Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissues.

The phenotypic and functional states of a cell are modulated by a complex interactive molecular hierarchy of multiple omics layers, involving the genome, epigenome, transcriptome, proteome, and metabolome. Spatial omics approaches have enabled the capture of information from different molecular layers directly in the tissue context. However, current technologies are limited to map one to two modalities at the same time, providing an incomplete representation of cellular identity.

Unlocking growth: Investigating asymmetry in the financial inclusion-growth nexus in financially inclusive middle east economies.

Financial inclusion is a crucial element of financial development that transmits cheap financial services to provide advantages to entire segments of society and stimulates economic growth. Our investigation evaluates the asymmetric financial inclusion-economic growth nexus in the top 10 financially inclusive Middle East nations (Israel, Oman, Iran, Qatar, Turkey, Saudi Arabia, Bahrain, Egypt, United Arab Emirates, and Kuwait). Earlier studies adopted panel data tools, which yielded typical outcomes on the association between financial inclusion and economic growth despite few economies did not indicate such a link individually.

Systematic establishment of the relationship between skin absorption and toxicity of furanoids via in silico, in vitro, and in vivo assessments.

Furanoids are a class of contaminants prevalent in both airborne and occupational environments, with potential health implications through inhalation, oral ingestion, and skin penetration. Given their diminutive molecular size, there is a presumption that furanoids can readily permeate the skin. To systematically explore this presumption, we investigated the skin absorption and toxicity of a series of furans (furfuryl alcohol, furfuryl acetate, furfural, methyl 2-furoate, and 5-methylfurfural) using in silico, in vitro, and in vivo models.

What does corporate environmental citizenship really mean?

Background: Corporate environmental citizenship receives little scholarly attention and the definitions remain unclear due to past studies defining corporate environmental citizenship in different perspectives.

Objective: The aim of this paper is to clarify the conceptualization of corporate environmental citizenship. It also proposes a plausible and useful definition for corporate environmental citizenship.

Decomposing scale, technique and composition effects of foreign direct investment on environmental quality.

This study aimed to investigate how the decomposing scale effect, technique effect and composition effect of foreign direct investment (FDI) impact on carbon dioxide (CO) emissions for 115 nations spanning 1999 to 2019 by employing Generalised Method of Moments (GMM) model. The results indicated that FDI, real GDP per capita, capital-labor ratio, institutional quality and urbanization increase CO emissions while the square of real GDP per capita and trade openness contributed to reducing CO emissions. Also, our findings fail to support Environmental Kuznets Curve (EKC) theory.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM).

How Does Mg Interact with ATP? Biomolecular Structure through the Lens of Liquid-Jet Photoemission Spectroscopy.

Liquid-jet photoemission spectroscopy (LJ-PES) allows for a direct probing of electronic structure in aqueous solutions. We show the applicability of the approach to biomolecules in a complex environment, exploring site-specific information on the interaction of adenosine triphosphate in the aqueous phase (ATP) with magnesium (Mg), highlighting the synergy brought about by the simultaneous analysis of different regions in the photoelectron spectrum. In particular, we demonstrate intermolecular Coulombic decay (ICD) spectroscopy as a new and powerful addition to the arsenal of techniques for biomolecular structure investigation.

Site-Specific Photochemistry along a Protonated Peptide Scaffold.

We present a detailed study of the time-dependent photophysics and photochemistry of a known conformation of the two protonated pentapeptides Leu-enkephalin (Tyrosine-Glycine-Glycine-Phenylalanine-Leucine, YGGFL) and its chromophore-swapped analogue FGGYL, carried out under cryo-cooled conditions in the gas phase. Using ultraviolet-infrared (UV-IR) double resonance, we record excited state IR spectra as a function of time delay between UV and IR pulses. We identify unique Tyr OH stretch transitions due to the S state and the vibrationally excited triplet state(s) formed by intersystem crossing, T(v).

Nutritional, physicochemical, and functional properties of Hawaiian taro (Colocasia esculenta) flours: A comparative study.

Taro (Colocasia esculenta) flour is a viable carbohydrate alternative and a functional additive for food formulation; however, different taro varieties may possess distinct characteristics that may influence their suitability for food production. This study evaluated the nutritional, physicochemical, and functional properties of flours from five Hawaiian taro varieties: Bun-Long, Mana Ulu, Moi, Kaua'i Lehua, and Tahitian. Tahitian, Bun-long, and Moi had high total starch contents of 40.

LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest.

Sign language recognition presents significant challenges due to the intricate nature of hand gestures and the necessity to capture fine-grained details. In response to these challenges, a novel approach is proposed-Lightweight Attentive VGG16 with Random Forest (LAVRF) model. LAVRF introduces a refined adaptation of the VGG16 model integrated with attention modules, complemented by a Random Forest classifier.

Stereotactic body radiotherapy for distant metastases to the head and neck.

Purpose: To report clinical outcomes for patients with metastatic disease to the head and neck (HN) treated with stereotactic body radiation therapy (SBRT).

Methods: A retrospective review of patients treated with SBRT to HN sites from 2012 to 2020 was conducted. Treatment indications included the following: oligometastases, oligoprogression, and control a dominant area of progression (DAP).

EnViTSA: Ensemble of Vision Transformer with SpecAugment for Acoustic Event Classification.

Recent successes in deep learning have inspired researchers to apply deep neural networks to Acoustic Event Classification (AEC). While deep learning methods can train effective AEC models, they are susceptible to overfitting due to the models' high complexity. In this paper, we introduce EnViTSA, an innovative approach that tackles key challenges in AEC.

How does government efficiency affect carbon emission intensity? A comprehensive empirical study.

This study utilized panel data from 132 countries spanning from 1996 to 2019 to examine the effect of government efficiency on carbon emission intensity. Using a fixed effect model, the study found that stronger government efficiency is associated with a significant decrease in carbon emission intensity. Robustness tests were performed, the results of which consistently supported the main findings.

TIPE proteins control directed migration of human T cells by directing GPCR and lipid second messenger signaling.

Tissue infiltration by circulating leukocytes via directed migration (also referred to as chemotaxis) is a common pathogenic mechanism of inflammatory diseases. G protein-coupled receptors (GPCRs) are essential for sensing chemokine gradients and directing the movement of leukocytes during immune responses. The tumor necrosis factor α-induced protein 8-like (TIPE or TNFAIP8L) family of proteins are newly described pilot proteins that control directed migration of murine leukocytes.

Treatment times for delivering adjuvant breast radiotherapy at a cancer centre in Ontario, Canada.

Background: Time is a valuable commodity that impacts hospital flow, patient experience and economic resources. This study aims to identify factors that affect daily treatment time over a course of radiation therapy (RT) in patients who underwent adjuvant breast RT.

Methods: In all adjuvant breast/chestwall RT patients treated from October 2017 to May 2018, daily set-up, beam delivery time, and overall treatment times were collected.

Evaporation and scattering of neon, methane, and water from a dodecane flat liquid jet.

The evaporation and scattering of Ne, CD4, and D2O from a dodecane flat liquid jet are investigated in a molecular beam apparatus. The experiment yields translational energy distributions as a function of scattering angle by means of a rotatable mass spectrometer. In the evaporation experiments, one observes a Maxwell-Boltzmann distribution with a cos θ angular distribution superimposed on a weak, isotropic background.

Plant-CNN-ViT: Plant Classification with Ensemble of Convolutional Neural Networks and Vision Transformer.

Plant leaf classification involves identifying and categorizing plant species based on leaf characteristics, such as patterns, shapes, textures, and veins. In recent years, research has been conducted to improve the accuracy of plant classification using machine learning techniques. This involves training models on large datasets of plant images and using them to identify different plant species.

Molecular Cage Reports on Its Contents: Spectroscopic Signatures of Cryo-Cooled K- and Ba-Benzocryptand Complexes.

UV photofragment spectroscopy and IR-UV double resonance methods are used to determine the structure and spectroscopic responses of a three-dimensional [2.2.2]-benzocryptand cage to the incorporation of a single K or Ba imbedded inside it (labeled as K-BzCrypt, Ba-BzCrypt).

Recent Advances in Traffic Sign Recognition: Approaches and Datasets.

Autonomous vehicles have become a topic of interest in recent times due to the rapid advancement of automobile and computer vision technology. The ability of autonomous vehicles to drive safely and efficiently relies heavily on their ability to accurately recognize traffic signs. This makes traffic sign recognition a critical component of autonomous driving systems.

HGR-ViT: Hand Gesture Recognition with Vision Transformer.

Hand gesture recognition (HGR) is a crucial area of research that enhances communication by overcoming language barriers and facilitating human-computer interaction. Although previous works in HGR have employed deep neural networks, they fail to encode the orientation and position of the hand in the image. To address this issue, this paper proposes HGR-ViT, a Vision Transformer (ViT) model with an attention mechanism for hand gesture recognition.

Cine MRI-based analysis of intrafractional motion in radiation treatment planning of head and neck cancer patients.

Purpose/objective(s): To investigate intrafraction motion of (HN) target volumes and to determine patient-specific planning target volume (PTV) margins.

Materials/methods: MR-cine imaging was performed for radiation treatment planning in HN cancer patients treated with definitive EBRT (n = 62) or SBRT (n = 4) on a 1.5 T MRI between 2017-2019.

Fine-Tuned Temporal Dense Sampling with 1D Convolutional Neural Network for Human Action Recognition.

Human action recognition is a constantly evolving field that is driven by numerous applications. In recent years, significant progress has been made in this area due to the development of advanced representation learning techniques. Despite this progress, human action recognition still poses significant challenges, particularly due to the unpredictable variations in the visual appearance of an image sequence.

SCL: Self-supervised contrastive learning for few-shot image classification.

Few-shot learning aims to train a model with a limited number of base class samples to classify the novel class samples. However, to attain generalization with a limited number of samples is not a trivial task. This paper proposed a novel few-shot learning approach named Self-supervised Contrastive Learning (SCL) that enriched the model representation with multiple self-supervision objectives.

Gait-CNN-ViT: Multi-Model Gait Recognition with Convolutional Neural Networks and Vision Transformer.

Gait recognition, the task of identifying an individual based on their unique walking style, can be difficult because walking styles can be influenced by external factors such as clothing, viewing angle, and carrying conditions. To address these challenges, this paper proposes a multi-model gait recognition system that integrates Convolutional Neural Networks (CNNs) and Vision Transformer. The first step in the process is to obtain a gait energy image, which is achieved by applying an averaging technique to a gait cycle.

Malaysian Women's Viewpoint on HPV Screening and Vaccination: A Study on Barriers.

Cervical cancer is the second most common cancer in low-income countries and the third most common cancer in Malaysia among women aged 15 to 44. This is a huge concern because of the high mortality rate compared to other countries. Cervical cancer is caused by a common sexually transmitted human papillomavirus (HPV).