Miracle-dz/UniFAR-FTUs huggingface dataset:
The Mediating Role of Organizational Culture in Managing the Relationship Between Quality and Innovation: A Conceptual Model Proposal

Quality and Innovation play a fundamental role in helping organizations secure sustainable competitive advantage. However, the nature of their relationship has seen contradictory results. This ongoing research project seeks to relaunch the debate on the relationship between TQM and Innovation, doing so from a novel perspective that considers the cultural orientation of an organization as the key success factor in mediating the relationship between TQM and Innovation. It sets to understand if the creation of a cultural orientation to Quality supports the development of Innovation capabilities. In a first report of this project, the outcomes of this work are the review of the literature on the relationship between Quality and Innovation, the proposal of a conceptual model and the establishment of a series of hypothesis to further study their relationship.
Cognitive-Based Crack Detection for Road Maintenance: An Integrated System in Cyber-Physical-Social Systems

Effective road maintenance can not only achieve a balance between limited resources and long-term high-efficiency performance of road but also reduce the loss of life and property caused by road damage to vehicles and pedestrians. Due to the lack of a multidimensional dynamic monitoring system and enough extremely special data, the existing road maintenance system cannot accurately assess the road surface condition and provide timely early warning of sudden road damage. In this article, the M-RM system is proposed, that is, a metaverse-enabled road maintenance system based on cyber–physical–social systems (CPSSs), which fully utilizes the social and artificial system information of CPSS, as well as the simulation, monitoring, diagnosis and prediction functions of road systems in the virtual world of the metaverse. Then, in the road damage detection of system model in the virtual world, for the virtual data of the core assets of the metaverse, we propose an adaptive and information-preserving data augmentation (AIDA) algorithm-based nonclassical receptive field suppression and enhancement, an algorithm developed from human visual cognition. This algorithm enables the generation of a large amount of scarce fidelity data and avoids the introduced noise from impairing the performance of nonaugmented data. Finally, a crack detection algorithm named pay attention twice (PAT) is proposed, which uses the generated virtual data for training, and achieves secondary attention to high-frequency targets by fusing frequency-division convolution and mixed-domain attention mechanism. The detection performance of small targets in uncertain environments is enhanced. The metaverse system built in the current research can not only be used for road maintenance but also empower the traffic metaverse by using the traffic flow prediction module embedded in the algorithm. Experimental results demonstrate that the proposed algorithm can be applied to the road damage detection task under different noise and weather conditions, and the performance outweighs other state-of-the-art algorithms.
Thermal conductivity of Si–Ge superlattices

The thermal conductivity of Si–Ge superlattices with superlattice periods 30 2 × 109 W m−2 K−1 at 200 K. Superlattices with relatively longer periods, L>130 A, have smaller thermal conductivities than the short-period samples. This unexpected result is attributed to a strong disruption of the lattice vibrations by extended defects produced during lattice-mismatched growth.
Parametric Analysis and Optimization of Inlet Inflection Angle in Torque Converters

Torque converters are widely used in all means of transportations, such as cars, buses, trucks, and the list can go on. Since power is transmitted via fluid, the blade geometry which forms the flow passages is crucial to torque converter performance. The inlet deflection angle is an important blade design parameter with respect to both performance and manufacturability of torque converters. In the conventional design procedure, inlet deflection angle is often given by the designer’s experience or is selected based on experimental data if available. This study presents a method of optimizing the inlet deflection angle for torque converters and provides a series of non-inferior solutions for the decision maker to select from. The advantages of the method proposed consist of improved design quality and significantly shorter design cycle. A combination of computational analysis and global optimization algorithm was used in this study. A torque converter base model was evaluated using computational fluid dynamics for predicting its performance. The proper grid density and turbulence model were selected through correlation to the experimental data available. The following tasks were automated and integrated to form a parameterized design loop: 1) torque converter flow field CAD modeling, 2) meshing, and 3) CFD simulations and results post-processing. Selecting peak efficiency, stall torque ratio and stall pump capacity factor as objective functions, a multi-objective genetic algorithm was included in the design loop to optimize the torque converter performance.The CFD results proved to be in good agreement with the experimental data over the range of operating conditions considered in this study. The influence of inlet deflection angle on the performance of torque converter was determined through a parametric analysis and a series of Pareto-optimal solutions were determined by the optimization procedure, which proved to improve the performance of the base model torque converter.Copyright © 2013 by ASME
Optical properties of relaxor ferroelectric crystal: Pb(Zn1/3Nb2/3)O3-4.5 % PbTiO3

Abstract High quality Pb(Zn1/3Nb2/3)O3-4.5%PbTiO3 single crystal sample with the stable polarization (well poled) were used for the optical measurements in this work. For the single crystal, poled along ⟨111⟩ direction, the wavelength dependence of the refractive index (n1 and n3) was measured by the Minimum Deviation Method. The Sellmeier optical coefficients, Eo=5.25eV, λo=0. 236μm, So=0.7×1014m−2 and Ed=20.48eV for n3, and Eo=5.46eV, λo=0. 227μm, So=0.8×1014m−2 and Ed=22.52eV for n1, of the PZN-PT, were obtained through fitting the single-term oscillator equation. The effects of crystal-lattice distortion and poling direction on optical properties of crystal were discussed.
2021 February Texas Ice Storm Induced Spring GPP Reduction Compensated by the Higher Precipitation

Climate extremes are more frequent and affect the carbon cycle. On 10–20 February, an exceptional winter storm in Texas brought severe ecological and economic effects. However, its impacts on vegetation activities and the carbon cycle are unclear. This study evaluated the early 2021 ice storm effects on spring phenology and the carbon cycle. The results showed that the ice storm led to a significant later vegetation spring phenology and a reduction of 42.32 Tg C in gross primary production (GPP) and a reduction of 34. 47 Tg C net ecosystem production (NEP) in spring. In the 2021 spring, Texas became a carbon source from the carbon sink. More precipitation in late spring and summer precipitation recharged the rootzone soil moisture, which enhanced summer vegetation GPP and NEP and compensated for the effects of the ice storm on spring carbon uptake. The summer GPP enhancement offset all the spring GPP reduction, and thus GPP was increased by 4.97% during 2021. 91.47% of the spring NEP reduction was compensated by summer NEP enhancement due to higher root zone soil moisture. Due to the NEP enhancement during autumn, NEP did not decrease as well and increased by 10.88% during 2021. This observation‐based research highlights the seasonal compensation effects on the interactions between extreme climate events and the biosphere.
What Benefits Can SMEs in the Food Industry Gain from Innovative Products?

This paper is aimed at investigating the benefits that SMEs in the food industry gain by having innovative products. For this research, a questionnaire to collect data from SME representatives was distributed through email after drawing on the database in Thailand. The 83 SMEs from the food industry that responded were divided into two groups: 1) 38 non-innovative ones that had delivered no innovative products and 2) 45 innovative that had created new products for this type of industry. The author adopted t-testing to find the difference of benefits in a range of aspects, including: cost saving, fewer team members, less office space needed, time savings, decrease in routine work, fast in response time, increase in collaboration, greater market penetration and work flexibility. The results revealed benefits for innovative SMEs in all aspects considered when compared with non-innovative ones. In particular, innovative SMEs exhibited quicker response times and increased collaboration for the business than their counterparts. The findings support the focal SMEs taking advantage of the benefits of innovation for their business by creating and releasing onto the innovative products.
Power spectrum, correlation function, and tests for luminosity bias in the CfA redshift survey

We describe and apply a method for directly computing the power spectrum for the galaxy distribution in the extension of the Center for Astrophysics Redshift Survey. Tests show that our technique accurately reproduces the true power spectrum for k greater than 0.03 h Mpc(exp -1). The dense sampling and large spatial coverage of this survey allow accurate measurement of the redshift-space power spectrum on scales from 5 to approximately 200 h(exp -1) Mpc. The power spectrum has slope n approximately equal -2.1 on small scales (lambda less than or equal 25 h(exp -1) Mpc) and n approximately -1.1 on scales 30 less than lambda less than 120 h(exp -1) Mpc. On larger scales the power spectrum flattens somewhat, but we do not detect a turnover. Comparison with N-body simulations of cosmological models shows that an unbiased, open universe CDM model (OMEGA h = 0.2) and a nonzero cosmological constant (CDM) model (OMEGA h = 0.24, lambda(sub zero) = 0.6, b = 1.3) match the CfA power spectrum over the wavelength range we explore. The standard biased CDM model (OMEGA h = 0.5, b = 1.5) fails (99% significance level) because it has insufficient power on scales lambda greater than 30 h(exp -1) Mpc. Biased CDM with a normalization that matches the Cosmic Microwave Background (CMB) anisotropy (OMEGA h = 0.5, b = 1.4, sigma(sub 8) (mass) = 1) has too much power on small scales to match the observed galaxy power spectrum. This model with b = 1 matches both Cosmic Background Explorer Satellite (COBE) and the small-scale power spect rum but has insufficient power on scales lambda approximately 100 h(exp -1) Mpc. We derive a formula for the effect of small-scale peculiar velocities on the power spectrum and combine this formula with the linear-regime amplification described by Kaiser to compute an estimate of the real-space power spectrum. Two tests reveal luminosity bias in the galaxy distribution: First, the amplitude of the pwer spectrum is approximately 40% larger for the brightest 50% of galaxies in volume-limited samples that have M(sub lim) greater than M*. This bias in the power spectrum is independent of scale, consistent with the peaks-bias paradigm for galaxy formation. Second, the distribution of local density around galaxies shows that regions of moderate and high density contain both very bright (M less than M* = -19.2 + 5 log h) and fainter galaxies, but that voids preferentially harbor fainter galaxies (approximately 2 sigma significance level).
Pilot Testing and Preliminary Psychometric Validation of Situational Judgment Test of Resistance to Sunk Cost

The sunk-cost fallacy is an anomaly in decision-making that has been proven in various experimental studies. However, individual differences in the tendency to fall into sunk-cost fallacy have not been sufficiently reported. This preliminary study contains a psychometric evaluation report of the Resistance to Sunk Costs (RtSC) measurement instrument, a component of the Adult Decision Making Competence instrument (A-DMC; De Bruin, Parker, & Fischhoff, 2007) which is modified into Indonesian socio-cultural and economic contexts. The RtSC instrument uses a situational judgment test model, therefore it is adequate to measure the psychological construct of sunk-cost fallacy. The data analysis techniques used in this study were Item Factor Analysis (IFA) and graded response models. Respondents in this study were 217 students in Indonesia. The analysis results show that the 1-factor model of resistance to sunk costs fits the data. At the item level, based on the IFA, it was found that two out of ten items were found to be misfits. The results of the GRM analysis on the remaining eight items indicate that the items fit the GRM. However, the distinguishing power and reliability were found to be low. It can be concluded that this preliminary study provides a variety of important information as suggestions for improvement for our modified scale. Several theoretical and methodological implications are discussed.
Nutritional and haemato-biochemical modulation in dairy goats during mid-pregnancy

The present study was conducted to assess the influence of mid-pregnancy on the nutrient utilization, haematological and blood biochemical profile in gravid goats. Sixteen indigenous non-descript does of approximately 3–4 years of age were randomly allotted to two equal groups (PREG and NPREG) of eight each based on individual BW. The goats of pregnant group (PREG) were synchronized, mated and were left for routine group feeding, care and management. They were brought to experiment just 60 days after mating along with the non-pregnant (NPREG) group; both the groups were offered basal diet comprised of concentrate mixture and wheat straw to meet their nutrient requirements. A metabolic trial of six day duration was conducted at 90 days after mating on all the experimental goats to assess the nutritional modulation along with any changes of haematological and blood biochemical parameters at mid pregnancy stages. The results revealed no variation in intake and digestibility of DM, OM and CP. However, the digestibility of NDF, ADF and hemicellulose was higher for PREG does as compared to NPREG control. The balance of nitrogen was positive and comparable between the groups. Blood haematobiochemical profile showed no significant influence of pregnancy on different blood metabolites except that of low serum urea. The serum variables representative of the liver function was within the normal range and were comparable between the groups. It is concluded that mid-pregnancy induces no perceptible nutritional modulation except for subtle improvements in fibre digestibility, and possibly protein utilization in dairy goats.
Sex‐dependent body mass and respiratory responses on Euschistus heros individuals resistant to imidacloprid

In insect‐resistant populations, adaptive fitness is intimately related to the physiological responses of males and females to different stressors. By using laboratory‐selected imidacloprid‐resistant individuals of the Neotropical brown stink bug Euschistus heros, one of the most prevalent pests in soybean fields in the Neotropical region, we evaluated whether resistance to imidacloprid (synergized by piperonyl butoxide—PBO) would differentially affect the longevity, body mass and respiratory responses of E. heros males and females. We used an imidacloprid‐susceptible E. heros strain (ImiSusc), whose individuals were reared under controlled and imidacloprid‐free conditions for over a decade, to select the PBO‐synergized imidacloprid‐resistant strain (ImiPBOSel). After eight generations using PBO‐synergized imidacloprid, our results revealed that resistant individuals exposed only to dry residues of imidacloprid (tarsal contact) could survive at concentrations as high as 168 μg a.i./cm2, which is equivalent to 40‐fold the label recommendation for field applications. Furthermore, ImiPBOSel males and females exhibited higher longevity, higher body mass and elevated respiratory activity than ImiSusc individuals. Altogether, the findings described here showed that imidacloprid resistance can select E. heros individuals with better metabolic capacities, which can complicate the management of this pest under field conditions.
Coronary artery disease and its vascular associates in patients with chronic nonsurgical hypoparathyroidism

Patients with chronic hypoparathyroidism (cHypoPT) are prone to intracranial‐calcification, cataract and nephrocalcinosis. In this study, we systematically investigated the possibility of increased coronary artery calcification (CAC) and coronary artery disease (CAD) in them.
Disentangling the components of pollen limitation in a widespread herb with gametophytic self-incompatibility.

PREMISE OF THE STUDY Seed production is frequently limited by the receipt of insufficient or low-quality pollen, collectively termed, pollen limitation (PL). In taxa with gametophytic self-incompatibility (GSI), incompatible pollen can germinate on stigmas but pollen tubes are arrested in styles. This allows for estimates of pollen performance before, during, and after self-recognition, and insight into the factors underlying pollen quality limitation in GSI taxa. METHODS We scored pollen performance following self- and outcross pollinations in Argentina anserina to identify the location of self-recognition and establish the relationship between pollen tubes and seed production. We then estimated quantity and quality components of PL from >3,300 field-collected styles. We combined our results with other studies to test the prediction that low pollen quality, but not quantity, drives higher PL in self-incompatible (SI) taxa than self-compatible taxa (SC). KEY RESULTS Self and outcross pollen germinated readily on stigmas, but 96% of germinated self-pollen was arrested during early tube elongation. Reproduction in the field was more limited by pollen quality than quantity, and pollen failure near the location of self-recognition was a stronger barrier to fertilization than pollen germination. Across 26 taxa, SI species experienced stronger pollen quality, but not quantity, limitation than SC species. CONCLUSIONS Evaluating pollen performance at multiple points within pistils can elucidate potential causes of pollen quality limitation. The receipt of incompatible pollen inhibits fertilization success more than insufficient pollen receipt or poor pollen germination in A. anserina. Likewise, pollen quality limitation drives high overall PL in other SI taxa. This article is protected by copyright. All rights reserved.
Risk-sensitive MPCs with Deep Distributional Inverse RL for Autonomous Driving

In robot learning from demonstration (LfD), a visual representation of a cost function inferred from Inverse Reinforcement Learning (IRL) provides an intuitive tool for humans to quickly interpret the underlying objectives of the demonstration. The inferred cost function can be used by controllers, for example, Model Predictive Controllers (MPCs). In this work, we improve the recently developed IRL-MPC framework, by enhancing it in a risk-sensitive formulation to be more applicable for safety-critical applications like autonomous driving. Our risk-sensitive MPCs together with the distributional costmap demonstrate lower collision rates in the CARLA simulator for autonomous driving tasks compared to other learning-based baseline methods.
Differentiating characteristics among three new goat populations from northern India

Three non-descript goat populations, viz. Kumaoni and Garhwali of Uttarakhand hills, and Rohilkhandi of upper Ganges alluvial plain of Uttar Pradesh (India) were characterized phenotypically with standard morphometric parameters. The animals were also evaluated for their reproductive and production performance. The null hypothesis that Garhwali, Kumaoni and Rohilkhandi goat populations are same was tested using value of discriminant functions (D), Wilksâ€™ Lambda and Boxâ€™s M statistics. The classification results revealed that 84.9% of all the goats were correctly classified to their own population. This could be used by livestock development agencies to take up appropriate breeding program for the improvement of native stock for future genetic conservation. The milk composition of Uttarakhand goats did not differ much due to geographic identities except for milk fat percentage. The study revealed that body height, body length, horn pattern, face length, and chest girth were the most discriminating and unique variables to separate Rohilkhandi, Kumaoni and Garhwali goat populations.
Adventure Therapy for Adolescents with Complex Trauma: A Scoping Review and Analysis

Background: Childhood adversity is linked with mental health concerns, including complex trauma (CT), whereas positive experiences may be restorative. Treatment for CT with adolescents commonly uses therapies administered indoors. Yet outdoor adventure, being rich in positive experiences, may also be appropriate. Purpose: This article examines how adventure practices may be healing for adolescents with CT. Methodology/Approach: A scoping review of literature since 2014 on adventure therapy (AT) for 12- to 18-year-olds with CT was undertaken. Refining searches from six databases identified six texts which met inclusion criteria. A seventh paper was added manually. Findings/Conclusions: CT-informed adventure tended toward a tri-phasic approach: safety, processing, and integration. Adventure benefits included improvements in attachment, skills, schemas, and stress management. An ecological approach was identified, through the analysis, as were some well-intended but harmful practices that a human rights-based practice framework may help avoid. Implications: Adopting an ecological and human rights-based approach as frames for AT research and practice may yield new insights and enhance program effectiveness for youth with CT. This should apply to adventure generally and specifically to AT; however, more research is needed given the paucity of available texts.
Flood Forecasting Method Based on Improved VMD-FOS-QR-RBL

To improve the accuracy, reliability and validity of flood prediction models, this study proposes a regularized broad learning (RBL) model based on an improved variational mode decomposition (VMD). Firstly, grey correlation analysis was used to improve the endpoint effect of the VMD and the particle swarm optimisation (PSO) algorithm was used to optimise the VMD parameters. Then, using orthogonal triangular decomposition (QR), redefining the hidden layer output of BL model and adding forgettable online sequence learning mechanism (FOS) to construct online sequence BL (FOS-QR-RBL), which can significantly improve the computational efficiency of BL model. Finally, a flood forecasting method based on improved VMD-FOS-QR-RBL was constructed by combining the FOS-QR-RBL with the improved VMD and applying it to regional flood forecasting. The experimental results show that the computational efficiency of FOS-QR-RBL is improved by 35% and 23.68% compared with RBL and QR-RBL, respectively. The mean absolute error (MAE) of the coupling model of VMD and FOS-QR-RBL is reduced by 80.30% and 84.10% respectively, and the nash efficiency coefficient ( $\text{E}_{\mathrm {ns}}$ ) is increased by 15.51% and 28.16% respectively, compared with that of the coupling model of FOS-QR-RBL with ensemble empirical mode decomposition (EEMD) and adaptive noise complete ensemble empirical mode decomposition (CEEMDAN). The results of the optimal operation based on VMD-FOS-OR-RBL show that the model can effectively reduce the economic losses caused by regional flooding.