Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim to analytically interpret the waiting times predicted by machine learning models and provide patients with an explanation of the expected waiting time. Here, underestimating waiting times can cause patient dissatisfaction, so preventing this in predictive models is necessary.

A novel machine learning-based prediction method for patients at risk of developing depressive symptoms using a small data.

The prediction of depression is a crucial area of research which makes it one of the top priorities in mental health research as it enables early intervention and can lead to higher success rates in treatment. Self-reported feelings by patients represent a valuable biomarker for predicting depression as they can be expressed in a lower-dimensional network form, offering an advantage in visualizing the interactive characteristics of depression-related feelings. Furthermore, the network form of data expresses high-dimensional data in a compact form, making the data easy to use as input for the machine learning processes.

Short tandem repeat expansions in cortical layer-specific genes implicate in phenotypic severity and adaptability of autism spectrum disorder.

Aim: Short tandem repeats (STRs) are repetitive DNA sequences and highly mutable in various human disorders. While the involvement of STRs in various genetic disorders has been extensively studied, their role in autism spectrum disorder (ASD) remains largely unexplored. In this study, we aimed to investigate genetic association of STR expansions with ASD using whole genome sequencing (WGS) and identify risk loci associated with ASD phenotypes.

Functionalized γ-Boehmite Covalent Grafting Modified Polyethylene for Lithium-Ion Battery Separator.

In the field of lithium-ion batteries, the challenges posed by the low melting point and inadequate wettability of conventional polyolefin separators have increased the focus on ceramic-coated separators. This study introduces a highly efficient and stable boehmite/polydopamine/polyethylene (AlOOH-PDA-PE) separator. It is crafted by covalently attaching functionalized nanosized boehmite (γ-AlOOH) whiskers onto polyethylene (PE) surfaces.

Can carbon reduction policies promote sustainable construction development? Evidence from China's green building market.

Carbon emissions have become a global challenge, and China, as the world's largest developing country, has a serious emissions problem. Developing green buildings is an important way of reducing carbon emissions. China's low-carbon city pilot policy may be an effective way of promoting green building development and reducing these emissions.

Loss of Katnal2 leads to ependymal ciliary hyperfunction and autism-related phenotypes in mice.

Autism spectrum disorders (ASD) frequently accompany macrocephaly, which often involves hydrocephalic enlargement of brain ventricles. Katnal2 is a microtubule-regulatory protein strongly linked to ASD, but it remains unclear whether Katnal2 knockout (KO) in mice leads to microtubule- and ASD-related molecular, synaptic, brain, and behavioral phenotypes. We found that Katnal2-KO mice display ASD-like social communication deficits and age-dependent progressive ventricular enlargements.

Design of high-performance entangling logic in silicon quantum dot systems with Bayesian optimization.

Device engineering based on computer-aided simulations is essential to make silicon (Si) quantum bits (qubits) be competitive to commercial platforms based on superconductors and trapped ions. Combining device simulations with the Bayesian optimization (BO), here we propose a systematic design approach that is quite useful to procure fast and precise entangling operations of qubits encoded to electron spins in electrode-driven Si quantum dot (QD) systems. For a target problem of the controlled-X (CNOT) logic operation, we employ BO with the Gaussian process regression to evolve design factors of a Si double QD system to the ones that are optimal in terms of speed and fidelity of a CNOT logic driven by a single microwave pulse.

Research on Chinese medicinal materials cultivation: A bibliometric and visual analysis.

Chinese medicinal materials (CMMs) are important strategic resource in China. The cultivation process of medicinal plants is the key link which directly affect the quality and efficacy. The literatures of CMMs cultivation were acquired from China National Knowledge Infrastructure (CNKI) database and State Intellectual Property Office (SIPO) patent database for the years between 2001 and 2021.

GCNGAT: Drug-disease association prediction based on graph convolution neural network and graph attention network.

Predicting drug-disease associations can contribute to discovering new therapeutic potentials of drugs, and providing important association information for new drug research and development. Many existing drug-disease association prediction methods have not distinguished relevant background information for the same drug targeted to different diseases. Therefore, this paper proposes a drug-disease association prediction model based on graph convolutional network and graph attention network (GCNGAT) to reposition marketed drugs under the distinguishment of background information.

Bidirectional de novo peptide sequencing using a transformer model.

In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely employed to identify peptide sequences, and numerous tools have been proposed over the past two decades. Recently, deep learning approaches have been introduced for de novo sequencing.

Protein-lipid acyl chain interactions: Depth-dependent changes of segmental mobility of phospholipid in contact with bacteriorhodopsin.

Boundary lipids surrounding membrane proteins play an essential role in protein function and structure. These protein-lipid interactions are mainly divided into electrostatic interactions between the polar amino acids of proteins and polar heads of phospholipids, and hydrophobic interactions between protein transmembrane sites and phospholipid acyl chains. Our previous report (Kawatake et al.

ψ(2S) Suppression in Pb-Pb Collisions at the LHC.

The production of the ψ(2S) charmonium state was measured with ALICE in Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV, in the dimuon decay channel. A significant signal was observed for the first time at LHC energies down to zero transverse momentum, at forward rapidity (2.

Comparison of geological clusters between influenza and COVID-19 in Thailand with unsupervised clustering analysis.

The coronavirus disease (COVID-19) pandemic has considerably impacted public health, including the transmission patterns of other respiratory pathogens, such as the 2009 pandemic influenza (H1N1). COVID-19 and influenza are both respiratory infections that started with a lack of vaccination-based immunity in the population. However, vaccinations have been administered over time, resulting in a transition of the status of both diseases from a pandemic to an endemic.

Polyelectrolytes: From Seminal Works to the Influence of the Charge Sequence.

We propose a selected tour of the physics of polyelectrolytes (PE) following the line initiated by de Gennes and coworkers in their seminal 1976 paper. The early works which used uniform charge distributions along the PE backbone achieved tremendous progress and set most milestones in the field. Recently, the focus has shifted to the role of the charge sequence.

Modeling the compaction of bacterial chromosomes by biomolecular crowding and the cross-linking protein H-NS.

Cells orchestrate the action of various molecules toward organizing their chromosomes. Using a coarse-grained computational model, we study the compaction of bacterial chromosomes by the cross-linking protein H-NS and cellular crowders. In this work, H-NS, modeled as a mobile "binder," can bind to a chromosome-like polymer with a characteristic binding energy.

Oxygen vacancy healing boosts the piezoelectricity of bone scaffolds.

Although barium titanate (BaTiO) presented tremendous potential in achieving self-powered stimulation to accelerate bone repair, pervasive oxygen vacancies restricted the full play of its piezoelectric performance. Herein, BaTiO-GO nanoparticles were synthesized by the growth of BaTiO on graphene oxide (GO), and subsequently introduced into poly-L-lactic acid (PLLA) powders to prepare PLLA/BaTiO-GO scaffolds by laser additive manufacturing. During the synthesis process, CO and C-OH in GO would respectively undergo cleavage and dehydrogenation at high temperature to form negatively charged oxygen groups, which were expected to occupy positively charged oxygen vacancies in BaTiO and thereby inhibit the formation of oxygen vacancies.

A prospective approach to detect advanced persistent threats: Utilizing hybrid optimization technique.

Advanced Persistent Threat (APT) attacks pose significant challenges for AI models in detecting and mitigating sophisticated and highly effective cyber threats. This research introduces a novel concept called Hybrid HHOSSA which is the grouping of Harris Hawk Optimization (HHO) and Sparrow Search Algorithm (SSA) characteristics for optimizing the feature selection and data balancing in the context of APT detection. In addition, the light GBM as well as the weighted average Bi-LSTM are optimized by the proposed hybrid HHOSSA optimization.

Allelopathic Mechanisms in - L. Intercropping.

Tree-crop intercropping is of great significance in food security, land protection, and sustainable agriculture. However, the mechanisms of allelopathy between plant species during intercropping are still limited. This study focuses on the allelopathic effects in the intercropping between and L.