Miracle-dz/UniFAR-FTUs huggingface dataset:
Deferred Compensation and Gift Exchange: An Experimental Investigation into Multi-Period Lab or Contracts

This paper examines the relationship between firms’ wage offers and workers’ supply of effort in a multi-period environment. If firms are able to commit to a schedule of wage payments, in equilibrium they will offer de ferred compensation: first-period productivity is positive and wages are zero, while last-period productivity is zero and wages are positive. Workers respond to deferred com pensation by supplying sufficient effort to avoid dismissal. In the absence of commit ment, in equilibrium firms pay zero wages and workers supply low effort. The experiment produces strong evidence of these predictions. In an experimental treatment where fir ms are able to commit to future wage payments, we frequently observe deferred compensati on and relatively high worker effort. In a treatment where commitment is not poss ible we observe no deferred compensation, much lower wages, and little worker e ffort. A third treatment where commitment is not possible, but firms are able to b uild a reputation, produces an intermediate result. Finally, we also find some evi d nce of gift exchange. In the treatment where firms were able to commit to wage offers, wor ker increased the effort levels in response to above equilibrium wage offers by a huma n, but not in response to similar offers by a computer. However, the estimated effect of gifts on worker behavior is of considerably smaller magnitude than the effect of d eferred compensation. In the absence of commitment, we observe a stronger role for gift exchange. Workers increase their effort levels in response to generous wage offer an d firms increase their offers in response to previous effort levels, even though nei ther the wage offer nor effort level has a theoretical effect on incentives.
Wind Turbine Cross-Sectional Stiffness Analysis Using Internally Layered Solid Elements

An efficient finite element modeling approach is presented for analyzing the general cross-sectional stiffness properties and stress distribution of thin- and thick-walled sections with isotropic and general anisotropic materials. The procedure is based on discretizing the walls of the section using a single layer of displacement-based elements whereby the element’s stiffness is obtained using Gaussian quadrature through each layer. The interlaminar stresses are recovered at points of interest via a three-dimensional equilibrium-based postprocessing scheme that uses the distribution of in-plane stress gradients derived in the local laminate coordinate system. The theory is illustrated by application to three composite sections of various shapes and material layups.
Metacognition and Reflection by Interdisciplinary Experts: Insights from Cognitive Science and Philosophy

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article.
Advances in Density-Functional Calculations for Materials Modeling

During the past two decades, density-functional (DF) theory has evolved from niche applications for simple solid-state materials to become a workhorse method for studying a wide range of phenomena in a variety of system classes throughout physics, chemistry, biology, and materials science. Here, we review the recent advances in DF calculations for materials modeling, giving a classification of modern DF-based methods when viewed from the materials modeling perspective. While progress has been very substantial, many challenges remain on the way to achieving consensus on a set of universally applicable DF-based methods for materials modeling. Hence, we focus on recent successes and remaining challenges in DF calculations for modeling hard solids, molecular and biological matter, low-dimensional materials, and hybrid organic-inorganic materials.
What works best in promoting climate citizenship? A randomised, systematic evaluation of nudge, think, boost and nudge+

Nudges have been increasingly deployed to deliver climate policies in the last decade. Recent evidence shows nudges are hard to scale–up. So can we use nudges more effectively, or should we rely on other tools of behaviour change? We argue that reflective strategies can enhance nudges by encouraging agency and ownership in citizens. We test this by systematically comparing nudges to reflective interventions like thinks, boosts, and nudge+ over orders of low-carbon meals using an online experiment with 3,074 participants in the United Kingdom. We find all behavioural interventions increase intentions for climate-friendly diets, but encouraging reflection prior to nudg-ing (“nudge+”) strengthens these treatment effects. There is no evidence of negative behavioural spillovers as measured by participants’ donations to pro-social charities. There is potential for reflective policies in promoting climate citizenship.
Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging

Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging 1 with minimal invasiveness 2 Andrea Antonini 1,2,8 , Andrea Sattin 1,3,4,8 , Monica Moroni 4,5,6 , Serena Bovetti 1 , Claudio Moretti 1,3 , 3 Francesca Succol 1 , Angelo Forli 1,4 , Dania Vecchia 1,4 , Vijayakumar P. Rajamanickam 1,2,7 , Andrea 4 Bertoncini 7 , Stefano Panzeri 4,5 , Carlo Liberale 2,7 , Tommaso Fellin 1,4,* 5 6
Why do established practices deinstitutionalize ?

Drawing on 63 in-depth interviews from three American multinationals, we investigate how individual actors negotiate the interplay of insider and outsider pressures on the deinstitutionalization of four employment practices in an institutionally complex setting. Existing institutional theory highlights different degrees of deinstitutionalization, from complete abandonment of practices to partial erosion, with an underlying presumption of organizations and actors striving for stability and stasis. However, our study finds that actor reconciliation of interacting insider and outsider pressures can result in three distinct phases of deinstitutionalization (complete, partial, and negotiated deinstitutionalization) which crucially coexist, suggesting perpetual instability and change. We conceptualize the individual-level enabling conditions for each of these different phases of deinstitutionalization, highlighting a range of actor responses as well as differences in how they exercise agency across each phase. Examining actor negotiation of the interplay of insider and outsider pressures improves our understanding of how individuals engage in differential institutional work when responding to practice deinstitutionalization.
The reliability and validity of the cone evasion walk test in patients with hip osteoarthritis

Background: Hip osteoarthritis (OA) can result in joint pain, stiffness, compromised balance, hindered mobility, and decreased functional independence. The Cone Evasion Walk Test (CEW) was designed for evaluating balance by evaluating the capacity to evade obstacles. Consequently, the study’s objective was to assess the validity and reliability of the CEW in hip OA patients. Methods: A total of 24 patients with hip OA were enrolled. Patients performed trials for the CEW and the timed up and go test (TUG). Between the trials, patients rested for an hour. The falls within the previous 12-month period were reported. Results: The analysis showed that the CEW has excellent reliability and high validity in hip OA. (p < 0.001). The relative (intraclass correlation [ICC] coefficient) and absolute (SEM and SRD95) reliability of the CEW were 0.96 (0.88–0.98 95% CI), 0.56, and 1.54, respectively. The Spearman correlation coefficient between the CEW and the TUG was 0.74 (p < 0.001) and between the CEW and the falls in the last 12 months was 0.51 (p > 0.05). Conclusions: The CEW is effective for evaluating the function, dynamic balance, and mobility in patients with hip OA and could be a more accurate measure of the dynamic balance activities in the community.
The Impact of Knowledge Management on Organizational Innovation

Every organization wants to create unique products and services, but not all organizations achieve this. Those that successfully offer exceptional products and services thanks to better execution processes can be called innovative organizations. However, the desire to be an innovative organization alone is not enough, organizations need to develop new processes in order to be successful and to properly manage the knowledge of the organization. This article analyzes the impact of knowledge management on organizational innovation, and presents the research conducted in Lithuania. Many researchers see a positive impact on organizational innovation, as knowledge management practices that prioritize the generation of new knowledge and learning at the organizational level are important for achieving positive results in innovation. Thus, knowledge generation has a positive correlation with organizational innovation creation, but some researchers, e.g. Donate and de Pablo (2015) consider this relationship to be indirect. The results of a study by Lee, Leon, Hew, and Ooi (2013) revealed that knowledge acquisition is not strongly related to an organization’s technology innovation process. Capon, Farley, Lehmann, and Hulbert (1992) argue that the acquisition of knowledge does not affect an organization’s ability to innovate. However, there are other studies, e.g. Darroc and McNaughton (2002) and Tan and Nasurdin (2011) argue that knowledge acquisition strongly influences the process of technological innovation. The aim of this article is to determine whether this impact is direct or indirect, not only to limit technological innovations, and to determine which trends are typical for Lithuanian organizations.
A Comparative Study of Retrorectus Mesh Placement Versus Properitoneal Mesh Placement in Open Repairs of Ventral Hernias

Background Ventral hernias affect millions of patients each year. Surgery is the main line of management and various techniques have been advocated; however, mesh repair has become the norm and different approaches have been described regarding the plane of mesh fixation, but none of them are standardized. Open repair is commonly practiced, and the two most commonly performed methods are retrorectus and properitoneal mesh placement. Objectives To compare the postoperative outcomes between the retrorectus plane and the properitoneal plane of fixation of mesh in open ventral hernia repair. Methods Between September 2018 and August 2020, 56 patients with midline ventral hernia admitted to Ramaiah Hospital, Bengaluru were chosen for this prospective comparative study. Group A had 28 patients who underwent open retrorectus mesh repair and 28 patients in Group B underwent open properitoneal mesh repair. The postoperative outcomes were studied in terms of operating time, postoperative complications, and early recurrence at the end of six months and 24 months post-surgery. Results The operative time for retrorectus mesh placement was significantly lower than properitoneal mesh placement. The latter had a higher complication rate overall with an incidence of 18%, with seroma being the most common complication; however, the difference in complication rates was not statistically significant. Skin necrosis was identical in both groups and 0% of cases in both groups had SSI or mesh infection. Three patients (10.71%) in the retrorectus group and two patients (7.10%) in the properitoneal group developed recurrence at 24 months follow-up. Conclusion Retrorectus mesh repair and properitoneal mesh repair in open ventral abdominal hernias have equally good postoperative outcomes.
Evaluation of the performance of photocatalytic systems for the treatment of indoor air in medical environments

La photocatalyse est une technologie d’oxydation avancee qui peut etre utilisee pour ameliorer la qualite de l'air dans les environnements interieurs et pourrait etre mise en œuvre dans les milieux medicaux. Dans les hopitaux, les salles d'operation sont tres exigeantes en matiere de qualite de l'air interieur et necessitent des systemes qui minimisent les concentrations des polluants generes par les differentes activites. Dans ce travail, le devenir de deux polluants specifiques des blocs operatoires, l’acrylonitrile (produit chimique trouve dans la fumee chirurgicale) et l'isoflurane (gaz anesthesique) lorsqu'ils passent dans un dispositif de traitement d’air photocatalytique est etudie. Tout d'abord, une evaluation parametrique de la degradation de l'isoflurane et de l'acrylonitrile en etudiant l'influence de la vitesse de l'air, de l'intensite lumineuse, de la geometrie du media photocatalytique, de la concentration initiale en polluants, de la presence de co-polluants chimiques, de la presence de particules et l’humidite relative sur leur efficacite de degradation est realisee. En second lieu, l’innocuite de l’utilisation de ce procede pour la degradation de l’isoflurane et de l’acrylonitrile par l’identification des eventuels intermediaires formes au cours de leur degradation est etudiee. Les experiences sont menees dans un reacteur dynamique en boucle fermee concu pour etudier les polluants a faibles concentrations. Enfin, pour mieux comprendre comment le changement de geometrie du media photocatalytique influence l'efficacite de la degradation, des simulations avec ANSYS14.5 sont effectuees et discutees au regard des resultats experimentaux.
Probabilistic Risk Assessment and Its Application in Complex Integrated Task Risk Assessment

In view of the characteristics of complex integration tasks such as launch tasks, such as complex processes, many systems involved, and frequent human-computer interaction, the probabilistic risk evaluation (PRA) method is introduced to realize the quantitative risk assessment of complex integration tasks. In this paper, the development and application status of PRA method are analyzed, and key technologies such as comprehensive modeling analysis of human factors reliability based on human error rate prediction (THERP) and human cognitive reliability (HCR) models, importance ranking, and uncertainty analysis based on Monte Carlo simulation are studied. Taking the propellant leakage in the launch tasks as an example, the PRA method is applied to quantitatively evaluate the risk of this scenario, and the results show that the PRA method has good applicability in the risk assessment of complex integration tasks, and can provide decision-making support for institutional risk management and control of complex integration tasks.
Multi-objective optimization of simultaneous buffer and service rate allocation in manufacturing systems based on a data-driven hybrid approach

The challenge presented by simultaneous buffer and service rate allocation in manufacturing systems represents a difficult non-deterministic polynomial problem. Previous studies solved this problem by iteratively utilizing a generative method and an evaluative method. However, it typically takes a long computation time for the evaluative method to achieve high evaluation accuracy, while the satisfactory solution quality realized by the generative method requires a certain number of iterations. In this study, a data-driven hybrid approach is developed by integrating a tabu search–non-dominated sorting genetic algorithm II with a whale optimization algorithm–gradient boosting regression tree to maximize the throughput and minimize the average buffer level of a manufacturing system subject to a total buffer capacity and total service rate. The former algorithm effectively searches for candidate simultaneous allocation solutions by integrating global and local search strategies. The prediction models built by the latter algorithm efficiently evaluate the candidate solutions. Numerical examples demonstrate the efficacy of the proposed approach. The proposed approach improves the solution efficiency of simultaneous allocation, contributing to dynamic production resource reconfiguration of manufacturing systems.
Deep Multi-task Convolutional Neural Networks for Efficient Classification of Face Attributes

Facial feature recognition is an important subject in computer vision with numerous applications. The human face plays a significant role in social interaction and personology. Valuable information such as identity, age, gender, and emotions can be revealed via facial features. The purpose of this paper is to present a technique for detecting age, smile, and gender from facial images. A multi-task deep learning (MT-DL) framework was proposed that can simultaneously estimate three important features of the human face with remarkable accuracy. Additionally, the proposed approach aims to reduce the number of trainable network parameters while leveraging the combination of features from different layers to increase the overall accuracy. The conducted tests demonstrate that the proposed method outperforms recent advanced techniques in all three accuracy criteria. Moreover, it was demonstrated that multi-task learning (MTL) is capable of improving the accuracy by 1.55% in the smile task, 2.04% in the gender task, and 3.52% in the age task even with less available data, by utilizing tasks with more available data. Furthermore, the trainable parameters of the network in the MTL mode for estimating three tasks simultaneously increase only by about 40% compared to the single-task mode. The proposed method was evaluated on the IMDB-WIKI
Pulmonary lesion classification using convolutional neural network for endobronchial ultrasonogram

This dissertation aims to develop a method to help classify pulmonary lesions from endobronchial ultrasonography images by proposing new features that are extracted from an EBUS image based on medical knowledge and a pulmonary lesion classification framework. The proposed features, namely the adaptive weighted-sum of the upper triangular gray-level co-occurrence matrix and the adaptive weighted-sum of the lower triangular gray-level co-occurrence matrix are used to determine heterogeneity, which is one of the most important characteristics of malignancy. The proposed features together with other standard features are used as input data for the proposed classification framework that uses the weighted ensemble classification based on the efficacy of the other three classification models. The first model uses random forest to classify a lesion based on the combination of radiomics features, the proposed features, and the patient's data. The second model uses EBUS images as input data to the tuned DenseNet 169 to classify a lesion. The third model uses multi-patch EBUS images as input data to the convolutional neural network to classify a lesion. The classification by the weighting ensemble function can improve the performance of the framework by combining the distinctive characteristics of each model. The data consists of 200 EBUS images from 200 patients: 124 malignant and 76 benign. From the experiment, it was found that the proposed framework yields 95% accuracy, 100% sensitivity, and 86.67% specificity.
A Spectroscopic Analysis of the Hyades Cool Giants

High-resolution spectroscopic observations of the four cool giants in the Hyades cluster, taken at the Elginfield Observatory, are analyzed. The velocity of γ Tau between 2002 and 2009 is constant to a few m s−1; small variations, compatible with the planetary orbit, are seen for ε Tau. The primary-to-secondary mass ratio of θ1 Tau is found to be 2.33 ± 0.07. Absolute radial velocities are determined for three of the giants from third-signature plots that correct for granulation blueshifts: 38,615 ± 50, 38,760 ± 100, and 38,570 ± 50 m s−1 for γ Tau, δ Tau, and ε Tau respectively. Line–depth ratios show that γ Tau is 33 ± 5 K, δ Tau is 53 ± 10 K, and θ1 Tau is 30 ± 6 K hotter than ε Tau. Although the λ6253 line bisectors are similar for all four giants, there are significant differences in the line profiles. Fourier analysis of the profile shapes yields projected rotation rates of 2.1, 2.4, 2.8, and 2.8 km s−1 for γ Tau, δ Tau, ε Tau, and θ1 Tau respectively, with an uncertainty of ±0.3 km s−1. The corresponding radial–tangential macroturbulence dispersions are 5.07, 5.66, 5.55, and 4.65 km s−1, with a uncertainty of ±0.10 km s−1. Scale factors for third-signature plots are close to unity, ±10%, implying that the granulation velocity gradient through their photospheres is similar to the Sun's. Bisector mapping returns flux differences between granules and lanes, with average granule-to-lane temperature differences ∼125 K.
Impact of tacrolimus intra-patient variability in adverse outcomes after organ transplantation

Tacrolimus (Tac) is currently the most common calcineurin-inhibitor employed in solid organ transplantation. High intra-patient variability (IPV) of Tac (Tac IPV) has been associated with an increased risk of immune-mediated rejection and poor outcomes after kidney transplantation. Few data are available concerning the impact of high Tac IPV in non-kidney transplants. However, even in kidney transplantation, there is still a controversy whether high Tac IPV is indeed detrimental in respect to graft and/or patient survival. This may be due to different methods employed to evaluate IPV and distinct time frames adopted to assess graft and patient survival in those reports published up to now in the literature. Little is also known about the influence of high Tac IPV in the development of other untoward adverse events, update of the current knowledge regarding the impact of Tac IPV in different outcomes following kidney, liver, heart, lung, and pancreas tran splantation to better evaluate its use in clinical practice.