Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Intellectual and Social Alignment on Organizational Agility: A Configurational Theory Approach

Literature has shown that business-information technology (IT) alignment can exert both positive and negative influences on organizational agility, giving rise to the IT alignment-agility paradox. To better understand this paradox at a more granular level, we conceptualize the sensing and responding dimensions of organizational agility as two independent constructs and suggest a nonlinear analytical approach. Based on configurational and contextual perspectives, this study investigates how intellectual and social alignment and organizational and environmental elements combine into multiple configurations to affect sensing and responding capabilities. Fuzzy-set qualitative comparative analysis (fsQCA) is used to analyze the survey data from 135 dyads of business and IT executives from the Chinese shipbuilding industry. Results show that different equifinal pathways can be used to achieve high sensing and responding capabilities, in which intellectual and social alignment play heterogeneous roles depending on the specific contexts. This study extends the ITenabled agility literature by deepening our understanding of the effects of multidimensional IT alignment on multidimensional organizational agility and providing new insights into the IT alignment-agility paradox.
Recent Metaheuristic-Based Optimization for System Modeling and PID Controllers Tuning

: Recently, several methods and techniques, including the metaheuristic algorithms, have been developed, to identify and control systems. In this paper, four recent algorithms, such as Ant Lion optimizer (ALO), Differential Evolution (DE), Bat Algorithm (BA), and Harmony Search (HS), are chosen and considered for a one-paper comparison for the first time and exclusively applied to four different types of behaviors. The present contribution concerns the systematic analysis and comparison between the mentioned algorithms for the two tasks of system modeling and for the tuning of proportional, integral, and derivative (PID) controllers. Comparisons with conventional methods, such as Least Squares (LS) for identification and Reference Model (RM) for control, are made with different instructions to highlight the efficiency of this methods Further, the details on their performance metrics in terms of premature convergence and dynamic searches are provided. Simulations results demonstrate how accurately they help to obtain optimal solutions and show the most reliable method for the two main tasks of control and identification. Moreover, the present results confirm that the Differential Evolution strategy has the best performance, stable convergence feature, robustness, and insensitivity to disturbance and signal excitation .
Inclusive Economic Growth: Relationship between Energy and Governance Efficiency

The ambitious goal of the European Union (EU) countries is to achieve carbon neutrality by providing inclusive economic growth, which requires the development of relevant incentives and initiatives. Furthermore, such incentives and initiatives should guarantee the achievement of the declared goals. Energy sectors are the core determinant of inclusive economic growth. Traditional energy resources (coal oriented) have a higher negative impact on nature and people’s well-being than on economic and social benefits. However, the transition to renewable energy raises new issues in achieving goals of inclusive economic growth: affordable and clean energy, responsible energy consumption, and energy infrastructure. The analysis of the theoretical framework found that the digitalization of government could be a core instrument for handling the abovementioned issues. The paper aims to justify the role of green energy in achieving inclusive economic growth empirically. The study applies the following methods: fully modified Ordinary Least Square (OLS) and canonical cointegrating regression. The findings allow concluding that institutional quality passively affects inclusive economic growth and that the digitalization of government has a U-shaped impact on inclusive economic growth. In this case, countries should boost the digital transformation of public services and continuously increase the quality of institutions.
Some duality results for a class of multivariate semi-markov processes

The duality results well known for classical random walk and generalized by Janssen (1976) for (J-X) processes (or sequences of random variables defined on a finite Markov chain) are extended to a class of multivariate semi-Markov processes. Just as in the classical case, these duality results lead to connections between some models of risk theory and queueing theory.
A large-scale forward genetic screen for maize mutants with altered lignocellulosic properties

The development of efficient pipelines for the bioconversion of grass lignocellulosic feedstocks is challenging due to the limited understanding of the molecular mechanisms controlling the synthesis, deposition, and degradation of the varying polymers unique to grass cell walls. Here, we describe a large-scale forward genetic approach resulting in the identification of a collection of chemically mutagenized maize mutants with diverse alterations in their cell wall attributes such as crystalline cellulose content or hemicellulose composition. Saccharification yield, i.e. the amount of lignocellulosic glucose (Glc) released by means of enzymatic hydrolysis, is increased in two of the mutants and decreased in the remaining six. These mutants, termed candy-leaf (cal), show no obvious plant growth or developmental defects despite associated differences in their lignocellulosic composition. The identified cal mutants are a valuable tool not only to understand recalcitrance of grass lignocellulosics to enzymatic deconstruction but also to decipher grass-specific aspects of cell wall biology once the genetic basis, i.e. the location of the mutation, has been identified.
Production of Nano Hydroxyapatite and Mg-Whitlockite from Biowaste-Derived products via Continuous Flow Hydrothermal Synthesis: A Step towards Circular Economy

Biowastes from agriculture, sewage, household wastes, and industries comprise promising resources to produce biomaterials while reducing adverse environmental effects. This study focused on utilising waste-derived materials (i.e., eggshells as a calcium source, struvite as a phosphate source, and CH3COOH as dissolution media) to produce value-added products (i.e., calcium phosphates (CaPs) derived from biomaterials) using a continuous flow hydrothermal synthesis route. The prepared materials were characterised via XRD, FEG-SEM, EDX, FTIR, and TEM analysis. Magnesium whitlockite (Mg-WH) and hydroxyapatite (HA) were produced by single-phase or biphasic CaPs by reacting struvite with either calcium nitrate tetrahydrate or an eggshell solution at 200 °C and 350 °C. Rhombohedral-shaped Mg-WH (23–720 nm) along with tube (50–290 nm diameter, 20–71 nm thickness) and/or ellipsoidal morphologies of HA (273–522 nm width) were observed at 350 °C using HNO3 or CH3COOH to prepare the eggshell and struvite solutions, and NH4OH was used as the pH buffer. The Ca/P (atomic%) ratios obtained ranged between 1.3 and 1.7, indicating the formation of Mg-WH and HA. This study showed that eggshells and struvite usage, along with CH3COOH, are promising resources as potential sustainable precursors and dissolution media, respectively, to produce CaPs with varying morphologies.
Near-optimal nonholonomic motion planning for a system of coupled rigid bodies

How does a falling cat change her orientation in midair without violating angular momentum constraint? This has become an interesting problem to both control engineers and roboticists. In this paper, we address this problem together with a constructive solution. First, we show that a falling cat problem is equivalent to the constructive nonlinear controllability problem. Thus, the same principle and algorithm used by a falling cat can be used for space robotic applications, such as reorientation of a satellite using rotors and attitude control of a space structure using internal motion, and other robotic tasks, such as dextrous manipulation with multifingered robotic hands and nonholonomic motion planning for mobile robots. Then, using ideas from Ritz approximation theory, we develop a simple algorithm for motion planning of a falling cat. Finally, we test the algorithm through simulation on two widely accepted models of a falling cat. It is interesting to note that one set of simulation results closely resembles the real trajectories employed by a falling cat. >
Combined Prediction Model of Gas Concentration Based on Indicators Dynamic Optimization and Bi-LSTMs

In order to accurately predict the gas concentration, find out the gas abnormal emission in advance, and take effective measures to reduce the gas concentration in time, this paper analyzes multivariate monitoring data and proposes a new dynamic combined prediction method of gas concentration. Spearman’s rank correlation coefficient is applied for the dynamic optimization of prediction indicators. The time series and spatial topology features of the optimized indicators are extracted and input into the combined prediction model of gas concentration based on indicators dynamic optimization and Bi-LSTMs (Bi-directional Long Short-term Memory), which can predict the gas concentration for the next 30 min. The results show that the other gas concentration, temperature, and humidity indicators are strongly correlated with the gas concentration to be predicted, and Spearman’s rank correlation coefficient is up to 0.92 at most. The average R2 of predicted value and real value is 0.965, and the average prediction efficiency R for gas abnormal or normal emission is 79.9%. Compared with the other models, the proposed dynamic optimized indicators combined model is more accurate, and the missing alarm of gas abnormal emission is significantly alleviated, which greatly improves the early alarming accuracy. It can assist the safety monitoring personnel in decision making and has certain significance to improve the safety production efficiency of coal mines.
Measurement of pH field of chemically reacting flow in microfluidic devices by laser-induced fluorescence

The interaction between chemical reactions and the flow field in microfluidic devices is investigated by a laser-induced fluorescence technique refined for use at microscopic spatial resolution. The pH distribution of chemically reacting flow at a Y-junction in a neutralization reaction in a microfluidic device is successfully visualized at a spatial resolution of 0.89 µm × 0.89 µm.
Multivariate birth-and-death processes as approximations to epidemic processes

This paper presents the theory of a multivariate birth-and-death process and its representation as a branching process. The bivariate linear birth-and-death process may be used as a model for various epidemic situations involving two types of infective. Various properties of the transient process are discussed and the distribution of epidemic size is investigated. For the case of a disease spread solely by carriers when the two types of infective are carriers and clinical infectives the large population version of a model proposed by Downton (1968) is further developed and shown under appropriate circumstances to closely approximate Downton's model.
Picosecond GaAs-Based Photoconductive Optoelectronic Detectors

Picosecond photoconductive-switch performance was demonstrated with a novel material deposited by molecular beam epitaxy at low substrate temperatures using Ga and As4 beam fluxes. For a photoconductive-gap switch fabricated on a coplanar transmission line, the speed is 1.6 ps (full width at half maximum) and the voltage response is 10 to 100 times greater than that of conventional photoconduc­tive switches. Since LT GaAs is compatible with GaAs device and IC technologies, this photoconduc­tive switch may find extensive use in high-speed device and circuit testing.
COHERENT, REGULAR AND SIMPLE SYSTEMS IN ZERO DECOMPOSITIONS OF PARTIAL DIFFERENTIAL SYSTEMS

This paper studies triangular differential systems arising from various decompositions of partial differential polynomial systems. In theoretical aspects, we emphasizeon translating differential problems into purely algebraic ones. Rosenfeld's lemma is extended to a more general setting; relations between passivity and coherence are clarified;regular systems and simple systems are generalized and proposed, respectively. In algorithmic aspects, we review the Ritt-Wu and Seidenberg algorithms, and outline a methodfor decomposing a differential polynomial system into simple ones. Some applications arealso discussed.
An EEMD-based method for removing residual blood oxygen signal noise by combining wavelet and singular spectrum analysis

Blood oxygen content plays an important role in clinical diagnosis and treatment. However, interference signals will be introduced in the process of the signal acquisition, which will affect the accuracy of measurement results. Although the filter can eliminate most of the interference, there will still be a part of the residual interference signal. In order to eliminate these residual interference, this paper proposes a signal denoising method based on ensemble empirical mode decomposition (EEMD), lifting wavelet transform (LWT) and singular spectrum analysis (SSA). Firstly, the measured signal is decomposed by EEMD to obtain multiple modal components (IMF). The high-frequency components are denoised by LWT, and then reconstructed with the low-frequency components. Finally, the SSA is carried out on the reconstructed signal, the appropriate components are selected to reconstruct the signal to obtain the final denoised signal. After testing the EEMD-LWT-SSA method with simulated and measured signals, it can be seen that the method can effectively suppress the residual noise in signals and improve the accuracy of data.
Simultaneous X-ray and optical observations of GX 339-4 in an X-ray high state

Optical emission, soft X-rays, and hard X-rays have been observed simultaneously from the black hole candidate GX 3339-4 in a typical high state. Each of these components is interpreted as arising from a characteristic region of the accretion disk. Considered as a black hole, GX 339-4 lacks the variable 2 keV blackbody component that would be emitted from the 'solid' surface of a neutron star in the low-mass neutron star binaries. The X-ray emission in the high state is therefore extremely soft and stable in time. The intermediate disk region is optically thick and geometrically thin. The observed soft X-ray component with a 'disk blackbody' spectrum comes from this region. The innermost disk region is dynamically unstable due to the effect of general relativity and possibly due to radiation pressure. This region is responsible for the generation of the hard X-ray tail through Comptonization.
Psychobiosocial Experiences in Physical Education: A Semantic Differential Scale

ABSTRACT The objective of this study was to develop and validate the Psychobiosocial Experience Semantic Differential in Physical Education (PESD-PE) scale, a new holistic measure of discrete emotion-related feelings (i.e., psychobiosocial experiences) as conceived within the individual zones of optimal functioning (IZOF) framework. A preliminary version of the PESD-PE was administered to 336 students (171 girls, 165 boys), while the final version was administered to a new sample of 352 students (186 girls, 166 boys) aged 14–19 years. Overall, findings provided evidence of factorial and construct validity for a model containing 33 items loading into 11 modalities, with 3 items each. Convergent, discriminant, and nomological validity of the PESD-PE was also found. This new measure of discrete experiences will help increase our knowledge about the reciprocal effects between emotion-related feelings and performance, and will also inform practical interventions aimed at creating more adaptive psychobiosocial experiences in accordance with physical education goals.
Anisotropic spatial sampling designs for urban pollution

Summary. Isotropic processes form an inadequate basis in modelling many spatially distributed data. In particular environmental phenomena often have strong anisotropic spatial variation, especially when the regions monitored are very large. We extend a recently proposed optimal sampling strategy by assuming a spatial anisotropic random field as the basis for the data generator mechanism. The procedure is based on a geographical space transformation indicated by Sampson and Guttorp. We discuss the optimal design and we develop a sequential procedure for selecting a network of monitoring stations in environmental surveys. Some data on sulphur dioxide pollution in Padua (Italy) are analysed to illustrate the method.
Fail-safe visual-inertial navigation for UAVs

In this paper, we propose a visual-inertial state estimation framework which is able to detect and mitigate failure modes to ensure best possible state estimation for platform control at all times. The main focus here is on the proposed sensor switching method which allows seamless switching between integration of pure inertial cues, the use of inertial-optical ow based velocity estimates, and the use of visual-inertial based position estimates for the control of an inherently unstable aerial vehicle. The switching mechanism automatically detects if a state estimator part is faulty and reduces the sensory input to the remaining, healthy, information streams. In addition, a re-initialization sequence is run for the faulty segment until the full system is recovered. With the additional capability of each segment for self-calibration, the system is both self-calibrating and self-healing. The full framework has been integrated on an embedded platform on-board a real 500g small aerial vehicle and run at 30Hz camera stream and 1kHz inertial readings for live demonstration.
Reproductive performance of captive-reared Indian white shrimp, Penaeus indicus, broodstocks over two generations

Closing the complex life cycle of closed thelycum shrimp in captivity is one of the fundamental challenges in breeding programs. In the present study, we investigated the sexual maturity, broodstock development, and spawning performance of two generations of captive-reared Indian white shrimp, Penaeus indicus, over 36 months originated from a single stock of wild brooders. The post larvae (GN-1) produced from wild P. indicus (G0) and P.L. (GN-2) produced from captive-reared (GN-1) broodstocks were nursery (1000 PL m-3) and grow-out (12 shrimp m-2) reared, and subsequently raised in broodstock ponds (1 shrimp m-2). The annual salinity and photoperiod in broodstock ponds varied between 20 to 36 ppt, and 11.2 -12.5 L and 11.5-12.8 D hours, respectively. The light intensity varied between 91 ± 6 lux at dusk to 75,358 ± 1719 lux at noon. The size at first impregnation or mating was 16.45 ± 1.7 g (132 DOC) and 17.62 ± 1.9 g (90 DOC), respectively, in GN-1 and GN-2 females. By 220 DOC, 25% of the GN-1 females initiated gonad development, whereas 55% of the GN-2 females recorded developing ovaries or were in stage II at 150 DOC. The broodstock attained an average final body weight of 38.85 ± 1.5 g (GN-1) and 42.65 ± 1.8 g (GN-2) by 360 DOC. The highest (p<0.01) eggs per gram body weight (5137 ± 303 eggs g-1) and hatchability, H (83 ± 0.7%), was recorded in wild broodstocks (G0) followed by GN-2 (1,715 ± 162 eggs g-1; H: 69 ± 2%) and GN-1 (1,476 ± 151 eggs g-1; H: 75 ± 1%). However, captive-reared broodstock had better survival (89-92%) than wild broodstocks (71 ± 0.8%). Further, indoor maturation trial (21 days) using ablated broodstocks (GN-1) revealed 79% of the impregnated broodstocks undergo molting, resulting in the loss of sperm pack and subsequent reduction in mating efficacy to 29%. The average sperm count and percentage of normal sperm also recorded (p<0.05) reduction during the maturation cycle. The data generated in the present investigation can form the baseline information for developing the breeding strategy for the genetic improvement of Indian white shrimp in India.
Mill's Constitution of Liberty: an alternative behavioural policy framework

Abstract This paper offers an interpretation of the behavioural evidence that casts doubt over whether people always have preferences or, if they do, that they are stable. If people do not have preferences in this sense, then the usual policy evaluation standard of preference satisfaction cannot be used in these cases. The paper then develops, to fill this gap, a Millian policy framework where policy is judged by whether it advances what Mill understands by individual liberty in On Liberty. This yields many recognisable policies but offers a different evaluative standard for them. It also yields some policy innovations: e.g. a basic income and a flat tax.
Estimating a Product of Means: Bayesian Analysis with Reference Priors

Abstract Suppose that we observe X ∼ N(α, 1) and, independently, Y ∼ N(β, 1), and are concerned with inference (mainly estimation and confidence statements) about the product of means θ = αβ. This problem arises, most obviously, in situations of determining area based on measurements of length and width. It also arises in other practical contexts, however. For instance, in gypsy moth studies, the hatching rate of larvae per unit area can be estimated as the product of the mean of egg masses per unit area times the mean number of larvae hatching per egg mass. Approximately independent samples can be obtained for each mean (see Southwood 1978). Noninformative prior Bayesian approaches to the problem are considered, in particular the reference prior approach of Bernardo (1979). An appropriate reference prior for the problem is developed, and relatively easily implementable formulas for posterior moments (e.g., the posterior mean and variance) and credible sets are derived. Comparisons with alternative noninf.
For Heart Rate Assessments from Drone Footage in Disaster Scenarios

The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning.