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With the advancement of artificial intelligence, the dominance of deep learning (DL) models over ordinary machine learning (ML) algorithms has become a reality in recent years due to its capability of handling complex pattern recognition without manual feature pre-definition. With the growing demands for power savings, building energy loss reduction could benefit from DL techniques. For buildings/rooms with the varying number of occupants, heating, ventilation, and air conditioning (HVAC) systems are often found in operations without much necessity. To reduce the building’s energy loss, accurate occupancy detection/prediction (ODP) results could be used to control the proper operations of HVACs. However, ODP is a challenging issue due to multiple reasons, such as improper selection/deployment of sensors, inefficient learning algorithms for pattern recognition, varying room conditions, etc. To overcome the above challenges, we propose a DL-based framework, i.e., Deep Weighted Fusion Learning (DWFL), to detect and predict occupancy counts with optimal multi-sensor fusion structure. DWFL fuses the extracted features from multiple types of sensors with the priority/weight assignment to each sensor. Such weight assignment considers different room conditions and the pros/cons of each type of sensor. To evaluate DWFL model in terms of occupancy prediction accuracy, we have set up an experimental testbed with low-cost cameras, carbon dioxide (CO2), and passive infrared (PIR) sensors. Among the recently proposed occupancy detection models, DeepFusion utilized deep learning model on heterogeneous sensor data and achieved 88% accuracy in occupancy count estimation (Xue et al., 2019). Another deep learning-based model MI-PIR achieved 91% accuracy on raw analog data from PIR sensors (Andrews et al., 2020). Our research outcome is 94%. Therefore, the experiment results show that our DWFL scheme outperforms the state-of-the-art ODP methods by 3%.

Lotus corniculatus is an important perennial legume forage species and has been widely used to study the relationships between plants and rhizobia or arbuscular mycorrhizal fungi. Composite plants (wild-type shoots with transgenic hairy roots) can be produced via genetic transformation mediated by Agrobacterium rhizogenes. The A. rhizogenes puncture method and a method of cutting embryonic roots and coating the hypocotyl incision with A. rhizogenes were used to induce hairy roots from seedlings. The identification of transgenic hairy roots from composite plants is also an important task. Here, young branches from adult plants were used as explants to produce composite plants instead of seedlings via the one-step cutting method in the natural environment. The results showed that the explants of young branches had higher transformation frequency than those of seedlings, and the composite plants obtained from the young branches had greater growth and were also more robust than the plants obtained from the seedlings. In this study, a system for the biosynthesis of betalains named RUBY was integrated into an expression vector as a reporter gene. It is very easy to distinguish transgenic roots from nontransgenic roots based on the red color of the hairy roots. Young branches were used as explants for hairy root transformation with higher transformation frequency than the seedlings. RUBY was used as a reporter gene to distinguish transgenic roots from nontransgenic roots based on the red color of the hairy roots.

A laboratory model of a single pile embedded in Nanyang expansive soil and subjected to water infiltration is applied in this study to examine the interaction between the expansive soil and pile foundation upon water infiltration. The soil matric suction decreases as a result of the rising soil-water content. The amount of soil ground heave reaches its peak of 10.7 mm after 200 hours of water infiltration. As matric suction decreases, pile shaft friction also declines, which causes more of the load at the pile head to be carried by the pile base resulting in more pile settlements. A new numerical simulation method is provided to simulate this issue by coupling the subsurface flow, soil deformation, and hygroscopic swelling to investigate the expansive soil-pile response upon water infiltration. From the numerical simulation model, hygroscopic strain arises as a result of elevated moisture levels resulting from the entry of water, and due to ground heave and the mobilization of lateral soil swelling, the shear stress at the interface between the soil and the pile gradually increases over time. It reaches its maximum value of 4420 Pa at upper depths around 200 hours after the infiltration. The comparison between the lab model testing data and the numerical model results demonstrates a good level of concurrence.

Abstract Background An early diagnosis of pancreatic cancer (PC) is extremely difficult because of the lack of sensitive liquid biopsy methods and effective biomarkers. We attempted to evaluate whether circulating inflammatory marker could complement CA199 for the detection of early-stage PC. Methods We enrolled 430 patients with early-stage PC, 287 patients with other pancreatic tumors (OPT), and 401 healthy controls (HC). The patients and HC were randomly divided into a training set (n = 872) and two testing sets (n1 = 218, n2 = 28). The receiver operating characteristic (ROC) curves were investigated to evaluate the diagnostic performance of circulating inflammatory markers ratios, CA199, and combinations of the markers ratios in the training set, which would then be validated in the two testing sets. Results Circulating fibrinogen, neutrophils, and monocytes in patients with PC were significantly higher while circulating albumin, prealbumin, lymphocytes, and platelets of patients with PC were significantly lower compared to those of HC and OPT (all P

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. This study aimed to build a prognostic signature for HCC patients based on immune-related genes (IRGs) and epigenetics-related genes (EPGs). RNA-seq data from Gene Expression Omnibus were used for dynamic network biomarker (DNB) analysis to identify 56 candidate IRG–EPG–DNBs and their first-neighbor genes. These genes were screened using LASSO-Cox regression analysis to finally obtain five candidate genes—RNF2, YBX1, EZH2, CAD, and PSMD1—which constituted the prognostic signature panel. According to this panel, patients in The Cancer Genome Atlas and International Cancer Genome Consortium were divided into high- and low-risk groups. The prognosis, clinicopathological features, and immune cell infiltration significantly differed between the two risk groups. The prognostic ability of the signature panel and expression profiling were further validated using online databases. We used an independent cohort of patients to validate the expression profiles of the five genes using reverse transcription–PCR. CMap and CellMiner predicted four small molecule drug–protein pairs based on the five prognostic genes. Of them, two market drugs approved by the Food and Drug Administration (AT-13387 and KU-55933) have emerged as candidates for HCC study. This new signature panel may serve as a potential prognostic marker, engendering the possibility of novel personalized therapy with classification of HCC patients.

ObjectiveThe primary objective of this randomized controlled trial was to find a more economical and feasible intervention for maladaptive perfectionism, which is a risk and maintenance mechanism for various psychopathologies.MethodsIn total, 64 university students who met the total inclusion criteria were randomly assigned to either group CBT with positive psychotherapy intervention or a 16-week waitlist (WL). The intervention group received 2 h of therapy for eight weekly sessions. Measurements of maladaptive perfectionism and the symptoms of depression and anxiety were conducted at baseline, post-intervention, and follow-up.ResultsThere was no statistically significant difference in the scores of the Frost Multidimensional Perfectionism Scale, Self-Rating Depression Scale, and Self-Rating Anxiety Scale between the intervention group and the waitlist group at baseline (all p > 0.05). The intervention group had a significant main effect of time and a time × group interaction effect of the maladaptive aspects of perfectionism, Concern over Mistakes and Doubts about Actions, and depression and anxiety scores in comparison with the waitlist group at the post-intervention and 8-week follow-up and had no statistically significant effects on the scores for Personal Standards, Parental Expectation, and Parental Criticism. The analysis showed that group intervention reduced symptoms of depression and anxiety while reducing maladaptive aspects of perfectionism.ConclusionThis study added to the literature on CBT interventions for maladaptive perfectionism and indicated that group CBT with positive psychotherapy intervention had substantial long-term effects on the maladaptive perfectionism of university students in China. Moreover, the results indicated that the intervention increased participants’ self-acceptance.

Prostate cancer: stem cell treatment targets microRNA A microRNA shown to promote prostate cancer growth can be targeted through a treatment derived from stem cells. Prostate cancer is lethal for many men, and its growth is promoted by testosterone. However, some “castration-resistant” strains keep growing even after treatments that reduce testosterone levels. Xiaoyi Huang at Harbin Medical University Cancer Hospital, China, and co-workers examined the role of microRNA-375 in the progression of castration-resistant prostate cancer. They found that microRNA-375 was over-expressed in cancer tissue samples and promoted tumor growth by interfering with a specific signaling pathway. The team applied a treatment comprising extracellular vesicles called exosomes that are derived from human stem cells and loaded with molecules that suppress microRNA-375. The treatment inhibited microRNA-375 and thereby repressed the cancer growth, while also reducing the cancer’s resistance to the testosterone-blocking drug enzalutamide.

Abstract The graphene microchannel heat sinks have attracted extensive attention due to its high cooling efficiency in microelectric devices. The interfacial thermal resistance (ITR) between graphene as the bottom layer of microchannel and water is one of the key factors of its good working performance. In this paper, the impacts of structure defects in graphene surfaces on ITR of the graphene–water interface are investigated using molecular dynamic simulations. The results indicate that graphene layer with different types of structure defects shows different variation trends of ITR as the defect concentration or temperature increases. A peak ITR reduction of nearly 30% is generated with the Stone‐Wales defect of 2%. Finally, the density of phonon states and interfacial binding energy analysis are performed to verify the correctness of the simulation results. The present work expands the understanding of structure defects effect on thermal transport in graphene microchannel.

The rapid development of nanotechnology has aroused considerable attentions toward understanding the effects of engineered nanomaterials (ENMs) on the propagation of antibiotic resistance. Molybdenum disulfide (MoS2) is an extensively used ENM and poses potential risks associated with environmental exposure; nevertheless, the role of MoS2 toward antibiotic resistance genes (ARGs) transfer remains largely unknown. Herein, it was discovered that MoS2 nanosheets accelerated the horizontal transfer of RP4 plasmid across Escherichia coli in a dose-dependent manner (0.5–10 mg/L), with the maximum transfer frequency 2.07-fold higher than that of the control. Integration of physiological, transcriptomics, and metabolomics analyses demonstrated that SOS response in bacteria was activated by MoS2 due to the elevation of oxidative damage, accompanied by cell membrane permeabilization. MoS2 promoted bacterial adhesion and intercellular contact via stimulating the secretion of extracellular polysaccharides. The ATP levels were maximally increased by 305.7 % upon exposure to MoS2, and the expression of plasmid transfer genes was up-regulated, contributing to the accelerated plasmid conjugation and increased ARG abundance in soil. Our findings highlight the roles of emerging ENMs (e.g., MoS2) in ARGs dissemination, which is significant for the safe applications and risk management of ENMs under the development scenarios of nanotechnology.

BackgroundSystemic inflammation is important in the development of extrahepatic cholangiocarcinoma (ECC). The aim of this study was to compare the prognostic power of preoperative peripheral blood inflammatory markers and the novel FLR-N score in patients with resectable ECC.MethodsA total of 140 patients with resectable ECC and 140 healthy controls (HCs) were recruited for the study. The Mann−Whitney U test was used to evaluate the differences in inflammatory markers between groups. Kaplan−Meier and Cox regression analyses were used to evaluate the prognostic power of preoperative fibrinogen, albumin, prealbumin, bilirubin, neutrophils, lymphocytes, monocytes, platelets, fibrinogen-to-lymphocyte ratio (FLR), fibrinogen-to-albumin ratio (FAR), fibrinogen-to-prealbumin ratio (FPR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), FLR-neutrophil (FLR-N) score, and CA19-9 in patients with resectable ECC. Nomogram was developed based on the results of multivariate Cox analyses.ResultsPatients with resectable ECC had significantly higher levels of neutrophils, monocytes, fibrinogen, FLR, FAR, FPR, NLR, PLR, and MLR and lower levels of lymphocytes, albumin, and prealbumin than HCs (all P < 0.01). Albumin, prealbumin, and FPR had a good ability to distinguish between ECC patients with total bilirubin < 34 µmol/L and HCs (AUCs of 0.820, 0.827, and 0.836, respectively). Kaplan−Meier analysis showed that high neutrophil, fibrinogen, FLR, FAR, PLR, MLR, and FLR-N score values were associated with poor survival in patients with resectable ECC. Multivariate analyses indicated that neutrophils (P = 0.022), FLR (P = 0.040), FLR-N score (P < 0.0001), and positive lymph node metastasis (P = 0.016) were independent factors for overall survival (OS). Nomogram were developed to predict OS for patients with ECC.ConclusionThe prognostic roles of inflammatory markers in patients with resectable ECC were different. The preoperative neutrophil count, FLR and FLR-N score could serve as noninvasive markers for predicting the prognosis of resectable ECC.

This study investigated the relationships between parental responsiveness, teaching responsiveness, and creativity, as well as the mechanism underlying these associations. We collected data from 584 Chinese college students via convenience sampling method and used self-report scales to measure their perceived parental responsiveness, teaching responsiveness, creative self-efficacy, and creativity. We employed structural equation modeling (SEM) to examine the relationships among these variables and the mediation effect. The results revealed that both parental responsiveness and teaching responsiveness were positively related to student creativity. Moreover, creative self-efficacy mediated the relationships of parental responsiveness, teaching responsiveness, and creativity. The findings highlight the significance of responsiveness from parents and teachers on student creativity and verify the potential mediating role of creative self-efficacy. These findings suggest that teachers and parents can foster creativity by providing warm and supportive responses to students’ creative needs.

The safety of microplastics (MPs) and associated health effects has been one of the major concerns worldwide. However, the role of photoaging toward the risk of MPs in water ecosystems remains inconclusive yet. In this study, the size of polyamide (PA, ∼32.50 μm) MPs was obviously decreased after photoaging in water containing fulvic acid (FA) and humic acid (HA) (∼19.75 and ∼24.30 μm, respectively). Nanoplastics were formed (4.65% and 2.03%, respectively) and hydrophilia and colloidal stability was improved due to the formation of oxygen-containing functional groups. FA-aged PA exhibited higher inhibition on body length and weight of developing zebrafish than HA-aged and pristine PA. Photoaged MPs in intestine were more difficult to be depurated by zebrafish, leading to the disappearance of intestinal folding, shedding of more enterocytes, and emaciation of intestinal microvilli. Dietary lipid digestion in larvae was inhibited by aged PA due to oxidative stress-triggered lipid peroxidation and inhibition of lipase activities and bile acids secretion. Exposure of photoaged MPs down-regulated genes (cd36, dgat1a, dgat2, mttp, etc.) associated with triglyceride resynthesis and transportation, resulting in lipid maladsorption and growth inhibition. Our findings highlight the potential negative effects of environmentally aged MPs on diet digestion and nutrient assimilation in fish.

In the process of 3D modeling of geological body with fault, it is the primary problem to calculate the intersecting line between fault plane and various geological models. To quickly locate geological models intersecting fault planes, this paper adopts the algorithm of intersection detection of hybrid bounding boxes. Firstly, the principal component analysis is used to generate the bounding box of the tightly bounding geological model. Then, based on the separation axis theorem, an improved algorithm is proposed to realize the intersection detection of hybrid bounding boxes, which effectively reduces the number of detection and improves the efficiency. Experimental results show that this algorithm can greatly shorten the time of intersection test, and improve the efficiency of intersection calculation. This paper provides an algorithm basis for quickly locating the geological model cut by fault plane.

Stat6 promotes M2 macrophage polarization. Here the authors characterize Trim24-CBP-Stat6 circuit regulating M2 macrophage polarization via Stat6 acetylation, and show it contributes to pro-tumorigenic macrophage activity in mice.

Cellulose nanocrystals (CNCs) have received a significant amount of attention due to their excellent physiochemical properties. Herein, based on bioinspired layered materials with excellent mechanical properties, a CNCs-graphene layered structure with covalent linkages (C-C bond) is constructed. The mechanical properties are systematically studied by molecular dynamics (MD) simulations in terms of the effects of temperature, strain rate and the covalent bond content. Compared to pristine CNCs, the mechanical performance of the CNCs-graphene layered structure has significantly improved. The elastic modulus of the layered structure decreases with the increase of temperature and increases with the increase of strain rate and covalent bond coverage. The results show that the covalent bonding and van der Waals force interactions at the interfaces play an important role in the interfacial adhesion and load transfer capacity of composite materials. These findings can be useful in further modeling of other graphene-based polymers at the atomic scale, which will be critical for their potential applications as functional materials.

Potential functions play an essential role in the heat transport of the nano-scale materials when they are investigated by molecular dynamics simulations. In this paper, the thermal conductivity of bilayer graphene (BLG) is calculated by the non-equilibrium molecular dynamics using different in-layer and interlayer potentials. It is found that the Kolmogorov-Crespi (K-C) potential gives a lower thermal conductivity than Lennard-Jones (L-J) potential when they are used to describe the interlayer interaction of C–C atoms. The calculation results using K-C potential show that compared to L-J potential, there is about 10% reduction in thermal conductivity of BLG. For the in-layer interaction potentials, the TERSOFF potential provides much higher thermal conductivity than it from REBO and AIREBO potentials. In addition, the thermtal conductivity of BLG shows notably different temperature-dependence and same size effect calculated with various potentials. Based on the phonon density of states and phonon dispersion calculations, we find the simulation results calculated by K-C + REBO potential are in excellent agreement with the experimental values.

The current study mainly explored the influence of fluid intelligence (IQ) and emotional intelligence (EI) on affective decision-making from a developmental perspective, specifically, during the transition from childhood into early adolescence. Meanwhile, their age-related differences in affective decision-making were explored. A total of 198 participants aged 8–12 completed the Iowa Gambling Task (IGT), the Cattell’s Culture Fair Intelligence Test and the Trait Emotional Intelligence Questionnaire-Child Form. Based on the net scores of IGT, the development of affective decision-making ability did not increase monotonically with age, and there was a developmental trend of an impaired IGT performance in early adolescence (aged 11–12), especially in the early learning phase (first 40 trials) of the IGT. More importantly, IQ and EI played different roles for children and early adolescents: IQ and EI jointly predicted the IGT performance for 8–10 years old children, whereas only EI contributed to the IGT performance of 11–12 years old early adolescents. The present study extends the evidence how cognitive processing and emotional processing interact in affective decision-making from the developmental perspective. Furthermore, it provides insights of future research and intervention with early adolescents’ poor affective decision-making.

The accurate identification of effective microseismic events has great significance in the monitoring, early warning, and forecasting of rockburst hazards. However, the conventional identification methods have displayed difficulties in achieving satisfactory results. A microseismic signal identification method which combines variational mode decomposition (VMD) and multiscale singular spectrum entropy was proposed in this paper. The original signal was firstly broken down into a given number K variational mode components, which are ranked by frequency in descending order. Then, the characteristic pattern matrix was constructed according to the mode component signals, and the identification model of the microseismic signals based on the support vector machine was built by performing a multiscale singular spectrum entropy calculation of the collected vibration signals, constructing eigenvectors of signals. Finally, a comparative analysis of the microseismic events and blasting vibration signals in the experiment proved that the different characteristics of the two kinds of signals can be fully expressed by using multiscale singular spectrum entropy. Experimental results further confirmed the effective identification performance of this proposed method.

Systemic lupus erythematosus (SLE) is an autoimmune disorder mediated by excessive autoantibodies. Here the authors show that an E3 ubiquitin ligase, Peli1, negatively modulates noncanonical NF-κB signaling to restrain lupus-like symptoms in mice, and that Peli1 expression inversely correlates with SLE severity in humans.

Children usually miss additional information when they focus on objects or events. This common phenomenon is termed as inattentional blindness. To explore the age-related degree of this phenomenon, we applied a motion task to study the developmental difference of inattentional blindness. A group of 7-to-14-year-old children and adults participated in Experiment 1. The results showed that there was no significant developmental difference in sustained inattentional blindness. Considering that young children’s performance on the primary task was poor, we hypothesized that the difficulty of the primary task may contribute to the negative findings. Therefore, we decreased the difficulty of the primary task in Experiment 2. Still, the developmental difference in inattentional blindness rates was absent. Overall, current results implied that the ability of a person to detect an unexpected moving stimuli does not always increase with age. The age-related inattentional blindness seems highly dependent on tasks.

Wood plastic composites (WPCs) incorporating graphene nano-platelets (GNPs) were fabricated using hot-pressed technology to enhance thermal and mechanical behavior. The influences of thermal filler content and temperature on the thermal performance of the modified WPCs were investigated. The results showed that the thermal conductivity of the composites increased significantly with the increase of GNPs fillers, but decreased with the increase of temperature. Moreover, thermogravimetric analysis demonstrated that coupling GNPs resulted in better thermal stability of the WPCs. The limiting oxygen index test also showed that addition of GNPs caused good fire retardancy in WPCs. Incorporation of GNPs also led to an improvement in mechanical properties as compared to neat WPCs. Through a series of mechanical performance tests, it could be concluded that the flexural and tensile moduli of WPCs were improved with the increase of the content of fillers.

Wood Plastic Composites (WPCs) are a new generation of green composites that could optimize the use of harvested trees and increase the entire value chain. In this study, the electrical and mechanical properties of WPCs containing carbon blacks (CB), flake graphite (FG) and carbon nanotubes (CNTs) have been investigated. The electrical property of WPCs is improved significantly owing to the introduction of these carbon nanomaterial fillers. The volume and surface resistivity values of the investigated composites all obviously decreased with the increase in filler content, especially CNTs, which displayed the most satisfactory results. Based on a series of laboratory experiments carried out to investigate the mechanical performance, it can be concluded that the addition of the carbon nanomaterial fillers decreases the mechanical properties of WPCs slightly with the increase in filler content because of the weak interfacial interactions between the fillers and polymer matrix.

This study aimed to investigate two aspects of sustained attention in intellectually gifted children: first, the differences to intellectually average children; second, the differences between receiving standard education and enrichment education. Study 1 compared sustained attention between 24 intellectually gifted and 26 intellectually average children. The results showed that intellectually gifted children had better performance than their average peers, not only for the whole task but also on all indices. Study 2 compared sustained attention between 24 intellectually gifted children who received standard education and 24 intellectually gifted children who received enrichment education. The results showed that intellectually gifted children who received enrichment education performed better than those who received standard education. These findings are consistent with previous work and provide support for the implementation of enrichment education for intellectually gifted children.

Cisatracurium besylate is an ideal non-depolarizing muscle relaxant which is widely used in clinical application. However, some studies have suggested that cisatracurium besylate can affect cell proliferation. Moreover, its specific mechanism of action remains unclear. Here, we found that the number of GFP-LC3 (green fluoresent protein-light chain 3) positive autophagosomes and the rate of mitochondria fracture both increased significantly in drug-treated GFP-LC3 and MitoDsRed stable HeLa cells. Moreover, cisatracurium promoted the co-localization of LC3 and mitochondria and induced formation of autolysosomes. Levels of mitochondrial proteins decreased, which were reversed by the lysosome inhibitor Bafinomycin A1. Similar results with evidence of dose-dependent effects were found in both HeLa and Human Umbilical Vein Endothelial Cells (HUVECs). Cisatracurium lowered HUVEC viability to 0.16 (OD490) at 100 µM and to 0.05 (OD490) after 48 h in vitro; it increased the cell death rate to 56% at 100 µM and to 60% after 24 h in a concentration- and time-dependent manner (p < 0.01). Cell proliferation decreased significantly by four fold in Atg5 WT (wildtype) MEF (mouse embryonic fibroblast) (p < 0.01) but was unaffected in Atg5 KO (Knockout) MEF, even upon treatment with a high dose of cisatracurium. Cisatracurium induced significant increase in cell death of wild-type MEFs even in the presence of the apoptosis inhibitor zVAD. Thus, we conclude that activation of both the autophagic cell death and cell apoptosis pathways contributes to cisatracurium-mediated cell injury.

Image processing and analysis techniques are commonly utilized in various fields such as geology, underwater engineering, environmental conservation, marine resource exploration, and soil and geological assessments, particularly for examining drilling rock samples. However, processing images of rocks drilled underwater is challenging due to the intricate nature of aquatic settings, where factors such as light reflection and refraction, irregular sizes of rocks, and overlapping particles introduce noise, obscure textures, and distort colors in the images. Although improved versions of the mask region-based convolutional neural network have shown promise for quick and accurate analysis of large sets of underwater rock images, these methods can still be affected by inconsistencies in rock appearance, texture, and lighting. To address these issues, a comprehensive approach is introduced using the segment anything model. Our methodology begins with the application of Gaussian filters to reduce noise and smooth images, followed by the deployment of underwater image enhancement. Further, histogram equalization is applied to better the contrast and employ the segment anything model approach for the detailed understanding of rock features by extracting information on rock size and shape. EeEquivalent area circle diameter and axial ratio are used to generate particle size alignment maps and to ascertain shape details. Our approach has achieved an average precision rate of 80.6%, outperforming other strategies and yielding more precise rock information analysis. [ABSTRACT FROM AUTHOR]