Miracle-dz/UniFAR-FTUs huggingface dataset:
PARAMETER CALIBRATION FOR ELECTRIC ARC FURNACE MODELS USING SIMULATION AND NEURAL NETWORKS

Electric arc furnaces provide a relatively simple way for melting metals. They are used in the production of highly purified steel, aluminium, copper and other metals. However, they are considered the most damaging load for electrical power systems. It is very important, therefore, to have arc furnace models that can determine the behavior of this type of load with a high degree of accuracy. In this way, it would be possible to assess the impact in terms of power quality indices for the power system to which they are connected. When using electric arc furnace models in practice, a key issue is the calibration of the model’s parameters. In this paper, we show a procedure for calibrating all the parameters of an AC electric arc furnace model using real measurements of voltages and currents. A multilayer neural network is used as an emulator of the electric arc furnace model. The neural network is trained using data obtained from the simulation of the electric arc furnace model implemented in Matlab®-Simulink®. Once the network is trained, the parameters of interest are obtained by solving an inverse problem. The results obtained show a maximum percentage error of 4.1% for the rms value of the current involved in the electrical arc.
High Performance Error Tolerant Adders for Image Processing Applications

In this paper, we proposed High Performance Error Tolerant Adders (HPETA) which have an efficient design and quality metrics for inexact computing applications. To achieve high performance, Multiplexer Based Approximate Full Adders (MBAFA) are proposed in the inaccurate part of the HPETA design. High speed, energy and area efficiency have been achieved by the critical path delay reduction and the number of gate-level logic reduction. The performances of the proposed MBAFA and HPETA are investigated by comparing its speed, area, power and accuracy parameters with those of other existing error tolerant adder structures. The investigation of these designs is performed in the Cadence Encounter software using the Application Specific Integration Circuits (ASIC) TSMC 90-nm technology library. From the Simulation results, the proposed MBAFA-I based HPETA-I adder exhibits high speed, area efficiency, low power consumption, less Area-Delay Product (ADP) and 56.25%, 47.98%, 37.58%, 34.03%, 39.32% lesser Power-Delay Product (PDP) than the existing conventional CSLA, SAET-CSLA, ETCSLA, HSETA, HSSSA, respectively.
The impact of knowledge risk management on sustainability

Purpose The purpose of this study is to examine the effect of knowledge risk management (KRM) on organizational sustainability and the role of innovativeness and agility in this relationship. Design/methodology/approach The study presents the results of a quantitative survey performed among 179 professionals from knowledge-intensive organizations dealing with knowledge risks and their management in organizations. Data included in this study are from both private and public organizations located all over the world and were collected through an online survey. Findings The results have confirmed that innovativeness and agility positively impact the sustainability of organizations; agility also positively impacts organizational innovativeness. The partial influence of KRM on both innovativeness and agility of organizations has been confirmed as well. Research limitations/implications The paper findings contribute in different ways to the ongoing debates in the literature. First, they contribute to the general study of risk management by showing empirically its role in organizations in the given case of organizational sustainability. Second, by emphasizing the risks related to knowledge, this study contributes to emerging efforts highlighting the particular role of knowledge for sustained organizational development. Third, by linking KRM and organizational sustainability, this paper contributes empirically to building knowledge in this very recent field of study. This understanding is also useful for future development in the field of KM as a whole. Originality/value The paper lays the ground for both a deeper and more nuanced understanding of knowledge risks in organizations in general and regarding sustainability in particular. As such, the paper offers new food for thought for researchers dealing with the topics of knowledge risks, knowledge management and organizational risk management in general.
Compact and cost-effective multi-channel optical spectrometer for fine FBG sensing in IoT technology

Optical fiber sensor networks have attracted much attention in IoT technology and a fiber Bragg grating is one of key sensor devices there because of their advantages in a high affinity for optical fiber networks, compactness, immunity to electromagnetic interference and so on. Nevertheless, its sensitivity is not always satisfactory so as to be usable together with widespread cost-effective multi-channel spectrometers. In this paper, we introduce a new cost-effective approach for a portable multi-channel spectrometer with high spectral resolution and demonstrates some preliminary experimental results for fine FBG sensing.
Multifunctional Control of On-chip Generated Photons by a Single Collective Mode in Monolithically Integrated All-Dielectric Scalable Optical Circuits.

Recently we proposed the use of a single collective Mie mode of coupled dielectric resonators arranged in metastructures designed to simultaneously enhance the emission rate, control the direction, and propagation of emitted photons from an embedded single photon source (SPS) [J. Opt. Soc. Am. B 33(12), 2414(2016); J. Appl. Phys.120, 243103(2016)]. Here we extend the analysis to include the necessary additional two functions of beam splitting and controlled combing of photons from two distinct on-chip sources for interference. Thus, the same single Mie mode of the designed system provides all the required five functions in different spatial regions of an on-chip integrated optical circuit, enabling full control over photon interference for classical and quantum optical information processing. Single photon source architectures suited for such on-chip scalable integration are discussed.
An Islanding Detection Methodology Combining Decision Trees and Sandia Frequency Shift for Inverter Based Distributed Generations

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This study presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only when the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.
Preclinical Development of a Therapy for Chronic Traumatic Spinal Cord Injury in Rats Using Human Wharton’s Jelly Mesenchymal Stromal Cells: Proof of Concept and Regulatory Compliance

(1) Background: the use of Mesenchymal Stromal Cells (MSC) in emerging therapies for spinal cord injury (SCI) hold the potential to improve functional recovery. However, the development of cell-based medicines is challenging and preclinical studies addressing quality, safety and efficacy must be conducted prior to clinical testing; (2) Methods: herein we present (i) the characterization of the quality attributes of MSC from the Wharton’s jelly (WJ) of the umbilical cord, (ii) safety of intrathecal infusion in a 3-month subchronic toxicity assessment study, and (iii) efficacy in a rat SCI model by controlled impaction (100 kdynes) after single (day 7 post-injury) and repeated dose of 1 × 106 MSC,WJ (days 7 and 14 post-injury) with 70-day monitoring by electrophysiological testing, motor function assessment and histology evaluation; (3) Results: no toxicity associated to MSC,WJ infusion was observed. Regarding efficacy, recovery of locomotion was promoted at early time points. Persistence of MSC,WJ was detected early after administration (day 2 post-injection) but not at days 14 and 63 post-injection. (4) Conclusions: the safety profile and signs of efficacy substantiate the suitability of the presented data for inclusion in the Investigational Medicinal Product Dossier for further consideration by the competent Regulatory Authority to proceed with clinical trials.
Comparison of spectrophotometric and electrochemical pH measurements for calculating freshwater pCO2

Inland waters have an important role in the global carbon cycle, contributing significantly to terrestrial carbon fluxes through downstream export and exchange of CO2 with the atmosphere. However, large uncertainties in freshwater inorganic carbon fluxes remain. One contributing factor is uncertainty in carbonate system calculations for estimating the partial pressure of CO2 (pCO2) from pH and alkalinity in freshwater systems. The uncertainty stems largely from inaccurate pH values caused by glass pH electrode measurements in low ionic strength systems. This study compares indicator‐based spectrophotometric and electrochemical pH measurements and their application for calculating freshwater pCO2. Our study found that, compared to a pCO2 reference method, pH electrode‐based estimates of pCO2 were overestimated by 230 ± 200 μatm (n = 54) where indicator‐based spectrophotometric pH estimates of pCO2 were 58 ± 33 μatm (n = 34) over the range of 100–1600 μatm. Furthermore, we found that when ionic strength was assumed to be zero, calculated pCO2 error was ~ 20% of the reference pCO2. A 19‐d field study using autonomous spectrophotometric pH and pCO2 sensors found an average error in calculated pCO2 of −70 ± 57 μatm (n = 1685). Although, our focus is on riverine CO2, these findings and subsequent conclusions apply to all freshwater systems. Spectrophotometric pH measurements will improve future freshwater pCO2 calculations and better quantify inland waters' role in the global carbon budget.
Watershed Hepatocellular Carcinoma – Utility of Cone Beam CT for Transcatheter Therapy and Case Report

McCabe S1*, Lim M2, Maddineni S1 and Rozenblit G1 1Department of Radiology, Westchester Medical Center/New York Medical College, Valhalla, NY, USA 2Division of Interventional Radiology, Westchester Medical Center/New York Medical College, Valhalla, NY, USA *Corresponding author: McCabe S, Department of Radiology, Westchester Medical Center/New York Medical College, Valhalla, NY, USA, Tel: (914) 493-7560; E-mail: sam.mccabe@wmchealth.org
Comparison between mono and multi repository structures

The comparison of Mono and Multi Repository structures is a highly debated topic in the software development field. Despite the choice of repository structure is the first main step in development; so far, this comparison has only been made on a small or local scale. Here, Mono and Multi Repository structures have been compared from different aspects using thousands of projects. First, an algorithm shared for collecting and identifying Mono and Multi Repository projects and save them into the database. Database was used for making different comparisons for example the usage intensity of both structure types over time, the developer's preference over structure type based on their country and so on. Also, all these comparisons have been made according to the team size and development period for each repository structure.
Effect of Fiber Weave Structure in Printed Circuit Boards on Signal Transmission Characteristics

In this paper, we characterized and compared signal transmission performances of traces with different specifications of fiber weave. Measurements demonstrated that the dielectric constant, impedance fluctuation, and differential skew were all affected by fiber weave style. For flattened fiber weaves, the dielectric constant fluctuation reached 0.18, the impedance fluctuation amplitude was 1.0 Ω, and the differential skew was 2 ps/inch. For conventional fiber weaves, the three parameters were 0.44, 2.5 Ω, and 4 ps/inch respectively. Flattened fiber weave was more favorable for high-speed signal control. We also discussed the other methods to improve the fiber weave effect. It turned out that NE-glass (new electronic glass) fiber weave also had better performance in reducing impedance fluctuation and differential skew. Furthermore, made the signal traces and fiber weave bundles with an angle or designing the long signal line parallel to the weft direction both are simple and effective methods to solve this problem.
Blockchain and Deep Learning for Cyber Threat-Hunting in Software-Defined Industrial IoT

The softwarized infrastructure of Software-Defined Industrial Internet of Things (SDIIoT) offers a cost-effective solution to improve flexibility and reliability in network management but faces several critical challenges. First, th Majority of SDIIoT entities operate over wireless channel, which expose them to a variety of attacks (e.g., man-in-the-middle, replay, and impersonation attacks) and also the centralized nature of SDN controller is prone to single point attacks. Second, network traffic in the SDIIoT is associated with large scale, high dimension and redundant data, all of which present significant hurdles in the development of efficient flow analyzer. In this regard, we present a novel blockchain and Deep Learning (DL) integrated framework for protecting confidential information and hunting cyber threats against SDIIoT and their network traffic. First the blockchain module is proposed to securely transmit industrial data from IIoT sensors to controllers of SDN via forwarding nodes (i.e., OpenFLow switches) using Clique Proof-of-Authority (C-PoA) consensus mechanism. A novel flow analyzer based on DL architecture named LSTMSCAE-AGRU is designed by combining Long Short-Term Memory Stacked Contractive AutoEncoder (LSTMSCAE) with Attention-based Gated Recurrent Unit (AGRU) at the control plane. The latter first extracts low-dimensional features in an unsupervised manner, which is then fed to AGRU for hunting anomalous switch requests. The proposed framework can withstand a variety of well-known cyber threats and mitigate the single point of controller failure problem in SDIIoT.
THE AUTHORITARIAN FATHER: THE PREDICTIVE ROLE OF CONFLICT RESOLUTION STYLES AND THE ATTACHMENT DIMENSION

The authoritarian parenting style with its negative connotation has many adverse effects on various aspects of children's development, so the aim of this paper will be to identify potential predictors of the authoritarian parenting style of fathers. The concept of attachment and conflict resolution styles used by fathers are part of the model used in this paper which, together with the age of the fathers, represent important predictors of a father's authoritarian parenting style. A convenience sample included 101 fathers and their children from the territory of Northern Kosovo. The instruments used in the research are The Experience in Close Relationship Scale (Hanak and Dimitrijević, 2013; Brennan, Clark & Shaver, 1998), Conflict Management Styles Assessment (Adkins, 2006,) and the Parental Authority Questionnaire (Buri, 1991). The results partially proved the hypothesis, and were discussed in the context of attachment theory and previous empirical research that provides a strong framework of reference for understanding the results of this research.
Application of Nature-Inspired Multi-Objective Optimization Algorithms to Improve the Bakery Production Efficiency

: This contribution investigates the performance of nature-inspired multi-objective optimization algorithms to reduce the makespan and oven idle time of bakery manufacturing using a hybrid no-wait ﬂow shop scheduling model. As an example, the production data from a bakery with 40 products is investigated. We use the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to determine the tradeoffs between the two objectives. The computational results reveal that the nature-inspired optimization algorithms provide solutions with a signiﬁcant 8.7% reduction in makespan. Nonetheless, the algorithms provide solutions with a longer oven idle time to achieve the single goal of makespan minimization. This consequently elevates energy waste and production expenditure. The current study shows that an alternative Pareto optimal solution signiﬁcantly reduces oven idle time while losing a marginal amount of makespan. Furthermore, the Pareto solution reduces oven idle time by 93 min by expanding the makespan by only 8 min. The proposed approach has the potential to be an inﬂuential tool for small-and medium-sized bakeries seeking economic growth and, as a result, gain in market competition.
Encouraging Productive Behavior in Student Teams with Interventions

Teamwork pedagogies are used for teaching and learning in sociology, addressing general education goals, and developing students’ professional skills. Nevertheless, problems arise in group work that negatively affect learning, engagement, treatment of others, and team satisfaction. An intervention was added to an Introduction to Sociology course with an established teamwork pedagogy to improve these outcomes. We compared the results of student surveys before and after the intervention, finding improvement in students’ satisfaction with teamwork and students’ perceptions of their teammates. There were large, statistically significant improvements in interactional fairness. Students’ perceptions of learning improved, although the gains were not statistically significant. We theorize that the intervention improved the psychological safety climate for students, resulting in attitudes and dispositions that benefited social interactions in their teams. Our study demonstrates that faculty can encourage productive behavior in student teams with carefully crafted interventions.
Dual‐mode bandpass substrate integrated waveguide filter with a complementary split ring resonator

We present a new bandpass filter by combining an isosceles right‐triangle substrate integrated waveguide (SIW) cavity with a complementary split ring resonator (CSRR) together. The first and second modes of the SIW cavity are used to form a desirable passband with the help of a perturbation metallic via‐hole. We introduce a CSRR at the ground plate of the SIW cavity to produce two controllable transmission zeros at the upper stopband, which improve the upper stopband characteristic greatly. Moreover, at the lower stopband, we make use of a pair of T‐shape stub‐loaded resonators to generate a transmission zero, and thus improve the out‐of‐band rejection greatly. To validate our design scheme, a filter sample has been fabricated and measured. The measured results and simulation ones are in good agreements. The filters show advantages of compactness, sharp stopband rejection, high frequency‐selectivity, and controllable passband and transmission zeros.
Occult Hepatitis B Virus Infection: An Update

Occult hepatitis B virus (HBV) infection (OBI) refers to a condition in which replication-competent viral DNA is present in the liver (with detectable or undetectable HBV DNA in the serum) of individuals testing negative for the HBV surface antigen (HBsAg). In this peculiar phase of HBV infection, the covalently closed circular DNA (cccDNA) is in a low state of replication. Many advances have been made in clarifying the mechanisms involved in such a suppression of viral activity, which seems to be mainly related to the host’s immune control and epigenetic factors. OBI is diffused worldwide, but its prevalence is highly variable among patient populations. This depends on different geographic areas, risk factors for parenteral infections, and assays used for HBsAg and HBV DNA detection. OBI has an impact in several clinical contexts: (a) it can be transmitted, causing a classic form of hepatitis B, through blood transfusion or liver transplantation; (b) it may reactivate in the case of immunosuppression, leading to the possible development of even fulminant hepatitis; (c) it may accelerate the progression of chronic liver disease due to different causes toward cirrhosis; (d) it maintains the pro-oncogenic properties of the “overt” infection, favoring the development of hepatocellular carcinoma.
Morpho-Phylogenetic Evidence Reveals Novel Pleosporalean Taxa from Sichuan Province, China

Pleosporales is the largest and most morphologically diverse order in Dothideomycetes, including a large proportion of saprobic fungi. During the investigation of microfungi from decaying wood in Sichuan Province, several novel fungal taxa of asexual and sexual morphs were collected, identified, and well-described. Phylogenetic analyses based on SSU, ITS, LSU, RPB2 and TEF1α gene sequences suggested that these new taxa were related to Pleosporales and distributed in five families, viz. Amorosiaceae, Bambusicolaceae, Lophiostomataceae, Occultibambusaceae and Tetraplosphaeriaceae. The morphological comparison and molecular phylogeny evidence justify the establishment of six new taxa, namely Bambusicola guttulata sp. nov., Flabellascoma sichuanense sp. nov., Neoangustimassarina sichuanensis gen. et sp. nov., Occultibambusa sichuanensis sp. nov. and Pseudotetraploa bambusicola sp. nov. Among them, Neoangustimassarina was introduced as the second sexual morph genus in Amorosiaceae; Bambusicola guttulata, O. sichuanensis and P. bambusicola were isolated from bamboos, which contributed to the diversity of bambusicolous fungi. The detailed, illustrated descriptions and notes for each new taxon are provided, as well as a brief note for each family. The potential richness of fungal diversity in Sichuan Province is also discussed.