network construction

High performance organic solar cells (OSCs) are usually realized by using thermal post-treatment and/or additive, which can induce the formation of metastable morphology, leading to unfavorable device stability. In terms of the industrial production, the development of high efficiency as-cast OSCs is crucially important, but it remains a great challenge to obtain appropriate active layer morphology and high power conversion efficiency (PCE). Here, efficient as-cast OSCs are constructed via introducing a new polymer acceptor PY-TPT with a high dielectric constant into the D18:L8-BO blend to form a double-fibril network morphology...

The sodium (Na) metal anode encounters issues such as volume expansion and dendrite growth during cycling. Herein, a novel three-dimensional flexible composite Na metal anode was constructed through the conversion-alloying reaction between Na and ultrafine Sb2 S3 nanoparticles encapsulated within the electrospun carbon nanofibers (Sb2 S3 @CNFs). The formed sodiophilic Na3 Sb sites and the high Na+ -conducting Na2 S matrix, coupled with CNFs, establish a spatially confined "sodiophilic-conductive" network, which effectively reduces the Na nucleation barrier, improves the Na+ diffusion kinetics, and suppresses the volume expansion, thereby inhibiting the Na dendrite growth...

The poor bulk-phase and interphase stability, attributable to adverse internal stress, impede the cycling performance of silicon microparticles (μSi) anodes and its commercial application for high-energy-density lithium-ion batteries. In this work, we propose a groundbreaking gradient-hierarchically ordered conductive (GHOC) network structure, ingeniously engineered to enhance the stability of both bulk-phase and the solid electrolyte interphase (SEI) configurations of μSi. Within the GHOC network architecture, two-dimensional transition metal carbides (Ti3 C2 Tx ) acts as a conductive "brick", establishing a highly conductive inner layer on μSi, while the porous outer layer, composed of one-dimensional Tempo-oxidized cellulose nanofibers (TCNF) and polyacrylic acid (PAA) macromolecule, functions akin to structural "rebar" and "concrete", effectively preserves the tightly interconnected conductive framework though multiple bonding mechanisms, including covalent and hydrogen bonds...

BACKGROUND: CESC is the second most commonly diagnosed gynecological malignancy. Given the pivotal involvement of metabolism-related genes (MRGs) in the etiology of multiple tumors, our investigation aims to devise a prognostic risk signature rooted in cancer stemness and metabolism. METHODS: The stemness index based on mRNA expression (mRNAsi) of samples from the TCGA dataset was computed using the One-class logistic regression (OCLR) algorithm. Furthermore, potential metabolism-related genes related to mRNAsi were identified through weighted gene co-expression network analysis (WGCNA)...

Text content analysis for depression detection using machine learning techniques has become a prominent area of research. However, previous studies focused mainly on analyzing the textual content, neglecting the fundamental factors driving text generation. Consequently, existing models face the challenge of poor generalization to out-of-domain data as they struggle to capture the crucial features of depression. To address this, we propose a novel computational perspective of "stimulus-response patterns" that brings us closer to the essence of clinical diagnosis of depression...

For industrial processes, it is significant to carry out the dynamic modeling of data series for quality prediction. However, there are often different sampling rates between the input and output sequences. For the most traditional data series models, they have to carefully select the labeled sample sequence to build the dynamic prediction model, while the massive unlabeled input sequences between labeled samples are directly discarded. Moreover, the interactions of the variables and samples are usually not fully considered for quality prediction at each labeled step...

Multilabel feature selection solves the dimension distress of high-dimensional multilabel data by selecting the optimal subset of features. Noisy and incomplete labels of raw multilabel data hinder the acquisition of label-guided information. In existing approaches, mapping the label space to a low-dimensional latent space by semantic decomposition to mitigate label noise is considered an effective strategy. However, the decomposed latent label space contains redundant label information, which misleads the capture of potential label relevance...

In this work we develop a new scheme to construct a diabatic potential energy matrix (DPEM). We propose a diabatization method which is based on integrating the diabatic potential gradient difference to diabatize adiabatic ab initio energies. This method is capable of performing high-precision adiabatic-to-diabatic transformations, with a unique advantage in effectively handling the significant fluctuations in derivative-couplings caused by conical intersection (CI) seams. The above scheme is applied to the DPEM construction of the Na(3p) + H2 → NaH + H reaction...

This paper proposes a medical image fusion method in the non-subsampled shearlet transform (NSST) domain to combine a gray-scale image with the respective pseudo-color image obtained through different imaging modalities. The proposed method applies a novel improved dual-channel pulse-coupled neural network (IDPCNN) model to fuse the high-pass sub-images, whereas the Prewitt operator is combined with maximum regional energy (MRE) to construct the fused low-pass sub-image. First, the gray-scale image and luminance of the pseudo-color image are decomposed using NSST to find the respective sub-images...

AIMS: Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co-existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies. METHODS AND RESULTS: The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, 'limma' was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs)...

Plants produce diverse specialized metabolites (SMs) that do not participate in plant growth and development but help them adapt to various environmental conditions. In addition to aiding in plant adaptation, different SMs serve as active ingredients for pharmaceutical and cosmetics products. However, despite their significant role in plant adaptation and industrial importance, the genes involved in the biosynthesis and regulation of many SMs remain largely unknown. This hinders deciphering the specific role of SMs in plant adaptation and limits their industrial utilization...

Plant genetics plays a key role in determining root hair initiation and development. A complex network of genetic interactions therefore closely monitors and influences root hair phenotype and morphology. The significance of these genes can be studied by employing, for instance, loss-of-function mutants, overexpression plant lines, and fluorescently labeled constructs. Confocal laser scanning microscopy is a great tool to visually observe and document these morphological features. This chapter elaborates the techniques involved in handling of microscopic setup to acquire images displaying root hair distribution along the fully elongated zone of Arabidopsis thaliana roots...

Stroke is a leading cause of death and disability, and genetic risk factors play a significant role in its development. Unfortunately, effective therapies for stroke are currently limited. Early detection and diagnosis are critical for improving outcomes and developing new treatment strategies. In this study, we aimed to identify potential biomarkers and effective prevention and treatment strategies for stroke by conducting transcriptome and single-cell analyses. Our analysis included screening for biomarkers, functional enrichment analysis, immune infiltration, cell-cell communication, and single-cell metabolism...

The osseous vascular endothelium encompasses a vast intricate framework that regulates bone remodeling. Osteoporosis, an age-associated systemic bone disease, is characterized by the degeneration of the vascular architecture. Nevertheless, the precise mechanisms underpinning the metamorphosis of endothelial cells (ECs) with advancing age remain predominantly enigmatic. In this study, we conducted a systematic analysis of differentially expressed genes (DEGs) and the associated pathways in juvenile and mature femoral ECs, utilizing data sourced from the Gene Expression Omnibus (GEO) repositories (GSE148804) and employing bioinformatics tools...

This study aims to analyze the feasibility of building an evaluative model for the management of the Tuberculosis Prevention and Control Program in the State of Roraima, located on the border between Brazil and Venezuela. This is an evaluability assessment, a type of study used as a pre-evaluation of the development and implementation stages of a program, as well as throughout its execution. The study was developed in stages comprising the: (i) definition of the intervention to be analyzed and its objectives and goals; (ii) construction of the intervention logical model; (iii) screening of parties interested in the evaluation; (iv) definition of the evaluative questions; and (v) design of the evaluation matrix...

The multidomain protein BAG3 exerts pleiotropic oncogenic functions in many tumor entities including glioblastoma (GBM). Here, we compared BAG3 protein-protein interactions in either adherently cultured or stem-like cultured U251 GBM cells. In line with BAG3's putative role in regulating stem-like properties, identified interactors in sphere-cultured cells included different stem cell markers (SOX2, OLIG2, and NES), while interactomes of adherent BAG3-proficient cells indicated a shift toward involvement of BAG3 in regulation of cilium assembly (ACTR3 and ARL3)...

The design and preparation of flexible aerogel materials with high deformability and versatility have become an emerging research topic in the aerogel fields, as the brittle nature of traditional aerogels severely affects their safety and reliability in use. Herein, we review the preparation methods and properties of flexible aerogels and summarize the various controlling and design methods of aerogels to overcome the fragility caused by high porosity and nanoporous network structure. The mechanical flexibility of aerogels can be revolutionarily improved by monomer regulation, nanofiber assembly, structural design and controlling, and constructing of aerogel composites, which can greatly broaden the multifunctionality and practical application prospects...

BACKGROUND: Although the spatio-temporal structure of muscle activation in cutting have been studied extensively, including time-varying motor primitives and time-invariant motor modules under various conditions, the factorisation methods suitable for cutting are unclear, and the extent to which each factorisation method loses information about movement during dimensionality reduction is uncertain. RESEARCH QUESTION: To clarify the extent to which NMF, PCA and ICA retain information about movement when downscaling, and to explore the factorisation method suitable for cutting...

BACKGROUND: Tumor initiation and metastasis influence tumor immune exclusion and immunosuppression. Long non-coding RNA (lncRNA) LINC01614 is associated with the prognosis and metastasis of several cancers. However, the relationship between LINC01614 and cancer immune infiltration and the biofunction of LINC01614 in head and neck squamous cell carcinoma (HNSC) remain unclear. METHODS: The Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets were used to analyze the expression difference and diagnostic value of LINC01614 in normal and tumor tissues...

When detecting tomato leaf diseases in natural environments, factors such as changes in lighting, occlusion, and the small size of leaf lesions pose challenges to detection accuracy. Therefore, this study proposes a tomato leaf disease detection method based on attention mechanisms and multi-scale feature fusion. Firstly, the Convolutional Block Attention Module (CBAM) is introduced into the backbone feature extraction network to enhance the ability to extract lesion features and suppress the effects of environmental interference...