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Aggregate grading design is the foundation of concrete mix proportion design. Existing aggregate grading design methods are based on the tightest accumulation theory of homogeneous natural aggregates. However, this method has not been applied to mixed recycled aggregate (MRA) containing coal gangue brick aggregate (CGBA) (hereinafter referred to as MRA) due to significant differences in physical and mechanical properties. In this study, we subjected five types of MRA (initial particle size: 19–26.5 mm) to confined crushing, sieving, and grading composition analysis, then configured recycled concrete. We investigated the determination method of the optimal gradation of MRA, summarized the composition, particle distribution characteristics, and fractal characterization of the optimal gradation. This study focused on analyzing the factors that affect the compressive strength of recycled concrete, as well as examining the mix proportion design method. The results reveal that the optimal gradation of MRA can be determined using the five-stage loading method for approach minimum porosity. Our analysis of MRA gradation suggests that the mix proportion design of recycled concrete should be determined by considering the porosity of optimal gradation and the surplus volume coefficient of slurry. Finally, we determined that the water-binder (W/B) ratio is the primary factor that affects the compressive strength, while the CGBA’s intrinsic strength has a minimal impact. The replacement ratio of CGBA primarily affects the porosity of MRA and the W/B ratio, indirectly reducing recycled concrete’s compressive strength. Based on our findings, we recommend that the replacement ratio of CGBA should not exceed 50%. This study can promote the recycling of recycled concrete containing CGBA.

Saikosaponin D (SSd) is a naturally active product with strong pharmacological activity found in Bupleurum scorzonerifolium Willd. Studies have shown that endophytic fungi have great potential as sources of natural medicines. Fusarium acuminatum (CHS3), an SSd-producing endophytic fungus, was isolated from B. scorzonerifolium. To elucidate the effect of host plants on the production of SSd in CHS3, CHS3 was co-cultured with suspension cells of B. scorzonerifolium and SSd was detected using high-performance liquid chromatography (HPLC). Transcriptome sequencing (RNA-Seq) of CHS3 before and after co-culture was performed using an Illumina HiSeq 2500 platform. The results indicated that the content of SSd synthesised by CHS3 increased after co-culture with suspension cells of B. scorzonerifolium. Transcriptome analysis of CHS3 with differentially expressed genes (DEGs) showed that 1202 and 1049 genes were upregulated and downregulated, respectively, after co-culture. Thirty genes associated with SSd synthesis and 11 genes related to terpene backbone biosynthesis were annotated to the Kyoto Encyclopaedia of Genes and Genomes (KEGG). Combined with transcriptome data, it was speculated that the mevalonate (MVA) pathway is a possible pathway for SSd synthesis in CHS3, and the expression of key enzyme genes (HMGR, HMGCS, GGPS1, MVK, FDFT1, FNTB) was validated by qRT-PCR. In conclusion, the endophytic fungus CHS3 can form an interactive relationship with its host, thereby promoting SSd biosynthesis and accumulation by upregulating the expression of key enzyme genes in the biosynthesis pathway.

IntroductionThe wellbeing of retired teachers is often easily overlooked. This study aims to explore the mental health status and influencing factors of retired teachers.MethodFrom October to December 2022, a convenient sampling survey was conducted on retired teachers using the Symptom Checklist 90 (SCL-90), mainly using the χ2-test and logistic regression analysis.ResultsA sampling survey was conducted on 353 retired teachers, with an overall positive detection rate of 16.1%. The five factors with the highest positive detection rate were found to be obsessive-compulsive disorder (30.3%), interpersonal sensitivity (21.5%), paranoia (20.1%), anxiety (19.3%), and others (19.3%). The detection rates for the five factors, namely psychosis, depression, hostility, terror, and somatization, are all below 19%. The data on sex (χ2 = 4.626, P = 0.043), professional title (χ2 = 17.670, P = 0.003), income (χ2 = 9.960, P = 0.041), life satisfaction (χ2 = 27.348, P = 0.000), family relationships (χ2 = 51.451, P = 0.000), and physical health status (χ2 = 50.361, P = 0.000) show that the difference in mental health among retired teachers is statistically significant. The multivariate binary logistic regression analysis revealed that family relationships, life satisfaction, and physical health were important factors leading to mental health problems among retired teachers.DiscussionRetired teachers should cultivate a wide range of interests and hobbies, engage in regular physical exercise, develop healthy living habits, foster a positive family atmosphere, establish harmonious family relationships, promote community cultural construction, strengthen psychological intervention, and prevent psychological diseases.

A novel vernier effect filter is designed utilizing two cascaded Mach–Zehnder interferometers (MZIs). Integrating the filter into an erbium-doped fiber laser (EDFL), the tunability of laser wavelength is achieved. Each MZI comprises two sequentially interconnected 3 dB optical couplers (OCs), where the incoming light is initially split into two arms at the first OC and subsequently recombined at the second OC. Interference occurs due to the optical path difference between these two beams. Notably, the two MZIs exhibit closely matched free spectral ranges (FSRs), leading to the formation of a broadened envelope in the superimposed spectrum. By delicately adjusting the optical path difference between the two arms of one MZI, a little drift of the interference spectrum is induced. This small amount of drift, in turn, triggers a significant movement of the envelope, giving rise to the so-called vernier effect. Integrating the vernier effect filter into an EDFL, the wavelength of the fiber laser can be tuned from 1542.56 nm to 1556.62 nm, with a tuning range of 14.06 nm. Furthermore, by employing a high-precision stepper motor, a remarkable tuning accuracy of 0.01 nm is attainable. The side mode suppression ratio of all wavelengths is above 55 dB. In comparison to reported tunable fiber lasers utilizing MZI filters, the proposed fiber laser in this study offers enhanced precision and a more user-friendly tuning process.

Abstract Background Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and malignant thyroid calcified nodules. Methods This retrospective study, conducted at two centers, involved a total of 631 thyroid nodules, all of which were pathologically confirmed. Ultrasound image sets were employed for analysis. The primary evaluation index was the area under the receiver-operator characteristic curve (AUROC). We compared the diagnostic performance of deep learning (DL) methods with that of radiologists and determined whether DL could enhance the diagnostic capabilities of radiologists. Results The Xception classification model exhibited the highest performance, achieving an AUROC of up to 0.970, followed by the DenseNet169 model, which attained an AUROC of up to 0.959. Notably, both DL models outperformed radiologists (P

The von Neumann architecture is no longer sufficient for handling large-scale data. In-memory computing has emerged as the potent method for breaking through the memory bottleneck. A new 10T SRAM bitcell with row and column control lines called RC-SRAM is proposed in this article. The architecture based on RC-SRAM can achieve bi-directional and operand-controllable logic-in-memory and search operations through different signal configurations, which can comprehensively respond to various occasions and needs. Moreover, we propose threshold-controlled logic gates for sensing, which effectively reduces the circuit area and improves accuracy. We validate the RC-SRAM with a 28 nm CMOS technology, and the results show that the circuits are not only full featured and flexible for customization but also have a significant increase in the working frequency. At VDD = 0.9 V and T = 25 °C, the bi-directional search frequency is up to 775 MHz and 567 MHz, and the speeds for row and column Boolean logic reach 759 MHz and 683 MHz.

Background: Both calcification and colloid in thyroid nodules are reflected as echogenic foci in ultrasound images. However, calcification and colloid have significantly different probabilities of malignancy. We explored the performance of a deep learning (DL) model in distinguishing the echogenic foci of thyroid nodules as calcification or colloid. Methods: We conducted a retrospective study using ultrasound image sets. The DL model was trained and tested on 30,388 images of 1127 nodules. All nodules were pathologically confirmed. The area under the receiver-operator characteristic curve (AUC) was employed as the primary evaluation index. Results: The YoloV5 (You Only Look Once Version 5) transfer learning model for thyroid nodules based on DL detection showed that the average sensitivity, specificity, and accuracy of distinguishing echogenic foci in the test 1 group (n = 192) was 78.41%, 91.36%, and 77.81%, respectively. The average sensitivity, specificity, and accuracy of the three radiologists were 51.14%, 82.58%, and 61.29%, respectively. The average sensitivity, specificity, and accuracy of distinguishing small echogenic foci in the test 2 group (n = 58) was 70.17%, 77.14%, and 73.33%, respectively. Correspondingly, the average sensitivity, specificity, and accuracy of the radiologists were 57.69%, 63.29%, and 59.38%. Conclusions: The study demonstrated that DL performed far better than radiologists in distinguishing echogenic foci of thyroid nodules as calcifications or colloid.

ObjectiveTo investigate the effect of transrectal multimodal ultrasound combined with serum prostate-specific antigen (PSA)-related indicators and machine learning for the diagnosis of clinically significant prostate cancer.MethodsBased on Gleason score of postoperative pathological results, the subjects were divided into clinically significant prostate cancer groups(GS>6)and non-clinically significant prostate cancer groups(GS ≤ 6). The independent risk factors were obtained by univariate logistic analysis. Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) machine learning models were combined with clinically significant prostate cancer risk factors to establish the machine learning model, calculate the model evaluation indicators, construct the receiver operating characteristic curve (ROC), and calculate the area under the curve (AUC).ResultsIndependent risk factor items (P< 0.05) were entered into the machine learning model. A comparison of the evaluation indicators of the model and the area under the ROC curve showed the ANN model to be best at predicting clinically significant prostate cancer, with a sensitivity of 80%, specificity of 88.6%, F1 score of 0.897, and the AUC was 0.855.ConclusionEstablishing a machine learning model by rectal multimodal ultrasound and combining it with PSA-related indicators has definite application value in predicting clinically significant prostate cancer.

Coal gangue is a kind of solid waste. A high-ductility cement-calcined coal-gangue-powder-composite-based rapid repair material (HD-RRM) was prepared by partially replacing cement with calcined coal gangue powder (CCGP) for achieving high ductility and rapid hardening and conforming to the strength requirements of pavement layers. First, the physical and chemical properties and the reactivity of the CCGP were investigated. Second, HD-RRM material was prepared, and its tensile performance characteristic parameters were investigated. Lastly, the hydration products and microstructure of HD-RRM were characterized through tests (e.g., non-evaporable water content, scanning electron microscopy (SEM), X-ray diffraction (XRD), and comprehensive thermogravimetric analysis and differential scanning calorimetry (TG-DSC)). As indicated by the experimental results, the CCGP with a particle size of 1250 mesh exhibited the maximum potential reactivity. The optimal mixing ratio for HD-RRM in the experiments comprised a water–cement ratio of 0.27, a sand–cement ratio of 0.3, a fiber volume fraction of 2%, a cement content of 70%, a CCGP content of 20%, a fly ash (FA) content of 10%, and a superplasticizer content of 0.1%. Using the abovementioned mix design, the prepared HD-RRM was endowed with a 6 h ultimate elongation of 2.75%, an ultimate tensile strength of 7.58 MPa, a compressive strength of 45.4 MPa, and an average crack width of 125.53 μm, which meets the requirements of repair materials and provides a design method for CCGP resource utilization and asphalt concrete road and bridge deck repair.

Abstract Invasive species are a major driver of ecological and environmental changes that affect human health, food security, and natural biodiversity. The success and impact of biological invasions depend on adaptations to novel abiotic and biotic selective pressures. However, the molecular mechanisms underlying adaptations in invasive parasitic species are inadequately understood. Small hive beetles, Aethina tumida, are parasites of bee nests. Originally endemic to sub‐Saharan Africa, they are now found nearly globally. Here, we investigated the molecular bases of the adaptations to novel environments underlying their invasion routes. Genomes of historic and recent adults A. tumida from both the endemic and introduced ranges were compared. Analysis of gene–environment association identified 3049 candidate loci located in 874 genes. Functional annotation showed a significant bias toward genes linked to growth and reproduction. One of the genes from the apoptosis pathway encodes an “ecdysone‐related protein,” which is a crucial regulator in controlling body size in response to environmental cues for holometabolous insects during cell death and renewal. Genes whose proteins regulate organ size, ovary activation, and oviposition were also detected. Functions of these enriched pathways parallel behavioral differences between introduced and native A. tumida populations, which may reflect patterns of local adaptation. The results considerably improve our understanding of the underlying mechanisms and ecological factors driving adaptations of invasive species. Deep functional investigation of these identified loci will help clarify the mechanisms of local adaptation in A. tumida.

The small hive beetle (SHB), a social parasite of beehives, is native to sub-Saharan Africa and has spread to America, Europe, and Australia. Recently, these beetles invaded China, causing widespread colony collapses in the honeybee, Apis cerana. In this study, single nucleotide polymorphisms (SNPs) were identified in the beetle genome from its native range (Africa), a region that was invaded by SHBs nearly 30 years ago (America), and more recent invasions (Asia). The beetles in the United States formed the earliest branch and show signs of two decades of gene flow and local adaptation to differentiate this population from the native ones. The beetles in China were deep branched and showed the highest fixation index when compared to the US populations. The number of SNPs in overexpressed genes was significantly higher than the transcriptome. Gene-expression profiles presented here distinguish the characters between adult and larvae SHBs.

Streptovaricin C is an antibiotic containing a methylenedioxy bridge (MDB) moiety essential for its activity. Here, the authors show that a P450 monooxygenase StvP2 catalyses MDB formation, report its crystal structure in complex with the substrate, and elucidate mechanistic details of MDB formation.

Abstract Background The alarming spread of antimicrobial resistance requires the development of novel anti-infective drugs. Despite the recent research focus on the human microbiome and its likely value to understand and exploit inter-bacterial inhibitory phenomena as a source for antimicrobial strategies, the human microbiota has barely been investigated for the purpose of drug development. Results We performed a large screen analyzing over 3000 human skin isolates to evaluate bacterial competition within the human skin microbiota as a basis for the development of anti-infective therapeutics. We discovered a Staphylococcus hominis strain with strong and broad activity against Gram-positive pathogens that was mediated by the bacteriocin micrococcin P1 (MP1). In “probiotic” approaches, this strain led to reduced Staphylococcus aureus infection and accelerated closure of S. aureus-infected wounds. Furthermore, we used a nanoparticle strategy to overcome the physico-chemical limitations often encountered with natural substances such as MP1 and demonstrate a significant reduction of S. aureus infection by MP1-loaded nanoparticles. Conclusions Our study gives examples of how analysis of bacterial interactions in the human microbiota can be explored for the development of novel, effective anti-infective strategies. Video Abstract

The deformation performance of recycled aggregate concrete can be effectively improved when basalt fiber is reasonably added. In this paper, the effects of the basalt fiber volume fraction and the length–diameter ratio on the uniaxial compression-related failure characteristics, feature points of the complete stress–strain curve and the compressive toughness of recycled concrete under different replacement rates of recycled coarse aggregate were studied. The results showed that with the increase in the fiber volume fraction, the peak stress and peak strain of basalt fiber-reinforced recycled aggregate concrete first increased and then decreased. With the increase in the fiber length–diameter ratio, the peak stress and strain of the basalt fiber-reinforced recycled aggregate concrete first increased and then decreased, whereas the effect of the length–diameter ratio on peak stress and strain of the basalt fiber-reinforced recycled aggregate concrete was clearly smaller than that of the fiber volume fraction. Based on the test results, an optimized stress–strain curve model of concrete under uniaxial compression was proposed for the basalt fiber-reinforced recycled aggregate concrete. Furthermore, it was found that the fracture energy is more suitable for evaluating the compressive toughness of the basalt fiber-reinforced recycled aggregate concrete than the tensile–compression ratio.

The diffusion-based algorithm is a promising member of the family of recommendation algorithms. It makes recommendations through the diffusion process on user-object bipartite graphs. However, a user’s taste is often influenced by his/her trusted friends in social networks. In this paper, we propose a new trust-based diffusion on tripartite graphs, which integrates explicit trust relations and implicit trust relations into the diffusion process. Explicit trust relations are obtained from the social networks while implicit trust relations are inferred from implicit feedback. The experimental results indicate that our proposed method has a remarkable improvement in accuracy, and even only implicit trust relations employed, that is, diffusion on user-object bipartite graphs, the recommendation accuracy is still enhanced. We further present a general framework of applying implicit trust relations and explicit trust relations into basic network-based diffusion method, which is more general and flexible, and specific parameters can be selected to meet actual requirements for different datasets and real-world online platforms.

An experimental study on the bond behavior of reinforcing steel bars in thermal insulation concrete (TIC) mixed with glazed hollow beads (GHBs) and exposed to freeze-thaw (F-T) cycles was carried out. In order to investigate the effects of GHBs on freezing and thawing, the experimental results were compared with those of normal concrete (NC). The comparison shows that, after 300 F-T cycles, both bond behavior and mechanical properties of the TIC specimens are better than those of the NC specimens. Furthermore, in order to investigate the mechanism of frost effect on TIC, the CT scanning method was used to investigate the evolution of the inner structure of a TIC specimen exposed to F-T cycles. The CT images show that the deterioration of bond performance and mechanical properties of the TIC specimen appears to be caused by the increase of micropores in the TIC.

Olfaction is key to many insects. Odorant receptors (ORs) stand among the key chemosensory receptors mediating the detection of pheromones and kairomones. Small hive beetles (SHBs), Aethina tumida, are parasites of social bee colonies and olfactory cues are especially important for host finding. However, how interactions with their hosts may have shaped the evolution of ORs in the SHB remains poorly understood. Here, for the first time, we analyzed the evolution of SHB ORs through phylogenetic and positive selection analyses. We then tested the expression of selected OR genes in antennae, heads, and abdomens in four groups of adult SHBs: colony odor-experienced/-naive males and females. The results show that SHBs experienced both OR gene losses and duplications, thereby providing a first understanding of the evolution of SHB ORs. Additionally, three candidate ORs potentially involved in host finding and/or chemical communication were identified. Significantly different downregulations of ORs between the abdomens of male and female SHBs exposed to colony odors may reflect that these expression patterns might also reflect other internal events, e.g., oviposition. Altogether, these results provide novel insights into the evolution of SHB ORs and provide a valuable resource for analyzing the function of key genes, e.g., for developing biological control. These results will also help in understanding the chemosensory system in SHBs and other beetles.

This paper explores the security vulnerability of Personal Identification Number (PIN) or numeric passwords. Entry Device (PEDs) that use small strings of data (PINs, keys or passwords) as means of verifying the legitimacy of a user. Today, PEDs are commonly used by personnel in different industrial and consumer electronic applications, such as entry at security checkpoints, ATMs and customer kiosks, etc. In this paper, we propose a side-channel attack on a 4–6 digit random PIN key, and a PIN key user verification method. The intervals between two keystrokes are extracted from the acoustic emanation and used as features to train machine-learning models. The attack model has a 60% chance to recover the PIN key. The verification model has an 88% accuracy on identifying the user. Our attack methods can perform key recovery by using the acoustic side-channel at low cost. As a countermeasure, our verification method can improve the security of PIN entry devices.

To systematically study the effects of the number of d electrons of the first transition metal ions (Fe, Co, Ni, Cu and Zn) on the formation and stability of metal flavonoid complexes, we took the quercetin/M2+ complex as a model system to investigate the structures and properties of these complexes. Based on considerable structural information obtained through ESI-MSn, all of the first transition metal ions (Fe2+, Co2+, Ni2+, Cu2+ and Zn2+) were found to form different complexes with quercetin, while with the number of chelating flavonoids decreasing along with the reduction of the metal ionic radius. Quercetin forms different complexes with the above metal divalent ions through its 5-OH and 4-carbonyl groups; the complex stability is highly dependent on both the metallic ion and the flavonoid chelator itself. As for the central ion (M2+), when chelated with quercetin to form the complex, the stability of the complex decreased in the following order: Cu2+ > Ni2+ > Co2+ > Fe2+ > Zn2+. With flavonoid: metal stoichiometries at 2:1, the complexes formed between quercetin and metal ions (Fe2+, Ni2+, Co2+ and Zn2+) have the similar fragmentation mechanism, while Cu2+ displayed different fragmentation mechanism due to the concurrent oxidation.

This research analyzes the thermal and strain behavior of external thermal insulation cladding systems (ETICS) with Glazed Hollow Beads (GHB) thermal insulation mortar under hygrothermal cycles weather test in order to measure its durability under extreme weather (i.e., sunlight and rain). Thermometers and strain gauges are placed into different wall layers to gather thermal and strain data and another instrument measures the crack dimensions after every 4 cycles. The results showed that the finishing coat shrank at early stage (elastic deformation) and then the finishing coat tends to expand and become damaged at later stage (plastic deformation). The deformation of insulation layer is similar to that of the finishing coat but its variation amplitude is smaller. Deformation of substrate expanded with heat and contracted with cold due to the small temperature variation. The length and width of cracks on the finishing coat grew as the experiment progressed but with a decreasing growth rate and the cracks stopped growing around 70 cycles.

Objectives: This study aimed to evaluate the value of a model combining conventional ultrasonography and clinicopathologic features for predicting axillary status after neoadjuvant therapy in breast cancer. Methods: This retrospective study included 329 patients with lymph node-positive who underwent neoadjuvant systemic treatment (NST) from June 2019 to March 2022. Ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes were analyzed before and after NST. The diagnostic efficacy of ultrasound, clinicopathological characteristics, and combined model were evaluated using multivariate logistic regression and receiver operator characteristic curve (ROC) analyses. Results: The area under ROC (AUC) for the ability of the combined model to predict the axillary pathological complete response (pCR) after NST was 0.882, that diagnostic effectiveness was significantly better than that of the clinicopathological model (AUC of 0.807) and the ultrasound feature model (AUC of 0.795). In addition, eight features were screened as independent predictors of axillary pCR, including clinical N stage, ERBB2 status, Ki-67, and after NST the maximum diameter reduction rate and margins of breast lesions, the short diameter, cortical thickness, and fatty hilum of lymph nodes. Conclusions: The combined model constructed from ultrasound and clinicopathological features for predicting axillary pCR has favorable diagnostic results, which allowed more accurate identification of BC patients who had received axillary pCR after NST. Advances in knowledge: A combined model incorporated ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes demonstrated favorable performance in evaluating axillary pCR preoperatively and non-invasively. [ABSTRACT FROM AUTHOR]