Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Trade Credit a Sustainable Resource for Medium-Sized Italian Green Companies?

Medium-sized Enterprises (MEs) are a limited number of Small and Medium-sized Enterprises (SMEs) in EU-28 countries, but they contribute greatly to value added and employment. They are also key to pursuing sustainable local development in terms of green economic growth. Because trade credit is a crucial financial source for SMEs, this article investigates the importance of trade credit for Italian MEs, and particularly for ‘green’ MEs, rather than ‘non-green’ MEs. A panel analysis is applied to 101,250 observations over the period 2010–2019. We find that green MEs rely more on trade credit than non-green MEs. Moreover, trade credit is more important for younger, smaller, less profitable, and less liquid MEs. We further show that a substitution effect between trade and banking credit exists, and that the local development level affects the demand for trade credit. Our results demonstrate that trade credit supports sustainable development more than banking credit. Financial intermediaries should therefore include green parameters in the assessment of the creditworthiness of MEs, and policymakers should consider that trade credit and financial inclusion may be important in pursuing sustainable local development and economic growth.
Take me into the ball game: an examination of a brief psychological skills training and mindfulness-based intervention with baseball players

ABSTRACT Baseball is considered to be a mentally demanding sport requiring effective management of psychological factors. Stress management, resilience, coping, flow and mindfulness have shown to be related to positive performance outcomes. To date, there is scarcity of research regarding the effectiveness of short duration integrated Psychological Skills Training (PST) and mindfulness interventions with baseball players. This mixed-method study examined the effects of a six-session integrated PST and mindfulness intervention on a U.S.A. NCAA Division I collegiate baseball team’s (n = 25; ages 18–22, M = 19.29, SD = 3.44) stress, resilience, athletic coping skills, flow, mindfulness and athletes’ perceptions of the intervention. Paired sample t-test revealed statistically significant decreases in stress and increases in resilience, athletic coping skills, mindfulness and dimensions of flow following the intervention. Qualitative data obtained through final reflective journals revealed athletes’ overall positive perceptions of the intervention and applicability not only to baseball, but also different aspects of life. These results provide encouraging support for the utilization of brief integrated mental training intervention with collegiate baseball players.
Colors of Jupiter Trojan Dynamical Families as Measured by the Zwicky Transient Facility

We use data from the first two years of the public survey of the Zwicky Transient Facility to analyze colors of proposed Jupiter Trojan asteroid families. The well studied Eurybates cluster remains the only family with a significant number of color measurements, and we find that the average colors of this family are less red than typical Jupiter Trojans, in agreement with smaller studies. The limited number of objects detected in this and other surveys for the other families makes their colors continue to be uncertain.
Mobile learning applications to improve invertebrate zoology online teaching

The use of new technologies including personal mobile devices has become an indispensable tool in our daily lives, and thus its presence in education is becoming ever more ubiquitous In the current scenario imposed by the COVID‐19 pandemic, in which in‐person presence in classrooms has been enormously reduced at all educational levels, the use of mobile learning and cutting‐edge methods can greatly improve the way students learn and enhance their online‐learning experience Mobile applications, combined with extended reality technologies such as virtual reality (VR) and augmented reality (AR), are powerful tools that connect real and virtual environments and allow higher interaction for the user We have leveraged the advantages of mobile learning and extended reality technologies to develop a series of mobile applications and associated educational activities for university‐level courses involving invertebrate zoology field work In particular, we have developed (a) a VR SCUBA diving video to explore the diversity of a marine protected area;(b) an AR mobile app to visualize 3D models of marine invertebrates;and (c) a mobile‐based catalogue to explore the terrestrial biodiversity of one of the most diverse regions of Spain Here we provide detailed information describing the design and creation of these tools, as well as their application in class, to facilitate and encourage their use in higher education Despite the relatively recent application of these technologies in education, they have an enormous potential: they improve student motivation and learning, can be adapted to different learning styles, reduce social inequalities, and facilitate inclusiveness and diversity practices in the classroom [ABSTRACT FROM AUTHOR] Copyright of Invertebrate Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )
Transparent thin-film metrology with a high sensitivity transmission-mode quantitative phase microscope

A transmission-mode high sensitivity quantitative phase microscope (QPM) is developed for profiling transparent thin film structures. The QPM system is implemented with a common-path interferometry design and a high well-depth camera, which has allowed us to achieve an optical path length difference sensitivity of around 50 picometers. A frame averaging method can be used to further improve the sensitivity. To account for multiple interference within thin films, a transmission matrix model is developed to achieve accurate height profile reconstruction. With the correction model, the profiling accuracy can be improved from 20.6% to 4.0% for a MoS2 thin film with a thickness of around 25 nm.
Quantitative phase-contrast by using a modified phase retrieval algorithm

Spatial-filtering-based quantitative phase imaging of transparent objects is demonstrated. By combining a standard phase contrast microscopy technique with an optical-system-mimicking Gerchberg-Saxton phase retrieval algorithm, we successfully transformed a qualitative phase map into an accurate quantitative phase distribution of the examined object. Feeding a phase-induced intensity image into the modified phase retrieval algorithm is found to facilitate the convergence and ambiguities issues associated with the standard algorithms. Accurate phase recovery for two different kinds of objects supports the use of the suggested method as a single-shot quantitative phase contrast microscope.
An Automatically Initialized Level Set Method for Ochotona Curzoniae Image Segmentation

In order to effectively solve this problem that that the traditional level set method needs to mark the initial contour manually, a novel method that automatic initialization by utilizing deep learning is proposed in this paper. Firstly, a target detection network based on Faster-RCNN is used for target detection of ochotona curzoniae. Secondly, the detected target boxes are regarded as the initial contour of level set models, and ochotona curzoniae images are segmented by level set models, by which the problem of manually plotting the initial contour required by traditional level set models is solved. The experimental results of ochotona curzoniae image segmentation show that there is little difference between the level set segmentation method in which the initial contour of the target is automatically generated by deep learning(LSECA) is used to automatically target initial contour and the level set segmentation method where initial contour needs to be manually plotted. Therefore, the experimental results prove that it is feasible to automatically obtain the target initial contour through deep learning.
High-redshift Narrow-line Seyfert 1 Galaxies: A Candidate Sample

The study of narrow-line Seyfert 1 galaxies (NLS1s) is now mostly limited to low redshift (z < 0.8) because their definition requires the presence of the Hβ emission line, which is redshifted out of the spectral coverage of major ground-based spectroscopic surveys at z > 0.8. We studied the correlation between the properties of Hβ and Mg ii lines of a large sample of SDSS DR14 quasars to find high-z NLS1 candidates. Based on the strong correlation of FWHM(Mg II) = (0.880 ± 0.005) × FWHM(Hβ) + (0.438 ± 0.018), we present a sample of high-z NLS1 candidates having FWHM of Mg ii < 2000 km s−1. The high-z sample contains 2684 NLS1s with redshift z = 0.8–2.5 with a median logarithmic bolometric luminosity of 46.16 ± 0.42 erg s−1, logarithmic black hole mass of 8.01 ± 0.35 M ⊙, and logarithmic Eddington ratio of 0.02 ± 0.27. The fraction of radio-detected high-z NLS1s is similar to that of the low-z NLS1s and SDSS DR14 quasars at a similar redshift range, and their radio luminosity is found to be strongly correlated with their black hole mass.
The practice and challenges of adopting information and communication technologies in Chinese higher education

This review paper aims to analyze the practice and challenges of adopting information and communication technologies in Chinese higher education. The Information and communication technologies application in China education is expanding swiftly, which is positively promoted by the support of social enterprises and the development of educational resources. Information and communication technologies application into the educational system greatly influenced the Chinese higher education system; it is more convenient and efficient via Information and communication technologies than ever before. A large quantity of digital tools is adopted in the learning and teaching process. The content and form of higher education have altered to some extent. The Chinese government set the goals and policies of Information and communication technologies application in education in the purpose of systematically implementing Information and communication technologies in Chinese higher education. In this regard; a large quantity of digital tools is adopted in learning and teaching process. However, there is a range of challenges faced by Chinese higher education to adopt Information and communication technologies. These challenges include institutional structures, infrastructure and equipment, hardware-dominated approach, and teachers’ lack of adequate skills. To this end, it is recommended to integrate information and communication technologies into the education system require the higher education institutions teachers and students needs to support adequate skills, thus contributing to improving the challenges of information and communication technologies in Chinese higher education.
Stability analysis of binary transposition algorithms during attacks on text data

Different approaches to using of transposition methods for data protection are examined in the article. The author has conducted comparative analysis of the approaches to increasing strength to protect the text from various attacks when its length and the data amount given per one symbol are raised. Basic criteria of evaluation of the offered methods are marked as well. The increase of the computational complexity in the described approaches is calculated.
Quantative Evaluation of Myoglobin and Hemoglobin Oxygenation during Contraction using Near-Infrared Spectroscopy

By SABINA KUMAR 117 million people in the United States today suffers from a chronic disease associated with an insufficient oxygen delivery to muscle. Clinicians need a fast, easy, non-invasive way to measure oxygen saturation. Near-Infrared Spectroscopy (NIRS) is a non-invasive procedure whose signal reflects tissue oxygenation. We hypothesized however that near-infrared spectroscopy (NIRS) measures of hemoglobin and/or myoglobin 02 saturation do not reflect the venous oxygen saturation because of the Hb and Mb contributions to the NIRS signal. A computational model previously developed to describe the dynamic and spatial changes of O2 concentration in blood and tissue domains of contracting skeletal muscle was modified to quantify Hb and Mb contributions to the NIRS signal. In addition, the effect of blood flow kinetics in a normal and disease with NIRS signal was studied.
Modulation Type Recognition Algorithm Based on Modulation Instantaneous Structure Difference and Deep Learning

In order to solve the problems of signal modulation recognition in non-cooperative communication, this paper proposes a modulation type recognition algorithm based on instantaneous difference by neural network. Firstly, the method uses the structural difference of modulation parameters in time domain of modulation signal, and displays the difference in the form of image, so as to transform the modulation recognition problem into image recognition problem; secondly, it uses the advantage of convolution neural network to automatically extract features, and it classify different modulation signals; finally, a hierarchical neural network structure is formed to identify the unknown modulation signals.
Anhydrous tert-butanol production via extractive distillation using glycerol as an entrainer: technical performances simulation

tert-Butanol is widely used as a main solvent in the industries. The high purity of tert-butanol is required to fulfil the industrial standard for the solvent. Unfortunately, tert-butanol separation from water required a special distillation named extractive distillation due to the azeotropic point in the mixture. Thus, entrainer as a third component should be used to break the azeotropic point. Glycerol is one of the potential green entrainer used in the extractive distillation. The simulation of the extractive distillation using glycerol as entrainer for the separation of tert-butanol/water mixture was conducted in this study. The Aspen Plus Process Simulator V.10 was used to simulate the feasibility of the glycerol as an entrainer and determine the optimum operating condition of the extractive distillation and recovery column in the anhydrous tert-butanol production. The results show that the optimum configuration for the extractive distillation column design consists of the number of stages of 25, binary feed stage of 21, entrainer feed stage of 3, reflux ratio of 0.6, mixed feed temperature of 25°C, and an entrainer feed temperature of 45°C. The condenser and reboiler duties are -1171.04 kW and 1744.48 kW, respectively. Moreover, the tert-butanol purity with this configuration can be achieved up to 0.996 of mole fraction.
Anastomosis Groups and Pathogenicity of Rhizoctonia solani Kühn Isolates Isolated from Pistachio (Pistacia vera L.) Saplings in Siirt Province, Turkey

Pathogenicity and anastomosis groups of seven Rhizoctonia-like isolates obtained from infected pistachio (Pistacia vera L.) seedlings were determined, in the central district of Siirt province at Southeast Anatolia Region in Turkey. Browning on the crown root of the collected saplings and drying of plants were observed. In the pathogenicity test, the most virulent isolate was Rs2 with a disease severity of 93.75%. The anastomosis group of this isolate, which caused the saplings to dry completely was determined as Rhizoctonia solani AG-4. The moderately virulent Rs3 and Rs1 isolates were determined as the binucleate AG-F group. These two isolates caused yellowing of the seedling leaves and browning of the roots, however, the plants did not die and preserved their vitality to a certain extent. The R9 and R14 isolates identified as anastomosis group AG-F did not cause any symptoms on inoculated plants and on the negative control. The Rs7 and Rs10 isolates were identified as the anastomosis group AG-4 and were determined to be pathogenic in saplings. The results of this study are the first record for the virulence and anastomosis groups of Rhizoctonia species that cause root and crown root diseases in Siirt pistachio.
IR Spectroscopic Study of Triiodosilane (SiHI3) by Using Semi-empirical Quantum Program

In this research, the more important spectral properties of vibration HSiI3 molecule have been studied and calculated by using the semi-empirical theoretical program (HyperChem) method (MNDO-PM3) (Use the RHF wave function for close - shell systems, the spins are paired). The calculated vibration modes for Triiodosilane (SiHI3) were nine modes in the region (63-1815) cm−1, which is located in the far and middle infrared region. Total energy, dipole moment, energy gap, Core-core repulsion, Ionization potential and electron affinity (E.A.) have been calculated. Other properties are also plotted in two and three dimensions, such as electrostatic potential and charge density. In addition, the values of the occupied and unoccupied molecular orbitals were calculated.
Formation of 1-D/3-D Fused Perovskite for Efficient and Moisture Stable Solar Cells

Various organic cations (e.g., methylammonium (MA+), butylammonium (BA+), formamidinium (FA+), etc.) have been studied and used in organometallic halide perovskite solar cells (PSCs). Most of the c.
MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study

Abstract Background Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61–0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49–0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64–0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51–0.67], Noether’s test P = .02). Conclusions In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance.
Fog Computing in Healthcare: A Review

The Internet of things (IoT) connects multiple devices worldwide. It is a growing field in the healthcare system such as health monitoring and tracking, fitness program, and remote medical assistance. With the advent of IoT based technologies in healthcare, it can alleviate the pressure on healthcare systems and can reduce the healthcare cost, and increase the computing and processing speed. Cloud computing was introduced to manage larger and complex healthcare data in the IoT environment. Cloud computing uses centralized cloud data centers. The central server manages the data for all the IoT devices. The integration of IoT with the cloud has some major issues such as latency, bandwidth overuse, real-time response delays, protection, and privacy. So the concept of edge computing and fog computing came into existence to overcome these issues. This paper review the IoT-Fog-based system model architectures, similar paradigm, issues, and difficulties in the area of cloud computing and finally, the performance of some of these proposed systems is assessed using the iFogSim simulator.
High-speed visible laser light communication: devices, systems and applications

In recent years, high-speed visible light communications (VLC) have been identified as an essential part of communication technologies for next generation wireless network owing to the increasing demand for faster data transmission speeds. VLC offers the unique advantages of ultra-high data rate, unregulated and secure channels, free of EM interference. Compared with the LED-based VLC system, laser-based photonic systems are promising for compact, droop-free, and high-speed white lighting and VLC applications, making them ideal alternatives for building ultra-fast optical wireless data link. Besides the potential for achieving high data rate free-space communication links, i.e., the Li-Fi network, laser based VLC, or visible laser light communication (VLLC) technology can also enable underwater wireless optical communications (UWOC) for many important applications. This paper summarizes the recent progress in high-speed laser based VLC devices and explore VLLC-enabled networks, systems, and applications. I will describe state-of-the-art VLC transmitter and receiver technologies. Novel designs to overcome the inherent limitations will be covered. Finally, the innovations in VLC systems for industrial IoT, vehicular communication, and underwater wireless networks applications will be discussed.
The Effects of Acute Glucoprivation on Adrenomedullary Function in SHR and WKY Rats

We have shown previously, acute intraperitoneal administration of 2-deoxy-d-glucose (2DG) into Sprague-Dawley rats led to activation of the adrenal medulla chromaffin cells, indicated with increased protein kinase activity and increased tyrosine hydroxylase (TH) phosphorylation, as well as increased plasma adrenaline and glucose levels. Here we have used spontaneous hypertensive (SHR) and Wistar Kyoto (WKY) rats to investigate whether hypertension alters basal adrenal chromaffin cell function, or the response of these cells to acute 2DG treatment. At basal level, we found no differences in adrenal medulla TH protein, TH phosphorylation, TH activity or catecholamine levels between SHR and WKY despite a significant difference in the level of systolic blood pressure; nor were there differences in plasma catecholamine levels or blood glucose (BG). Furthermore, the vehicle animals evoked no significant changes in any parameter measured in SHR, but evoked significant increases in pSer19TH, plasma adrenaline and BG in WKY. Single episode of glucoprivation evoked increases in PKA and CDK/MAPK, pSer40TH, pSer31TH, TH activity, and plasma adrenaline and BG in SHR, and in addition evoked increases in PKC, CAMKII, and pSer19TH in WKY. These findings are significant which indicates hypertension does not impact catecholamine function in the adrenal gland. It also appears that hypertension does not alter the adrenal response to glucoprivation. The findings are also significant as WKY showed greater adrenal activation of protein kinases and TH phosphorylation in response to saline and 2DG when compared to SHR and possible reasons for these findings are further discussed.