Sex differences in the relationship between olfactory and cognitive impairment among subjects with subjective cognitive decline and mild cognitive impairment.

Background: Odor identification (OI) deficits are observed in both individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI), and serve as risk factors for dementia. Compared with males, females typically demonstrate superior OI performance and different risks of dementia. However, the role of sex in the relationship between OI dysfunction and cognitive impairment remains uncertain.

Plasma p-tau217 and p-tau217/Aβ1-42 are effective biomarkers for identifying CSF- and PET imaging-diagnosed Alzheimer's disease: Insights for research and clinical practice.

Introduction: With the advancement of disease-modifying therapies for Alzheimer's disease (AD), validating plasma biomarkers against cerebrospinal fluid (CSF) and positron emission tomography (PET) standards is crucial in both research and real-world settings.

Methods: We measured plasma phosphorylated tau (p-tau)217, p-tau181, amyloid beta (Aβ)1-40, Aβ1-42, and neurofilament light chain in research and real-world cohorts. Participants were categorized by brain amyloid status using US Food and Drug Administration/European Medicines Agency-approved CSF or PET methods.

Chemosensory anhedonia facilitates depressive symptoms and cognitive impairment in late-life depression.

Aim: Chemosensory anhedonia refers to the lack of hedonic ability to experience pleasure through the senses of smell and taste, which reduces the pleasure and comfort of food, and increases the risk of nutritional and immune deficiencies. However, there is no direct scientific evidence regarding chemosensory anhedonia in patients with late-life depression (LLD). The aim of this study was to investigate chemosensory anhedonia in patients with LLD, and its potential association with depressive symptoms and cognitive function.

Olfactory Dysfunction as a Marker for Cognitive Impairment in General Paresis of the Insane: A Clinical Study.

BACKGROUND General paresis of the insane (GPI) is characterized by cognitive impairment, neuropsychiatric symptoms, and brain structural abnormalities, mimicking many neuropsychiatric diseases. Olfactory dysfunction has been linked to cognitive decline and neuropsychiatric symptoms in numerous neuropsychiatric diseases. Nevertheless, it remains unclear whether patients with GPI experience olfactory dysfunction and whether olfactory dysfunction is associated with their clinical manifestations.

Abnormalities in Electroencephalographic Microstates in Patients with Late-Life Depression.

Background: Late-life depression (LLD) is characterized by disrupted brain networks. Resting-state networks in the brain are composed of both stable and transient topological structures known as microstates, which reflect the dynamics of the neural activities. However, the specific pattern of EEG microstate in LLD remains unclear.

Simulation of a Multistaggered Baffle Scrubber to Enhance the Efficiency of Simultaneous Desulfurization and Denitrification.

In this study, we conduct simulation research on simultaneous desulfurization and denitrification in a multistaggered baffle spray scrubber. By employing two-phase flow simulations within the Euler-Lagrange framework and calculating the gas-liquid mass transfer rate with user-defined functions, we comprehensively analyzed the effects of various operational parameters. Initially, we validated our simulation model by comparing the simulation results with experimental data.

Observation of Strong Anisotropic Interlayer Excitons.

Anisotropic interlayer excitons had been theoretically predicted to exist in two-dimensional (2D) anisotropy/isotropy van der Waals heterojunctions. However, experimental results consolidating the theoretical prediction and exploring the related anisotropic optoelectronic response have not been reported so far. Herein, strong photoluminescence (PL) of anisotropic interlayer excitons is observed in a symmetric anisotropy/isotropy/anisotropy heterojunction exemplified by 3L-ReS/1L-MoS/3L-ReS using monolayer (1L) MoS and trilayer (3L) ReS as components.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study.

Objective: Cognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity.

Relationships Among Short Self-Reported Sleep Duration, Cognitive Impairment, and Insular Functional Connectivity in Late-Life Depression.

Background: Both late-life depression (LLD) and short sleep duration increase the risk of cognitive impairment. Increased insular resting-state functional connectivity (FC) has been reported in individuals with short sleep duration and dementia.

Objective: This study aimed to investigate whether short sleep duration is associated with impaired cognition and higher insular FC in patients with LLD.

E Outlier: a Self-Supervised Framework for Unsupervised Deep Outlier Detection.

Existing unsupervised outlier detection (OD) solutions face a grave challenge with surging visual data like images. Although deep neural networks (DNNs) prove successful for visual data, deep OD remains difficult due to OD's unsupervised nature. This paper proposes a novel framework named E Outlier that can perform effective and end-to-end deep outlier removal.

Probing Nanoscale Exciton Funneling at Wrinkles of Twisted Bilayer MoS Using Tip-Enhanced Photoluminescence Microscopy.

In twisted bilayer (t2L) two-dimensional (2D) transition metal dichalcogenides, local strain at wrinkles strongly modulates the local exciton density and PL energy resulting in an exciton funneling effect. Probing such exciton behaviors especially at nanometer length scales is beyond the limit of conventional analytical tools due to the limited spatial resolution and low sensitivity. To address this challenge, herein we applied high-resolution tip-enhanced photoluminescence (TEPL) microscopy to investigate exciton funneling at a wrinkle in a t2L MoS sample with a small twist angle of 0.

Label propagation via local geometry preserving for deep semi-supervised image recognition.

In this paper, we propose a novel transductive pseudo-labeling based method for deep semi-supervised image recognition. Inspired from the superiority of pseudo labels inferred by label propagation compared with those inferred from network, we argue that information flow from labeled data to unlabeled data should be kept noiseless and with minimum loss. Previous research works use scarce labeled data for feature learning and solely consider the relationship between two feature vectors to construct the similarity graph in feature space, which causes two problems that ultimately lead to noisy and incomplete information flow from labeled data to unlabeled data.

Multimodal Nanoscopic Study of Atomic Diffusion and Related Localized Optoelectronic Response of WS/MoS Lateral Heterojunctions.

The atomic diffusion in transition metal dichalcogenides (TMDs) van der Waals heterojunctions (HJs) strongly modifies their optoelectronic properties in the nanoscale. However, probing such localized properties challenges the spatial resolution and the sensitivity of a variety of analytic tools. Herein, a multimodal nanoscopy (based on tip enhanced Raman spectroscopy (TERS) and photoluminescence (TEPL)) combined with the Kelvin probe force microscopy (KPFM) method was used to probe such nanoscale localized optoelectronic properties induced by atomic diffusion.

End-to-end novel visual categories learning via auxiliary self-supervision.

Semi-supervised learning has largely alleviated the strong demand for large amount of annotations in deep learning. However, most of the methods have adopted a common assumption that there is always labeled data from the same class of unlabeled data, which is impractical and restricted for real-world applications. In this research work, our focus is on semi-supervised learning when the categories of unlabeled data and labeled data are disjoint from each other.

ELM embedded discriminative dictionary learning for image classification.

Dictionary learning is a widely adopted approach for image classification. Existing methods focus either on finding a dictionary that produces discriminative sparse representation, or on enforcing priors that best describe the dataset distribution. In many cases, the dataset size is often small with large intra-class variability and nondiscriminative feature space.

Simultaneously learning affinity matrix and data representations for machine fault diagnosis.

Recently, preserving geometry information of data while learning representations have attracted increasing attention in intelligent machine fault diagnosis. Existing geometry preserving methods require to predefine the similarities between data points in the original data space. The predefined affinity matrix, which is also known as the similarity matrix, is then used to preserve geometry information during the process of representations learning.

NbSeTe-a new layered transition metal dichalcogenide superconductor.

Transition metal dichalcogenides (TMDCs) usually exhibit layered polytypic structures due to the weak interlayer coupling. 2H-NbSe is one of the most widely studied in the pristine TMDC family due to its high superconducting transition temperature (T   =  7.3 K) and the occurrence of a charge-density wave (CDW) order below 33 K.

Slice-Based Online Convolutional Dictionary Learning.

Convolutional dictionary learning (CDL) aims to learn a structured and shift-invariant dictionary to decompose signals into sparse representations. While yielding superior results compared to traditional sparse coding methods on various signal and image processing tasks, most CDL methods have difficulties handling large data, because they have to process all images in the dataset in a single pass. Therefore, recent research has focused on online CDL (OCDL) which updates the dictionary with sequentially incoming signals.

Topological phase transition induced by magnetic proximity effect in two dimensions.

We study the magnetic proximity effect on a two-dimensional topological insulator in a CrI/SnI/CrI trilayer structure. From first-principles calculations, the BiI-type SnI monolayer without spin-orbit coupling has Dirac cones at the corners of the hexagonal Brillouin zone. With spin-orbit coupling turned on, it becomes a topological insulator, as revealed by a non-vanishing Z invariant and an effective model from symmetry considerations.

The Structural and Electronic Properties of CdS/ZnS Core-Shell Nanowires.

The structural and electronic properties of the CdS/ZnS core-shell nanowires (NWs) oriented along [001] direction have been investigated by means of the first-principles calculation. It is found that CdS core suffers from the compressive strain in the CdS-core/ZnS-shell NWs, and ZnS core is stretched in the ZnS-core/CdS-shell NWs. A thicker ZnS shell can improve the NWs' stability, and a thicker CdS shell would decrease their stability.

Orbital change manipulation metal-insulator transition temperature in W-doped VO2.

A series of epitaxial V1-xWxO2 (0 ≤ x ≤ 0.76%) nanocrystalline films on c-plane sapphire substrates have been successfully synthesized. Orbital structures of V1-xWxO2 films with monoclinic and rutile states have been investigated by ultraviolet-infrared spectroscopy combined with first principles calculations.