Search

Abstract Background The Premonitory Urge for Tics Scale (PUTS) is a common self-report measure of premonitory urges for patients with tic disorders. This study aims to evaluate the Chinese version of the PUTS (PUTS-C) and to explore its association with psychiatric symptoms in Chinese children diagnosed with tic disorders. Methods The psychometric evaluation involved 204 outpatients with tic disorders, aged 7–16 years, who were divided into two age groups: (7–10 years, n = 103; 11–16 years, n = 95). Results The PUTS-C demonstrated good internal consistency (McDonald’sω = 0.84) and two-week test-retest reliability (0.76). We observed a statistically significant correlation between the total PUTS-C score and various Yale Global Tic Severity Scale (YGTSS) subscales and total tic severity scores. The PUTS-C score also showed significant correlations with the Children Yale-Brown Obsessive Compulsive Scale (CY-BOCS), Screening Child Anxiety-Related Emotional Disorders (SCARED), and Children’s Depression Inventory (CDI). Notably, premonitory urges independently predicted tic severity, beyond the influence of comorbid symptoms. A two-factor structure of the PUTS-C was identified in the total sample through factor analysis. Conclusions The PUTS-C possesses acceptable validity and good reliability. It appears that premonitory urges in Chinese patients with tic disorders are associated with obsessive-compulsive symptoms, anxiety, and depression, but can independently predict tic severity. Specific PUTS-C factors possibly related to motor and vocal tics. Future research should continue to investigate age-related differences and the association with tics and other sensory symptoms.

Advanced manufacturing research for sustainable battery life cycles is of utmost importance to reach net zero carbon emissions (European Commission, 2023a) as well as several of the United Nations Sustainable Development Goals (UNSDGs), for example: 30% reduction of CO2 emission, 10 million job opportunities and access to electricity for 600 million people (World Economic Forum, 2019). This editorial paper highlights international motivations for pursuing more sustainable manufacturing practices and discusses key research topics in battery manufacturing. Batteries will be central to our sustainable future as generation and storage become key components to on-demand energy supply. Four underlying themes are identified to address industrial needs in this field: 1. Digitalizing and automating production capabilities: data-driven solutions for production quality, smart maintenance, automation, and human factors, 2. Human-centric production: extended reality for operator support and skills development, 3. Circular battery life cycles: circular battery systems supported by service-based and other novel business models, 4. Future topics for battery value chains: increased industrial resilience and transparency with digital product passports, and next-generation battery chemistries. Challenges and opportunities along these themes are highlighted for transforming battery value chains through circularity and more sustainable production, with a particular emphasis on lithium-ion batteries (LIB). The paper concludes with directions for further research to advance a circular and sustainable battery value chain through utilizing the full potential of digitalization realising a cleaner, more energy-efficient society.

Summary: Originally derived from graphite, high-quality single-layer graphene is an excellent anti-wear and -friction additive in metal matrix. Here, the tribological performance of 3 different commercialized graphene derivatives (e.g., graphene oxide [GO], reduced graphene oxide [RGO], and graphene nanoplatelet [GNP]) as additives in a Cu matrix, were investigated from an industrial perspective. To increase the interaction of graphene derivatives with Cu particles, and addressing the aggregation problem of the graphene derivatives, different binders (polyvinyl alcohol [PVA] and cellulose nanocrystals [CNC]) were introduced into the system. Benefiting from such a strategy, a uniform distribution of the graphene derivatives in Cu matrix was achieved with graphene loading up to 5 wt %. After high-temperature sintering, the graphene is preserved and well distributed in the Cu matrix. It was found that the GNP-containing sample shows the most stable friction coefficient behavior. However, GO and RGO also improve the tribological performance of Cu under different circumstances.

Abstract Pressure‐induced swelling has been reported earlier for several hydrophilic layered materials. MXene Ti3C2Tx is also a hydrophilic layered material composed by 2D sheets but so far pressure‐induced swelling is reported for this material only under conditions of shear stress at MPa pressures. Here, high‐pressure experiments are performed with MXenes prepared by two methods known to provide “clay‐like” materials. MXene synthesized by etching MAX phase with HCl+LiF demonstrates the effect of pressure‐induced swelling at 0.2 GPa with the insertion of additional water layer. The transition is incomplete with two swollen phases (ambient with d(001) = 16.7Å and pressure‐induced with d(001) = 19.2Å at 0.2 GPa) co‐existing up to the pressure point of water solidification. Therefore, the swelling transition corresponds to change from two‐layer water intercalation (2L‐phase) to a never previously observed three‐layer water intercalation (3L‐phase) of MXene. Experiments with MXene prepared by LiCl+HF etching have not revealed pressure‐induced swelling in liquid water. Both MXenes also show no anomalous compressibility in liquid methanol. The presence of pressure‐induced swelling only in one of the MXenes indicates that the HCl+LiF synthesis method is likely to result in higher abundance of hydrophilic functional groups terminating 2D titanium carbide.

Abstract Operando monitoring of complex physical and chemical activities inside rechargeable lithium-ion batteries during thermal runaway is critical to understanding thermal runaway mechanisms and giving early warning of safety-related failure. However, most existing sensors cannot survive during such extremely hazardous thermal runaway processes (temperature up to 500 °C accompanied by fire and explosion). To address this, we develop a compact and multifunctional optical fiber sensor (12 mm in length and 125 µm in diameter) capable of insertion into commercial 18650 cells to continuously monitor internal temperature and pressure effects during cell thermal runaway. We observe a stable and reproducible correlation between the cell thermal runaway and the optical response. The sensor’s signal shows two internal pressure peaks corresponding to safety venting and initiation of thermal runaway. Further analysis reveals that a scalable solution for predicting imminent thermal runaway is the detection of the abrupt turning range of the differential curves of cell temperature and pressure, which corresponds to an internal transformation between the cell reversible and irreversible reactions. By raising an alert even before safety venting, this new operando measurement tool can provide crucial capabilities in cell safety assessment and warning of thermal runaway.

Focusing on the two-dimensional (2D) Su-Schrieffer-Heeger (SSH) model, we propose an additive rule between the real-space topological invariant s of disclinations (related to the Burgers vector B) and the reciprocal-space topological invariant p of bulk wave functions (the vectored Zak phase). The disclination-induced bound states in the 2D SSH model appear only if (s + p/2π) is nonzero modulo the lattice constant. These disclination-bound states are robust against perturbations respecting C4 point group symmetry and other perturbations within an amplitude determined by p. Besides the disclination-bound states, the proposed additive rule also suggests that a half-bound state extends over only half of a sample and a hybrid-bound state, which always have a nonvanishing component of s + p/2π.

Objective The objective of this study was to investigate the effects of different degrees of maternal dietary energy restriction on lipid deposition in embryonic tissues during the medium laying period (37 to 39 weeks) in Arbor Acres (AA) broiler breeders. Methods A single factor design was adopted, and 400 AA broiler breeders (20 weeks of age) with a similar weight were randomly allocated into four groups. The birds in the control group were fed a corn-soybean meal based diet, and those in trial groups were fed diets with 80%, 70%, and 50% energy levels of the basal diet. Incubated eggs from the medium laying period were collected. Samples of developing embryos at various stages were prepared for composition analysis. Results The embryo weight in the 80% energy group was higher than those of the other groups on embryonic day (E) 13, but at 21 E, they were significantly decreased with decreasing energy intake of the broiler breeders (p

With the frequent occurrence of various disasters, serious damage has been caused to social and economic development. Therefore, disaster management plays an increasingly significant role in controlling disasters and reducing losses. This study aims to provide a dynamic interaction assessment method for the emergency management department to manage disasters. For this purpose, the classical Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is first extended with bipolar 2-tuple linguistic information to model both the negative and positive influences among factors involved in coping with disaster. Then, the weights of influential factors are determined according to their total interaction relationships derived by extended DEMATEL. After that, the performances or states of factors are suggested to be appraised under a bipolar 2-tuple linguistic environment. Further, the performance or state simulation rule of factors is proposed based on their initial states and the interactions among them during disaster management. According to the simulation results, a weighted average operator is employed to obtain the overall performance values of emergency scenarios. Finally, an illustrative example and comparative analysis are presented for elucidating the feasibility and usefulness of the suggested method. Results of a case study show that the proposed method has the abilities to capture the interactions among influential factors and explore how the factors and their interactions affect disaster management. The proposed method could provide valuable information to emergency management departments for managing disasters more effectively.

ObjectivesTo evaluate the relationship between systemic family dynamics and adolescent depression.MethodsAn offline survey was distributed to 4,109 students in grades 6–12, with the final analysis including 3,014 students (1,524 boys and 1,490 girls) aged 10–18 years. The questionnaire included the Self-Rating Scale of Systemic Family Dynamics (SSFD), the Self-Rating Depression Scale (SDS), and demographic characteristics.ResultsFamily dynamics were negatively correlated with depressive symptoms, with better family dynamics (high scores) associated with lower levels of depression based on the SDS score. After adjusting for sociodemographic characteristics, an ordinal multiclass logistic regression analysis identified family atmosphere (OR = 0.952, 95% CI: 0.948–0.956, p < 0.001) as the most important protective family dynamic against depression, followed by individuality (OR = 0.964, 95% CI: 0.960–0.968, p < 0.001). Latent class analysis (LCA) created the low family dynamic and high family dynamic groups. There were significant differences in the mean SDS scores between the two groups (45.52 ± 10.57 vs. 53.78 ± 11.88; p < 0.001) that persisted after propensity matching. Family atmosphere and individuation had a favorable diagnostic value for depression, with AUCs of 0.778 (95% CI: 0.760–0.796) and 0.710 (95% CI: 0.690–0.730), respectively. The diagnostic models for depression performed well.ConclusionPoor family dynamics may be responsible for adolescent depression. A variety of early intervention strategies focused on the family may potentially avoid adolescent depression.

ObjectivesOur study aimed to identify the latent class of depressive symptoms in the Shanghai population during the city-wide temporary static management period and compare differences in the factors influencing depressive symptoms between medical staff and residents.MethodsAn online cross-sectional survey was conducted with 840 participants using questionnaires, including Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Pittsburgh Sleep Quality Index (PSQI), and self-compiled questionnaire (demographic characteristics and internet usage time). Latent class analysis (LCA) was performed based on participants' depressive symptoms. The latent class subgroups were compared using the chi-square test and t-test. Logistic regression was used in our study to analyze the factors influencing depressive symptoms within the medical staff group and residents group and then compare their differences.ResultsTwo distinct subgroups were identified based on the LCA: the group with low-depressive symptoms and the group with high-depressive symptoms. There were significant differences between the two groups (P < 0.05) on age, education level, marital status, internet usage time, identity characteristics (medical staff or residents), family income level, living style, overall quality of sleep, and anxiety levels. Furthermore, logistic regression analysis results showed that compared with the residents group, the participants in the group of medical staff with “increasing internet usage time” and the “daytime dysfunction” would have nearly two times the possibility of getting serious depressive symptoms.ConclusionsThere are differences in the factors influencing depression symptoms between medical staff and residents during the 2022 city-wide temporary static management period to fighting against the COVID-19 pandemic in Shanghai. We should pay special attention to those with increasing internet usage time and daytime dysfunction in medical staff working in a special environment such as the COVID-19 pandemic.

ObjectiveTo investigate the adaptability of Comprehensive Behavioral Intervention for Tics (CBIT) for a Chinese population, and evaluate the efficacy of combined CBIT and pharmacotherapy (CBIT + PT) compared to CBIT or pharmacotherapy (PT) alone for reducing tics and for improving the quality of life (QoL) in a sample of Chinese children with chronic tic disorders (CTD) and Tourette syndrome (TS).Materials and methodsIn this 10-week randomized controlled pilot trial, 37 outpatients aged between 6 and 16 years affected by TS and CTD were randomly assigned to receive CBIT (n = 22) or PT alone (n = 15). Considering the feasibility, the patients allocated to the CBIT treatment group could further choose whether to simultaneously take medicine voluntarily, resulting in a CBIT alone group (n = 12) and a CBIT + PT group (n = 10).ResultsAt baseline, no significant difference was found between the three groups in the demographic and clinical characteristics (p > 0.05). All three groups showed a significant reduction in tic severity after treatment assessed by the Yale Global Tic Severity Scale (YGTSS) severity score [F(2,33) = 35.05, p < 0.001, ηp2 = 0.51], the score of the Clinical Global Impression scale for Improvement (CGI-I) [F(1,34) = 13.87, p = 0.001, ηp2 = 0.29], and YGTSS impairment score [F(2,33) = 31.71, p < 0.001, ηp2 = 0.48]. Significant interactions were found between the time-point and group in emotional functioning [F(2,29) = 4.39, p = 0.02, ηp2 = 0.23], psychosocial functioning [F(2,29) = 5.93, p = 0.007, ηp2 = 0.29], and total QoL score [F(1,34) = 3.72, p = 0.04, ηp2 = 0.20] of Pediatric Quality of Life Inventory (PedsQL 4.0) for children suggesting a significantly larger improvement in emotional functioning, psychosocial functioning, and total QoL score of the life quality in the CBIT group for children self-report. PedsQL for proxy report only showed a significant main effect of time-point in physical functioning [F(1,33) = 8.35, p = 0.01, ηp2 = 0.2], emotional functioning [F(1,33) = 10.75, p = 0.002, ηp2 = 0.25], psychosocial functioning [F(1,34) = 11.38, p = 0.002, ηp2 = 0.26], and total Qol score [F(1,34) = 13.21, p = 0.001, ηp2 = 0.29].ConclusionCBIT is probably effective in reducing tic severity in Chinese children with tic disorders. CBIT + PT may not be superior to CBIT alone in reducing tic severity and improving quality of life. CBIT alone showed advantages in improving quality of life over CBIT + PT and PT alone. CBIT might be an appropriate treatment option for patients with tic disorder in Chinese mainland.

Tic is a combination of a series of static facial and limb movements over a certain period in some children. However, due to the scarcity of tic disorder (TD) datasets, the existing work on tic recognition using deep learning does not work well. It is that spatial complexity and time-domain variability directly affect the accuracy of tic recognition. How to extract effective visual information for temporal and spatial expression and classification of tic movement is the key of tic recognition. We designed the slow-fast and light-efficient channel attention network (SFLCA-Net) to identify tic action. The whole network adopted two fast and slow branch subnetworks, and light-efficient channel attention (LCA) module, which was designed to solve the problem of insufficient complementarity of spatial-temporal channel information. The SFLCA-Net is verified on our TD dataset and the experimental results demonstrate the effectiveness of our method.

The steel column performance in realistic structures during a fire has yet to be fully understood because existing research emphasizes single-story performance, thereby disregarding the influence of continuous steel columns in multi-story configurations devoid of fire. This paper presents a numerical study to comprehend the overall structural fire performance of continuous steel columns, considering the effect of loading ratios, restraint ratios, column continuity, and single-sided lateral moments. An advanced numerical model was initially developed using ABAQUS and validated against experimental tests. The validated numerical model was subsequently employed to investigate the effects of several parameters, including axial restraint ratios (α = 0.05–0.35) and axial load ratios (n = 0.3–0.8). The study findings indicated that the restraint ratios within the designed range have a slightly beneficial impact on the fire resistance of continuous steel columns. The column continuity did not exert a significant impact on the performance of steel columns in fire. Additionally, the comparison showed that the current design approach in EN 1993-1-2 was conservative for predicting the limiting temperature of internal and edge columns.

Urbanization has reduced river network connectivity, posing a great threat to water security. However, the mechanism through which changes in river network connectivity impact water security remains uncertain. River network connectivity and water security have been separately and thoroughly assessed by several researchers; however, few studies conducted a coupled assessment of these two aspects together, which may shed light on this mechanism. Based on assessment indicators developed in previous studies and key influence factors identified in the study area, this study proposed a comprehensive evaluation method to continually evaluate the adaptability between river network connectivity and water security in the Wuchengxiyu region, a highly urbanized area in Eastern China. The continuous evaluation was conducted for the period 2010–2019 based on the coupling coordination degree calculation formula. The results show that from 2010 to 2015, the coupling coordination degree between river network connectivity and water security followed a downward trend, due to the uncoordinated development between water systems and urbanization. After 2015, an increasing trend was observed with the implementation of environmental policies. In the past decade, the water surface rate and the coverage rate of suitable flow velocity decreased from 4.59% to 4.28% and from 54.1% to 30.9%, respectively, which may have negative effects on water quality and limit the improvement of regional flood control capacity. Moreover, the evaluation results also prove that policies such as the Ecological River–Lake Construction and the River Chief System have contributed to improve the quality of the water environment and regional flood control. The proposed assessment framework can be used as a guidance to evaluate the relationship between water network connectivity and water security; moreover, it provides new ideas for water network system protection and water quality maintenance in similar highly urbanized areas.

BackgroundThis study aimed to identify the threshold for success in supracondylar humeral fracture surgery by describing the learning curve for beginners and exploring the relationship between the learning curve and the prognosis of supracondylar fractures of the humerus.MethodsSurgical information was collected of the first 100 humeral fractures treated by four pediatric orthopedic surgeons. The relationship between operation time, wire placement success rate, and surgical experience was determined using the restricted cubic strip (RCS). The inflection point in the curve and other risk factors that may affect fracture prognosis were collected and subjected to multiple logistic regression to clarify the relationship between the learning curve and prognosis of supracondylar fractures of the humerus. After the training, the four fresh surgeons were interviewed in the form of questionnaires to get feedback from the trainees.ResultsA total of 400 supracondylar fractures of the humerus from four pediatric orthopedists were included in the study. On an RCS analysis, 65 surgical experiences were the inflection point of the learning curve. Before and after these 65 surgical experiences, there were significant differences in the patients' anatomical reduction (186 vs. 122, P < 0.001), conversion to incision (33 vs. 6, P = 0.008), and supervising physician guidance (28 vs. 2, P < 0.001). In the multiple logistic regression analysis, functional recovery after supracondylar fractures of the humerus was significantly associated with surgical experience, intraoperative conversion to incision, and post-operative infection. Four surgeons and a supervisor were interviewed. They believed that self-confidence establishment requires the experience accumulation of about 30 operations. The most critical surgical technique is the reduction of fractures.ConclusionsAlthough the accumulated experience of 30 operations can establish the self-confidence of trainers, fresh surgeons must accumulate experience with 65 operations to master closed reduction and internal fixation for supracondylar fractures. Surgical experience significantly impacts the post-operative recovery of patients with fractures.Level of EvidenceLevel III.

Abstract Background Chloroplasts are important semi-autonomous organelles in plants and algae. Unlike higher plants, the chloroplast genomes of green algal linage have distinct features both in organization and expression. Despite the architecture of chloroplast genome having been extensively studied in higher plants and several model species of algae, little is known about the transcriptional features of green algal chloroplast-encoded genes. Results Based on full-length cDNA (Iso-Seq) sequencing, we identified widely co-transcribed polycistronic transcriptional units (PTUs) in the green alga Caulerpa lentillifera. In addition to clusters of genes from the same pathway, we identified a series of PTUs of up to nine genes whose function in the plastid is not understood. The RNA data further allowed us to confirm widespread expression of fragmented genes and conserved open reading frames, which are both important features in green algal chloroplast genomes. In addition, a newly fragmented gene specific to C. lentillifera was discovered, which may represent a recent gene fragmentation event in the chloroplast genome. With the newly annotated exon-intron boundary information, gene structural annotation was greatly improved across the siphonous green algae lineages. Our data also revealed a type of non-canonical Group II introns, with a deviant secondary structure and intronic ORFs lacking known splicing or mobility domains. These widespread introns have conserved positions in their genes and are excised precisely despite lacking clear consensus intron boundaries. Conclusion Our study fills important knowledge gaps in chloroplast genome organization and transcription in green algae, and provides new insights into expression of polycistronic transcripts, freestanding ORFs and fragmented genes in algal chloroplast genomes. Moreover, we revealed an unusual type of Group II intron with distinct features and conserved positions in Bryopsidales. Our data represents interesting additions to knowledge of chloroplast intron structure and highlights clusters of uncharacterized genes that probably play important roles in plastids.

Abstract The genus Dioscorea is widely distributed in tropical and subtropical regions, and is economically important in terms of food supply and pharmaceutical applications. However, DNA barcodes are relatively unsuccessful in discriminating between Dioscorea species, with the highest discrimination rate (23.26%) derived from matK sequences. In this study, we compared genic and intergenic regions of three Dioscorea chloroplast genomes and found that the density of SNPs and indels in intergenic sites was about twice and seven times higher than that of SNPs and indels in the genic regions, respectively. A total of 52 primer pairs covering highly variable regions were designed and seven pairs of primers had 80%–100% PCR success rate. PCR amplicons of 73 Dioscorea individuals and assembled sequences of 47 Dioscorea SRAs were used for estimating intraspecific and interspecific divergence for the seven loci: The rpoB‐trnC locus had the highest interspecific divergence. Automatic barcoding gap discovery (ABGD), Poisson tree processes (PTP), and generalized mixed Yule coalescence (GMYC) analysis were applied for species delimitation based on the seven loci and successfully identified the majority of species, except for species in the Enantiophyllum section. Phylogenetic analysis of 51 Dioscorea individuals (28 species) showed that most individuals belonging to the same species tended to cluster in the same group. Our results suggest that the variable loci derived from comparative analysis of plastid genome sequences could be good DNA barcode candidates for taxonomic analysis and species delimitation.

Leaf chlorophyll content is an important indicator of the growth and photosynthesis of maize under water stress. The promotion of maize physiological growth by (AMF) has been studied. However, studies of the effects of AMF on the leaf chlorophyll content of maize under water stress as observed through spectral information are rare. In this study, a pot experiment was carried out to spectrally estimate the leaf chlorophyll content of maize subjected to different durations (20, 35, and 55 days); degrees of water stress (75%, 55% and 35% water supply) and two inoculation treatments (inoculation with Funneliformis mosseae and no inoculation). Three machine learning algorithms, including the back propagation (BP) method, least square support vector machine (LSSVM) and random forest (RF) method, were used to estimate the leaf chlorophyll content of maize. The results showed that AMF increased the leaf chlorophyll content, net photosynthetic rate (A), stomatal conductance (gs), transpiration rate (E), and water use efficiency (WUE) of maize but decreased the intercellular carbon dioxide concentration (Ci) of maize and atmospheric vapor pressure deficit (VPD) regardless of the water stress duration and degree. The first-order differential spectral data can better reflect the correlation between leaf chlorophyll content and spectrum of inoculated maize when compared with original spectral data. The BP model performed bestin modeling the maize leaf chlorophyll content, yielding the largest R2-values and smallest root mean square error (RMSE) values, regardless of stress duration. These results provide a reliable basis for the effective monitoring of the leaf chlorophyll content of maize under water stress.

Tourette’s syndrome (TS) is a childhood onset neuropsychiatric disorder. The underlying pathogenesis of TS remains unclear. A human induced pluripotent stem cell (hiPSC) line, derived from the peripheral blood mononuclear cells (PBMCs) from a TS patient, was generated by the reprogramming with episomal vectors expressing OCT4, SOX2, KLF4 and c-MYC. The generated hiPSC line is free of episomal vectors, with normal karyotype, expressing pluripotency markers and can differentiate into three germ layers in vivo. This hiPSC line from TS patient can offer a useful resource for studying the pathological mechanism of TS and screening effective drugs for therapeutic purpose.

Rare inherited variations in multiplex families with Gilles de la Tourette syndrome (GTS) are suggested to play an important role in the genetic etiology of GTS. In order to explore the rare inherited variations with the risk of GTS, whole-exome sequencing (WES) was performed in a family with three affected patients with GTS. Among the five novel rare variations identified by WES, CLCN2 G161S was presented in three patients, but not in four unaffected individuals, and thus co-segregated with GTS. A validation study was also performed in a cohort of Chinses Han population to further examine the identified rare variants. CLCN2 G161S was genotyped in 207 sporadic patients with tic disorder including 111 patients with GTS and 489 healthy controls. Compared with that in controls [allele frequency (AF) = 0], CLCN2 G161S had higher variant AF in patients with tic (AF = 0.00483) and in patients with GTS (0.00900), respectively. However, this variant was absent from the current 1000 Genome databases, and the variant AF is very low in the current public databases including ExAC (AF = 0.00001) and gnomAD (AF = 0.00003). Our results suggest that CLCN2 G161S might play a major role in the genetic etiology of GTS, at least in a Chinese Han population.

Soil physicochemical properties, bacterial communities and enzyme activities change with land subsidence resulting from coal mining. However, research on the responses of bacterial communities and enzyme activities to the soil properties in different degree of subsidence areas is limited. As such, we collected soil samples from a control area (C area), a moderate mining subsidence area (M area) and a severe mining subsidence area (S area) in Central China. Soil properties, such as the pH, total nitrogen (TN) content, total phosphorus (TP) content, available phosphorus (AP) content, organic matter (OM) content, and soil enzyme (urease, invertase, catalase and alkaline phosphatase) activities were measured in each sampling area at depths of 0-20 cm, 20-40 cm, and 40-60 cm. The results indicated that the soil physiochemical properties, soil urease activity, soil alkaline phosphatase activity and soil bacterial richness and diversity in the topsoil (0-20 cm) of the mining subsidence area were significantly lower than those in the C area. However, the soil enzyme activities within the deepest layer of the subsidence area were significantly greater than those of the C area. The bacterial communities within the depth of 0-20 cm were dominated by RB41, Pseudomonas, MND1, Nitrospira, Trichococcus, Sphingomonas and Dongia, whereas RB41 and Pseudomonas were the dominant species in the C area and subsidence area, respectively. Using correlation analysis, we found that the soil pH value, soil AP content and activities of the four enzymes were the main factors affecting the soil bacterial community structure. In addition, the soil nutrient contents, enzyme activities and bacterial richness and evenness decreased with increasing subsidence degree (classified by geological hazards, groundwater and landscape damage degree of coal mining subsidence). These results provide a reliable basis for environmental management of mining areas.

Face recognition has a great potential to play an important role in computer vision field. However, the majority of face recognition methods are based on the low-level features, which may not yield good results. Inspired by a simple deep learning model principal component analysis network (PCANet), we propose a novel deep learning network called circular symmetrical Gabor filter (2D)2PCA neural networks [CSGF(2D)2PCANet]. Previous models used in face recognition have three major issues of data redundancy, computation time, and no rotation invariance. We introduce the CSGF to address these issues. Two-directional 2-D PCA [(2D)2PCA] is used in feature extraction stage. Binary hashing, blockwise histograms, and linear SVM are used for the output stage. The proposed CSGF (2D)2PCANet learns highlevel features and provides more recognition information during the training phase, which may result in a higher recognition rate when testing the sample. We tested the proposed method on XM2VTS, ORL, AR, Extend Yale B, and LFW databases. Test results show that the CSGF (2D)2PCANet is more robust to the variation of occlusion, illumination, pose, noise, and expression, which is a promising method in face recognition.

Salinity gradient energy, as a type of blue energy, is a promising sustainable energy source. Its energy conversion efficiency is significantly determined by the selective membranes. Recently, nanofluidic membrane made by two-dimensional (2D) nanomaterials (e.g., graphene) with densely packed nanochannels has been considered as a high-efficient membrane in the osmotic power generation research field. Herein, the graphene oxide-cellulose acetate (GO–CA) heterogeneous membrane was assembled by combining a porous CA membrane and a layered GO membrane; the combination of 2D nanochannels and 3D porous structures make it show high surface-charge-governed property and excellent ion transport stability, resulting in an efficient osmotic power harvesting. A power density of about 0.13 W/m2 is achieved for the sea–river mimicking system and up to 0.55 W/m2 at a 500-fold salinity gradient. With different functions, the CA and GO membranes served as ion storage layer and ion selection layer, respectively. The GO–CA heterogeneous membrane open a promising avenue for fabrication of porous and layered platform for wide potential applications, such as sustainable power generation, water purification, and seawater desalination.

Sulfur has received considerable attention as a cathode material for lithium—sulfur (Li—S) batteries due to its high theoretical energy density (2567 W h kg−1), high earth abundance, and environmental benignity. However, the insulating nature of sulfur and the shuttle effect of soluble lithium polysulfides result in serious technical issues, such as low utilization rate of sulfur, reduced columbic efficiency, and poor cycling stability, which compromise the high theoretical performance of Li—S batteries. In the past years, various attempts have been made to achieve high specific capacity and reliable cycling stability of Li—S batteries. Incorporation of sulfur into functional host materials has been demonstrated to be effective to improve the electrochemical performance of sulfur-based cathodes via enhancing the electron and Li ion conductivities, immobilizing sulfur/lithium polysulfides in cathodes, and accommodating the volume changes in sulfur-based cathodes. Therefore, the rational design of sulfur-containing composites needs to be emphasized as key strategies to develop high-performance cathodes for Li—S batteries. In this perspective, after reviewing the achievements obtained in the design of sulfur-containing composites as cathodes for Li—S batteries, we propose the new issues that should be overcome to facilitate the practical application of Li—S batteries.

Lithium–sulfur batteries have high theoretical capacities but their performance is limited by poor conductivity and low stability. Here, the authors fabricate three-dimensional porous graphitic carbon composites containing sulfur nanoparticles and probe the effect of sulfur content on battery performance.

Buildings have U-shape façade designs for certain purposes such as lighting. However, such designs may lead to a higher fire hazard. In this paper, large scale experiments of upward flame spread over XPS insulation material were conducted to investigate the fire hazard of building’s U-shape façade wall geometry. Comparison to previous labora­tory scale experiments were also presented. Theoretical analysis was performed to reveal the mechanism of the U-shape geometry’s influences. It is found that such geometry design would increase the fire hazard of buildings: flame spread rate and flame height increased with U-shape’s geometrical factor. The results agreed with theoretical analysis. It is ex­pected that the buildings’ U-shape façade wall geometry would greatly benefit flame spread for full scale applications and increase the fire hazard. Thus engineers should be careful with such façade wall designs, especially for residential building designs.

Litchi downy blight, caused by Peronophythora litchii, is one of the major diseases of litchi and has caused severe economic losses. P. litchii has the unique ability to produce downy mildew like sporangiophores under artificial culture. The pathogen had been placed in a new family Peronophytophthoraceae by some authors. In this study, the whole transcriptome of P. litchii from mycelia, sporangia, and zoospores was sequenced for the first time. A set of 23637 transcripts with an average length of 1284 bp was assembled. Using six open reading frame (ORF) predictors, 19267 representative ORFs were identified and were annotated by searching against several public databases. There were 4666 conserved gene families and various sets of lineage-specific genes among P. litchii and other four closely related oomycetes. In silico analyses revealed 490 pathogen-related proteins including 128 RXLR and 22 CRN effector candidates. Based on the phylogenetic analysis of 164 single copy orthologs from 22 species, it is validated that P. litchii is in the genus Phytophthora. Our work provides valuable data to elucidate the pathogenicity basis and ascertain the taxonomic status of P. litchii.

CF3CBrCH2 (2-bromo-3,3,3-trifluoropropene, 2-BTP) is a potential replacement for CF3Br; however, it shows conflicted inhibition and enhancement behaviors under different combustion conditions. To better understand the combustion chemistry of 2-BTP, a theoretical study has been performed on its reactions with OH and H radicals. Potential energy surfaces were exhaustively explored by using B3LYP/aug-cc-pVTZ for geometry optimizations and CCSD(T)/aug-cc-pVTZ for high level single point energy refinements. Detailed kinetics of the major pathways were predicted by using RRKM/master-equation methodology. The present predictions imply that the –C(Br)=CH2 moiety of 2-BTP is most likely to be responsible for its fuel-like property. For 2-BTP + OH, the addition to the initial adduct (CF3CBrCH2OH) is the dominant channel at low temperatures, while the substitution reaction (CF3COHCH2 + Br) and H abstraction reaction (CF3CBrCH + H2O) dominates at high temperatures and elevated pressures. For 2-BTP + H, the addition to the initial adduct (CF3CBrCH3) also dominates the overall kinetics at low temperatures, while Br abstraction reaction (CF3CCH2 + HBr) and β-scission of the adduct forming CF3CHCH2 + Br dominates at high temperatures and elevated pressures. Compared to 2-BTP + OH, the 2-BTP + H reaction tends to have a larger effect on flame suppression, given the fact that it produces more inhibition species.

Genetic factors are important in the pathogenesis of Tourette syndrome (TS). Notably, Dopamine receptor D2 (DRD2) gene has been suggested as a possible candidate gene for this disorder. Several studies have demonstrated that DRD2/ANKK1 TaqIA polymorphism is associated with an increased risk of developing TS. However, past results remain conflicting. We addressed this controversy by performing a meta-analysis of the relationship between DRD2/ANKK1 TaqIA polymorphism and TS.Literature was searched in multiple databases including PUBMED, COCHRANE and WEB OF SCIENCE up to July 2014. The number of the genotypes for DRD2/ANKK1 TaqIA in the TS and control subjects was extracted and statistical analysis was performed using Review Manager 5.0.16 and Stata 12.0 software. Summary odds ratios (ORs) and 95% confidence intervals (95%CIs) were utilized to calculate the risk of TS with DRD2/ANKK1 TaqIA. Stratified analysis based on ethnicity was also conducted.523 patients with TS, 564 controls and 87 probands plus 152 relatives from five published studies were finally involved in this meta-analysis. Combined analysis revealed that the overall ORs for the DRD2/ANKK1 TaqIA A1 allele were 1.69 (95%CIs = 1.42-2.00) in the fixed-effect model and 1.66 (95%CIs = 1.33-2.08) in the random-effects model. Stratification by ethnicity indicated the TaqIA A1 allele was significantly associated with TS in Caucasians (fixed-effect model: OR=1.75, 95%CI = 1.43-2.16; random-effect model: OR=1.69, 95%CI = 1.25-2.28) and in Asians (OR=1.54, 95%CI = 1.12-2.10). Meta-analysis of the A1A1 vs. A2A2 (homozygous model), A1A2 vs. A2A2 (heterozygous model) and A1A1+A1A2 vs. A2A2 (dominant model) of this polymorphism revealed a significant association with TS in overall populations and Caucasians.This meta-analysis suggested that the DRD2/ANKK1 TaqIA polymorphism might contribute to TS susceptibility, especially in Caucasian population. However, further investigation with a larger number of worldwide studies should be conducted to verify the association.

Polyphenol oxidase (PPO) plays a key role in the postharvest pericarp browning of litchi fruit, but its underlying mechanism remains unclear. In this study, we cloned the litchi PPO gene (LcPPO, JF926153), and described its expression patterns. The LcPPO cDNA sequence was 2120 bps in length with an open reading frame (ORF) of 1800 bps. The ORF encoded a polypeptide with 599 amino acid residues, sharing high similarities with other plant PPO. The DNA sequence of the ORF contained a 215-bp intron. After carrying out quantitative RT-PCR, we proved that the LcPPO expression was tissue-specific, exhibiting the highest level in the flower and leaf. In the pericarp of newly-harvested litchi fruits, the LcPPO expression level was relatively high compared with developing fruits. Regardless of the litchi cultivar and treatment conditions, the LcPPO expression level and the PPO activity in pericarp of postharvest fruits exhibited the similar variations. When the fruits were stored at room temperature without packaging, all the pericarp browning index, PPO activity and the LcPPO expression level of litchi pericarps were reaching the highest in Nandaowuhe (the most rapid browning cultivar), but the lowest in Ziniangxi (the slowest browning cultivar) within 2 d postharvest. Preserving the fruits of Feizixiao in 0.2-μm plastic bag at room temperature would decrease the rate of pericarp water loss, delay the pericarp browning, and also cause the reduction of the pericarp PPO activity and LcPPO expression level within 3 d postharvest. In addition, postharvest storage of Feizixiao fruit stored at 4°C delayed the pericarp browning while decreasing the pericarp PPO activity and LcPPO expression level within 2 d after harvest. Thus, we concluded that the up-regulation of LcPPO expression in pericarp at early stage of postharvest storage likely enhanced the PPO activity and further accelerated the postharvest pericarp browning of litchi fruit.

People with neuropsychiatric disorders such as schizophrenia often display deficits in spatial working memory and attention. Evaluating working memory and attention in schizophrenia patients is usually based on traditional tasks and the interviewer’s judgment. We developed a simple Spatial Working Memory and Attention Test on Paired Symbols (SWAPS). It takes only several minutes to complete, comprising 101 trials for each subject. In this study, we tested 72 schizophrenia patients and 188 healthy volunteers in China. In a healthy control group with ages ranging from 12 to 60, the efficiency score (accuracy divided by reaction time) reached a peak in the 20–27 age range and then declined with increasing age. Importantly, schizophrenia patients failed to display this developmental trend in the same age range and adults had significant deficits compared to the control group. Our data suggests that this simple Spatial Working Memory and Attention Test on Paired Symbols can be a useful tool for studies of spatial working memory and attention in neuropsychiatric disorders.

To improve the safety of lithium ion batteries, a multi-component (MC) additive (consisting of vinylene carbonate (VC), 1,3-propylene sulfite (PS) and dimethylacetamide (DMAC)) is used in the baseline electrolyte (1.0 M LiPF6/ethylene carbonate (EC) + diethyl carbonate (DEC)). The electrolyte with the MC additive is named safety electrolyte. The thermal stabilities of fully charged Li(Ni1/3Co1/3Mn1/3)O2 (NCM) mixed with the baseline electrolyte and safety electrolyte, respectively, are investigated using a C80 micro-calorimeter. The electrochemical performances of the NCM/baseline electrolyte/Li and NCM/safety electrolyte/Li half cells are evaluated using galvanostatic charge/discharge, cyclic voltammetry and alternating current (AC) impedance. The experimental results demonstrate that the fully charged NCM-safety electrolyte system releases less heat and reduces the main sharp exothermic peak value to a great extent, with a reduction of 40.6%. Moreover, the electrochemical performances of NCM/safety electrolyte/Li half cells are not worse, and are almost as good as that of the NCM/baseline electrolyte/Li half cells.

Advanced manufacturing research for sustainable battery life cycles is of utmost importance to reach net zero carbon emissions (European Commission, 2023a) as well as several of the United Nations Sustainable Development Goals (UNSDGs), for example: 30% reduction of CO2 emission, 10 million job opportunities and access to electricity for 600 million people (World Economic Forum, 2019). This editorial paper highlights international motivations for pursuing more sustainable manufacturing practices and discusses key research topics in battery manufacturing. Batteries will be central to our sustainable future as generation and storage become key components to on-demand energy supply. Four underlying themes are identified to address industrial needs in this field: 1. Digitalizing and automating production capabilities: data-driven solutions for production quality, smart maintenance, automation, and human factors, 2. Human-centric production: extended reality for operator support and skills development, 3. Circular battery life cycles: circular battery systems supported by service-based and other novel business models, 4. Future topics for battery value chains: increased industrial resilience and transparency with digital product passports, and next-generation battery chemistries. Challenges and opportunities along these themes are highlighted for transforming battery value chains through circularity and more sustainable production, with a particular emphasis on lithium-ion batteries (LIB). The paper concludes with directions for further research to advance a circular and sustainable battery value chain through utilizing the full potential of digitalization realising a cleaner, more energy-efficient society. [ABSTRACT FROM AUTHOR]

Non-intrusive load monitoring (NILM) has become a widely used approach to monitor energy consumption by installing monitoring equipment at the power supply entrance. However, the accuracy of traditional deep neural network decomposition models falls short of meeting practical demand. To address this limitation, the present study introduces a novel hybrid neural network model, which integrates temporal feature extraction and an attention mechanism. The proposed model is designed to discern the salient attributes within power time series signals, thereby reducing the dimensionality of the resulting characteristic temporal signals via the application of Principal Component Analysis (PCA). Next, a Gated Recurrent Unit (GRU) neural network with an attention mechanism extracts the features of the generated information vector, and generates the load decomposition model after multiple iterations of learning. The experimental outcomes on the REDD public dataset substantiate the superiority of the proposed model over alternative deep learning techniques, including CNN, GRU, and GRU with attention. The proposed model demonstrates a significantly elevated degree of precision within the domain of load identification. [ABSTRACT FROM AUTHOR]