Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Changes in the Expression of Selected Genes from the ABC Family in Patients with Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by a lack of expression of hormone receptors (estrogen and progesterone), as cancer cells also do not overexpress the HER2 receptor. Due to their molecular profile, treatments for this type of breast cancer are limited. In some cases, the pharmacotherapy of patients with TNBC is hindered by the occurrence of multidrug resistance, which is largely conditioned by proteins encoded by genes from the ABC family. The aim of our study was to determine the expression profile of 14 selected genes from the ABC family using real-time PCR in 68 patients with TNBC by comparing the obtained results with clinical data and additionally using bioinformatics tools (Ualcan and The Breast Cancer Gene Expression Miner v4.8 (bc -GenExMiner v4.8)), as well as by comparing experimental data with data in the Cancer Genome Atlas (TCGA) database. Based on the conducted studies, we found different levels of gene expression depending on the age of patients, tumor sizes, metastases to lymph nodes, cell infiltration into adipose tissue, tumor stages, or lymphovascularinvasion. The results of the presented studies demonstrate the effect of the expression level of the studied genes on the clinical course and prognosis of patients with TNBC, and suggest how profiling the expression level of genes from the ABC family may be a useful tool in determining personalized TNBC treatment.
Phylogenomic Analysis Supports the Transfer of 20 Pathovars from Xanthomonas campestris into Xanthomonas euvesicatoria

The Gram-negative bacterial genus Xanthomonas includes numerous infra-specific taxa known as pathovars, which are defined primarily on host range and disease symptoms. With the advent of molecular sequence data, many pathovars have been transferred from X. campestris into other Xanthomonas species to better harmonise taxonomy and phylogeny. We performed whole-genome shotgun sequencing on pathotype strains of the following X. campestris pathovars: blepharidis, carissae, clerodendri, convolvuli, coriandri, daturae, euphorbiae, fici, heliotropii, ionidii, lawsoniae, mirabilis, obscurae, paulliniae, pennamericanum, spermacoces, uppalii, vernoniae, viegasii and zingibericola. These genomes showed more than 98% average nucleotide identity with the type-strain of X. euvesicatoria and less than 88% with the type-strain of X. campestris. We propose the transfer of these pathovars into X. euvesicatoria and present an emended species description for X. euvesicatoria.
Sensitivity Analysis in Factor Analysis Regression: A Numerical Study

Influence functions are derived for the parameters in the factor analysis (FA) regression and some measures are proposed to evaluate the influence on the estimated regression weights ƒÀF and on the squared correlation coefficient r2(ƒÀF). As an application, a numerical study is conducted to illustrate the present procedure and to show fundamental properties of influence in FA regression from the sensitivity perspective.
Effects of temperature on life table parameters of a newly described phytoseiid predator, Neoseiulus neoagrestis (Acari: Phytoseiidae) fed on Tyrophagus putrescentiae (Acari: Acaridae)

The predatory mite, Neoseiulus neoagrestis Khaustov and Döker (Acari: Phytoseiidae), recently described as new species for science, but seems to have a great potential to be used in biological control. In this study, as a first step to determine the optimum temperature (between three temperatures tested) for its mass rearing, we studied its biological characteristics and life table parameters fed on Tyrophagus putrescentiae (Schrank) (Acari: Acaridae) at three different temperatures (20, 25, and 30 °C) under laboratory conditions. Results show that immature development, oviposition period as well as reproductive potential of this predator are significantly vary depending on the temperature. The immature developmental times and adult longevity for females, are ranged between 5.42 to 10.42 days and 39.88 to 74.12 days, based on the temperature, respectively. Average total number of eggs laid by per female at 25 °C (62.29) and 30 °C (58.65) are more or less similar but higher than that determined at 20 °C (41.46). The highest net reproductive rate (R0) is 29.066 (offspring/individual) at 25 °C. In addition, the highest intrinsic rate of natural increase (r) is 0.241 day-1 at 30 °C. Furthermore, the highest finite rate of increase (λ = 1.272 day-1), and the shortest mean generation time (T = 13.416 days) and doubling time (DT = 2.874 days) are also determined at 30 °C. Our results demonstrate that N. neoagrestis successfully completed immature development, and can survive and reproduce at all tested temperatures. Nevertheless, a series of biological characteristics of this predator are differentially affected by the temperature. Finally, 25 °C and 30 °C seems to be more suitable for mass rearing of this predator on T . putrescentiae. Further studies should be conducted to determine biological characteristics and life table parameters of N. neoagrestis on several important pests such as spider mites, whiteflies and thrips.
Ground-target tracking with topography-based variable-structure IMM estimator

In this paper we present the development of a variable structure interacting multiple model estimator for tracking groups of ground targets on constrained paths using moving target indicator reports obtained from an airborne sensor. The targets are moving along a highway, with varying inter- visibility due to changing terrain conditions. In addition,the roads can branch, merge or cross. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography. The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variable structure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, improving performance and reducing computational load.
Social Values in Economic Environmental Valuation: A Conceptual Framework

Economic environmental valuation remains a much debated and contested issue. Concerns have been voiced that it is unable to capture the manifold immaterial values of ecosystems due to conceptual and methodological issues. Thus, additional value categories (social values) as well as novel valuation approaches like deliberative (monetary) valuation are areas of growing interest, yet the theoretical foundations are rather weak. Against this background, this article aims to develop a consistent conceptual framework for making sense of social values in economic environmental valuation. Based on a holistic view of society and individuals, the role of institutions, the social environment, culture and transcendental values is emphasised. To synthesise diverging concepts of value into an economic concept and to account for the multidimensionality of social values, the framework consists of three spheres: social, natural and contextual. The novel framework demonstrates that social values may be integrated into a preference-based utility framework when denoting a holistic understanding of social preferences and human embeddedness in nature and society.
Decomposition techniques for large-scale systems with nonadditive interactions: Stability and stabilizability

In this paper, we study decomposition techniques for nonlinear large-scale systems, which have the feature that the interactions between the various subsystems are nonadditive. Using the technique of decomposing a graph into its strongly connected components, we first rewrite the system differential equations into a hierarchical form, by renumbering and aggregating the original state variables, if necessary. In this hierarchical form, each subsystem interacts only with "lower" subsystems but not with "higher" subsystems. Once the system equations have been rearranged in this hierarchical form, we show that the overall system is uniformly asymptotically stable (respectively exponentially stable, globally exponentially stable) if and only if each of the subsystems is uniformly asymtotically stable (respectively exponentially stable, globally exponentially stable). The main technique used to do this is the converse Lyapunov theory. We then turn to problems of stabilizability, and show that, once the system equations have been arranged in hierarchical form, the overall system can be stabilized by a decentralized control law if and only if each of the subsystems can be stabilized. Several examples are presented to illustrate the various theorems.
Subsurface Ocean Temperature Responses to the Anthropogenic Aerosol Forcing in the North Pacific

Separating the climate response to external forcing from internal climate variability is a key challenge. While most previous studies have focused on surface responses, here we examine zonal‐mean patterns of North Pacific subsurface temperature responses. In particular, the changes since 1950 driven by anthropogenic aerosol emissions are found by using a pattern recognition method. Based on the single‐forcing large‐ensemble simulations from two models, we show that aerosol forcing caused a nonmonotonic temporal response and a characteristic zonal‐mean pattern within North Pacific, which is distinct from the pattern associated with internal variability. The aerosol‐forced pattern with the nonmonotonic temporal feature shows a substantial temperature change in subpolar regions and a reversed change on the southern flank of the subtropical gyre. A similar characteristic pattern and nonmonotonic time evolution are extracted from the subsurface observations, which likely reflect the subsurface responses to the aerosol forcing, although differences exist with the simulated responses.
Modulational instability and exact solutions of the modified quintic complex Ginzburg–Landau equation

We have formulated a model of an equation that governs dynamics of nonlinear waves in many non-equilibrium systems. Based on this new equation, we have reviewed the well-known Lange and Newell's criterion for modulational instability of Stoke waves. Some exact solutions of this wave equation have also been found through a proper combination of the Painlevé analysis and Hirota's bilinear technique.
A general classification rule for probability measures

Abstract : We consider the problem of classifying an unknown probability distribution based on a sequence of random samples drawn according to this distribution. Specifically, if A is a subset of the space of all probability measures M1(sigma) over some compact Polish space E, we want to decide whether or not the unknown distribution belongs to A or its complement. We propose an algorithm which leads a.s. to a correct decision for any A satisfying certain structural assumptions. A refined decision procedure is also presented which, given a countable collection Ai C M1(sigma), i = 1, 2,. each satisfying the structural assumption, will eventually determine a.s. the membership of the distribution in any finite number of the Ai. Applications to density estimation and the problem of order determination of Markov processes are discussed.
Diffeomorphic Surface Modeling for MRI-Based Characterization of Gastric Anatomy and Motility

<italic>Objective:</italic> Gastrointestinal magnetic resonance imaging (MRI) provides rich spatiotemporal data about the movement of the food inside the stomach, but does not directly report muscular activity on the stomach wall. Here we describe a novel approach to characterize the motility of the stomach wall that drives the volumetric changes of the ingesta. <italic>Methods:</italic> A neural ordinary differential equation was optimized to model a diffeomorphic flow that ascribed the deformation of the stomach wall to a continuous biomechanical process. Driven by this diffeomorphic flow, the surface of the stomach progressively changes its shape over time, while preserving its topology and manifoldness. <italic>Results:</italic> We tested this approach with MRI data collected from 10 rats under a lightly anesthetized condition, and demonstrated accurate characterization of gastric motor events with an error in the order of sub-millimeters. Uniquely, we characterized gastric anatomy and motility with a surface coordinate system common at both individual and group levels. Functional maps were generated to reveal the spatial, temporal, and spectral characteristics of muscle activity and its coordination across different regions. The peristalsis at the distal antrum had a dominant frequency and peak-to-peak amplitude of <inline-formula><tex-math notation="LaTeX">$\text{5.73}\pm \text{0.55}$</tex-math></inline-formula> cycles per minute and <inline-formula><tex-math notation="LaTeX">$\text{1.49}\pm \text{0.41}$</tex-math></inline-formula> mm, respectively. The relationship between muscle thickness and gastric motility was found to be distinct between two functional regions in the proximal and distal stomach. <bold>Conclusion:</bold> These results demonstrate the efficacy of using MRI to model gastric anatomy and function. <italic>Significance:</italic> The proposed approach is expected to enable non-invasive and accurate mapping of gastric motility for preclinical and clinical studies.
Combining STAT3-Targeting Agents with Immune Checkpoint Inhibitors in NSCLC

Simple Summary Signal transducer and activator of transcription 3 (STAT3) plays a critical role in the development and progression of non-small cell lung cancer (NSCLC) tumors. Several reports suggest that STAT3 is involved in immunosuppression and the promotion of resistance to immune checkpoint inhibitors. In this review, we discuss the potential therapeutic strategy of combining STAT3 inhibition with immune checkpoint inhibitors to overcome drug resistance and enhance their efficacy in NSCLC. Abstract Despite recent therapeutic advances, non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death. Signal transducer and activator of transcription 3 (STAT3) is a transcription factor (TF) with multiple tumor-promoting effects in NSCLC, including proliferation, anti-apoptosis, angiogenesis, invasion, metastasis, immunosuppression, and drug resistance. Recent studies suggest that STAT3 activation contributes to resistance to immune checkpoint inhibitors. Thus, STAT3 represents an attractive target whose pharmacological modulation in NSCLC may assist in enhancing the efficacy of or overcoming resistance to immune checkpoint inhibitors. In this review, we discuss the biological mechanisms through which STAT3 inhibition synergizes with or overcomes resistance to immune checkpoint inhibitors and highlight the therapeutic strategy of using drugs that target STAT3 as potential combination partners for immune checkpoint inhibitors in the management of NSCLC patients.
Technostress in older onliners: a scale adaptation study

ABSTRACT In this study, it was aimed to bring the scale with proven psychometric qualities to Turkish culture by testing the validity and reliability of the Technostress Scale developed by Nimrod to measure the stress caused by the use of information and communication technology (ICT) in older adults. After the scale was translated into Turkish, it was distributed to 551 participants in total selected by convenience sampling method, aged 60 and over. For the content validity of the scale, expert opinion was consulted. Exploratory Factor Analysis (EFA) was applied to determine the factor structure of the scale, and Confirmatory Factor Analysis (CFA) was applied to test the accuracy of the determined factor structure, and the internal consistency coefficient was calculated for its reliability. As a result of the EFA, it was found that the percentage of the total explained variance was . 67 and that the items were grouped under five factors. According to the results of the first and second order CFA, it was found that the Turkish version of the scale showed an acceptable factorial validity. Moreover, the reliability study indicated that Cronbach’s Alpha internal consistency of the scale was . 78 and it was found that correlations changed between r = . 28–. 56. The results of the analysis indicated that the Turkish version of the Technostress Scale is a valid and reliable instrument that can be used to assess the stress levels of older onliners using ICT.
Enhancing Hungarian students’ English language skills on the basis of literary texts in the three-dimensional space

In our paper we introduce a bilingual language learning material developed in the framework of the so-called three dimensional virtual library model (3DVLM). This model inspired by the history and organization of the famous ancient Library of Alexandria forms the basis of the virtual library project which started about eight years ago as part of the Cognitive Infocom-munications (CogInfoCom) research. The current version of the 3DVLM uses the excellent 3D features of the MaxWhere Seminar System which makes it suitable for both individual learning and classroom use. In the following, we would like to introduce first the basic framework of our development, then describe in detail the data structure and organization of the developed bilingual language learning material. The basic idea of the material is to present selected phrases and contexts from classical literary works in English and from their parallel translations in Hungarian in order to improve both the language skills and background knowledge of Hungarian language learners at an advanced level. We found that using web technology was especially useful for developing the language learning material and the developed hypertext structure formed a scale-free network of interconnected nodes.
Deep Learning Multi-Class Approach for Human Fall Detection Based on Doppler Signatures

Falling events are a global health concern with short- and long-term physical and psychological implications, especially for the elderly population. This work aims to monitor human activity in an indoor environment and recognize falling events without requiring users to carry a device or sensor on their bodies. A sensing platform based on the transmission of a continuous wave (CW) radio-frequency (RF) probe signal was developed using general-purpose equipment. The CW probe signal is similar to the pilot subcarriers transmitted by commercial off-the-shelf WiFi devices. As a result, our methodology can easily be integrated into a joint radio sensing and communication scheme. The sensing process is carried out by analyzing the changes in phase, amplitude, and frequency that the probe signal suffers when it is reflected or scattered by static and moving bodies. These features are commonly extracted from the channel state information (CSI) of WiFi signals. However, CSI relies on complex data acquisition and channel estimation processes. Doppler radars have also been used to monitor human activity. While effective, a radar-based fall detection system requires dedicated hardware. In this paper, we follow an alternative method to characterize falling events on the basis of the Doppler signatures imprinted on the CW probe signal by a falling person. A multi-class deep learning framework for classification was conceived to differentiate falling events from other activities that can be performed in indoor environments. Two neural network models were implemented. The first is based on a long-short-term memory network (LSTM) and the second on a convolutional neural network (CNN). A series of experiments comprising 11 subjects were conducted to collect empirical data and test the system’s performance. Falls were detected with an accuracy of 92.1% for the LSTM case, while for the CNN, an accuracy rate of 92.1% was obtained. The results demonstrate the viability of human fall detection based on a radio sensing system such as the one described in this paper.
Critical Angle Formulation of Nonuniform Plane Waves for Determining Correct Refraction Angles at Planar Interface

The expressions and properties of the critical angles of nonuniform plane waves for determining the correct refraction angle at the infinite planar interface of two linear, isotropic, and homogeneous media are presented. The two media could be lossless or lossy. For the case where the complex wave vector of Adler–Chu–Fano formulation and the normal vector to the interface are coplanar, a critical angle equation, which is simpler than the extant one, under the condition that one or two critical angles exist, is formulated. In addition, for the case where the complex wave vector and normal vector to the interface are noncoplanar, a critical angle equation is formulated, rendering the 3-D nonuniform plane wave refraction feasible for utilization in many areas of optics. The presented critical angle equations were validated for various nonuniform plane waves and media.
On the theoretical backgrounds of cluster analysis based on the eigenvalue problem of the association matrix

Let m be a fixed integer. It is proved that an nxn symmetric random matrix: consisting of mxm blocks has m large in absolute value eigenvalues of order√ n while the remaining eigenvalues are of order fn as n tends to infinity. We assume the associations between observations to be independent random variables i.e. the sample is in some sense infinite dimensional. This random matrix cluster structure-can be obtained by means of the eigenvectors corresponding to the extremal eigenvalues. of the association matrix
Towards the next generation of brain/machine interface

We report on the latest development of our photonics-based brain-machine interface. This work done in collaboration between UNSW and Macquarie University – and supported by the US Office of Naval Research – directly addresses the long-term DARPA challenge of producing implantable chips with 1 million neural connections. To the best of our knowledge, no technology has demonstrated the potential so far to scale up to such a massive number of channels.
Strip steel target detection algorithm based on single image rapid defog and morphological interframe difference

In the production process of strip steel, detecting wave edge in real time is quite important, otherwise it will contribute to the abandonment of strip steel materials. At this stage, an automatic identification system based on machine vision which aims to figure out the wave edge of strip steel is gradually being put into use. However, it is shown that the complicated environment of the factory makes it difficult to reach its goals. In order to solve this problem, this paper designs a motion strip steel target detection algorithm based on single image rapid defog and morphological interframe difference. Firstly, based on the physical model of foggy image degradation, using a simple mean filtering to estimate the environmental light and global atmospheric light, thus the removal of water mist in video screen is realized. Then, using interframe differential method to extract the motion strip steel in the image, and the noise is filtered by mask segmentation and morphological operator. At last, the experimental results show that the optimization algorithm is more accurate and effective compared with the traditional motion target detection algorithm.