Miracle-dz/UniFAR-FTUs huggingface dataset:
Linking green HRM practices to environmental performance through pro-environment behaviour in the information technology sector

PurposeExisting literature acknowledges the role of green human resource management (GHRM) in shaping employees’ pro-environmental behaviour and environmental performance. However, limited studies have investigated the specific impacts of GHRM practices on pro-environmental behaviour from the employees’ perspectives. This study aims to conceptualise GHRM practices as internal resources that can be used to stimulate employee pro-environmental information technology (IT) behaviour.Design/methodology/approachThe hypothesised relationships were tested with the aid of partial least square path modelling of data collected from 333 IT professionals in ISO 14001 companies in Malaysia.FindingsThe results suggest that green training and development, performance management and empowerment and participation are essential in stimulating pro-environmental IT behaviour. Besides, the mediating effects of pro-environmental IT behaviour were significant for the impacts of green training and development, performance management and green empowerment and participation on environmental IT performance.Research limitations/implicationsThe results indicate that GHRM practices are significant predictors of environmental IT performance, but training and development could be counter-productive to performance unless it stimulates employees’ engagement in pro-environmental behaviour.Originality/valueThis study contributes to the resource-based view of HRM by examining GHRM practices as organisational resources for stimulating employee pro-environmental IT behaviour to support environmental IT performance.
Metabolomic analyses of highbush blueberry ( Vaccinium corymbosum L.) 1 genotypes revealed mechanisms of resistance to aluminum toxicity

37 Aluminum (Al) is an important factor that limits plant growth under acidic soil 38 conditions. However, several plant species developed distinct mechanisms that limit 39 the damage caused by high Al concentrations. In highbush blueberry ( Vaccinium 40 corymbosum ), the Al resistance mechanisms are not fully understood. This study 41 was designed to evaluate the effect of Al toxicity on roots and leaves of highbush 42 blueberry genotypes with contrasting Al resistance [Star (Al-sensitive) and Camellia 43 and Cargo (Al-resistant)] and identify the main molecular and physiological 44 strategies underpinning adaptive Al stress responses in nutrient solution. After 48 h 45 of the Al treatment, the reduced form of ascorbate (ASC) was higher in roots, but 46 unchanged in leaves of Cargo and Camellia genotypes compared to the control. We 47 also observed decreased root exudation of oxalate in the Al-treated sensitive cultivar 48 Star throughout the treatment period. However, in the resistant cultivar (Camellia), 49 the exudation of oxalate increased 2.4-and 2.8-fold at 24 and 48 h, respectively, 50 compared with t=0. The Al treatment affected differentially the enzyme activity and 51 gene expression of the tricarboxylic acid (TCA) cycle enzymes. The NAD-dependent 52 malate dehydrogenase (NAD-MDH) expression in roots of cultivar Cargo was 53 reduced at 24 h and increased at 48 h, whereas in leaves the expression was higher 54 at 24 h and decreased at 48 h compared to the control. The citrate synthase (CS)
Thermosteam: BioSTEAM's Premier Thermodynamic Engine

Thermosteam is a thermodynamic engine capable of solving mass and energy balances, estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. All chemical data in Thermosteam is imported from the chemicals library (C. Bell & contributors, 2020), an open-source compilation of data and functions for the estimation of pure component chemical and mixture properties. Thermosteam’s fast and flexible platform has enabled the evaluation of conceptual and emerging biochemical production processes. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) — capable of modeling reactors, distillation columns, heat exchangers, and other unit operations — has adopted Thermosteam as its premier thermodynamic engine (Cortés-Peña et al., 2020). Published biorefinery designs modeled in BioSTEAM implement thermodynamic property packages created with Thermosteam (BioSTEAM Development Group, 2020), including a cornstover biorefinery for the production of cellulosic ethanol, a lipid-cane biorefinery for the co-production of ethanol and biodiesel, and a wheatstraw biorefinery for the production of cellulosic ethanol (Cortés-Peña et al., 2020; Sanchis-Sebastiá et al., 2020).
Discrete-Time Modeling of High Power Asymmetric Half-Bridge LED Constant-Current Driver Controlled by Digital Current Mode

The high-power Asymmetric half-bridge Converter (AHBC) LED constant current driver controlled by digital current mode is a fourth-order system. Static operating point, parasitic resistance, load characteristics, sampling effect, modulation mode and loop delay will have great influence on its dynamic performance. In this paper, the small-signal pulse transfer function of the driver is established by the discrete-time modeling method for two operating points with three modulation modes of trailing-edge, leading-edge and double-edge. And, the effects of parasitic parameters, delay, sampling and load etc. are fully considered in modeling. For a large number of complex exponential matrix operations, the first order Taylor formula is used for approximate calculation after the coefficient matrix is obtained by substituting the data. Then, the designed average current mode compensators based on state-space averaging small-signal model(SSA) are used for analog and digital control, and the loop characteristics and control performance are analyzed. Simulation and experimental comparison results show that the proposed discrete-time model(DTM) can more accurately describe the characteristics of resonant peak, high-frequency dynamic and loop delay, and is very suitable for the design of high frequency digital controller.
XAFS Study of Ti-Silicalite - Structure of Framework Ti(IV) in the Presence and Absence of Reactive Molecules (H2O, NH3) and Comparison with Ultraviolet-Visible and Ir Results

X-ray absorption at the Ti K edge (both XANES and EXAFS) of a very pure Ti-silicalite containing a small fraction of Ti(IV) substituting for Si(IV) has been performed in order to study the effect of the presence or absence of ligands such as H 2 O and NH 3 on the Ti(IV) coordination sphere. In particular, the effect of an outgassing treatment at 400 K and of the interaction with NH 3 has been studied and described in detail. It has been found that the Ti(IV) is fourfold coordinated in the samples outgassed at 400 K and expands its coordination sphere number with action of adsorbates. The process is partially reversible at room temperature
Numerical Study on the Flow Mechanism of Compressor Rotor Blade Vibration under Different Inlet Probe Configurations

In the performance test of a compressor, the overstrain alarm of a rotor blade occurred and it was thought to be caused by a large-sized inlet probe. To explain and further avoid the occurrence of this phenomenon, the influences of probe strut configuration on the vibration strain of the compressor rotor blade and the corresponding flow mechanism are studied by using a one-way fluid-structure coupling calculation method. Firstly, the probe strut is simplified as a cylinder with a diameter of 10 mm and located upstream of the inlet stator with the strut wake impinging on the stator blade according to the compressor test. Then, the three scenarios are considered: moving the strut away from the stator blade in axial direction, shifting the strut half of the stator pitch circumferentially, and reducing the strut diameter. The analysis results show that the characteristics of blade vibration are determined by the excitation force on the rotor blade. Under the interaction between the large-sized strut and the compressor, in addition to the excitation force with the strut passing frequency, a force with a lower frequency, namely, the strut-wake-induced frequency, is also observed. The amplitude of the excitation force on the rotor blade depends on the probe configuration. When one of the excitation force frequencies is close to a natural frequency of the rotor blade, the blade resonates, and the amplitude of blade strain varies with the amplitude of the excitation force. In order to reduce the adverse effect of upstream strut wake on the compressor rotor blade vibration, the inlet probe strut should be designed with a smaller diameter and be placed further upstream of the stator in such a way that the strut wake vortex passes through the midpassage of the following stator.
A new visual/inertial integrated navigation algorithm based on sliding-window factor graph optimisation

Abstract Visual–Inertial Navigation Systems (VINS) plays an important role in many navigation applications. In order to improve the performance of VINS, a new visual/inertial integrated navigation method, named Sliding-Window Factor Graph optimised algorithm with Dynamic prior information (DSWFG), is proposed. To bound computational complexity, the algorithm limits the scale of data operations through sliding windows, and constructs the states to be optimised in the window with factor graph; at the same time, the prior information for sliding windows is set dynamically to maintain interframe constraints and ensure the accuracy of the state estimation after optimisation. First, the dynamic model of vehicle and the observation equation of VINS are introduced. Next, as a contrast, an Invariant Extended Kalman Filter (InEKF) is constructed. Then, the DSWFG algorithm is described in detail. Finally, based on the test data, the comparison experiments of Extended Kalman Filter (EKF), InEKF and DSWFG algorithms in different motion scenes are presented. The results show that the new method can achieve superior accuracy and stability in almost all motion scenes.
Probabilistic models for thermal properties of concrete

Thermal conductivity and specific heat of concrete are highly influential parameters for the heat transfer into the material during fire exposure. Reviewing the available literature has shown that there is a large scatter in the data for these thermal parameters. To quantify that uncertainty, novel probabilistic models for thermal conductivity and specific heat of concrete at elevated temperatures are developed. Analysis of available experimental data indicates that a temperature-dependent Gamma distribution can be recommended for both thermal properties. Closed-form equations for the temperature-dependent mean and standard deviation are derived. Thus, for both the thermal conductivity and the specific heat, a continuous probability distribution as a function of temperature is obtained, which can be easily implemented in numerical simulations. Using the example of the probabilistic analysis of a simply supported concrete slab exposed to the standard fire, the models are compared with the commonly used deterministic representation of the thermal properties. It is shown that the calculated probabilities of failure using the deterministic models are an order of magnitude lower and therefore unconservative. This analysis suggests that accounting for the uncertainty in thermal properties for concrete slabs can have a significant effect on evaluating the safety and therefore should not be ignored in cases of high importance.
Development of a Physiologically Based Pharmacokinetic Model of Mitragynine, Psychoactive Alkaloid in Kratom (Mitragyna Speciosa Korth.), In Rats and Humans

ABSTRACT Mitragynine is a major psychoactive alkaloid in leaves of kratom (Mitragyna speciosa Korth.). To understand its disposition in organs, this study aimed to develop a physiologically based pharmacokinetic (PBPK) model that predicts mitragynine concentrations in plasma and organ of interests in rats and humans. The PBPK model consisted of six organ compartments (i.e. lung, brain, liver, fat, slowly perfused tissues, and rapidly perfused tissue). From systematic searching, three pharmacokinetic studies of mitragynine (two studies in rats and 1 study in humans) were retrieved from the literature. Berkeley Madonna Software (version 8.3.18) was used for model development and model simulation. The developed PBPK model consisted of biologically relevant features following involvement of (i) breast cancer-resistant protein (BCRP) in brain, (ii) a hepatic cytochrome P450 3A4 (CYP3A4)-mediated metabolism in the liver, and (iii) a diffusion-limited transport in fat. The simulations adequately describe simulated and observed data in the two species with different dosing regimens. PBPK models of mitragynine in rats and humans were successfully developed. The models may be used to guide optimal mitragynine dosing regimens.
Occupational exposure to noise in the extractive industry and earthworks – a systematic review protocol

Occupational noise-induced hearing loss (ONIHL) is one of the most recognised occupational diseases globally. Mining and earthworks are among those with the greatest impact in this matter. A systematic review addressing the noise exposure characterisation, in order to develop a preventive design, is being proposed in this protocol. The Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) guidelines were used to draw the research outline, where the study and report characteristics are provided. All of the selected keywords and databases/journals were priorly identified and are now presented. The search methodology is clarified, and an example for Scopus is provided. A methodology to deal with bias within studies is proposed, and all the systematic review narrative processes of the systematic review are discussed in the protocol, including information that will be extracted from the selected records. The Preferred Reporting Items for Systematic Review and Meta-analysis guidelines will be used to help develop the review.
The influence of workforce agility on high-growth firms: The mediating role of innovation

An agile workforce refers to a workforce that is proactive, flexible and resilient in dealing with non-routine and unpredictable circumstances. Even though past research suggests that agility could have a positive effect on firm performance, there is hardly any empirical evidence on whether agility matters for high-growth firms (HGFs). The purpose of this research is therefore to investigate the extent to which workforce agility increases the likelihood of firms becoming HGFs in the high-tech manufacturing sector of a developing economy, and whether the relationship is mediated by new product innovation. We develop a theoretical framework that explains how and why a firm that has an agile workforce that is proactive in creating new products, flexible in responding to changing environment, and resilient in turbulent times, is more likely to create innovative products, and thus secure temporary monopoly, which increases the likelihood of the firm becoming a HGF. Then, utilizing firm-level data from high-tech manufacturing sector of a developing country, Iran, we test several hypotheses using logistic regressions. We find that workforce agility significantly increases the probability of high-tech manufacturing firms becoming HGFs, but that this relationship is mediated by new product innovation. Implications are drawn for theory and practice.
Difficult knowledge boundaries during requirements determination

ABSTRACT Academics and practitioners assume that knowledge sharing and knowledge integration are critical to effective team performance. However, the findings from empirical studies are at best mixed and in some cases contradictory. This study investigates the complex relationships between these factors as well as the moderating role of project objects (e.g., design outputs such as personas, journey maps, use cases, prototypes, etc.) in small project teams. Our case study explores how knowledge-based interactions and object usage coexist in impacting the performance of a small cross-disciplinary project team tasked with deciding the requirements for a connected health information system. A conceptual model is presented that illuminates some empirical nuances that are not addressed within extant literature. The paper uses the concept of boundary objects to explain these nuances. While static boundary objects supported lower levels of communication, malleable boundary objects were required for more in-depth communication.
Effect of Recombinant Bovine Somatotropin (rBST) Administration on Residual BST and Insulin-like Growth Factor-I Levels in Various Tissues of Cattle

This study was performed to investigate the effects of recombinant bovine somatotropin (rBST) administration on residual BST and insulin-like growth factor-I (IGF-I) levels in various tissues. Two experiments, (A) and (B) were conducted as follows. (A) Beef cattle (average b. w. of 450kg) were divided into three groups: control (CONT), low-dose (LOW) and high-dose (HIGH) groups. The CONT group received neither rBST nor vehicle. The LOW and HIGH groups were treated for 20 weeks by s. c. injection with 250mg rBST at one-week intervals and 500mg rBST at two-week intervals, respectively. (B) Beef cattle were divided into four groups: control (CONT) group, as described in experiment (A), and sustained-release, low-dose (SR-L), sustained-release, medium-dose (SR-M) and sustained-release, high-dose (SR-H) groups. SR-L, SR-M and SR-H were treated at two-week intervals for 24 weeks by s. c. injection with doses of 0.42mg rBST/kg b. w. (0.03mg rBST/kg b. w./day), 0.84mg rBST/kg b. w. (0.06mg rBST/kg b. w./day) and 1.26mg rBST/kg b. w. (0.09mg rBST/kg b. w./day), respectively. In both experiments, animals were killed two weeks after the final treatment.In experiment (A), residual BST and IGF-I levels in muscle tissues of the LOW and HIGH groups were not affected by rBST administration. In experiment (B), residual BST and IGF-I levels in muscle, fat, liver and kidney tissues of treated groups were not different from that of the CONT group, either. These results suggest that levels of BST and IGF-I in various tissues are not increased at two weeks after rBST administration.
A review of biomimetic scaffolds for bone regeneration: Toward a cell‐free strategy

Abstract In clinical terms, bone grafting currently involves the application of autogenous, allogeneic, or xenogeneic bone grafts, as well as natural or artificially synthesized materials, such as polymers, bioceramics, and other composites. Many of these are associated with limitations. The ideal scaffold for bone tissue engineering should provide mechanical support while promoting osteogenesis, osteoconduction, and even osteoinduction. There are various structural complications and engineering difficulties to be considered. Here, we describe the biomimetic possibilities of the modification of natural or synthetic materials through physical and chemical design to facilitate bone tissue repair. This review summarizes recent progresses in the strategies for constructing biomimetic scaffolds, including ion‐functionalized scaffolds, decellularized extracellular matrix scaffolds, and micro‐ and nano‐scale biomimetic scaffold structures, as well as reactive scaffolds induced by physical factors, and other acellular scaffolds. The fabrication techniques for these scaffolds, along with current strategies in clinical bone repair, are described. The developments in each category are discussed in terms of the connection between the scaffold materials and tissue repair, as well as the interactions with endogenous cells. As the advances in bone tissue engineering move toward application in the clinical setting, the demonstration of the therapeutic efficacy of these novel scaffold designs is critical.
Programmable Chip Based High Performance MEC Router for Ultra-Low Latency and High Bandwidth Services in Distributed Computing Environment

SUMMARY With the spread of smart cities through 5G and the development of IoT devices, the number of services requiring ﬁrm assurance of high capacity and ultra-low delay quality in various forms is increasing. However, continuous growth of large data makes it di ﬃ cult for a centralized cloud to ensure quality of service. For this, a variety of distributed application architecture researches, such as MEC (Mobile | Mutli-access Edge Computing), are in progress. However, vendor-dependent MEC technology based on VNF (Virtual Network Function) has performance and scalability issues when deploying a variety of 5G-based services. This paper proposes PRISM-MECR, an SDN (Software Deﬁned Network) based hardware accelerated MEC router using P4[3] programmable chip, to improve forwarding performance while minimizing load of host CPU cores in charge of forwarding among MEC technologies.
Stroke as a Presenting Feature of COVID-19

Objective: To analyze the coronavirus disease-2019 (COVID-19) patients presenting with acute stroke by determining their clinical characteristics, hospitalization course and prognosis. The common and conventional stroke risk factors in these patients were assessed with the aim of determining the role and contribution of the COVID-19 infection to stroke pathogenesis. Methods: Retrospective observational study involving 24 patients from a single tertiary care center over a time period of three months. Risk factors such as Age, Hypertension, Diabetes Mellitus, smoking status and underlying cardiac history were analyzed. COVID-19 relevant laboratory and radiological data were documented. Results: 87.5% of patients had ischemic stroke, with 58.3% of total patients being younger than 55 years. An equal incidence of both Diabetes Mellitus and Hypertension (37.5%) was identified. 29.2% were completely asymptomatic for COVID-19, of which 85.7% had no chest X-ray changes on admission. Eight patients (61.5%) developed pneumonia during admission despite an initially normal chest X-ray. Conclusion: Patients without COVID-19 symptoms and with normal chest radiography presenting with stroke does not rule out a possible underlying COVID-19 infection. Such patients may be positive for the virus and may go on to develop pneumonia shortly after suffering from strokes. This could suggest that stroke in COVID-19 patients is a possible initial presenting feature and consequence of the inflammatory state triggered by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection. It is imperative to analyze the association of COVID-19 and stroke, and to maintain a high index of suspicion of COVID-19 infection in stroke patients, to enhance early detection and reduce transmission.
High-Frequency Nonlinear Model Predictive Control of a Manipulator

Model Predictive Control (MPC) promises to endow robots with enough reactivity to perform complex tasks in dynamic environments by frequently updating their motion plan based on measurements. Despite its appeal, it has seldom been deployed on real machines because of scaling constraints. This paper presents the first hardware implementation of closed-loop nonlinear MPC on a 7-DoF torque-controlled robot. Our controller leverages a state-of-the art optimal control solver, namely Differential Dynamic Programming (DDP), in order to replan state and control trajectories at real-time rates (1kHz). In addition to this experimental proof of concept, an exhaustive performance analysis shows that our controller outperforms open-loop MPC on a rapid cyclic end-effector task. We also exhibit the importance of a sufficient preview horizon and full robot dynamics through comparisons with inverse dynamics and kinematic optimization.