Creating and Transforming a Second-Rank Antisymmetric Field- Strength Tensor F αβ in Minkowski Space using MATHEMATICA

As the laws of physics are expressed in a manner that makes their invariance under coordinate transformations manifest, they should be written in terms of tensors. Furthermore, tensors make manifest the characteristics and behaviors of electromagnetic fields through inhomogeneous, anisotropic, and compressible media. Electromagnetic fields are expressed completely in tensor form, Fαβ, which implies both electric field E and magnetic field B rather than separately in the vector fields. This study presents the Mathematica platform that generates and transforms a second-rank antisymmetric field-strength tensor Fαβ and whiskbroom pattern in Minkowski space. The platforms enhance the capabilities of students and researchers in tensor analysis and improves comprehension of the elegant features of complete structure in physics

Exosomes from Human Adipose Tissue-Derived Mesenchymal Stem Cells Promote Epidermal Barrier Repair by Inducing de Novo Synthesis of Ceramides in Atopic Dermatitis.

Atopic dermatitis (AD) is a multifactorial, heterogeneous disease associated with epidermal barrier disruption and intense systemic inflammation. Previously, we showed that exosomes derived from human adipose tissue-derived mesenchymal stem cells (ASC-exosomes) attenuate AD-like symptoms by reducing multiple inflammatory cytokine levels. Here, we investigated ASC-exosomes' effects on skin barrier restoration by analyzing protein and lipid contents. We found that subcutaneous injection of ASC-exosomes in an oxazolone-induced dermatitis model remarkably reduced trans-epidermal water loss, while enhancing stratum corneum (SC) hydration and markedly decreasing the levels of inflammatory cytokines such as IL-4, IL-5, IL-13, TNF-α, IFN-γ, IL-17, and TSLP, all in a dose-dependent manner. Interestingly, ASC-exosomes induced the production of ceramides and dihydroceramides. Electron microscopic analysis revealed enhanced epidermal lamellar bodies and formation of lamellar layer at the interface of the SC and stratum granulosum with ASC-exosomes treatment. Deep RNA sequencing analysis of skin lesions demonstrated that ASC-exosomes restores the expression of genes involved in skin barrier, lipid metabolism, cell cycle, and inflammatory response in the diseased area. Collectively, our results suggest that ASC-exosomes effectively restore epidermal barrier functions in AD by facilitating the de novo synthesis of ceramides, resulting in a promising cell-free therapeutic option for treating AD

Tumor-infiltrating T lymphocytes evaluated using digital image analysis predict the prognosis of patients with diffuse large B-cell lymphoma

Background The implication of the presence of tumor-infiltrating T lymphocytes (TIL-T) in diffuse large B-cell lymphoma (DLBCL) is yet to be elucidated. We aimed to investigate the effect of TIL-T levels on the prognosis of patients with DLBCL. Methods Ninety-six patients with DLBCL were enrolled in the study. The TIL-T ratio was measured using QuPath, a digital pathology software package. The TIL-T ratio was investigated in three foci (highest, intermediate, and lowest) for each case, resulting in TIL-T–Max, TIL-T–Intermediate, and TIL-T–Min. The relationship between the TIL-T ratios and prognosis was investigated. Results When 19% was used as the cutoff value for TIL-T–Max, 72 (75.0%) and 24 (25.0%) patients had high and low TIL-T–Max, respectively. A high TIL-T–Max was significantly associated with lower serum lactate dehydrogenase levels (p < .001), with patient group who achieved complete remission after RCHOP therapy (p < .001), and a low-risk revised International Prognostic Index score (p < .001). Univariate analysis showed that patients with a low TIL-T–Max had a significantly worse prognosis in overall survival compared to those with a high TIL-T–Max (p < .001); this difference remained significant in a multivariate analysis with Cox proportional hazards (hazard ratio, 7.55; 95% confidence interval, 2.54 to 22.42; p < .001). Conclusions Patients with DLBCL with a high TIL-T–Max showed significantly better prognosis than those with a low TIL-T–Max, and the TIL-T–Max was an independent indicator of overall survival. These results suggest that evaluating TIL-T ratios using a digital pathology system is useful in predicting the prognosis of patients with DLBCL

A second hit somatic (p.R905W) and a novel germline intron-mutation of TSC2 gene is found in intestinal lymphangioleiomyomatosis: a case report with literature review

Background Tuberous sclerosis complex (TSC) is an autosomal dominant disorder characterized by hamartomas in multiple organs associated with germline mutations in TSC1 and TSC2, including exonic, intronic, or mosaic mutations. Gastrointestinal (GI) tract Lymphangioleiomyomatosis (LAM) is an extremely rare manifestation of TSC, with few reported cases. Herein, we aimed to determine the driver mutation, pathogenesis, and relationship of germline and somatic mutations of LAM through whole-genome sequencing (WGS) of the tumor and blood samples and whole transcriptome sequencing (WTS) analysis. Case presentation A nine-year-old girl with a full-blown TSC presented with abdominal masses detected during a routine check-up. Resected intestinal masses were diagnosed as LAM by thorough pathological examination. Interestingly, the LAM presented a somatic TSC2 gene mutation in exon 24 (p.R905W, c.C2713T), and the patient had intron retention by a novel germline mutation in the intron region of TSC2 (chr16:2126489, C > G). Conclusion Our case suggests that intron retention by a single nucleotide intronic mutation of TSC2 is sufficient to develop severe manifestations of TSC, but the development of LAM requires an additional somatic oncogenic mutation of TSC2.This work was supported by IITP grant funded by the Korean government (MSIP) (No.2019-0567)

Receptive and Productive Vocabulary Knowledge of Negative Prefixes by EFL Students

This study intends to examine English as a Foreign Language (hereafter EFL) learners’ knowledge of negational prefixes in English adjectives in both the receptive and productive aspects. Although negative prefixes demand much working memory from EFL learners and have a crucial impact on the meaning of the sentence, not much research has attempted to analyze their awareness of negative prefixes systematically. Influenced by studies on native speakers’ (hereafter NSs) knowledge of negative prefixes, an experiment was conducted to reveal EFL learners’ understanding and the usage of English negative prefixes. To serve this purpose, six high school students in Korea participated in a self-paced reading and fillin-the blank test. The results showed that Korean EFL students are not sensitive to the correctness of the forms of the prefixes to the bases. However, they demonstrated intuition over etymological differences. They dichotomized un- to native English word and IN-(in-,im-,ir-, il-) to the Latinate origin word more severely than NSs. The results also revealed that un- is the most favored negational prefix among the EFL learners and they rely heavily on orthographical information when producing it. These findings hopefully make contribution to developing more effective vocabulary teaching methods in EFL classrooms

Two-Step k-means Clustering Based Information Entropy for Detecting Environmental Barriers Using Wearable Sensor

Walking is the most basic means of transportation. Therefore, continuous management of the walking environment is very important. In particular, the identification of environmental barriers that can impede walkability is the first step in improving the pedestrian experience. Current practices for identifying environmental barriers (e.g., expert investigation and survey) are time-consuming and require additional human resources. Hence, we have developed a method to identify environmental barriers based on information entropy considering that every individual behaves differently in the presence of external stimuli. The behavioral data of the gait process were recorded for 64 participants using a wearable sensor. Additionally, the data were classified into seven gait types using two-step k-means clustering. It was observed that the classified gaits create a probability distribution for each location to calculate information entropy. The values of calculated information entropy showed a high correlation in the presence or absence of environmental barriers. The results obtained facilitated the continuous monitoring of environmental barriers generated in a walking environment

Pedagogical Mathematica Platform Visualizing the Coriolis Effects in 3-Cell Atmospheric Circulation Model

The atmospheric flow in the 3-Cell model of global atmosphere circulation is described by the Lagrange's equation of the non-inertial frame where pressure force, frictional force and fictitious force are mixed in complex form. The Coriolis force is an important factor which requires calculation of fictitious force effects on atmospheric flow viewed from the rotating Earth. We make new Mathematica platform to solve Lagrange's equation by numerical analysis in order to analyze dynamics of atmospheric general circulation in the non-inertial frame. It can simulate atmospheric circulation process anywhere on the earth. It is expected that this pedagogical platform can be utilized to help students studying the atmospheric flow understand the mechanisms of atmospheric global circulation

Variation of Solar, Interplanetary and Geomagnetic Parameters during Solar Cycles 21-24

The length of solar cycle 23 has been prolonged up to about 13 years. Many studies have speculated that the solar cycle 23/24 minimum will indicate the onset of a grand minimum of solar activity, such as the Maunder Minimum. We check the trends of solar (sunspot number, solar magnetic fields, total solar irradiance, solar radio flux, and frequency of solar X-ray flare), interplanetary (interplanetary magnetic field, solar wind and galactic cosmic ray intensity), and geomagnetic (Ap index) parameters (SIG parameters) during solar cycles 21-24. Most SIG parameters during the period of the solar cycle 23/24 minimum have remarkably low values. Since the 1970s, the space environment has been monitored by ground observatories and satellites. Such prevalently low values of SIG parameters have never been seen. We suggest that these unprecedented conditions of SIG parameters originate from the weakened solar magnetic fields. Meanwhile, the deep 23/24 solar cycle minimum might be the portent of a grand minimum in which the global mean temperature of the lower atmosphere is as low as in the period of Dalton or Maunder minimum

Pedagogical Mathematica Platform Visualizing the Coriolis Effects in 3-Cell Atmospheric Circulation Model

The atmospheric flow in the 3-Cell model of global atmosphere circulation is described by the Lagrange's equation of the non-inertial frame where pressure force, frictional force and fictitious force are mixed in complex form. The Coriolis force is an important factor which requires calculation of fictitious force effects on atmospheric flow viewed from the rotating Earth. We make new Mathematica platform to solve Lagrange's equation by numerical analysis in order to analyze dynamics of atmospheric general circulation in the non-inertial frame. It can simulate atmospheric circulation process anywhere on the earth. It is expected that this pedagogical platform can be utilized to help students studying the atmospheric flow understand the mechanisms of atmospheric global circulation

DeepPM: Transformer-based Power and Performance Prediction for Energy-Aware Software

Many system-level management and optimization techniques need accurate estimates of power consumption and performance. Earlier research has proposed many high-level/source-level estimation modeling works, particularly for basic blocks. However, most of them still need to execute the target software at least once on a fine-grained simulator or real hardware to extract required features. This paper proposes a performance/power prediction framework, called Deep Power Meter (DeepPM), which estimates them accurately only using the compiled binary. Inspired by the deep learning techniques in natural language processing, we convert the program instructions in the form of vectors and predict the average power and performance of basic blocks based on a transformer model. In addition, unlike existing works based on a Long Short-Term Memory (LSTM) model structure, which only works for basic blocks with a small number of instructions, DeepPM provides highly accurate results for long basic blocks, which takes the majority of the execution time for actual application runs. In our evaluation conducted with SPEC2006 benchmark suite, we show that DeepPM can provide accurate prediction for performance and power consumption with 10.2% and 12.3% error, respectively. DeepPM also outperforms the LSTM-based model by up to 67.2% and 34.9% error for performance and power, respectively. © 2022 EDAA