Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Hedging Strategies Under Model Misspecification and Trading Restrictions

The following paper focuses on the incompleteness arising from model misspecification combined with trading restrictions. While asset price dynamics are assumed to be continuous time processes, the hedging of contingent claims occurs in discrete time. The trading strategies under consideration are understood to be self-financing with respect to an assumed model which may deviate from the "true" model, thus associating duplication costs with respect to a contingent claim to be hedged. Based on the robustness result of Gaussian hedging strategies, saying that a superhedge is achieved for convex payoff functions if the "true" asset price volatility is dominated by the assumed one, the error of time discretising these strategies is analysed. It turns out that the time discretisation of Gaussian hedges gives rise to a duplication bias caused by asset price trends, which can be avoided by discretising the hedging model instead of discretising the hedging strategies. Additionally, it is shown that on the one hand binomial strategies incorporate similar robustness features as Gaussian hedges. On the other hand, the distribution of the cost process associated with the binomial hedge coincides with the distribution of the cost process associated with the Gaussian hedge in the limit. Together, the last results yield a strong argument in favour of discretising the hedge model instead of time discretising the strategies.
The Causality Between Economic Growth and Immigration in Germany and Switzerland

This paper analyses the relationship between immigration and the economic growth in Germany and Switzerland during the period 1970-2005 by using a cointegration approach. Both countries have gone through a similar learning process. First they encouraged low-skilled and temporary workers. More recently, they have attracted high-skilled people and restricted the recruitment of low-skilled immigrants. Our empirical analysis reveals important differences between Germany and Switzerland. The results may be useful for other countries that attract immigrants to compensate for shortages in the labour market and in response to the ageing of the population.
Double Forward Propagation for Memorized Batch Normalization

Batch Normalization (BN) has been a standard component in designing deep neural networks (DNNs). Although the standard BN can significantly accelerate the training of DNNs and improve the generalization performance, it has several underlying limitations which may hamper the performance in both training and inference. In the training stage, BN relies on estimating the mean and variance of data using a single mini-batch. Consequently, BN can be unstable when the batch size is very small or the data is poorly sampled. In the inference stage, BN often uses the so called moving mean and moving variance instead of batch statistics, i.e., the training and inference rules in BN are not consistent. Regarding these issues, we propose a memorized batch normalization (MBN), which considers multiple recent batches to obtain more accurate and robust statistics. Note that after the SGD update for each batch, the model parameters will change, and the features will change accordingly, leading to the Distribution Shift before and after the update for the considered batch. To alleviate this issue, we present a simple Double-Forward scheme in MBN which can further improve the performance. Compared to related methods, the proposed MBN exhibits consistent behaviors in both training and inference. Empirical results show that the MBN based models trained with the Double-Forward scheme greatly reduce the sensitivity of data and significantly improve the generalization performance.
A smart ACO‐inspired named data networking forwarding scheme with clustering analysis

Different from the traditional IP network, named data networking (NDN) performs the stateful and adaptive forwarding, which faces some severe challenges such as efficient and self‐organized content retrieval. The current proposals are very difficult to address such challenges; therefore, this paper proposes a novel and smart NDN forwarding scheme by introducing both ant colony optimization and clustering analysis. At first, the discrete content concentration model is established with network load to address interest forwarding; in particular, we investigate the situation where the content retrieval is failed. Then, dot product method is used to compute similarity relation between 2 routers, which is considered as the clustering reference attribute. In addition, density‐based spatial clustering, ie, a clustering method, is exploited to detect core nodes that are used to cache the contents during the process of data forwarding. Finally, the proposed smart forwarding scheme is simulated over Mini‐NDN, and the simulation results show that it has better performance than the existent 3 schemes in terms of content retrieval rate, hop count, load balance degree, execution time, and throughput.
The Inhibitory Effects of Interleukin‐6 on Synaptic Plasticity in the Rat Hippocampus Are Associated with an Inhibition of Mitogen‐Activated Protein Kinase ERK

Several cytokines have short‐term effects on synaptic transmission and plasticity that are thought to be mediated by the activation of intracellular protein kinases. We have studied the effects of interleukin‐6 (IL‐6) on the expression of paired pulse facilitation (PPF), posttetanic potentiation (PTP), and long‐term potentiation (LTP) in the CA1 region of the hippocampus as well as on the activation of the signal transducer and activator of transcription‐3 (STAT3), the mitogen‐activated protein kinase ERK (MAPK/ERK), and the stress‐activated protein kinase/c‐Jun NH2‐terminal kinase (SAPK/JNK). IL‐6 induced a marked and dose‐dependent decrease in the expression of PTP and LTP that could be counteracted by the simultaneous treatment with the tyrosine kinase inhibitor lavendustin A (LavA) but did not significantly affect PPF. The IL‐6‐induced inhibition of PTP and LTP was accompanied by a simulation of STAT3 tyrosine phosphorylation and an inhibition of MAPK/ERK dual phosphorylation, in the absence of changes in the state of activation of SAPK/JNK. Both effects of IL‐6 on STAT3 and MAPK/ERK activation were effectively counteracted by LavA treatment. The results indicate the tyrosine kinases and MAPK/ERK are involved in hippocampal synaptic plasticity and may represent preferential intracellular targets for the actions of IL‐6 in the adult nervous system.
CHANGES IN RESTING SALIVARY TESTOSTERONE, CORTISOL AND INTERLEUKIN-6 AS BIOMARKERS OF OVERTRAINING.

Background Overtraining (OVT) is a concern for many athletes. Immunological (increased interleukin-6 [IL-6]) and hormonal (increased cortisol [C], decreased free testosterone [fT]) biomarkers have been analyzed during training to detect OVT development. Methods This study determined if resting levels of salivary IL-6, T, and C change during a pre-season resistance training (RT) program in 20 Division I American football players (mean ± SD: age = 19.1 ± 1.1 years; height = 185.4 ± 6.7 cm; mass = 102.0 ± 22.2 kg; body fat = 14.7 ± 7.6%). 1RM squat, bench press and Olympic-style clean, IL-6, C and T were assessed at baseline (WK1), week 4 (WK4), week 6 (WK6) along with psychological status (PS) to determine affective state. Results 1RM (bench press: 121.6 ± 36.3 kg vs. 127.4 ± 35.9 kg, squat: 187.2 ± 30.2 kg, 190.9 ± 28.1 kg, clean: 116.8 ± 14.6 kg, vs. 119.2 ± 14.5 kg), IL-6 (1.42 ± 1.77 pg/mL vs. 5.60 ± 12.57 pg/mL) and C (2.57 ± 2.46 nmol/L vs. 5.33 ± 4.94) increased signihcantly from WK1 to WK6 (p < .05), fT decreased signihcantly (417.44 ± 83.63 pmol/Lvs. 341.10 ± 87.79 pmol/L) from WK1 to WK6 (p < .05). PS was minimally affected during the study. Signihcant biomarker changes were detected, but no OVT was induced (i.e. performance improved). Conclusion Therefore, directional changes in these biomarkers may not be sufficiently reflective of OVT in RT programs.
Rapid acting fentanyl formulations in breakthrough pain in cancer. Drug selection by means of the System of Objectified Judgement Analysis

Drug selection of rapid acting fentanyl formulations in the treatment of breakthrough pain in patients with cancer is performed by the System of Objectified Judgement Analysis method. All seven available formulations were included in the analysis. The following selection criteria were used: number of available strengths, variability in the rate of absorption, interactions, clinical efficacy, side effects, ease of administration and documentation. No direct double-blind comparative studies between two or more formulations were identified and the clinical documentation of all formulations is limited. The most distinguishing criterion was ease of use. This led to slightly higher scores for Abstral, Instanyl and PecFent than for the other formulations. The pros and cons of each formulation should be discussed with the patient, and the most suitable formulation selected for each individual patient.
Maturity of judgement in decision making for predictive testing for nontreatable adult‐onset neurogenetic conditions: a case against predictive testing of minors

International guidelines developed to minimize harm from predictive testing for adult‐onset, nontreatable neurogenetic conditions such as Huntington disease (HD) state that such testing should not be available to minors. Some authors have proposed that predictive testing for these conditions should be available to minors at the request of parents and/or of younger adolescents themselves. They highlight the lack of empirical evidence that predictive testing of minors causes harm and suggest that refusing to test minors may be detrimental. The current study focuses on the context of predictive test requests by adolescents younger than 18 years, and presents arguments and evidence that the risk of potential harm from testing such young people is sufficiently high to justify continued caution in this area. A study based on a model of psychosocial maturity found that the 3 factors involved in maturity of judgement in decision making – responsibility, temperance and perspective – continue to develop into late adolescence. There is also evidence that the prefrontal areas of the brain, which are involved in executive functions such as decision making, are not fully developed until early adulthood. Combined with evidence of adverse long‐term effects, from research with adults who have undergone predictive testing, these findings constitute grounds for retaining a minimum age of 18 years for predictive testing for nontreatable conditions. Further research on assessment of maturity will assist with reaching a consensus on this issue.
Educational differences in psychological distress? Results from a population-based sample of men and women in Sweden in 2012

Background Mental health problems are more frequent in socially disadvantaged groups, but the results vary between different studies, different populations and different measures of mental health. This paper investigated the association between educational level, economic difficulties and psychological distress in men and women in Sweden. Methods The study population included 24 510 respondents aged 25–74 years who responded to a survey questionnaire in Mid-Sweden in 2012 (response rate 53%). Psychological distress was measured with the 12-item version of the General Health Questionnaire, and multivariate logistic regression models were used in statistical analyses, adjusting for age, employment status and social support. Results The prevalence of psychological distress was higher in women (16.4%) than in men (11.3%; p<0.001). Persons with low and medium educational level had a lower risk of psychological distress than persons with high educational level after adjustment for confounders. Economic difficulties had a strong association with psychological distress (OR 2.80 (95% CI 2.39 to 3.27) and OR 2.40 (95% CI 2.12 to 3.71) in men and women, respectively) after adjustment for confounders. Conclusion We found a strong association between economic difficulties and psychological distress in this study, but no inverse association between educational level and psychological distress. On the contrary, persons with high education had more psychological distress than persons with low and medium education when age, employment status and social support were taken into account. The findings were similar in men and women.
Associations between Alternative Accounting Profitability Measures and Security Returns

The importance of accounting information on security price determination is of interest to both security analysts and accountants. Beaver [3], Downes and Dyckman [6], Gonedes [12], Beaver and Manegold [4], and others have investigated the possible relationships between accounting information and market information. Rosenberg [26] has shown the existence of extra-market components of covariance in security returns while Simkowitz and Logue (S–L) [28] have derived the interdependent structure of security returns. However, none of this research has explicitly investigated how the empirical results can be affected by alternative accounting profitability measures within an industry simultaneously.
Emotion recognition of serious game players using a simple brain computer interface

Understanding player's cognitive state and emotional response is necessary to make serious games more challenging and enhance the quality of human-machine interaction and gaming experience. Previous emotion recognition using brain computer interfaces (BCIs) is either relying a large number of wet electrodes or combining both brain signals with other peripheral physiological signals. In this paper, we investigate whether a simple BCI with only a few electrodes can identify basic or complex emotions in more natural settings like playing a game. We performed an experiment with 42 participants, who played a brain-controlled video game wearing a single electrode BCI headset and provided a self-assessed valence/arousal feedback at the end of each trial. By analyzing the data obtained from the self-evaluated questionnaires and the attention and meditation recordings from the BCI device, we introduce an automatic emotion recognition method that classifies four emotional states with the average recognition accuracy 66.04%.
Low circulating levels of IGF-1 in healthy adults are associated with reduced β-cell function, increased intramyocellular lipid, and enhanced fat utilization during fasting.

CONTEXT Low serum IGF-1 levels have been linked to increased risk for development of type 2 diabetes. However, the physiological role of IGF-1 in glucose metabolism is not well characterized. OBJECTIVE Our objective was to explore glucose and lipid metabolism associated with variations in serum IGF-1 levels. DESIGN, SETTING AND PARTICIPANTS IGF-1 levels were measured in healthy, nonobese male volunteers aged 18 to 50 years from a biobank (n = 275) to select 24 subjects (age 34.8 ± 8.9 years), 12 each in the lowest (low-IGF) and highest (high-IGF) quartiles of age-specific IGF-1 SD scores. Evaluations were undertaken after a 24-hour fast and included glucose and glycerol turnover rates using tracers, iv glucose tolerance test to estimate peripheral insulin sensitivity (IS) and acute insulin and C-peptide responses (indices of insulin secretion), magnetic resonance spectroscopy to measure intramyocellular lipids (IMCLs), calorimetry, and gene expression studies in a muscle biopsy. MAIN OUTCOME MEASURES Acute insulin and C-peptide responses, IS, and glucose and glycerol rate of appearance (Ra) were evaluated. RESULTS Fasting insulin and C-peptide levels and glucose Ra were reduced (all P < .05) in low-IGF compared with high-IGF subjects, indicating increased hepatic IS. Acute insulin and C-peptide responses were lower (both P < .05), but similar peripheral IS resulted in reduced insulin secretion adjusted for IS in low-IGF subjects (P = 0.044). Low-IGF subjects had higher overnight levels of free fatty acids (P = .028) and β-hydroxybutyrate (P = .014), increased accumulation of IMCLs in tibialis anterior muscle (P = .008), and a tendency for elevated fat oxidation rates (P = .058); however, glycerol Ra values were similar. Gene expression of the fatty acid metabolism pathway (P = .0014) was upregulated, whereas the GLUT1 gene was downregulated (P = .005) in the skeletal muscle in low-IGF subjects. CONCLUSIONS These data suggest that serum IGF-1 levels could be an important marker of β-cell function and glucose as well as lipid metabolic responses during fasting.
Rare variants in RNF213, a susceptibility gene for moyamoya disease, are found in patients with pulmonary hypertension and aggravate hypoxia-induced pulmonary hypertension in mice

Ring finger 213 (RNF213) is a susceptibility gene for moyamoya disease (MMD), a progressive cerebrovascular disease. Recent studies suggest that RNF213 plays an important role not only in MMD, but also in extracranial vascular diseases, such as pulmonary hypertension (PH). In this study, we undertook genetic screening of RNF213 in patients with PH and performed functional analysis of an RNF213 variant using mouse models. Direct sequencing of the exons in the C-terminal region of RNF213, where MMD-associated mutations are highly clustered, and of the entire coding exons of BMPR2 and CAV1, the causative genes for PH, was performed in 27 Japanese patients with PH. Two MMD-associated rare variants (p.R4810K and p.A4399T) in RNF213 were identified in two patients, three BMPR2 mutations (p.Q92H, p.L198Rfs*4, and p.S930X) were found in three patients, whereas no CAV1 mutations were identified. To test the effect of the RNF213 variants on PH, vascular endothelial cell (EC)-specific Rnf213 mutant transgenic mice were exposed to hypoxia. Overexpression of the EC-specific Rnf213 mutant, but neither Rnf213 ablation nor EC-specific wild-type Rnf213 overexpression, aggravated the hypoxia-induced PH phenotype (high right ventricular pressure, right ventricular hypertrophy, and muscularization of pulmonary vessels). Under hypoxia, electron microscopy showed unique EC detachment in pulmonary vessels, and western blots demonstrated a significant reduction in caveolin-1 (encoded by CAV1), a key molecule involved in EC functions, in lungs of EC-specific Rnf213 mutant transgenic mice, suggestive of EC dysfunction. RNF213 appears to be a genetic risk factor for PH and could play a role in systemic vasculopathy.
Development, Characterization, and Testing of a SiC-Based Material for Flow Channel Inserts in High-Temperature DCLL Blankets

Flow channel inserts (FCIs) are the key elements in the high-temperature dual-coolant lead-lithium blanket, since in this concept the flowing PbLi reaches temperatures near 700 °C and FCIs should provide the necessary thermal and electrical insulations to assure a safe blanket performance. In this paper, the use of a SiC-sandwich material for FCIs consisting of a porous SiC core covered by a dense chemical vapor deposition-SiC layer is studied. A fabrication procedure for porous SiC is proposed and the resulting materials are characterized in terms of thermal and electrical conductivities (the latter before and after being subjected to ionizing radiation) and flexural strength. SiC materials with a wide range of porosities are produced; in addition, preliminary results using an alternative route based on the gel-casting technique are also presented, including the fabrication of hollow samples to be part of future lab-scale FCI prototypes. Finally, to study the corrosion resistance of the material in hot PbLi, corrosion tests under static PbLi at 700 °C and under flowing PbLi at ~10 cm/s and 550 °C, with and without a 1.8–2T magnetic field, were performed to materials coated with a 200–400- $\mu \text{m}$ -thick dense SiC layer, obtaining promising results.
Dynamic User Profiling for Streams of Short Texts

In this paper, we aim at tackling the problem of dynamic user profiling in the context of streams of short texts. Profiling users' expertise in such context is more challenging than in the case of long documents in static collection as it is difficult to track users' dynamic expertise in streaming sparse data. To obtain better profiling performance, we propose a streaming profiling algorithm (SPA). SPA first utilizes the proposed user expertise tracking topic model (UET) to track the changes of users' dynamic expertise and then utilizes the proposed streaming keyword diversification algorithm (SKDA) to produce top-k diversified keywords for profiling users' dynamic expertise at a specific point in time. Experimental results validate the effectiveness of the proposed algorithms.
Squeeze-SegNet: a new fast deep convolutional neural network for semantic segmentation

The recent researches in Deep Convolutional Neural Network have focused their attention on improving accuracy that provide significant advances. However, if they were limited to classification tasks, nowadays with contributions from Scientific Communities who are embarking in this field, they have become very useful in higher level tasks such as object detection and pixel-wise semantic segmentation. Thus, brilliant ideas in the field of semantic segmentation with deep learning have completed the state of the art of accuracy, however this architectures become very difficult to apply in embedded systems as is the case for autonomous driving. We present a new Deep fully Convolutional Neural Network for pixel-wise semantic segmentation which we call Squeeze-SegNet. The architecture is based on Encoder-Decoder style. We use a SqueezeNet-like encoder and a decoder formed by our proposed squeeze-decoder module and upsample layer using downsample indices like in SegNet and we add a deconvolution layer to provide final multi-channel feature map. On datasets like Camvid or City-states, our net gets SegNet-level accuracy with less than 10 times fewer parameters than SegNet.
Can a Poll Tax Ever Be Acceptable?: Evidence from Colonial New Zealand

Poll taxes, while simple in concept, have a regressive effect and unsurprisingly are usually unpopular for this reason which is why they are not commonly used today. Poll taxes were imposed in 19th century New Zealand, with one of the earliest being a form of poll tax imposed by the Nelson Province in 1856 to fund public education. Despite the inherent shortcomings of a poll tax, the Nelson education tax was eventually accepted and defended by the community and produced revenue to fund public education. This paper examines the history of the Nelson poll tax to determine why it was successful when elsewhere, both in earlier and later times, poll taxes have been the focus of considerable dissent which has eventually lead to their demise. Among other reasons, the poll tax revenue being ear-marked for a specific purpose that was perceived by the wider community as important was a major factor in the success of the tax.
Graph Bayesian Optimization: Algorithms, Evaluations and Applications

Network structure optimization is a fundamental task in complex network analysis. However, almost all the research on Bayesian optimization is aimed at optimizing the objective functions with vectorial inputs. In this work, we first present a flexible framework, denoted graph Bayesian optimization, to handle arbitrary graphs in the Bayesian optimization community. By combining the proposed framework with graph kernels, it can take full advantage of implicit graph structural features to supplement explicit features guessed according to the experience, such as tags of nodes and any attributes of graphs. The proposed framework can identify which features are more important during the optimization process. We apply the framework to solve four problems including two evaluations and two applications to demonstrate its efficacy and potential applications.