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"Yue Yang"
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DTI-HeNE: a novel method for drug-target interaction prediction based on heterogeneous network embedding
Background
Prediction of the drug-target interaction (DTI) is a critical step in the drug repurposing process, which can effectively reduce the following workload for experimental verification of potential drugs’ properties. In recent studies, many machine-learning-based methods have been proposed to discover unknown interactions between drugs and protein targets. A recent trend is to use graph-based machine learning, e.g., graph embedding to extract features from drug-target networks and then predict new drug-target interactions. However, most of the graph embedding methods are not specifically designed for DTI predictions; thus, it is difficult for these methods to fully utilize the heterogeneous information of drugs and targets (e.g., the respective vertex features of drugs and targets and path-based interactive features between drugs and targets).
Results
We propose a DTI prediction method DTI-HeNE (DTI based on Heterogeneous Network Embedding), which is specifically designed to cope with the bipartite DTI relations for generating high-quality embeddings of drug-target pairs. This method splits a heterogeneous DTI network into a bipartite DTI network, multiple drug homogeneous networks and target homogeneous networks, and extracts features from these sub-networks separately to better utilize the characteristics of bipartite DTI relations as well as the auxiliary similarity information related to drugs and targets. The features extracted from each sub-network are integrated using pathway information between these sub-networks to acquire new features, i.e., embedding vectors of drug-target pairs. Finally, these features are fed into a random forest (RF) model to predict novel DTIs.
Conclusions
Our experimental results show that, the proposed DTI network embedding method can learn higher-quality features of heterogeneous drug-target interaction networks for novel DTIs discovery.
Journal Article
بيان الدورة العامة الحادية عشرة للجنة المركزية المنبثقة عن المؤتمر الوطني الثامن للحزب الشيوعي الصيني : (أقر في 12 أغسطس-آب-عام 1966)
عقدت الدورة العامة الحادية عشرة للجنة المركزية المنبثقة عن المؤتمر الوطني الثامن للحزب الشيوعي الصيني في بكين من 1 الى 12 أغسطس (آب) عام 1966، وقد ترأس الدورة العامة الحادية عشرة الرفيق ماو تسي تونغ، وحضرها أعضاء اللجنة المركزية وأعضاؤها المرشحون : وحضرها كذلك الرفاق من مختلف المكاتب الاقليمية للجنة المركزية ومن لجان الحزب في المقاطعات والبلديات والمناطق ذات الحكم الذاتي وأعضاء فرقة الثورة الثقافية للجنة المركزية والرفاق في الدوائر المعنية للجنة المركزية وممثلو المدرسين والطلاب الثوريين في الجامعات والمعاهد العليا بالعاصمة . وقد أقرت الدورة العامة الحادية عشرة بعد المناقشة « قرار اللجنة المركزية للحزب الشيوعي الصيني حول الثورة الثقافية البروليتارية الكبرى » . كما صادقت الدورة العامة بعد النقاش على القرارات السياسية المهمة والاجراءات المهمة فيما يختص بالمسائل الداخلية والخارجية التي أجازها المكتب السياسي للجنة المركزية منذ الدورة العامة العاشرة للجنة المركزية المنبثقة عن المؤتمر الوطني الثامن التي عقدت في سبتمبر (أيلول) عام 1962.
Book
Terabit-Scale Orbital Angular Momentum Mode Division Multiplexing in Fibers
Internet data traffic capadty is rapidly reaching limits imposed by optical fiber nonlinear effects. Having almost exhausted available degrees of freedom to orthogonally multiplex data, the possibility is now being explored of using spatial modes of fibers to enhance data capadty. We demonstrate the viability of using the orbital angular momentum (OAM) of light to create orthogonal, spatially distinct streams of data-transmitting channels that are multiplexed in a single fiber. Over 1.1 kilometers of a specially designed optical fiber that minimizes mode coupling, we achieved 400-gigabits-per-second data transmission using four angular momentum modes at a single wavelength, and 1.6 terabits per second using two OAM modes over 10 wavelengths. These demonstrations suggest that OAM could provide an additional degree of freedom for data multiplexing in future fiber networks.
Journal Article
Heat loss evaluation for heating building envelope based on relevance vector machine
Due to the influence of many factors, there is no reasonable evaluation method for the heat loss evaluation of the envelope, which leads to the deviation of the evaluation results of building energy consumption. By comparing different regression analysis models and considering the heat transfer characteristics of the envelope and heat loss evaluation needs, the dynamic reference value of heat loss evaluation “temperature baseline” which meets different energy saving standards is established. The evaluation method of instantaneous heat loss of the envelope is proposed and the heat loss is studied. The results showed that the performance indexes of relevance vector machine (RVM) regression model was superior to the other two regression models(response surface methodology (RSM), support vector machine (SVM). Based on the RVM regression model, the dynamic prediction model of “temperature baseline” was established by combining numerical simulation with regression analysis. Taking a residential building as an example, the envelope temperature baselines meeting the energy saving standard of 75% and 50% were obtained by using the prediction model, the temperature baselines of walls and windows that save 75% energy were −0.6°C and 1.9 °C respectively, and those that save 50% energy were 1.2°C and 4.5°C. The infrared image and heat loss evaluation method found that 87% of the points exceeded the temperature baseline by more than 2°C, and the total heat loss of the wall with an area of 13m 2 was 471W. The heat loss evaluation method based on RVM proposed in this paper can objectively evaluate the heat loss of building.
Journal Article
Non-KREEP origin for Chang’e-5 basalts in the Procellarum KREEP Terrane
Mare volcanics on the Moon are the key record of thermo-chemical evolution throughout most of lunar history
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–
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. Young mare basalts—mainly distributed in a region rich in potassium, rare-earth elements and phosphorus (KREEP) in Oceanus Procellarum, called the Procellarum KREEP Terrane (PKT)
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—were thought to be formed from KREEP-rich sources at depth
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–
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. However, this hypothesis has not been tested with young basalts from the PKT. Here we present a petrological and geochemical study of the basalt clasts from the PKT returned by the Chang’e-5 mission
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. These two-billion-year-old basalts are the youngest lunar samples reported so far
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. Bulk rock compositions have moderate titanium and high iron contents with KREEP-like rare-earth-element and high thorium concentrations. However, strontium–neodymium isotopes indicate that these basalts were derived from a non-KREEP mantle source. To produce the high abundances of rare-earth elements and thorium, low-degree partial melting and extensive fractional crystallization are required. Our results indicate that the KREEP association may not be a prerequisite for young mare volcanism. Absolving the need to invoke heat-producing elements in their source implies a more sustained cooling history of the lunar interior to generate the Moon’s youngest melts.
Isotopic analysis of basalt clasts returned from the Moon by the Chang’e-5 mission indicates that the rocks were derived from a mantle source that lacked potassium, rare-earth elements and phosphorus.
Journal Article
Trends in the Incidence of Vulvar and Vaginal Cancers With Different Histology by Race, Age, and Region in the United States (2001–2018)
Objectives: The race, age, and region-stratified incidence of vulvar (VUC) and vaginal (VAC) cancers with different histology were unclear. Methods: Data was retrieved from the United States Cancer Statistics database. Average annual percent change (AAPC) and incidence rate ratio (IRR) were calculated. Results: Overall, VUC incidence increased from 18.3 (per 1,000,000 woman-years) to 19.6, but VAC incidence decreased from 5.6 to 4.4. VUC squamous cell carcinoma (SCC) incidence increased (AAPC, 0.96; 95% CI, 0.66–1.25), VUC adenocarcinoma (ADE) incidence stabilized (AAPC, −0.24; 95% CI, −1.44 to 0.98), and VUC other malignancies (OM) incidence decreased (AAPC, −1.31; 95% CI, −2.58 to −0.02). While VAC incidence decreased for any histology (AAPC, -0.63; 95% CI, −1.03 to −0.22; AAPC, −1.60; 95% CI, −2.80 to −0.39; and AAPC, −1.57; 95% CI, −2.24 to −0.89 for SCC, ADE, and OM). Similar trends were observed in most of the stratifications. Conclusion: VUC and VAC incidences varied by histology overall and within stratifications by race, age, and region. The incidence decreased for VUC and VAC with all histologies, except for the increasing VUC SCC incidence.
Journal Article
High‐Performance Flexible Pressure Sensor with a Self‐Healing Function for Tactile Feedback
High‐performance flexible pressure sensors have attracted a great deal of attention, owing to its potential applications such as human activity monitoring, man–machine interaction, and robotics. However, most high‐performance flexible pressure sensors are complex and costly to manufacture. These sensors cannot be repaired after external mechanical damage and lack of tactile feedback applications. Herein, a high‐performance flexible pressure sensor based on MXene/polyurethane (PU)/interdigital electrodes is fabricated by using a low‐cost and universal spray method. The sprayed MXene on the spinosum structure PU and other arbitrary flexible substrates (represented by polyimide and membrane filter) act as the sensitive layer and the interdigital electrodes, respectively. The sensor shows an ultrahigh sensitivity (up to 509.8 kPa–1), extremely fast response speed (67.3 ms), recovery speed (44.8 ms), and good stability (10 000 cycles) due to the interaction between the sensitive layer and the interdigital electrodes. In addition, the hydrogen bond of PU endows the device with the self‐healing function. The sensor can also be integrated with a circuit, which can realize tactile feedback function. This MXene‐based high‐performance pressure sensor, along with its designing/fabrication, is expected to be widely used in human activity detection, electronic skin, intelligent robots, and many other aspects. A MXene‐based high‐performance flexible piezoresistive sensor is fabricated by a simple spraying method. Due to the abundant hydrogen bonds of polyurethane, the pressure sensor owns a self‐healing function. By integrating the flexible piezoresistive sensor with manipulator, resistance–voltage converter, SGS‐THOMSON Microelectronics (STM) 32 microprogrammed control unit signal analysis unit, and touchscreen, a tactile feedback system is achieved.
Journal Article
Enhanced YOLOv11 Framework for Accurate Multi-Fault Detection in UAV Photovoltaic Inspection
Stains, defects, and snow accumulation constitute three prevalent photovoltaic (PV) anomalies; each exhibits unique color and thermal signatures yet collectively curtail energy yield. Existing detectors typically sacrifice accuracy for speed, and none simultaneously classify all three fault types. To counter the identified limitations, an enhanced YOLOv11 framework is introduced. First, the hue-saturation-value (HSV) color model is employed to decouple hue and brightness, strengthening color feature extraction and cross-sensor generalization. Second, an outlook attention module integrated into the backbone precisely delineates micro-defect boundaries. Third, a mix structure block in the detection head encodes global context and fine-grained details to boost small object recognition. Additionally, the bounded sigmoid linear unit (B-SiLU) activation function optimizes gradient flow and feature discrimination through an improved nonlinear mapping, while the gradient-weighted class activation mapping (Grad-CAM) visualizations confirm selective attention to fault regions. Experimental results show that overall mean average precision (mAP) rises by 1.8%, with defect, stain, and snow accuracies improving by 2.2%, 3.3%, and 0.8%, respectively, offering a reliable solution for intelligent PV inspection and early fault detection.
Journal Article