Miracle-dz/UniFAR-FTUs huggingface dataset:
GJA1/CX43 High Expression Levels in the Cervical Spinal Cord of ALS Patients Correlate to Microglia-Mediated Neuroinflammatory Profile

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder affecting motoneurons (MNs) with a fatal outcome. The typical degeneration of cortico-spinal, spinal, and bulbar MNs, observed in post-mortem biopsies, is associated with the activation of neuroimmune cells. GJA1, a member of the connexins (Cxs) gene family, encodes for connexin 43 (Cx43), a core gap junctions (GJs)- and hemichannels (HCs)-forming protein, involved in cell death, proliferation, and differentiation. Recently, Cx43 expression was found to play a role in ALS pathogenesis. Here, we used microarray and RNA-seq datasets from the NCBI of the spinal cord of control (NDC) and ALS patients, which were stratified according to the GJA1 gene expression. Genes that positively or negatively correlated to GJA1 expression were used to perform a genomic deconvolution analysis (GDA) using neuroimmune signatures. Expression analysis revealed a significantly higher GJA1 expression in the MNs of ALS patients as compared to NDC. Gene deconvolution analysis revealed that positively correlated genes were associated with microglia activation, whereas negatively correlated genes were associated with neuronal activation profiles. Moreover, gene ontology analysis, performed on genes characterizing either microglia or neuronal signature, indicated immune activation or neurogenesis as main biological processes. Finally, using a synthetic analysis of drugs able to revert the GJA1 transcriptomic signatures, we found a specific drug profile for ALS patients with high GJA1 expression levels, composed of amlodipine, sertraline, and prednisolone. In conclusion, our exploratory study suggests GJA1 as a new neuro-immunological gene correlated to microglial cellular profile in the spinal cord of ALS patients. Further studies are warranted to confirm these results and to evaluate the therapeutic potential of drugs able to revert typical GJA1/CX43 signature in ALS patients
Time- and Amplitude-Controlled Power Noise Generator against SPA Attacks for FPGA-Based IoT Devices

Power noise generation for masking power traces is a powerful countermeasure against Simple Power Analysis (SPA), and it has also been used against Differential Power Analysis (DPA) or Correlation Power Analysis (CPA) in the case of cryptographic circuits. This technique makes use of power consumption generators as basic modules, which are usually based on ring oscillators when implemented on FPGAs. These modules can be used to generate power noise and to also extract digital signatures through the power side channel for Intellectual Property (IP) protection purposes. In this paper, a new power consumption generator, named Xored High Consuming Module (XHCM), is proposed. XHCM improves, when compared to others proposals in the literature, the amount of current consumption per LUT when implemented on FPGAs. Experimental results show that these modules can achieve current increments in the range from 2.4 mA (with only 16 LUTs on Artix-7 devices with a power consumption density of 0.75 mW/LUT when using a single HCM) to 11.1 mA (with 67 LUTs when using 8 XHCMs, with a power consumption density of 0.83 mW/LUT). Moreover, a version controlled by Pulse-Width Modulation (PWM) has been developed, named PWM-XHCM, which is, as XHCM, suitable for power watermarking. In order to build countermeasures against SPA attacks, a multi-level XHCM (ML-XHCM) is also presented, which is capable of generating different power consumption levels with minimal area overhead (27 six-input LUTS for generating 16 different amplitude levels on Artix-7 devices). Finally, a randomized version, named RML-XHCM, has also been developed using two True Random Number Generators (TRNGs) to generate current consumption peaks with random amplitudes at random times. RML-XHCM requires less than 150 LUTs on Artix-7 devices. Taking into account these characteristics, two main contributions have been carried out in this article: first, XHCM and PWM-XHCM provide an efficient power consumption generator for extracting digital signatures through the power side channel, and on the other hand, ML-XHCM and RML-XHCM are powerful tools for the protection of processing units against SPA attacks in IoT devices implemented on FPGAs.
Operations for entrepreneurs: Can Operations Management make a difference in entrepreneurial theory and practice?

Although entrepreneurship‐related papers have had some representation in Production and Operations Management (POM) over the past 30 years, the topic still seems a bit like a poor stepchild in the research of operations management (OM) scholars. Yet, entrepreneurship is important to the economy, and many schools are growing significantly their entrepreneurship programs and offerings but often without reference to or inclusion of operations courses. This paper is motivated by the question of the operations needs of new ventures and how they might differ from the needs of large, established firms. Toward that end, we review briefly the state of entrepreneurship scholarship in POM (and beyond), present our own (field‐based) research (and cases), and propose a framework for what we call “operations for entrepreneurs,” that we hope can be a basis for further productive research and curriculum development by the OM community.
Sequestering of Kähler moduli in type IIB string theory

In this thesis we employ string perturbation theory in toroidal orbifold models to study aspects of supersymmetry breaking in type IIB string theory. First, we determine the dependence of physical Yukawa couplings on blow-up moduli in models with D3-branes at orbifold singularities. Blow-up moduli are scalar fields describing the size of small blow-up cycles in the compactification geometry. In models implementing moduli stabilisation these fields can acquire F-terms and break supersymmetry. We examine the modulidependence of physical Yukawa couplings at string tree-level by computing disk correlation functions involving a Yukawa interaction of visible sector fields and an arbitrary number of blow-up moduli. We perform the calculation for one blow-up insertion explicitly and find that the correlation function vanishes if the blow-up modulus is associated with a small cycle distant to the visible sector. For more than one blow-up insertion we show that all such correlation functions are exponentially suppressed by the compactification volume. We explain how these results are relevant to suppressing soft terms to scales parametrically below the gravitino mass. Further, we determine corrections to holomorphic Yukawa couplings on D3branes at an orbifold singularity due to non-perturbative effects such as gaugino condensation on a stack of D7-branes. This can be done by calculating a one-loop threshold correction to the gauge coupling on the D7-branes. We show that, if present, the new contributions to Yukawa couplings are not aligned with the tree-level couplings. As the new Yukawa couplings contribute to soft A-terms they are sources of flavour-changing neutral currents. Last we discuss an effect unrelated to supersymmetry breaking. We show that orbifold models with D3-branes at orbifold singularities can exhibit kinetic mixing of different massless Abelian factors. For this to be possible, the relevant U(1) factors have to be associated with more than one orbifold singularity.
Towards Developing Metrics to Evaluate Digital Engineering

Model‐based systems engineering (MBSE) is an increasingly accepted practice in the Systems Engineering (SE) community, however, little has been done to empirically show that MBSE provides value. Furthermore, as the industry continues in the direction of digital transformation, MBSE will become a critical component of the larger Digital Engineering (DE) approach. This paper presents a measurement framework for selecting and developing appropriate metrics to assess the value/benefits of MBSE and subsequently DE. Utilizing expected benefits identified in a review of MBSE literature, a causal map was hypothesized to show how expected benefits (potential metrics) influence and relate to each other. This was done in order to systematically determine which benefits would be the most impactful to measure. The hypothesized causal model was presented for feedback to subject‐matter experts from a working group developing the first DE measurement framework. This group is a joint effort with industry, academia, and the USA government to develop DE metric standards. Once the causal map was finalized, a case study was used to partially validate the causal model. Based on the causal map and subsequent analysis, we can recommend the first metrics to be employed for DE/MBSE based on the most influential nodes of the causal model. The potential metric candidates include: system quality, defects, time, rework, ease of making changes, system understanding, Effort, accessibility of information, collaboration, project methods/processes, and use of DE/MBSE tools. We believe a concerted effort across the industry to focus on measuring these variables is the most effective way to establish proof of the value of MBSE and DE.
The impact of brand affiliation on asset values: the case of UK hotels

ABSTRACT Using the hedonic pricing method, we study more than 400 hotel transactions in the United Kingdom between 2000 and 2015 to determine the impact of brands on hotel market values. We initially find that hotel brands are negatively associated with hotel values in our sample. However, after controlling for endogeneity, we find that brand affiliation produces no significant impact on hotel transaction values. These results suggest that it is the characteristics of branded hotels, rather than the fact of being branded, that determine the transaction values. To the best of our knowledge, this is one of the first studies to examine the impact of brands on hotel values, and the first to account for the role of endogeneity when comparing the transaction value of branded and unbranded hotels.
The influence of communication adequacy on resistance to change: Case study of selected dealership companies in the Durban metropolitan region

This study aims to assess the impact of communication adequacy on resistance to change at selected dealership companies in the Durban Metropolitan Region. Recent studies suggest that there could be various other factors that influence resistance including leadership skills, demographic factors and theoretical components of resistance to change. The study uses the non-random purposive sampling collected from 270 staff at selected dealership companies in the Durban Metropolitan Region using questionnaires administered to employees. The structural equation model was also applied in analyzing the data. The findings of the study show that there is a significant relationship between communication adequacy based on structure and channel efficiency in relation to resistance communication based on channel efficiency positively influencing resistance to change. The study further provides practical implications for the employees at the selected dealership companies to consider more strategic and appropriate communication tools.
Salt and Metal Tolerance Involves Formation of Guttation Droplets in Species of the Aspergillus versicolor Complex

Three strains of the Aspergillus versicolor complex were isolated from a salty marsh at a former uranium mining site in Thuringia, Germany. The strains from a metal-rich environment were not only highly salt tolerant (up to 20% NaCl), but at the same time could sustain elevated Cs and Sr (both up to 100 mM) concentrations as well as other (heavy) metals present in the environment. During growth experiments when screening for differential cell morphology, the occurrence of guttation droplets was observed, specifically when elevated Sr concentrations of 25 mM were present in the media. To analyze the potential of metal tolerance being promoted by these excretions, proteomics and metabolomics of guttation droplets were performed. Indeed, proteins involved in up-regulated metabolic activities as well as in stress responses were identified. The metabolome verified the presence of amino sugars, glucose homeostasis-regulating substances, abscisic acid and bioactive alkaloids, flavones and quinones.
Efficacy and Safety of Gegen Qinlian Decoction for Pediatric Diarrhea: A Systematic Review and Meta-Analysis

Objective To evaluate the clinical efficacy and safety of Gegen Qinlian decoction in the treatment of pediatric diarrhea. Methods A search for relevant RCTs was performed from which a systematic review and meta-analysis was conducted. This meta-analysis was registered at INPLASY (reference number ID: INPLASY202180105). Results (1) Eleven trials involving 1126 patients were included in the meta-analysis. (2) Two trials recorded the adverse events. (3) The meta-analysis showed that compared with the control group, the experimental group has a significantly shorter duration of diarrhea in children (MD = −18.64, 95% CI (−23.76, −13.52), P < 0.00001), duration of fever (MD = −19.43, 95% CI (−25.76, −13.11), P < 0.00001), duration of vomiting [MD = −22.51, 95% CI (−29.92, −15.09), P < 0.00001], duration of correcting dehydration (MD = −23.35, 95% CI (−35.48, −11.22), P=0.0002), and the effective rate (OR = 4.64, 95% CI (3.12, 6.90), P < 0.00001). Conclusion There were significant differences in the clinical efficacy in the treatment of pediatric diarrhea between the experimental and control groups. Thus, Gegen Qinlian decoction may have certain advantages in the treatment of pediatric diarrhea. In addition, we conclude the following: (1) the application of Gegen Qinlian decoction to treat this disease is recommended for >5 days. (2) We recommend conducting multicenter RCTs to avoid the impact of regional differences on the results. (3) We recommend using the unmodified Gegen Qinlian decoction, which may have better efficacy.
A Monte Carlo Method for Image Classification Using SVM

Support Vector Machines are a widely used tool in Machine Learning. They have some important advantages with regards to the more popular Deep Neural Networks. For the problem of image classification, multiple SVMs may be used and the issue of finding the best hyperparameters adds additional complexity and increases the overall computational time required. Our goal is to develop and study Monte Carlo algorithms that allow faster discovery of good hyperparameters and training of the SVMs, without impacting negatively the final accuracy of the models. We also employ GPUs and parallel computing in order to achieve good utilisation of the capabilities of the available hardware. In this paper we describe our methods, provide implementation details and show numerical results, achieved on the publicly available Architectural Heritage Elements image Dataset.
Carbon Footprint Research Based on Input–Output Model—A Global Scientometric Visualization Analysis

Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future.
Derivation of Gell-Mann-Nishijima formula from the electromagnetic field modes of a hadron

When an electron probes another elementary particle Q, the wave function of the electron can be separated into two independent parts, the first part represents the electronic motion, the second part represents the electromagnetic field mode around the particle Q. In analogy with optical modes $TEM_{nlm}$ for a laser resonator, when the electromagnetic field around the particle Q forms into a mode, the quantum numbers of the mode satisfy the Gell-Mann-Nishijima formula, these quantum numbers are recognized as the charge number, baryon number and strangeness number. The modes are used as a visual model to understand the abstract baryon number and strangeness number of hadrons.
Large Deviations for Discrete-Time Processes with Averaging

Part 1 Introduction to large deviations: Cramer-type results (the classical Cramer theorem the extensions of Cramer's theorem) large deviations on the space of probability measures application to statistical mechanics basic large deviations concepts large deviations for sums of independent and identically distributed variables in function space applications to recursive estimation and control theory. Part 2 Large deviations for non-Markovian recursive scheme with additive "white noise". Part 3 Large deviation for the recursive scheme with stationary disturbances: large deviations for the sums of stationary large deviations for recursive scheme with the Wold-type disturbances. Part 4 Generalization of Cramar's theorem: large deviations for sums of stationary sequences large deviations for sums of semimartingales. Part 5 Mixing for Markov processes: definitions main results preliminary results proofs of theorems 5.1-5.6 mixing coeficients for recursive procedure. Part 6 The averaging principle for some recursive schemes. Part 7 Normal deviations. Part 8 Large deviations for Markov processes: examples Markovian noncompact case auxiliary results proofs of theorems 8.6-8.8 proof of theorem 8.9. Part 9 Large deviations for stationary processes: compact nonsingular case noncompact nonsingular case. Part 10 Large deviations for empirical measures: Markov chain with Doeblin-type condition noncompact Markov case stationary compact case stationary noncompact case. Part 11 Large deviations for empirical measures: compact case noncompact case.
Does Ecological Compensation Reduce
Air Pollutant Emissions? - Evidence
from Quasi-Natural Experiments in China

The concept and theory of ecological compensation (EC) have been widely studied in the past 20 years, but its practical effects have not yet been agreed upon. Based on a panel data from 281 prefecture-level cities in China from 2009 to 2018, this paper examines the impact of air ecological compensation (AEC) policy on air pollutant emissions and its mechanism with time-varying DID model. The study found that AEC will reduce the emissions of sulfur dioxide, PM2.5, industrial smoke and dust, which remained significant after a series of robustness test. Mechanism analysis concluded that AEC can reduce air pollutant emissions mainly by promoting green technology innovation, strengthening pollution treatment intensity and improving energy efficiency. The effect of AEC varied with city characteristics, in cities with high proportion of Industrial, low environmental regulation intensity and high fiscal pressure, AEC have significant or better policy effects, while, AEC does not have significant policy effects in cities with high environmental regulations intensity and low financial pressure. China should consider further promoting the pilot scope of AEC, but it also needs to improve the compensation standard and compensation mechanism to achieve better policy effects.
False Vision Graphics in Logo Design Based on Artificial Intelligence in the Visual Paradox Environment

There are numerous fresh ways of thinking and creativity as a result of the ongoing development of art design. How do you create a fantastic logo that has extraordinary artistic effects? The incorrect interpretation of artistic graphics can cause a special visual phenomenon known as the contradiction between visual images and objective reality, which causes people's visual systems to produce points of interest. Wrong vision graphics, or visual paradox, can give people a wonderful experience that transcends time and space and reveals the enigmatic beauty that is concealed in the natural order, which is in line with the design goals of sign art. The integration of design and artificial intelligence has drawn a lot of attention as science and technology have advanced. Designing an intelligent and comfortable user experience is more important than ever, especially given the world's growing digital demand. The technical limitations of algorithm black boxes exacerbate the power disparity between humans and algorithms, which is inherent in artificial algorithms. According to its research, artificial intelligence's algorithm is responsible for roughly 60% of its calculations. Random forest technology's current benefits and drawbacks are contrasted with those of popular algorithms, and a clear vision of its potential applications in the future is presented. The artificial algorithm's recommended operation mechanism chooses the algorithm's nontechnical neutrality and value orientation.
Dietary Acid Load Was Positively Associated with the Risk of Hip Fracture in Elderly Adults

Previous studies have shown that dietary acid load (DAL) harms bone health, but the evidence is inconsistent and insufficient. This study examined the relationships between DAL and the risk of hip fracture. This case–control study contained 1070 pairs of 1:1 age-, city-, and gender-matched incident cases and controls (mean age, 71 years) recruited in Guangdong, China. Dietary information was collected using a validated 79-item food frequency questionnaire through face-to-face interviews. DAL was estimated based on established algorithms for the potential renal acid load (PRAL) and net endogenous acid production (NEAP). Higher PRAL and NEAP were dose-dependently associated with a higher risk of hip fracture in both the conditional logistic regression model and restricted cubic spline analysis after adjusting for potential covariates. The multivariate-adjusted odds ratios and 95% CI of hip fracture for tertiles 2 and 3 (vs. 1) of DAL were 1.63 (1.18, 2.25) and 1.92 (1.36, 2.71) for PRAL and 1.81 (1.30, 2.53) and 2.55 (1.76, 3.71) for NEAP in all participants (all p-trends < 0.001), respectively. Subgroup analyses showed more pronounced associations in participants with a lower body mass index. Our findings suggested positive associations between the estimated DAL and the risk of hip fractures in the elderly Chinese population.