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Parent-child, teacher-student, and peer relationships are important for adolescents, and can be related to bullying victimization. However, limited research explores whether, how much, and how these three interpersonal relationships are related to bullying victimization based on different grade levels (junior high and high school) and victimization status (victims and bully victims) in a Chinese cultural context. The present research addressed the gap. Participants were 945 Chinese students in junior high and high school (M[subscript age] = 14.11, SD = 1.48). The results showed that the three interpersonal relationships were significantly and negatively associated with bullying victimization, except parent-child relationships in bully victims. However, the predictive power of the three interpersonal relationships on bullying victimization varied. Compared to high school students, parent-child and teacher-student relationships in junior high school students had greater predictive power for bullying victimization. Compared to pure victims, teacher-student relationships in bully victims had greater predictive power for bullying victimization. Compared to bully victims, parent-child relationships of pure victims had greater predictive power for bullying victimization. Furthermore, the three interpersonal relationships had different roles in bullying victimization among groups. For junior high school students, high school students, and pure victims, parent-child relationships were related to bullying victimization directly and indirectly through the mediating roles of teacher-student and classmate relationships. For bully victims, teacher-student relationships were related to bullying victimization indirectly through the mediating role of relationships with classmates. Thus, anti-bullying policies and interventions need to be more individually tailored. Moreover, parent-child relationships are an important protective factor against bullying among Chinese adolescents.

This study aimed to explore the relationship between alterations in plasma metabolites and treatment responses amongst antipsychotic-naïve female patients with schizophrenia. A total of 38 antipsychotic-naïve female schizophrenia patients (ANS) and 19 healthy female controls (HC) were recruited. Plasma samples were obtained from all participants, and targeted metabolomics were measured with FIA-MS/MS and LC-MS/MS. The positive and negative syndrome scale (PANSS) was used to assess the severity of psychotic symptoms before and after eight weeks of treatment. Receiver operator characteristics (ROC) curves were used to predict diagnostic and therapeutic responses. A total of 186 metabolites passed quality control procedures and were used in statistical analysis to identify potential biomarkers. Before treatment, the ANS patients had lower levels of γ -Aminobutyric Acid (GABA) and higher levels of Cholesteryl esters (CE) (20:3), Cholic Acid (CA) and Glycocholic Acid (GCA) compared to the HCs. These four differential metabonomic markers were synthesised into a combinatorial biomarker panel. This panel significantly distinguished ANS from HC. Moreover, this biomarker panel was able to effectively predict therapeutic responses. Our results suggest that plasma CE (20:3), CA, GCA, and GABA levels may be useful for diagnosing and predicting antipsychotic efficacy amongst female schizophrenia patients. [ABSTRACT FROM AUTHOR]

Summary: Tassel branch number (TBN) is a key agronomic trait for adapting to high‐density planting and grain yield in maize. However, the molecular regulatory mechanisms underlying tassel branching are still largely unknown.Here, we used molecular and genetic studies together to show that ZmELF3.1 plays a critical role in regulating TBN in maize.Previous studies showed that ZmELF3.1 forms the evening complex through interacting with ZmELF4 and ZmLUX to regulate flowering in maize and that RA2 and TSH4 (ZmSBP2) suppresses and promotes TBN in maize, respectively. In this study, we show that loss‐of‐function mutants of ZmELF3.1 exhibit a significant increase of TBN. We also show that RA2 directly binds to the promoter of TSH4 and represses its expression, thus leading to reduced TBN. We further demonstrate that ZmELF3.1 directly interacts with both RA2 and ZmELF4.2 to form tri‐protein complexes that further enhance the binding of RA2 to the promoter of TSH4, leading to suppressed TSH4 expression and consequently decreased TBN.Our combined results establish a novel functional link between the ELF3‐ELF4‐RA2 complex and miR156‐SPL regulatory module in regulating tassel branching and provide a valuable target for genetic improvement of tassel branching in maize. [ABSTRACT FROM AUTHOR]

Summary: Flowering time is a key agronomic trait determining environmental adaptation and yield potential of crops. The regulatory mechanisms of flowering in maize still remain rudimentary.In this study, we combine expressional, genetic, and molecular studies to identify two homologous SQUAMOSA PROMOTER BINDING PROTEIN‐LIKE (SPL) transcription factors ZmSPL13 and ZmSPL29 as positive regulators of juvenile‐to‐adult vegetative transition and floral transition in maize.We show that both ZmSPL13 and ZmSPL29 are preferentially expressed in leaf phloem, vegetative and reproductive meristem. We show that vegetative phase change and flowering time are moderately delayed in the Zmspl13 and Zmspl29 single knockout mutants and more significantly delayed in the Zmspl13/29 double mutants. Consistently, the ZmSPL29 overexpression plants display precocious vegetative phase transition and floral transition, thus early flowering. We demonstrate that ZmSPL13 and ZmSPL29 directly upregulate the expression of ZmMIR172C and ZCN8 in the leaf, and of ZMM3 and ZMM4 in the shoot apical meristem, to induce juvenile‐to‐adult vegetative transition and floral transition.These findings establish a consecutive signaling cascade of the maize aging pathway by linking the miR156‐SPL and the miR172‐Gl15 regulatory modules and provide new targets for genetic improvement of flowering time in maize cultivars. [ABSTRACT FROM AUTHOR]

Maize (Zea mays) originated in southern Mexico and has spread over a wide latitudinal range. Maize expansion from tropical to temperate regions has necessitated a reduction of its photoperiod sensitivity. In this study, we cloned a quantitative trait locus (QTL) regulating flowering time in maize and show that the maize ortholog of Arabidopsis thaliana EARLY FLOWERING3, ZmELF3.1, is the causal locus. We demonstrate that ZmELF3.1 and ZmELF3.2 proteins can physically interact with ZmELF4.1/4.2 and ZmLUX1/2, to form evening complex(es; ECs) in the maize circadian clock. Loss-of-function mutants for ZmELF3.1/3.2 and ZmLUX1/2 exhibited delayed flowering under long-day and short-day conditions. We show that EC directly represses the expression of several flowering suppressor genes, such as the CONSTANS, CONSTANS-LIKE, TOC1 (CCT) genes ZmCCT9 and ZmCCT10, ZmCONSTANS-LIKE 3, and the PSEUDORESPONSE REGULATOR (PRR) genes ZmPRR37a and ZmPRR73, thus alleviating their inhibition, allowing florigen gene expression and promoting flowering. Further, we identify two closely linked retrotransposons located in the ZmELF3.1 promoter that regulate the expression levels of ZmELF3.1 and may have been positively selected during postdomestication spread of maize from tropical to temperate regions during the pre-Columbian era. These findings provide insights into circadian clock-mediated regulation of photoperiodic flowering in maize and new targets of genetic improvement for breeding. ZmELF3.1/3.2 bridge ZmELF4.1/4.2 and ZmLUX1/2 to form evening complexes and promote flowering and adaptation of maize to temperate regions. [ABSTRACT FROM AUTHOR]

The current study examined the characteristics of targets of bullying using a sample of students from two distinct school types (key vs. non-key), wherein key middle schools are defined as having better teaching resources and higher performing students than non-key middle schools. Open-ended, self-report surveys were collected from 322 Chinese students in sixth to 11th grades. Two cycle coding methods analyses generated 3,566 original codes in which 21 main categories and 77 subcategories were extracted. Five major themes emerged: multiple deviant personalities; prominent puniness and imperfect body characteristics accompanied by polarization of appearance; polarization school engagement and academic performance; psychological and behavioral problems; and problematic family and social contexts. Results of chi-square analysis indicated characteristics of targets of bullying were significantly different between key and non-key school in 12 main categories. Implications for ecological systems theory and person-group dissimilarity theory as well as bullying prevention approaches in schools are discussed. [ABSTRACT FROM AUTHOR]

Keywords: maize; dense planting; lodging resistance; D1; ZmSPL12 EN maize dense planting lodging resistance D1 ZmSPL12 622 624 3 04/11/22 20220401 NES 220401 Introduction of the semi-dwarf genes ( I sd1 i in rice, I RhtB1b i and I RhtD1b i in wheat) has drastically increased lodging resistance and grain yields in these two important crops since the 1960s, resulting in the so called "Green Revolution" (Hedden, 2003). Together, our results demonstrate that I ZmSPL12 i could mimic the function of "Green Revolution" genes to confer reduced plant height and increased lodging resistance, thus facilitating high-density planting and increased yield in maize. [Extracted from the article]

Summary: Maize is a major staple crop widely used for food, feedstocks and industrial products. Shade‐avoidance syndrome (SAS), which is triggered when plants sense competition of light from neighbouring vegetation, is detrimental for maize yield production under high‐density planting conditions. Previous studies have shown that the red and far‐red photoreceptor phytochromes are responsible for perceiving the shading signals and triggering SAS in Arabidopsis; however, their roles in maize are less clear. In this study, we examined the expression patterns of ZmPHYC1 and ZmPHYC2 and found that ZmPHYC1, but not ZmPHYC2, is highly expressed in leaves and is regulated by the circadian clock. Both ZmPHYC1 and ZmPHYC2 proteins are localized to both the nucleus and cytoplasm under light conditions and both of them can interact with themselves or with ZmPHYBs. Heterologous expression of ZmPHYCs can complement the Arabidopsis phyC‐2 mutant under constant red light conditions and confer an attenuated SAS in Arabidopsis in response to shading. Double knockout mutants of ZmPHYC1 and ZmPHYC2 created using the CRISPR/Cas9 technology display a moderate early‐flowering phenotype under long‐day conditions, whereas ZmPHYC2 overexpression plants exhibit a moderately reduced plant height and ear height. Together, these results provided new insight into the function of ZmPHYCs and guidance for breeding high‐density tolerant maize cultivars. [ABSTRACT FROM AUTHOR]

Branching/tillering is an important parameter of plant architecture and is tightly regulated by both internal factors (such as plant hormones) and external factors (such as light conditions). How the various signaling pathways converge to coordinately regulate branching is not well understood. Here, we report that in Arabidopsis, FHY3 and FAR1, two homologous transcription factors essential for phytochrome A-mediated light signaling, and SMXL6/SMXL7/SMXL8, three key repressors of the strigolactone (SL) signaling pathway, directly interact with SPL9 and SPL15 and suppress their transcriptional activation of BRC1, a key repressor of branching, thus promoting branching. In addition, FHY3 and FAR1 also directly up-regulate the expression of SMXL6 and SMXL7 to promote branching. Simulated shade treatment reduces the accumulation of FHY3 protein, leading to increased expression of BRC1 and reduced branching. Our results establish an integrated model of light and SL coordinately regulating BRC1 expression and branching through converging at the BRC1 promoter. In plants, branching is regulated by both hormones and external cues such as light. Here the authors show that in Arabidopsis, the phytochrome A-signaling components FHY3 and FAR1, and SMXL proteins that repress strigolactone signaling, both interact with SPL proteins to control expression of the branching regulator BRC1. [ABSTRACT FROM AUTHOR]

The impact of motors breakdown and failures on mobile robot motor bearing is an important concern for robot industries. For this reason, predictive motor lifetime and bearing fault classification techniques are being investigated extensively as a method of decreasing motor downtime and enhancing mobile robot reliability. With increasing attention on neural network technologies, many researchers have carried out lots of the relevant experiments and analyses, very plentiful and important conclusions are obtained. In this article, a classification method based on discrete wavelet transform (DWT) and long short-term memory network (LSTM) a proposed to find and classify fault type of mobile robot permanent magnet synchronous motor (PMSM). First, a set of mobile robot motor vibration signal were collected by the sensors. Second, the obtained vibration signal is decomposed into six frequency bands by the DWT. Haar function is selected as the mother function in the processing. The energy of every frequency band was calculated as a classification feature. Thirdly, four classification features with high classification rate are obtained. The feature vector is used as input of the neural network, and the fault type is identified by LSTM classifier with deviation unit. From the results of the experiments provided in the paper, the method can detect the fault type accurately and it is feasible and effective under different motor speed. [ABSTRACT FROM AUTHOR]

Psychopathy is the most notorious trait in the Dark Triad, and it is strongly linked to many kinds of aggressive behaviors. However, not every individual who is characterized by psychopathy engages in aggression, which suggests that certain factors may attenuate the intensity of the relations between psychopathy and aggression. The purpose of the current study was to explore the protective roles of the consideration of future consequences (CFC) (high CFC-Future and low CFC- Immediate) in attenuating aggression related to psychopathy using proactive aggression (Study 1) and cyber-aggression (Study 2) behavior indexes. College students (Study 1; N = 1,058) and adults (Study 2; N = 350) voluntarily participated in this study. The results demonstrated that the relationship between psychopathy and aggressive behaviors was moderated by CFC-Future and CFC-Immediate. Individuals with high psychopathy scores who also had high CFC-Future scores or low CFC-Immediate scores exhibited less proactive aggression (Study 1) and left fewer aggressive online comments on news websites (Study 2). The results of the present study suggested that CFC serves as a buffer against aggression related to psychopathy and may extend the knowledge of the relationship between psychopathy and aggression. [ABSTRACT FROM AUTHOR]

Emotion recognition based on EEG signals is a critical component in Human-Machine collaborative environments and psychiatric health diagnoses. However, EEG patterns have been found to vary across subjects due to user fatigue, different electrode placements, and varying impedances, etc. This problem renders the performance of EEG-based emotion recognition highly specific to subjects, requiring time-consuming individual calibration sessions to adapt an emotion recognition system to new subjects. Recently, domain adaptation (DA) strategies have achieved a great deal success in dealing with inter-subject adaptation. However, most of them can only adapt one subject to another subject, which limits their applicability in real-world scenarios. To alleviate this issue, a novel unsupervised DA strategy called Multi-Subject Subspace Alignment (MSSA) is proposed in this paper, which takes advantage of subspace alignment solution and multi-subject information in a unified framework to build personalized models without user-specific labeled data. Experiments on a public EEG dataset known as SEED verify the effectiveness and superiority of MSSA over other state of the art methods for dealing with multi-subject scenarios. [ABSTRACT FROM AUTHOR]

Totems are symbols or representations of human's affiliations with, and/or categorizations of, animals, plants and inanimate objects. Totemism is related to fundamental human belief systems based on totems. Investigating totems and totemism psychologically is a unique way to explore human minds. We have critically examined Wundt, Freud and many other scholars and scientists who made distinguished contributions to scientific research on totems and totemism almost in the past two centuries –i.e., totemic psychology, which is the study of our mind's categorization and affiliation in the human and natural world today. Understanding and appreciating their totemic psychology can help psychologists today enhance their understanding in other fields—e.g., ecological and environmental psychology, biological psychology, cognitive psychology, personality, social and ethnic psychology, clinical and counseling psychology, cultural psychology, and religious or spiritual psychology. Unfortunately, recent data from a content analysis via PsycInfo and a cross-cultural survey study (N =273) showed that well-trained psychologists around the world and psychology students in the United States and in China are unfamiliar with Wundt and Freud's totemic contributions to psychology today. The implications, benefits, and lessons of totems and today's totemic psychology are discussed here. [ABSTRACT FROM AUTHOR]

In this study, we address the problem of noisy image super-resolution. Noisy low resolution (LR) image is always obtained in applications, while most of the existing algorithms assume that the LR image is noise-free. As to this situation, we present an algorithm for noisy image super-resolution which can achieve simultaneously image super-resolution and denoising. And in the training stage of our method, LR example images are noise-free. For different input LR images, even if the noise variance varies, the dictionary pair does not need to be retrained. For the input LR image patch, the corresponding high resolution (HR) image patch is reconstructed through weighted average of similar HR example patches. To reduce computational cost, we use the atoms of learned sparse dictionary as the examples instead of original example patches. We proposed a distance penalty model for calculating the weight, which can complete a second selection on similar atoms at the same time. Moreover, LR example patches removed mean pixel value are also used to learn dictionary rather than just their gradient features. Based on this, we can reconstruct initial estimated HR image and denoised LR image. Combined with iterative back projection, the two reconstructed images are applied to obtain final estimated HR image. We validate our algorithm on natural images and compared with the previously reported algorithms. Experimental results show that our proposed method performs better noise robustness. [ABSTRACT FROM AUTHOR]

Combined the mechanism of gob-side entry retaining by roof cutting pressure relief and the geological conditions of Jiaozishan coal mine, the influence of gob-side entry retaining from the depth of blasting bore in the process of roof cutting pressure relief was studied by the method of FLAC3D numerical simulation. When the depth of blasting bore was 4m, it was most significant that the surrounding rock stress of roadway transferred to the roadway deep; meanwhile, the surrounding rock deformation was also the minimum. And the result was applied to an industrial practice in the intake airflow roadway of the 9706 working face. When the working face was mined, the surrounding rock deformation was basically identical between the coalside entry in front of the working face and the gob-side entry behind the working face, which met the requirements of retaining roadway and production in the next working face. It successfully reduced the difficulty of protecting roadway and the loss of coal pillar, and achieved remarkable economic and social benefits. [ABSTRACT FROM AUTHOR]

The tracking and recognition of facial activities from images or videos have attracted great attention in computer vision field. Facial activities are characterized by three levels. First, in the bottom level, facial feature points around each facial component, i.e., eyebrow, mouth, etc., capture the detailed face shape information. Second, in the middle level, facial action units, defined in the facial action coding system, represent the contraction of a specific set of facial muscles, i.e., lid tightener, eyebrow raiser, etc. Finally, in the top level, six prototypical facial expressions represent the global facial muscle movement and are commonly used to describe the human emotion states. In contrast to the mainstream approaches, which usually only focus on one or two levels of facial activities, and track (or recognize) them separately, this paper introduces a unified probabilistic framework based on the dynamic Bayesian network to simultaneously and coherently represent the facial evolvement in different levels, their interactions and their observations. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge. Given the model and the measurements of facial motions, all three levels of facial activities are simultaneously recognized through a probabilistic inference. Extensive experiments are performed to illustrate the feasibility and effectiveness of the proposed model on all three level facial activities. [ABSTRACT FROM PUBLISHER]

Facial action recognition is concerned with recognizing the local facial motions from image or video. In recent years, besides the development of facial feature extraction techniques and classification techniques, prior models have been introduced to capture the dynamic and semantic relationships among facial action units. Previous works have shown that combining the prior models with the image measurements can yield improved performance in AU recognition. Most of these prior models, however, are learned from data, and their performance hence largely depends on both the quality and quantity of the training data. These data-trained prior models cannot generalize well to new databases, where the learned AU relationships are not present. To alleviate this problem, we propose a knowledge-driven prior model for AU recognition, which is learned exclusively from the generic domain knowledge that governs AU behaviors, and no training data are used. Experimental results show that, with no training data but generic domain knowledge, the proposed knowledge-driven model achieves comparable results to the data-driven model for specific database and significantly outperforms the data-driven models when generalizing to new data set. [ABSTRACT FROM PUBLISHER]

A new optimizing method of mathematical analytical modeling of induced current for electronic anti-fouling technology is used in the present study to solve the problem of large calculated amount and complex deducing process caused by traditional segmented function method under different excitation signal, and an exact 2D finite element method is used to calculate induced current in a real electronic anti-fouling system, and the finite element calculation results can fit well with the results calculated by the optimizing analytical model of induced current under the excitation signal with different waveform. Furthermore, the average power density of induced current and the efficiency of energy transformation for EAF system are calculated to estimate the system performance under different excitation signal. The calculation result shows that: 1 the positive - negative square wave excitation signal can make the largest average power density of induced current and the sine wave excitation signal makes the smallest; 2 the sawtooth wave excitation signal can make the highest efficiency of energy transformation and the positive - negative square wave excitation signal makes the lowest. [ABSTRACT FROM AUTHOR]