Gradual pollen presentation in 'Bluecrop': an adaptive mechanism to improve pollination efficiency and outcrossing.

Gradual pollen presentation is a plant reproductive mechanism to improve pollination efficiency and accuracy and promote outcrossing. 'Bluecrop' has a typical gradual pollen presentation mechanism. 'Bluecrop' exhibits an inverted bell-shaped flower with a white coloration.

The relationship between academic stress and depression among college students during the COVID-19 pandemic: a cross-sectional study from China.

Background: The COVID-19 pandemic is a global public health crisis. During the COVID-19 pandemic, mental health has attracted great attention. However, there is a lack of research on the relationship between academic stress and depression in Chinese college students and its mechanisms.

A new multiregional carbon emissions forecasting model based on a multivariable information fusion mechanism and hybrid spatiotemporal graph convolution network.

Developing scientific and effective carbon emissions reduction policies relies heavily on precise carbon emission trend prediction. The existing complex spatiotemporal correlation and diverse range of influencing factors associated with multi-regional carbon emissions pose significant challenges to accurately modeling these trends. Under this constraint, this study is inspired by graph learning to establish a hybrid dynamic and static graph-based regional carbon emission network framework, which introduces a novel research standpoint for investigating short-term carbon emissions prediction (CEP).

Phenylalanine-Arginine-β-Naphthylamide Enhances the Photobactericidal Effect of Methylene Blue on .

To investigate the effectiveness, dosing sequence, concentration, and mechanism of antimicrobial photodynamic inactivation (aPDI) using methylene blue (MB) plus phenylalanine-arginine-β-naphthylamide (PAβN) against . bacterial suspension was incubated with MB for different times (5-240 min), and then, 10 J/cm red light was irradiated. The efflux pump inhibitor (EPI) PAβN (10-100 μg/mL) was combined with MB (1-20 μM) in different sequences (PAβN-first, PAβN+MB, PAβN-after).

Three-Dimensional Collision Avoidance Method for Robot-Assisted Minimally Invasive Surgery.

In the robot-assisted minimally invasive surgery, if a collision occurs, the robot system program could be damaged, and normal tissues could be injured. To avoid collisions during surgery, a 3-dimensional collision avoidance method is proposed in this paper. The proposed method is predicated on the design of 3 strategic vectors: the collision-with-instrument-avoidance (CI) vector, the collision-with-tissues-avoidance (CT) vector, and the constrained-control (CC) vector.

The impact of family functioning on depression in college students: A moderated mediation model.

Background: The depression of college students is increasing. Family dysfunction is a potential risk factor for depression. More research is needed to uncover the relationship and influencing mechanism.

Biohybrid magnetic microrobots: An intriguing and promising platform in biomedicine.

Biohybrid magnetic microrobots (BMMs) have emerged as an exciting class of microrobots and have been considered as a promising platform in biomedicine. Many microorganisms and body's own cells show intriguing properties, such as morphological characteristics, biosafety, and taxis abilities (e.g.

Carbon reduction behavior of waste power battery recycling enterprises considering learning effects.

The carbon reduction behavior of waste power battery recycling (WPBR) enterprises is essential for promoting resource conservation and environmental protection. Introducing the learning effects of carbon reduction research and development (R&D) investment, this study constructs an evolutionary game model between local governments and WPBR enterprises to study the behavior choice of carbon reduction. The paper explores the evolutionary process and factors affecting carbon reduction behavior choices of WPBR enterprises from internal R&D motivation and external regulation perspectives.

Physician scheduling problem in Mobile Cabin Hospitals of China during Covid-19 outbreak.

In this paper, we investigate a novel physician scheduling problem in the Mobile Cabin Hospitals (MCH) which are constructed in Wuhan, China during the outbreak of the Covid-19 pandemic. The shortage of physicians and the surge of patients brought great challenges for physicians scheduling in MCH. The purpose of the studied problem is to get an approximately optimal schedule that reaches the minimum workload for physicians on the premise of satisfying the service requirements of patients as much as possible.

Discovery of Orally Bioavailable -Benzylpiperidinol Derivatives as Potent and Selective USP7 Inhibitors with In Vivo Antitumor Immunity Activity against Colon Cancer.

USP7 emerges as a potential therapeutic target for cancers, as it plays an important role in the development of tumorigenesis by stabilizing multiple cancer-relevant proteins. Nevertheless, the discovery of drug-like USP7 inhibitors remains challenging. Herein, we report a series of -benzylpiperidinol derivatives as potent and selective USP7 inhibitors (e.

The driving effect of technological innovation on green development: dynamic efficiency spatial variation.

In order to further explore the internal transmission mechanism between technological innovation and green development in manufacturing industry under the background of obvious development characteristics in the new era, this paper constructed an integrated methodology system to evaluate the internal impact mechanism of technological innovation value chain efficiency on green development efficiency based on spatial perspective. First, the Network Slack-based model and Global Malmquist-Luenberger model are constructed to reveal the internal development law of technological innovation and green development of manufacturing industry. Secondly, the spatial Dubin model is employed to analyze the impact of current development characteristics and technological innovation on green development.

Design, Synthesis, and Biological Evaluation of Triazolone Derivatives as Potent PPARα/δ Dual Agonists for the Treatment of Nonalcoholic Steatohepatitis.

Peroxisome proliferator-activator receptors α/δ (PPARα/δ) are regarded as potential therapeutic targets for nonalcoholic steatohepatitis (NASH). However, PPARα/δ dual agonist exhibited poor anti-NASH effects in a phase III clinical trial, probably due to its weak PPARα/δ agonistic activity and poor metabolic stability. Other reported PPARα/δ dual agonists either exhibited limited potency or had unbalanced PPARα/δ agonistic activity.

An Adaptive Deep Ensemble Learning Method for Dynamic Evolving Diagnostic Task Scenarios.

Increasingly, machine learning methods have been applied to aid in diagnosis with good results. However, some complex models can confuse physicians because they are difficult to understand, while data differences across diagnostic tasks and institutions can cause model performance fluctuations. To address this challenge, we combined the Deep Ensemble Model (DEM) and tree-structured Parzen Estimator (TPE) and proposed an adaptive deep ensemble learning method (TPE-DEM) for dynamic evolving diagnostic task scenarios.

Antimicrobial photodynamic therapy for oral Candida infection in adult AIDS patients: A pilot clinical trial.

Background: Antimicrobial photodynamic therapy (aPDT) using methylene blue (MB) plus potassium iodide (KI) has been shown to be effective in killing Candida albicans in many in vitro and in vivo studies, however, there are limited reports of clinical investigations. This study aimed to explore the clinical application of aPDT with MB plus KI for the treatment of oral infection caused by C. albicans in adult acquired immune deficiency syndrome (AIDS) patients.

Automatic Acetowhite Lesion Segmentation via Specular Reflection Removal and Deep Attention Network.

Automatic acetowhite lesion segmentation in colposcopy images (cervigrams) is essential in assisting gynecologists for the diagnosis of cervical intraepithelial neoplasia grades and cervical cancer. It can also help gynecologists determine the correct lesion areas for further pathological examination. Existing computer-aided diagnosis algorithms show poor segmentation performance because of specular reflections, insufficient training data and the inability to focus on semantically meaningful lesion parts.

SCNET: A Novel UGI Cancer Screening Framework Based on Semantic-Level Multimodal Data Fusion.

Upper gastrointestinal (UGI) cancer has been identified as one of the ten most common causes of cancer deaths globally. UGI cancer screening is critical to improving the survival rate of UGI cancer patients. While many approaches to UGI cancer screening rely on single-modality data such as gastroscope imaging, limited studies have been dedicated to UGI cancer screening exploiting multisource and multimodal medical data, which could potentially lead to improved screening results.

Data-Driven Analysis of Radiologists' Behavior for Diagnosing Thyroid Nodules.

Thyroid nodule has been a common and serious threaten to human health. With the identification and diagnosis of thyroid nodules in the general population, large volumes of examination reports in clinical practice have been accumulated. They provide data basics of analyzing radiologists' behavior of diagnosing thyroid nodules.

Elaborated pollen packaging and dispensing mechanism induced by petal architecture from a Papaveraceae species.

Secondary pollen presentation (SPP) is a reproductive strategy that enhances the efficiency of pollen transfer, which has been explored for more than 200 years, resulting in 10 identified types of SPP. The ephemeral plant L. (Papaveraceae) has an elaborate petal structure.

Decomposition analysis of China's CO emissions (2000-2016) and scenario analysis of its carbon intensity targets in 2020 and 2030.

To address the unprecedented increase in China's CO emissions over the past decades, the Chinese government has implemented many policies that are aimed at reducing carbon intensity. Applying the LMDI method, this study conducts a decomposition analysis of the drivers influencing China's CO emissions by examining the details of 41 industry sub-sectors during 2000-2016; further, it predicts the carbon intensity reduction potential in 2020 and 2030 based on various official policies and documents. We conclude that energy intensity was the primary indicator that reduced CO emissions, whereas the effects of carbon intensity, energy mix, and industrial structure were relatively minor.

Blockchain-Based Medical Records Secure Storage and Medical Service Framework.

Accurate and complete medical data are one valuable asset for patients. Privacy protection and the secure storage of medical data are crucial issues during medical services. Secure storage and making full use of personal medical records has always been a concern for the general population.

Interval-valued distributed preference relation and its application to group decision making.

As an important way to help express the preference relation between alternatives, distributed preference relation (DPR) can represent the preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another simultaneously. DPR, however, is unavailable in some situations where a decision maker cannot provide the precise degrees of one alternative over another due to lack of knowledge, experience, and data. In this paper, to address this issue, we propose interval-valued DPR (IDPR) and present its properties of validity and normalization.

SPD-based Logistics Management Model of Medical Consumables in Hospitals.

Background: With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals.

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users.

Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation.

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer.

Intelligent technique for knowledge reuse of dental medical records based on case-based reasoning.

With the rapid development of both information technology and the management of modern medical regulation, the generation of medical records tends to be increasingly intelligent. In this paper, Case-Based Reasoning is applied to the process of generating records of dental cases. Based on the analysis of the features of dental records, a case base is constructed.