiac fibrosis and is upregulated in ischemic cardiomyopathy patient hearts. Enhanced expression of NAP1L1 can promote cardiac fibroblasts (CFs) proliferation, migration, and differentiation into myofibroblasts. In contrast, loss of NAP1L1 decreased fibrosis‐related mRNA and protein levels, inhibited the trans‐differentiation, and blunted migration and proliferation of CFs after Transforming Growth Factorβ1（TGF‐β1）stimulation. In vivo, NAP1L1 knockout mice enhanced cardiac function and reduced fibrosis area in response to MI stimuli. Mechanically, NAP1L1 binding to Yes‐associated protein 1 (YAP1) protein influences its stability, and silencing NAP1L1 can inhibit YAP1 expression by promoting its ubiquitination and degradation in CFs. Collectively, NAP1L1 could potentially be a new therapeutic target for various cardiac disorders, including myocardial fibrosis.

Since the 20th century, there has been a wave of digitalization in homes and businesses worldwide, and smart homes have gradually become a high-profile business sector. However, behind fierce competition in the digital home market, the importance of user experience for companies to enhance their competitiveness as a business model for providing services to home users is often overlooked. Combining the industry’s basic theories and our own empirical research, this study expands the assessment perspective and assessment methods on the basis of the industry’s existing assessment methods and constructs a comprehensive assessment system that is both innovative and practical - the Smart Home Product Competitiveness Index (PCI). The index constructs a three-in-one smart home product competitiveness index assessment system for brand power, product power, and marketing power from the perspective of long-term user experience. Twelve representative enterprises were selected from the five categories of camps, covering three demand levels, six typical scenarios, and 17 mainstream products. This study shows that Internet enterprises are characterized as all-round. Traditional home appliance manufacturers, Internet enterprises, and communication carriers must strengthen the construction of product power. The competitiveness assessment method for digital home enterprises from the perspective of long-term user experience proposed in this study is effective and can provide a reference for subsequent related studies.

Rivers are one of the important sources of water supply and benthic diatoms are a crucial part of the river ecosystem. It is necessary to investigate the effects of environmental factors on river benthic diatoms. In this study, the benthic diatom assemblages, environment factors including physical–chemical factors, and altitude factors were intensively investigated in gradient tributaries of Taizi River, northeast China. The CCA method was used to explore the relationships between benthic diatom assemblages and environmental factors. The results demonstrated that the altitude, distance to river source, water temperature, TN, SS, average water depth, TP, and CODCr were the environmental factors that accounted for significant (P < 0.05) portions of the total variance in species composition. These suggest that the diatom assemblage is a good indicator of environmental change, and it is not only sensitive to physical–chemical factors but also significantly sensitive to large-scale factors (e.g., altitude, distance to river source). HIGHLIGHTS The diatom assemblage is a good indicator of environmental change.; Altitude, distance to river source, water temperature, TN, SS, average water depth, TP, and CODCr were the environmental factors that determine the community structure of diatoms.; The diatom assemblage is also sensitive to large-scale factors (e.g., altitude, distance to river source).;

The quality of the drinking water source reservoirs has always been a research hotspot. However, few have studies focused on the water quality of reservoirs over a relatively long period with time series analysis. In this paper, based on water quality and hydrological data from 2010 to 2020, considering 8 water quality parameters, CCME-WQI with time series analysis was used to explore the interannual and seasonal changes in water quality in the Weishui Reservoir. Furthermore, the main factors affecting water quality were discussed through correlation analysis. The ARIMA model is used to predict water quality in the future. The results show that the water quality was seriously polluted from 2012 to 2013. After 2018, the water quality gradually improved and stabilized. In addition, the water quality is affected by inflow, showing the characteristics of poor water quality in summer and winter. The key parameters affecting water quality are TN and TP, which are almost 2 times higher than the grade II standard of water quality standard. Through the ARIMA model, it is predicted that CCME-WQI is maintained at 80.46 indicating that the water quality will be stable in the future. HIGHLIGHTS CCME-WQI with time series analysis was used to explore changes in water quality of the Weishui Reservoir.; The water quality is mainly affected by inflow.; The key parameters affecting the water quality are TN and TP.; The ARIMA model was used to predict the changing trend of the water quality indicating that CCME-WQI is basically maintained at 80.46 and the water quality will be stable in the future.;

Two-dimensional (2D) irregular packing problems are widespread in manufacturing industries such as shipbuilding, metalworking, automotive production, aerospace, clothing and furniture manufacturing. Research on 2D irregular packing problems is essential for improving material utilization and industrial automation. Much research has been conducted on this problem with significant research results and certain algorithms. The work has made important contributions to solving practical problems. This paper reviews recent advances in the domain of 2D irregular packing problems based on a variety of research papers. We first introduce the basic concept and research background of 2D irregular packing problems and then summarize algorithms and strategies that have been proposed for the problems in recent years. Conclusion summarize development trends and research hotspots of typical 2D irregular shape packing problems. We hope that this review could provide guidance for researchers in the field of 2D irregular packing.

Injectable hydrogel has the advantage to fill the defective area and thereby shows promise as therapeutic implant or cell/drug delivery vehicle for tissue repair. In this study, an injectable hyaluronic acid hydrogel in situ dual-enzymatically cross-linked by galactose oxidase (GalOx) and horseradish peroxidase (HRP) was synthesized and optimized, and the therapeutic effect of this hydrogel encapsulated with bone mesenchymal stem cells (BMSC) and nerve growth factors (NGF) for traumatic brain injury (TBI) mice was investigated. Results from in vitro experiments showed that either tyramine-modified hyaluronic acid hydrogels (HT) or NGF loaded HT hydrogels (HT/NGF) possessed good biocompatibility. More importantly, the HT hydrogels loaded with BMSC and NGF could facilitate the survival and proliferation of endogenous neural cells probably by neurotrophic factors release and neuroinflammation regulation, and consequently improved the neurological function recovery and accelerated the repair process in a C57BL/6 TBI mice model. All these findings highlight that this injectable, BMSC and NGF-laden HT hydrogel has enormous potential for TBI and other tissue repair therapy.

Mapping is a fundamental application of remote sensing images, and the accurate evaluation of remote sensing image information extraction using artificial intelligence is critical. However, the existing evaluation method, based on Intersection over Union (IoU), is limited in evaluating the extracted information’s boundary accuracy. It is insufficient for determining mapping accuracy. Furthermore, traditional remote sensing mapping methods struggle to match the inflection points encountered in artificial intelligence contour extraction. In order to address these issues, we propose the mean inflection point distance (MPD) as a new segmentation evaluation method. MPD can accurately calculate error values and solve the problem of multiple inflection points, which traditional remote sensing mapping cannot match. We tested three algorithms on the Vaihingen dataset: Mask R-CNN, Swin Transformer, and PointRend. The results show that MPD is highly sensitive to mapping accuracy, can calculate error values accurately, and is applicable for different scales of mapping accuracy while maintaining high visual consistency. This study helps to assess the accuracy of automatic mapping using remote sensing artificial intelligence.

Fast and high-accuracy detection of underwater targets based on side scan sonar images has great potential for marine fisheries, underwater security, marine mapping, underwater engineering and other applications. The following problems, however, must be addressed when using low-resolution side scan sonar images for underwater target detection: (1) the detection performance is limited due to the restriction on the input of multi-scale images; (2) the widely used deep learning algorithms have a low detection effect due to their complex convolution layer structures; (3) the detection performance is limited due to insufficient model complexity in training process; and (4) the number of samples is not enough because of the bad dataset preprocessing methods. To solve these problems, an improved neural network for underwater target detection—which is based on side scan sonar images and fully utilizes spatial pyramid pooling and online dataset preprocessing based on the You Look Only Once version three (YOLO V3) algorithm—is proposed. The methodology of the proposed approach is as follows: (1) the AlexNet, GoogleNet, VGGNet and the ResNet networks and an adopted YOLO V3 algorithm were the backbone networks. The structure of the YOLO V3 model is more mature and compact and has higher target detection accuracy and better detection efficiency than the other models; (2) spatial pyramid pooling was added at the end of the convolution layer to improve detection performance. Spatial pyramid pooling breaks the scale restrictions when inputting images to improve feature extraction because spatial pyramid pooling enables the backbone network to learn faster at high accuracy; and (3) online dataset preprocessing based on YOLO V3 with spatial pyramid pooling increases the number of samples and improves the complexity of the model to further improve detection process performance. Three-side scan imagery datasets were used for training and were tested in experiments. The quantitative evaluation using Accuracy, Recall, Precision, mAP and F1-Score metrics indicates that: for the AlexNet, GoogleNet, VGGNet and ResNet algorithms, when spatial pyramid pooling is added to their backbone networks, the average detection accuracy of the three sets of data was improved by 2%, 4%, 2% and 2%, respectively, as compared to their original formulations. Compared with the original YOLO V3 model, the proposed ODP+YOLO V3+SPP underwater target detection algorithm model has improved detection performance through the mAP qualitative evaluation index has increased by 6%, the Precision qualitative evaluation index has increased by 13%, and the detection efficiency has increased by 9.34%. These demonstrate that adding spatial pyramid pooling and online dataset preprocessing can improve the target detection accuracy of these commonly used algorithms. The proposed, improved neural network with spatial pyramid pooling and online dataset preprocessing based on the YOLO V3 method achieves the highest scores for underwater target detection results for sunken ships, fish flocks and seafloor topography, with mAP scores of 98%, 91% and 96% for the above three kinds of datasets, respectively.

This work suggested that Cu2+ ion coordinated by the peptide with a histidine (His or H) residue in the first position from the free N-terminal reveals oxidase-mimicking activity. A biotinylated polymer was prepared by modifying His residues on the side chain amino groups of lysine residues (denoted as KH) to chelate multiple Cu2+ ions. The resulting biotin-poly-(KH-Cu)20 polymer with multiple catalytic sites was employed as the signal label for immunoassay. Prostate specific antigen (PSA) was determined as the model target. The captured biotin-poly-(KH-Cu)20 polymer could catalyze the oxidation of o-phenylenediamine (OPD) to produce fluorescent 2,3-diaminophenazine (OPDox). The signal was proportional to PSA concentration from 0.01 to 2 ng/mL, and the detection limit was found to be eight pg/mL. The high sensitivity of the method enabled the assays of PSA in real serum samples. The work should be valuable for the design of novel biosensors for clinical diagnosis.

The modification of stereoregulated functionalized polymers on the surface of natural rubber (NR) is a challenging task. This work provided a practicable grafting method to design photochromic polymer brushes on the NR surfaces using surface-initiated ring-opening metathesis polymerization (SI-ROMP). The designed photochromic polymer brushes were based on norbornenes with spiropyrin (SP) pendents, and grew from the surface of NR films in the presence of Grubbs 2nd catalyst. The results showed that the grafting rate of polymer brushes with photoisomerization structure reached up to 44.91 %. The modified natural rubber (NR-SP) films exhibited rapid coloring/decolorization property under UV irradiation and visible light. This photochromic property initiated by the light-induced isomerisation of the spiropyran structure and the increased surface energy under light stimuli. NR-SP films exhibited stable photochromic characteristics and outstanding anti-fatigue properties after exposing to over six cycles of consecutive UV/Vis irradiation. A simple and practical strategy for the preparation of highly sensitive photochromic natural rubber materials is proposed and provides a potential application in the fields of information storage and anti-counterfeiting.

Abnormal fluctuations in the mold can easily lead to slag entrainment during the thin slab continuous casting process. It is difficult to guarantee the uniform growth of the shell solidification of the slab. The quality of the slab is seriously affected. In this study, the data on thin slab mold level fluctuation were collected from a complete casting sequence of low-carbon steel in a Chinese plant. The discrete wavelet transform (DWT) method is used to decompose the mold level fluctuation and different process parameters. The frequency composition of abnormal fluctuations was clarified, and the causes of the abnormal fluctuations were revealed. The results show that the frequency ranges of abnormal fluctuations are concentrated in 0.3125–0.625 Hz and 0.625–1.25 Hz, and the low set mold level is where the maximum amplitude occurs. Within the time-frequency range, changes in parameters such as electromagnetic braking, mold oscillation, casting speed, stopper rod, and tundish weight cannot be completely matched to abnormal fluctuations collected by the eddy current sensor (ECS). It was found that the abnormal fluctuations in the ECS were that its equipment was disturbed through the analysis of the fluctuations collected by the radioactive source detection (RSD). The degree of disturbance is related to the height of the set mold level. The maximum fluctuation difference exceeded 6 mm between different collection methods when the set mold level was low. In this plant, the position of the ECS is to avoid the area of violent fluctuations of the surface molten steel and be moved appropriately towards the submerged entry nozzle (SEN) to reduce disturbance. When the current ECS position is unchanged, the mold level is set at approximately 305–309 mm, and the casting speed is matched to 4.8 m/min, which minimizes the disturbance with the ECS measurement.

This study examined effects of different processing methods on phenolic compounds in flaxseed meal. The optimal SE treatment was 1.0 MPa for 3 min, and the contents of total flavonoids and phenolic acid were 2.26 times and 1.63 times of the control group, respectively. Notably, erucic acid increased 85.76 %. Optimal extrusion conditions (15 % moisture content, 140 °C, 29 hz) led to the presence of rutin and a 2.81 times increase in protocatechuic acid content over the control. Fermenting with 3 % Bacillus subtilis for 4 days yielded gallic acid in bound form and vanillic acid in free form, with protocatechuic acid increasing 40.65 % compared to the control. Among all the treatments, extrusion produced the highest levels of phenolic compounds in flaxseed meal. Each treatment significantly increased the open ring isomer ester phenol (SDG) compared to the control. Overall, various processing methods impacted the phenolic content and composition in flaxseed meal differently.

In higher plants, the regulatory roles of cAMP (cyclic adenosine 3′,5′-monophosphate) signaling remain elusive until now. Cellular cAMP levels are generally much lower in higher plants than in animals and transiently elevated for triggering downstream signaling events. Moreover, plant adenylate cyclase (AC) activities are found in different moonlighting multifunctional proteins, which may pose additional complications in distinguishing a specific signaling role for cAMP. Here, we have developed rapeseed (Brassica napus L.) transgenic plants that overexpress an inducible plant-origin AC activity for generating high AC levels much like that in animal cells, which served the genetic model disturbing native cAMP signaling as a whole in plants. We found that overexpression of the soluble AC activity had significant impacts on the contents of indole-3-acetic acid (IAA) and stress phytohormones, i.e. jasmonic acid (JA), abscisic acid (ABA), and salicylic acid (SA) in the transgenic plants. Acute induction of the AC activity caused IAA overaccumulation, and upregulation of TAA1 and CYP83B1 in the IAA biosynthesis pathways, but also simultaneously the hyper-induction of PR4 and KIN2 expression indicating activation of JA and ABA signaling pathways. We observed typical overgrowth phenotypes related to IAA excess in the transgenic plants, including significant increases in plant height, internode length, width of leaf blade, petiole length, root length, and fresh shoot biomass, as well as the precocious seed development, as compared to wild-type plants. In addition, we identified a set of 1465 cAMP-responsive genes (CRGs), which are most significantly enriched in plant hormone signal transduction pathway, and function mainly in relevance to hormonal, abiotic and biotic stress responses, as well as growth and development. Collectively, our results support that cAMP elevation impacts phytohormone homeostasis and signaling, and modulates plant growth and development. We proposed that cAMP signaling may be critical in configuring the coordinated regulation of growth and development in higher plants.

Deep-learning-based on convolutional neural networks (CNN) has been widely applied in synthetic aperture radar (SAR) target recognition and made significant progress. However, due to the physical effects of the equipment used to collect images, various degrees of speckle noise will be introduced into SAR images. Traditional CNN-based SAR target recognition methods are premised on the same noise intensity in the training and testing set, which is contrary to the target recognition in practice. To alleviate this problem, we propose a novel speckle noise resistant framework for SAR target recognition, called dual-consistency-alignment-based self-supervised learning. First, original SAR images are randomly added to speckle noise with different thresholds through multiplicative noise, after which contrastive pretraining is performed on unlabeled data. During this period, we combine instance pseudolabel consistency alignment and feature consistency alignment to align multiple threshold speckle noise views with original views under the same targets. Finally, the pretrained model is migrated to the downstream SAR speckle noise target recognition task. In this article, speckle noise modeling is conducted based on moving and stationary target capture and recognition data testing set, and experiment results reveal that this method can adapt to different intensities of speckle noise, is robust to modeled SAR image recognition, and maintains a high recognition rate even in small-sample learning.

A simple strategy was adopted for the preparation of an antimicrobial natural rubber/graphene oxide (NR/GO) composite film modified through the use of zwitterionic polymer brushes. An NR/GO composite film with antibacterial properties was prepared using a water-based solution-casting method. The composited GO was dispersed uniformly in the NR matrix and compensated for mechanical loss in the process of modification. Based on the high bromination activity of α–H in the structure of cis-polyisoprene, the composite films were brominated on the surface through the use of N-bromosuccinimide (NBS) under the irradiation of a 40 W tungsten lamp. Polymerization was carried out on the brominated films using sulfobetaine methacrylate (SBMA) as a monomer via surface-initiated atom transfer radical polymerization (SI-ATRP). The NR/GO composite films modified using polymer brushes (PSBMAs) exhibited 99.99% antimicrobial activity for resistance to Escherichia coli and Staphylococcus aureus. A novel polymer modification strategy for NR composite materials was established effectively, and the enhanced antimicrobial properties expand the application prospects in the medical field.

Angular resolution is crucial for the detailed study of gamma-ray sources and current Cherenkov telescopes (e.g., HESS, MAGIC, and VERITAS) that operate below tens of TeV. Several gamma-ray sources with a photon energy larger than 100 TeV have been revealed by the LHAASO in recent years; the angular resolution of the LHAASO is around 0.3∘. A gamma-ray detector with an angular resolution of less than 0.1∘ operating beyond 100 TeV is needed to study the detailed morphology of ultra-high-energy gamma-ray sources further. The cost-effectiveness is crucial for such large-area detectors. In this paper, the impact of telescope aperture, field of view, pixel size, optical point spread function, and signal integration time window on angular resolution is studied. These results can provide essential elements for the design of telescope arrays.

As a kind of alkaline waste produced in the alumina production process, red mud has a high annual output, large stockpiles, and low utilization rate in this country, which poses a huge threat to the resources and environment. Extracting a large amount of valuable metal elements contained in red mud is of great significance for realizing the resource utilization of red mud. This article briefly describes the nature and composition of red mud. Research status and existing problems of extraction of valuable metal elements from red mud such as the direct magnetic separation, reduction-magnetic separation and wet processes of Fe, the reduction sintering method, calcification-carbonation method, acid leaching method and sub-molten salt extraction process of Al, fire and wet extraction process of Ti; and the combined fire-wet and wet extraction process of Sc were reviewed. TIt is believed that the current challenge for industrialized recovery of valuable metals in red mud lies in the complex composition of red mud, which leads to the technical difficulty and processing cost of valuable metal recovery, and the lack of process research on the systematic recovery of multiple elements. It is proposed that the development of more efficient technologies for the recovery of valuable metals and the strengthening of relevant research on the systematic extraction of multiple valuable metals from red mud are the keys to the realization of red mud resource utilization in the future.

To improve the ambient strength and high temperature ductility, a novel Al-3.25Mg-0.37Zr-0.28Mn-0.19Y (wt.%) alloy has been fabricated by multidirectional forging and warm rolling. Microstructures and mechanical properties were investigated by light microscope, X-ray diffraction apparatus, transmission electron microscope, and tensile tester. The ultimate tensile strength, yield strength, and elongation of 354.67 ± 0.04, 254 ± 3 MPa, and 18.47% were achieved in the processed alloy, respectively, at room temperature. The maximum superplasticity of 412.5% was demonstrated in this fine-grained (grain size of 8.80 ± 1.06 μm) alloy at 793 K and 8.33 × 10−4 s−1. An ambient strengthening sequence was obtained: grain boundary strengthening > dislocation strengthening > Orowan strengthening > solid solution strengthening. The occurrence of Portevin–Le Chatelier effect or serrated flow in as-annealed alloy was confirmed by theoretical model estimation and experimental evidence. Microstructural evolution and flow stress curves confirmed that dynamic recovery and dynamic grain growth occurred at elevated temperatures; Sotoudeh-Bate curves were discovered at higher temperatures and lower strain rates. Solute Mg, dynamic grain growth, and flow localization were responsible for the formation of Sotoudeh-Bate curves. Modified Johnson–Cook constitutive equation considering dislocation variables and power-law constitutive equation were established. In this fine-grained alloy at 793 K and 8.33 × 10−4 s−1, the number of dislocations inside a grain was 6, the stress exponent was 2, the grain size exponent was 2, and the average activation energy for deformation was 140.10 kJ/mol. These pieces of evidence demonstrated that grain boundary sliding accommodated by intragranular dislocation controlled by lattice diffusion governs the rate-controlling process.

Abstract Background Dental injury caused by caries and trauma is the main cause of residual roots. Food trapped in the residual roots is difficult to clean. If the residual roots are not treated and cared for in time, flies can take advantage as soon as hygiene slips. Here, we present a rare case of human residual root myiasis caused by Clogmia albipunctata larvae, never previously reported. Case presentation A 26-year-old lady found two active, living larvae in her mouth while brushing her teeth. She did not present with fever, pain and any uncomfortable oral feeling. The intraoral examination revealed the right second mandibular molar was severely damaged as a result of caries, leaving a residual tooth root. The mucosa above it was mildly erythematous and edematous. No larvae and no inflamed gums were observed in her mouth. When normal saline was used to flush the area of the residual root with a syringe, four larvae appeared from the residual root. The larvae were observed by naked eye and under a light microscope. They were identified as the mature stage larvae of Clogmia albipunctata. Because the patient was in lactation, medication was not recommended. Treatment included the removal of all visible larvae followed by flushing the residual root with normal saline three times a day. The patient was followed-up weekly for one month. No more larvae were found and the erythematous and edematous mucosa healed completely. Conclusions The existence of a residual root can result in residual root myiasis. Myiasis caused by Clogmia albipunctata larvae or other fly larvae should be considered in cases of residual root infection.

This study explored the role of lymphocyte antigen 6 family member D (LY6D) in colon cancer stem cells’ (CCSCs) proliferation and invasion. LY6D was knocked down using siRNA, and the down-regulation of LY6D was verified using Western blotting. After LY6D knockdown, CCSCs’ proliferation, stemness, and invasion were suppressed, whereas apoptosis was increased. Gene Ontology (GO) enrichment analysis revealed that the differentially expressed genes (DEGs) between siLY6D and the negative control groups were significantly enriched in the cell–substrate adherens junction, focal adhesion, and cell–substrate junction terms. Meanwhile, the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the DEGs were significantly enriched in the MAPK pathway. In addition, Western blotting results showed that pBRAF and pERK1/2, cascade kinases of the MAPK pathway, were significantly down-regulated after LY6D knockdown. In addition, nude mice xenograft experiments showed that the siLY6D treatment decreased tumor sizes and weights and improved tumor-bearing mice survival rates compared with the control group. In conclusion, these findings indicate that LY6D, which is highly expressed in CCSCs, is a key factor involved in tumor growth and development and might be a potential cancer marker and therapeutic target for colon cancer.

After considering the spectral correlation of structure and statistics of the hyperspectral image, the redundancy reduction is optimized using reversible transformation of integer matrices in conjunction with the N-band integer reversible transformation of spectral matrices. This paper proposes a new quantization algorithm, XCJRCT, that uses invertible matrix transformation to remove spectral redundancy and optimize bit allocation in structure. The lifting scheme of the discrete wavelet transform (DWT) is used in conjunction with other algorithms to reduce redundancy and set partitioning in hierarchical trees (SPIHT) coding. The experimental results show that lossless compression is significantly better than JPEG-LS, WinZip, ARJ, and DPCM. Using the Jet Propulsion Laboratory (JPL) Canal test image (Band Sequential) as an example data set, the average compression ratio increases by about 73.691598%, 67.713276%, 65.175242%, and 59.107580%, respectively, compared to the above algorithms.