Miracle-dz/UniFAR-FTUs huggingface dataset:
The Importance of Heat Shock-Related 70-kDa Protein 2 Expression in Laryngeal Squamous Cell Carcinomas

Objective: Laryngeal squamous cell carcinoma has a high mortality rate, and approximately 60% of patients are in advanced stage at the time of diagnosis. Thus, determining the prognostic parameters of this cancer and markers related to these parameters are very important. There are studies showing that heat shock-related 70-kDa protein 2, which is used as a biomarker, may be associated with prognostic parameter in some cancers. However, no study has investigated the prognostic role of heat shock-related 70-kDa protein 2 in laryngeal squamous cell carcinoma in the literature. Thus, in our study, the aim was to examine the relationship between heat shock-related 70-kDa protein 2 expression and clinicopathological prognostic parameters in laryngeal squamous cell carcinoma. Materials and Methods: Our study included 104 patients diagnosed with laryngeal squamous cell carcinoma between January 2005 and January 2016. The correlation between heat shock-related 70-kDa protein 2 expression and prognostic parameters was investigated by using the immunohistochemical method with heat shock-related 70-kDa protein 2 antibody. Results: In all the cases, heat shock-related 70-kDa protein 2 positivity was determined in tumoral areas (100%). The overexpression rate of heat shock-related 70-kDa protein 2 in adjacent non-cancerous tissues with dysplasia was 48/104 (42%) (P < .0001). A significant relationship was found between heat shock-related 70-kDa protein 2 expression and important prognostic parameters such as macroscopic tumor size, lymphovascular invasion, primary tumor, lymph node metastasis, distant organ metastasis, tumor, node, metastasis (TNM) stage stage, recurrence, and survival rates (P < .05). Conclusion: Our study supports the presence of an association between high heat shock-related 70-kDa protein 2 expression levels and prognostic parameters in laryngeal squamous cell carcinoma. We consider that heat shock-related 70-kDa protein 2 can be used as a prognostic marker in laryngeal squamous cell carcinoma. In addition, it may be important in early diagnosis due to its increased expression even under laryngeal squamous cell carcinoma precursor conditions.
No . 980 THE IMPACT OF INTERGENERATIONAL TRANSFERS ON HOUSEHOLD WEALTH INEQUALITY IN JAPAN AND THE UNITED STATES

To help shed light on the implications of intergenerational transfers for wealth inequality, this paper examines whether or not individuals who receive intergenerational transfers from their parents are more likely to leave bequests to their children than those who do not using data for Japan and the United States. The estimation results show that the receipt of intergenerational transfers from parents and/or parents-in-law increases the likelihood of individuals’ leaving bequests to their own children in both Japan and the United States, which in turn is likely to contribute to the persistence or widening of wealth disparities. However, such a tendency is found to be stronger among less better-off households in both countries, and this may help alleviate the disequalizing effect of intergenerational transfers on the distribution of wealth, at least to some extent. JEL codes: D10, D31, D64, E21, I24
Spiking Neural Networks: A Survey

The field of Deep Learning (DL) has seen a remarkable series of developments with increasingly accurate and robust algorithms. However, the increase in performance has been accompanied by an increase in the parameters, complexity, and training and inference time of the models, which means that we are rapidly reaching a point where DL may no longer be feasible. On the other hand, some specific applications need to be carefully considered when developing DL models due to hardware limitations or power requirements. In this context, there is a growing interest in efficient DL algorithms, with Spiking Neural Networks (SNNs) being one of the most promising paradigms. Due to the inherent asynchrony and sparseness of spike trains, these types of networks have the potential to reduce power consumption while maintaining relatively good performance. This is attractive for efficient DL and if successful, could replace traditional Artificial Neural Networks (ANNs) in many applications. However, despite significant progress, the performance of SNNs on benchmark datasets is often lower than that of traditional ANNs. Moreover, due to the non-differentiable nature of their activation functions, it is difficult to train SNNs with direct backpropagation, so appropriate training strategies must be found. Nevertheless, significant efforts have been made to develop competitive models. This survey covers the main ideas behind SNNs and reviews recent trends in learning rules and network architectures, with a particular focus on biologically inspired strategies. It also provides some practical considerations of state-of-the-art SNNs and discusses relevant research opportunities.
Variational Image Regularization with Euler's Elastica Using a Discrete Gradient Scheme

This paper concerns an optimization algorithm for unconstrained non-convex problems which is particularly effective for objective functions with sparse connections between unknowns. The algorithm is based on applying a dissipation preserving numerical integrator to the gradient flow of an objective function, which guarantees energy decrease regardless of step size. The specific class of integrators used is called discrete gradient schemes. We have applied the discrete gradient schemes the non-convex problem of Euler's elastica regularization in variational image analysis. We will introduce the algorithm and prove a $\mathcal{O}(1/\sqrt{k})$ worst-case convergence rate estimate for non-convex problems with Lipschitz continuous gradients, before showing the application of the algorithm to the Euler's elastica problem. The algorithm is presented in serial and parallel versions. Numerical results show its use in imaging problems, its convergence rate, and compares the method to the iPiano algorithm.
Causal compatibility inequalities admitting quantum violations in the triangle structure

It has long been recognized that certain quantum correlations are incompatible with particular assumption about classical causal structure. Given a causal structure of unknown classicality, the presence of such correlations certifies the nonclassical nature of the causal structure in a device-independent fashion. In structures where all parties share a common resource, these nonclassical correlations are also known as nonlocal correlations. Any constraint satisfied by all correlations which are classically compatible with a given causal structure defines a causal compatibility criterion. Such criteria were recently derived for the Triangle structure (E. Wolfe et al., arXiv:1609.00672) in the form of polynomial inequalities, begging the question of whether any of those inequalities admit violation by quantum correlations. Numerical investigation suggests that they do not, and we further conjecture that the set of correlations admitted by the classical Triangle structure is equivalent to the set of correlations admitted by its quantum generalization whenever the three observable variables are binary. Our main contribution in this work, however, is the derivation of new causal compatibility inequalities for the Triangle structure which do admit quantum violation. This provides a robust-to-noise witness of quantum correlations in the Triangle structure. We conclude by considering the possibility of quantum resources potentially qualitatively different from those known previously.
Optimal Capital Regulation

We study constrained-efficient bank capital regulation in a model with market-imposed equity requirements. Banks hold equity buffers to insure against sudden loss of funding access. However, bank equity is privately costly in the model such that banks choose only partial self-insurance. Equity requirements are occasionally binding as a result. Constrained-efficient regulation requires banks to build up additional equity buffers and compensates them for the cost of equity with a permanent increase in lending margins. When buffers are depleted regulation relaxes market-imposed equity requirements by raising bank future prospects via temporarily elevated lending margins.
Preparation and crystal structure of azido bridged one-dimensional polymeric cadmium ( II ) complex , [ Cd ( N 3 ) 2 ( 2-ethylimidazole ) 2 ]

The title complex, [Cd(N3)2(2-ethylimidazole)2], I, has been prepared and characterized by X-ray single crystallography. The complex I crystallizes in the monoclinic system, Cc space group with a = 16.200(3), b = 12.926(3), c = 7.007(1) Å, β = 102.29(3), V = 1433.7(5) Å, Z = 4, R1 = 0.0239 and ωR2 = 0.0604 for 1874 independent reflections. Cd(II) atom has a slightly distorted octahedral coordination geometry, with four endon (μ-1,1) bridging azido ligands and two 2-ethylimidazole ligands bonding through nitrogen atom. The central cadmium(II) atoms are run in parallel to the c-axis and are doubly bridged with neighboring cadmium(II) atoms by the end-on (μ-1,1) bridging azido ligands. Thus, this complex has a one-dimensional zigzag chain structure in which the 2-ethylimidazole is in the cis conformation.
Traditional Psychological Tests Usage in Forensic Assessment

Several survey studies have been conducted on traditional psychological tests usage in different forensic settings, and they have indicated consistently that psychological tests play an important role in most forensic evaluations. However, there are both advantages and disadvantages of this utilization. The forensic evaluator should take into account a set of standards for the selection, administration, and interpretation of psychological tests in forensic assessment.
A Perspective on Industry Classification and Market Reaction to Corporate News: Evidence from India

Abstract In this paper, we provide a cross-industry perspective on the market reaction to different corporate news in the context of Indian stock market. We have studied the price and volume movements associated with eight broadly defined news categories namely Analyst Calls, Earnings, Earnings Forecasts, Finance, Legal and Regulatory, Management, Operations and Restructuring. We have employed the standard event study methodology on a sample of stocks listed on the National Stock Exchange of India for the purpose of our study. We observe that the market reaction to firm specific corporate news varies according to the type of news across different industry groups. We also observe that the sentiment of the news is a critical factor which influences the market reaction to such news flow across industry groups. We also provide a cross-industry perspective on the relative importance of different corporate news categories after taking into account the sentiment of the news in the context of Indian stock market.
Investment-specific technological change, taxation and inequality in the U.S.

Since 1980 the U.S. economy has experienced a large increase in income inequality. To explain this phenomenon we develop a life-cycle, overlapping generations model with uninsurable labor market risk, a detailed tax system and investment-specific technological change (ISTC). We calibrate our model to match key characteristics of the U.S. economy and study how ISTC, shifts in taxation, government debt and employment have contributed to the rise in income inequality. We find that these structural changes can account for close to one third of the observed increase in the post-tax income Gini. The main mechanisms in play are the rise in the wage premium of non-routine workers, resulting from capital-non-routine complementarity, as well as a reduction of the progressivity of the labor income tax schedule, which increases post-tax inequality. We show that ISTC alone accounts for roughly 15% of the change observed in post-tax income Gini, while the reduction in progressivity accounts for 16%.
High-Dose Vitamin C for Cancer Therapy

In recent years, the idea that Vitamin C (Vit-C) could be utilized as a form of anti-cancer therapy has generated many contradictory arguments. Recent insights into the physiological characteristics of Vit-C, its pharmacokinetics, and results from preclinical reports, however, suggest that high-dose Vit-C could be effectively utilized in the management of various tumor types. Studies have shown that the pharmacological action of Vit-C can attack various processes that cancerous cells use for their growth and development. Here, we discuss the anti-cancer functions of Vit-C, but also the potential for the use of Vit-C as an epigenetic regulator and immunotherapy enhancer. We also provide a short overview of the current state of systems for scavenging reactive oxygen species (ROS), especially in the context of their influencing high-dose Vit-C toxicity for the inhibition of cancer growth. Even though the mechanisms of Vit-C action are promising, they need to be supported with robust randomized and controlled clinical trials. Moreover, upcoming studies should focus on how to define the most suitable cancer patient populations for high-dose Vit-C treatments and develop effective strategies that combine Vit-C with various concurrent cancer treatment regimens.
Asymptotic Analysis for the Variance-Based Global Sensitivity Indices

We discuss the estimation of the uncertainty and sensitivity parameters for a model response under the assumption that the input variables are normally distributed and block-wise correlated with the covariance matrix, which is small in some norm. These conditions may arise when considering the impact of the group-wise neutron cross-sections' uncertainties on the uncertainty of some reactor parameters such as the neutron multiplication factor. The variance-based global sensitivity analysis, considered in our work, involves the calculation of multidimensional integrals. When the input uncertainties are small, the values of these integrals can be estimated using an asymptotic analysis method called the Laplace approximation. The asymptotic formulas for the output variance and for the global sensitivity indices have been obtained using the Laplace approximation method. It is demonstrated that the asymptotic formula for uncertainty propagation matches the uncertainty propagation formula being used in the local sensitivity analysis. The applicability of the obtained asymptotic approximations was successfully demonstrated on a test problem with realistic cross-section and covariance matrix values.
Decadal variability of twentieth‐century El Niño and La Niña occurrence from observations and IPCC AR4 coupled models

This study investigates the decadal variability of El Niño and La Niña occurrence in observations and examines that variability in a set of 20th Century climate simulations (20C3M) of coupled general circulation models (CGCMs) in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Wavelet analysis reveals that the observed frequency of El Niño events displays significant decadal variability with a period of about 12 years during 1920–1940, whereas the frequency of La Niña events shows significant decadal variations with a spectral peak at 16 years throughout the 20th century. Moreover, the frequencies of El Niño and La Niña events are influenced by different factors that are responsible for planetary teleconnections. The frequency of El Niño events is related the Atlantic Multidecadal Oscillation (AMO), while that of the La Niña events is associated with the Pacific Decadal Oscillation (PDO). Among the 15 IPCC AR4 CGCMs surveyed, csiro and miroc_medres CGCMs can reproduce the decadal variability of ENSO activity, and simulate partly its relationship with the Pacific and north Atlantic SSTa. These results will help us to further understand the important roles of the North Atlantic and North Pacific in ENSO variations.
Examining the mediating and moderating role of psychological capital in the job demands-resources model

vii Chapter 1Introduction . 1 Chapter 2Literature Review . 3 The JD-R Model . 3 Psychological Capital . 6 Rationale for using PsyCap as a Personal Resource . 11 The Role of PsyCap in the JD-R Model . 14 Conceptualising Work Related Outcomes . 17 Theoretical Research Models . 21 Chapter 2Method . 24 Research Design . 24 Measures . 24 Sample . 26 Procedure . 27 Data Analysis . 28 Chapter 3Results . 29 Measurement Validity and Reliability . 29 An Expansion of the Health Impairment Process: Model 1 . 37 An Expansion of the Motivation Process: Model 2 . 39 Chapter 4Discussion . 42 PsyCap in the South African Context . 42 PsyCap as a Moderator within the Health Impairment Process . 43 PsyCap as a Mediator within the Motivation Process . 45 Theoretical Contributions . 47 Practical Implications . 48 Limitations and Recommendations for Future Research . 49
Does sound lending infrastructure foster better financial reporting quality of SMEs?

Using an unbalanced panel dataset that contains financial information of 46,340 small and medium-sized enterprises (SMEs) across 11 European countries over 2007–2015, this study examines the impacts of soundness of institutional factors on SME financial reporting quality as (inversely) reflected by the degree of earnings management. We consider a comprehensive framework of country-level lending infrastructure proxies which includes information, legal, social and regulatory environments and show that SME financial reporting quality is better in economies where there is greater availability, depth and quality of credit information sharing between lenders and credit reporting service providers, as empirically shown by a lower level of earnings management. We also show that a well-established legal system, i.e. better judicial and bankruptcy protection systems, is effective in restraining SME earnings management incentives and, earnings management is less prevalent in economies that are subject to a higher stock of social capital which increases SME borrowing capacity. Furthermore, we find that the stringent tax and regulatory systems can foster better financial reporting quality, as earnings management may be less effective. Overall, our robust findings suggest that the soundness of country-level lending infrastructure plays a vital role in improving SME financial reporting quality.
Identifying leaks in the STEM recruitment pipeline among sexual and gender minority US secondary students

Purpose Research establishes the critical need to address the underrepresentation of women and racial/ethnic minorities in science, technology, engineering, and mathematics (STEM). While emergent research addresses similar challenges for sexual and gender minorities (SGM), this research remains scant and focuses on adult experiences. This analysis examines subgroup differences and the impact of bullying on STEM engagement outcomes among a national sample of SGM secondary students in the U.S. Method This report provides descriptive and multivariable regression analysis of national survey data (n = 539) on the experiences of pre-college students who identify as SGM, including the effects of within-school anti-SGM bullying on STEM identity, perceptions of STEM climate, and STEM intentions. Results Roughly 50% of the sample intended to enter a STEM field (compared to 25% in previous general samples). Bullying in school was negatively associated with STEM identity and perceptions of STEM climate. Sense of belonging is positively associated with perceptions of STEM climate and STEM intentions. Being non-binary and being a transgender man were associated with decreased sense of belonging and negative perception of STEM climate. Conclusion This report is the first to identify factors influencing STEM engagement among SGM secondary students and suggests that issues of STEM engagement are already present in adolescence. Moreover, the findings also establish the relationship between anti-SGM bullying and STEM outcomes highlighting the importance of this marginalization experience. Future research should further examine sub-group differences and the persistence of these effects. These findings highlight the need for research and intervention addressing STEM outcomes in SGM populations. Clinical trial registration https://clinicaltrials.gov/ct2/show/NCT03511131.
Hepatocyte Growth Factor / c-Met Signaling Is Required for b-Cell Regeneration

Hepatocyte growth factor (HGF) is a mitogen required for b-cell replication during pregnancy. To determine whether HGF/c-Met signaling is required for b-cell regeneration, we characterized mice with pancreatic deletion of the HGF receptor, c-Met (PancMet KO mice), in two models of reduced b-cell mass and regeneration: multiple low-dose streptozotocin (MLDS) and partial pancreatectomy (Ppx). We also analyzed whether HGF administration could accelerate b-cell regeneration in wild-type (WT) mice after Ppx. Mouse islets obtained 7 days post-Ppx displayed significantly increased c-Met, suggesting a potential role for HGF/c-Met in b-cell proliferation in situations of reduced b-cell mass. Indeed, adult PancMet KO mice displayed markedly reduced b-cell replication compared with WT mice 7 days post-Ppx. Similarly, b-cell proliferation was decreased in PancMet KO mice in the MLDS mouse model. The decrease in b-cell proliferation post-Ppx correlated with a striking decrease in D-cyclin levels. Importantly, PancMet KO mice showed significantly diminished b-cell mass, decreased glucose tolerance, and impaired insulin secretion compared with WT mice 28 days post-Ppx. Conversely, HGF administration in WT Ppx mice further accelerated b-cell regeneration. These results indicate that HGF/c-Met signaling is critical for b-cell proliferation in situations of diminished b-cell mass and suggest that activation of this pathway can enhance b-cell regeneration.