The development of the job satisfaction scale for hospital staff in Taiwan

The current study attempts to construct a valid and applicable job satisfaction scale for measuring the contentment level of hospital staff in Taiwan. The job description inventory (JDI) and Job Satisfaction Index (JSI) were adopted as the foundation of the job satisfaction measure for hospital staff in a selected hospital. To verify and validate the scale, data collected in 2012 and 2013, were analyzed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. Subsequently, Pearson correlations analysis was used to examine the strength and direction of the relationships between job satisfaction dimensions. Overall, the job satisfaction scale developed in this research illustrated valid and accurate measure for assessing hospital staffs' satisfaction. Both EFA and CFA results demonstrated that items consistently emerged six dimensions i.e. work environment, work achievement, compensation and benefits, education and training, promotion and evaluation, and management system. The findings also highlight that management support, work achievement, and promotion and evaluation are three critical factors that significantly contribute to high levels of job satisfaction for hospital staff

The Expressivity of Classical and Quantum Neural Networks on Entanglement Entropy

Analytically continuing the von Neumann entropy from R\'enyi entropies is a challenging task in quantum field theory. While the $n$-th R\'enyi entropy can be computed using the replica method in the path integral representation of quantum field theory, the analytic continuation can only be achieved for some simple systems on a case-by-case basis. In this work, we propose a general framework to tackle this problem using classical and quantum neural networks with supervised learning. We begin by studying several examples with known von Neumann entropy, where the input data is generated by representing $\text{Tr} \rho_A^n$ with a generating function. We adopt KerasTuner to determine the optimal network architecture and hyperparameters with limited data. In addition, we frame a similar problem in terms of quantum machine learning models, where the expressivity of the quantum models for the entanglement entropy as a partial Fourier series is established. Our proposed methods can accurately predict the von Neumann and R\'enyi entropies numerically, highlighting the potential of deep learning techniques for solving problems in quantum information theory.Comment: 57 pages, 25 figure

Konsep Demokrasi Politik Dalam Islam

Coexistence of chronic rhinosinusitis (CRS) with asthma appears to impair asthma control. Type-2 innate lymphoid cells (ILC2s) respond to the cytokines of thymic stromal lymphopoietin (TSLP), interleukin (IL)-25 and IL-33, thus contributing to airway diseases such as CRS and asthma. We investigate whether the augmented Th2-cytokines in CRS might be related to sinonasal tract ILC2s corresponding to enhanced IL-25, IL-33 and TSLP release in severe asthmatics, and be involved in asthma control. Twenty-eight asthmatics (12 non-severe and 16 severe) with CRS receiving nasal surgery were enrolled. The predicted FEV1 inversely associated with CRS severity of CT or endoscopy scores. Higher expression of Th2-driven cytokines (IL-4, IL-5, IL-9, and IL-13), TSLP, IL-25 and IL-33 in nasal tissues was observed in severe asthma. Severe asthmatics had higher ILC2 cell counts in their nasal tissues. ILC2 counts were positively correlated with Th2-cytokines. Nasal surgery significantly improved asthma control and lung function decline in severe asthma and CRS. The higher expression of IL-33/ILC2 axis-directed type 2 immune responses in nasal tissue of CRS brought the greater decline of lung function in severe asthma. ILC2-induced the upregulated activity of Th2-related cytokines in asthmatics with CRS may contribute to a recalcitrant status of asthma control

The differential interaction effect of mastery and performance climate on athletes’ emotional and physical exhaustion:The role of athletes’ gratitude.

Motivational climate (i.e., mastery and performance climate) has been found to shape athletes’ emotional and physical exhaustion, the core dimension of burnout. However, the interactional effect between mastery and performance climate on emotional and physical exhaustion has been rarely examined. In this study, we proposed that athletes’ gratitude will determine the interaction effect of mastery climate and performance climate on emotional and physical exhaustion. Specifically, we hypothesized that among athletes high in gratitude, mastery climate can mitigate the association between performance climate and emotional and physical exhaustion; among those low in gratitude, mastery climate can intensify the association between performance climate and emotional and physical exhaustion. Using a time-lagged survey, data from 293 athletes revealed a three-way interaction effect among mastery climate, performance climate, and gratitude. We did not find that mastery climate can mitigate the association between performance climate and emotional and physical exhaustion for those high in gratitude but found that among athletes low in gratitude, the positive association between performance climate and emotional and physical exhaustion was stronger in a higher mastery climate than in a lower mastery climate. Our study offers an interactionist perspective to help further understand the joint effect of mastery and performance climates on emotional and physical exhaustion by taking the role of individual differences into account.</p

Giant lipoma arising from deep lobe of the parotid gland

BACKGROUND: Lipomas are common benign soft tissue neoplasms but they are found very rarely in the deep lobe of parotid gland. Surgical intervention in these tumors is challenging because of the proximity of the facial nerve, and thus knowledge of the anatomy and meticulous surgical technique are essential. CASE PRESENTATION: A 71-year-old female presented with a large asymptomatic mass, which had occupied the left facial area for over the past fifteen years, and she requested surgical excision for a cosmetically better facial appearance. The computed tomography (CT) scan showed a well-defined giant lipoma arising from the left deep parotid gland. The lipoma was successfully enucleated after full exposure and mobilization of the overlying facial nerve branches. The surgical specimen measured 9 × 6 cm in size, and histopathology revealed fibrolipoma. The patient experienced an uneventful recovery, with a satisfying facial contour and intact facial nerve function. CONCLUSION: Giant lipomas involving the deep parotid lobe are extremely rare. The high-resolution CT scan provides an accurate and cost-effective preoperative investigative method. Surgical management of deep lobe lipoma should be performed by experienced surgeons due to the need for meticulous dissection of the facial nerve branches. Superficial parotidectomy before deep lobe lipoma removal may be unnecessary in selected cases because preservation of the superficial lobe may contribute to a better aesthetic and functional result

Multimodal Transformer Distillation for Audio-Visual Synchronization

Audio-visual synchronization aims to determine whether the mouth movements and speech in the video are synchronized. VocaLiST reaches state-of-the-art performance by incorporating multimodal Transformers to model audio-visual interact information. However, it requires high computing resources, making it impractical for real-world applications. This paper proposed an MTDVocaLiST model, which is trained by our proposed multimodal Transformer distillation (MTD) loss. MTD loss enables MTDVocaLiST model to deeply mimic the cross-attention distribution and value-relation in the Transformer of VocaLiST. Our proposed method is effective in two aspects: From the distillation method perspective, MTD loss outperforms other strong distillation baselines. From the distilled model's performance perspective: 1) MTDVocaLiST outperforms similar-size SOTA models, SyncNet, and PM models by 15.69% and 3.39%; 2) MTDVocaLiST reduces the model size of VocaLiST by 83.52%, yet still maintaining similar performance.Comment: Submitted to ICASSP 202

Comparison between simulation and experimental result of the scale down vertical concrete cask under the historical earthquake hit

In recent years, the final disposal facility for the long-term storage of high radioactive waste is an important issue and an urgent task for nuclear Industry. This study is focus on the understanding the procedure of dry storage system in a nuclear power plant. The dry storage system is known as transportable storage canister (TSC) packing by using spent fuel placed in vertical concrete cask (VCC) or VCC with add-on-shell (AOS) canister and then those conveyed VCC or AOS will be put on the concrete pad. A numerical simulation for evaluation the behavior of VCC and AOC under the earthquake hits is used the finite element model by LS-DYNA and the real seismic behavior is obtained using shaking table test. Test results indicate that the simulation by numerical model can slightly simulate the dynamic records by shaking table test. This is because that the behavior of shaking table test is the rocking motion but the numerical model is the sliding motion. The surface roughness between the cask and concrete pad is an important variable and it needs more numerical simulation to solve the interface and friction coefficient between the cask and concrete pad