Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovering the Unseen: Benchmarking the Generalization of Enhancement Methods to Real World Data in Heavy Fog

Due to the ill-posed problem of collecting data within adverse weather scenarios, especially within fog, most approaches in the field of image de-hazing are based on synthetic datasets and standard metrics that mostly originate from general tasks as image denoising or deblurring. To be able to evaluate the performance of such a system, it is necessary to have real data and an adequate metric. We introduce a novel calibrated benchmark dataset recorded in real, well defined weather conditions. The aim is to give a possibility to test developed approaches on real fog data. Furthermore, we claim to be the first showing an investigation of heavy fog conditions up to a total degradation of the considered images. We present a newly developed metric providing more interpretable insights into the system behavior and show how it is superior to several current evaluation methods as PSNR and SSIM. For this purpose, we evaluate current state-of-the-art methods from the area of image defogging and verify the proposed dataset and our developed evaluation framework.
Building a reliable, scalable and affordable RTC for AO instruments on ELTs

Addressing the unprecedented amount of computing power nee ded by the ELTs AO instruments real-time controllers (RTC) is one of the key technolo gical developments required for the design of the next generation AO systems. Throughput oriented arch itectures such as GPUs, providing orders of magnitude greater computational performance than high-en d CPUs, have recently appeared as attractive and economically viable candidates since the fast emergenc e of devices capable of general purpose computing. However, using for real-time applications a I /0 device which cannot be scheduled nor controlled internally by the operating system but is sent commands thro ugh a closed source driver comes with a number of challenges. Building on the experience of almost real-time end-to-end simulations using GPUs, and relying on the development of the COMPASS platform , a unified and optimized framework for AO simulations and real-time control, our team has engag ed into the development of a scalable, heterogeneous GPU-based prototype for an AO RTC. In this paper, we eview the main challenges arising when utilizing GPUs in real-time systems for AO and rank them in terms of impact significance and available solutions. We present our strategy, to mitigate t hese issues including the general architecture of our prototype, the real-time core and additional dedicated components for data acquisition and distribution. Finally, we discuss the expected performance in terms of latency and jitter on the basis of realistic benchmarks and focusing on the dimensioning of the MICADO AO module RTC.
Animacy and Syntactic Structure : Fronted NPs in English

It has long been known that whether the referent of a nominal is animate or not can be important in determining its syntactic or morphological realization. To describe this effect, researchers have proposed a number of hierarchies. The original hierarchy due to Silverstein (1976) conflates definiteness distinctions, animacy distinctions and person distinctions into one ordering called the ‘animacy hierarchy’. We follow Aissen (2003) (based on Croft 1988) in distinguishing separate hierarchies because they refer to different aspects of entity representation within language: the definiteness dimension is linked to the status of the entity as already known or not yet known at a particular point in the discourse, the person hierarchy depends on the participants within the discourse, and the animacy status is an inherent characteristic of the entities referred to. We moreover assume that the traditional definiteness hierarchy, which looks at the morphological marking of the nominal, is in fact a proxy for an ordering according to information status (see below). Each of these three aspects, however, contributes to making entities more or less salient or accessible at a particular point in the discourse. As long as one’s attention is limited to the distinction between grammatical and ungrammatical sentences, the importance of the animacy hierarchy is mainly relevant for languages with a richer morphology than English. In such languages animacy distinctions can influence
Phthalate is Associated with Impairments of Glucose Metabolism and Inflammatory Process in Glucose Homeostatic Organs in Mice Fed Fat Diet : The Role of the Antioxidant Vitamin E

We evaluate the effects of di (2-ethylhexyl) phthalate (DEHP) on glucose metabolism, and inflammatory process; and the ability of vitamin E to suppress these deleterious effects in white adipose tissue (WAT), liver, and pancreas of mice fed high fat diet (HFD). Mice were treated with 500 mg/kg body weight DEHP while receiving an HFD. After 4 weeks, a group of mice received an oral dose of vitamin E. Ten weeks later, blood glucose, plasma insulin were assessed and then, mice were sacrificed and concentrations of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and interferon (IFN)-γ from WAT, liver, and pancreas were measured. HFD-fed mice decreased weight gain following DEHP and vitamin E supplementations. HFD-fed mice expressed high levels of glucose and insulin. However, HFD-fed, DEHP treated mice expressed much higher level of glucose and low insulin concentration; decreased glucose, and increased insulin levels following vitamin E supplementation. TNF-α, IL-1β, and IFN-γ levels decreased in WAT and liver following DEHP administration. However, TNF-α, and IL-1β levels increased in all organs while the IFN-γ level decreased in WAT and pancreas following HFD-fed and DEHP treatment. Vitamin E decreased cytokine levels in HFD-fed mice, in WAT and the liver, and did not affect cytokine levels in the pancreas. [Nisubire D, Zeng Q, Yang X. Di(2ethylhexyl) Phthalate is Associated with Impairments of Glucose Metabolism and Inflammatory Process in Glucose Homeostatic Organs in Mice Fed Fat Diet: The Role of the Antioxidant Vitamin E. Life Sci J 2014;11(5):76-83]. (ISSN:1097-8135). http://www.lifesciencesite. com. 10
PERFORMANCE OF SINGLE CYLINDER CI ENGINE USING BLENDS OF RUBBER SEED BIODIESEL-TAGUCHI METHOD

The objective of the study is to optimize the parameters such as rubber seed biodiesel blend %, injection pressure and applied load of the single cylinder diesel engine with respect to specific fuel consumption and brake thermal efficiency through the Taguchi and ANOVA techniques. The optimum values of the parameters were found using Signal Noise ratio. Analysis of variance (ANOVA) was used to investigate the influence of parameters on the response. It was found that the applied load was the most dominant factor influencing the specific fuel consumption and brake thermal efficiency followed by injection pressure and biodiesel blend.
OPTIMIZING AREA ON THE GENERATION OF SPECIFIC CIRCUITS IN FPGAS FOR SIMD APPLICATIONS

We describe the current state of development of an environment for the automatic generation of specific circuits in FPGA for SIMD applications from high level specifications. The methodology used is based on the transformation of the whole algorithm in a graph of LUTs (Look Up Tables), without the use of library components, that implements all the required operations. The quality of the obtained circuitry is guaranteed by the use of “type inference”, a technique that is focus of current research on the design high level circuit generators, which is context dependent. Two sort of implementations of the iterative expressions are possible with these tools: with or without a complete unrolling. As a first case study, we have tested the efficiency of this environment in the implementation of an integer discrete wavelet transform (DWT).
An Econometric Estimation of the Aggregate Import Demand Function for Sierra Leone

This paper investigates the behaviour of aggregate import demand for Sierra Leone using times series data for the period 1977-2008. An Autoregressive Distributed Lag (ARDL) modeling process is employed to capture the effect of final consumption expenditure, government expenditure, investment expenditure, export expenditure and relative prices on import demand. The results suggest that there exists a cointegrating relationship between import demand and its determinants. In the long run, government expenditure, exports and consumption expenditures are the major determinant of Sierra Leone’s aggregate imports demand. The short run dynamics suggest that consumption and government expenditures have the highest influence on aggregate import demand in Sierra Leone. Relative price is however insignificant in both the long and short runs. These results imply that expenditure-reducing policies are more effective than exchange rate policy in correcting Sierra Leone's trade deficits. JEL Classification Codes: F10, F41, C22
Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation

There is much interest in computer vision to utilize commodity hardware for gaze estimation. A number of papers have shown that algorithms based on deep convolutional architectures are approaching accuracies where streaming data from mass-market devices can offer good gaze tracking performance, although a gap still remains between what is possible and the performance users will expect in real deployments. We observe that one obvious avenue for improvement relates to a gap between some basic technical assumptions behind most existing approaches and the statistical properties of the data used for training. Specifically, most training datasets involve tens of users with a few hundreds (or more) repeated acquisitions per user. The non i.i. d. nature of this data suggests better estimation may be possible if the model explicitly made use of such “repeated measurements” from each user as is commonly done in classical statistical analysis using so-called mixed effects models. The goal of this paper is to adapt these “mixed effects” ideas from statistics within a deep neural network architecture for gaze estimation, based on eye images. Such a formulation seeks to specifically utilize information regarding the hierarchical structure of the training data — each node in the hierarchy is a user who provides tens or hundreds of repeated samples. This modification yields an architecture that offers state of the art performance on various publicly available datasets improving results by 10-20%.
High-Affinity Internalizing Human scFv-Fc Antibody for Targeting FGFR 1-overexpressing Lung Cancer Running Title : scFv-Fc for Targeting FGFR 1-positive Lung Cancer Cells

2 Wroclaw Research Centre EIT+, Stablowicka 147, 54-066 Wroclaw, Poland * Corresponding author E-mail address: jacek.otlewski@uwr.edu. pl Phone: +48 71 375 2824 DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST The authors disclose no potential conflicts of interest
Hierarchical Multiobjective Routing in MPLS Networks with Two Service Classes – Heuristic Resolution and Sensitivity Analysis ∗

Modern multiservice network routing functionalities have to deal with multiple, heterogeneous and multifaceted QoS (Quality of Service) requirements. A heuristic approach devised to find “good” solutions to a hierarchical multiobjective alternative routing optimisation problem in MPLS networks with two service classes (and different types of traffic flows in each class), namely QoS and Best Effort (BE) services, formulated within a hierarchical network-wide optimisation framework, is presented. This heuristic resolution is based on a bi-objective constrained shortest path model and is applied to a test network used in a benchmarking case study. An experimental study based on analytic and discrete event simulation results is presented, allowing for an assessment of the quality of results obtained with this new heuristic resolution for various traffic matrices. A dynamic version of the routing method is formulated and its performance with the same case study network is analysed. A sensitivity analysis is performed by using relaxation and floating barrier techniques, so as to evaluate if the proposed heuristic treats the objective functions in a balanced way. The results of these tests led to the formulation of variants of the heuristic. A description and an experimental study of these variants
Evaluation of the effects of laparoscopic adjustable gastric banding versus laparoscopic sleeve gastrectomy on weight loss

Objectives: Obesity has become one of the most serious and ever increasing health problems of our times. Diet, exercise and medical treatment have proven to be insufficient. Operations such as laparoscopic adjustable gastric banding (LAGB) and laparoscopic sleeve gastrectomy (LSG) have gained popularity. The purpose of this study is to conduct a retrospective comparative analysis of the clinical results gained from patients treated with LSG and LAGB due to morbid obesity. Methods: The patients included in the study were selected among those who were diagnosed with morbid obesity and were operated with LAGB (n = 55) and LSG (n = 52) from May 2007 to December 2012. Both groups were compared in terms of the demographic characteristics, preoperative and postoperative conditions. Results: The groups were similar in terms of age, sex and BMI. In the 6 th month, there was a notable loss of appetite in the LSG group patients compared to the LAGB patients (69.2% vs. 23.6%, p < 0.001). The rate of excess weight loss in the LAGB group was 23.93% ± 7.98 % and 31.7% ± 7.49% in the LSG group in the postoperative 6 th months ( p = 0.002). The rate of excess weight loss was 45.36% ± 10.92% in the LAGB group and 60.3% ± 9.81% in the LSG group in the postoperative 12 th months ( p ˂ 0.001). Conclusions: When the two surgical operations for morbid obesity are compared LSG is found to be a more successful method in terms of body weight loss. Nevertheless, longer hospitalization can be associated with the technically more complicated nature of the operation and the fact that it requires resection.
Total arterial coronary grafting: outcomes, concerns and controversies

Choice of conduit remains the Achilles heel of coronary artery bypass grafting. Conduit choice is crucial as it is deemed to influence the long-term outcomes. While the important survival advantage of a left internal mammary artery graft over vein grafts is universally accepted, controversy reigns supreme regarding the next best conduit. There is plenty of evidence to suggest that arterial grafts are not only superior in terms of patency and survival, but they also protect the native coronary arteries against further progression of atherosclerotic disease. Total arterial coronary grafting, utilizing various configurations of bilateral internal mammary arteries, radial artery and occasionally right gastroepiploic artery is a safe and reproducible strategy. However, concerns about additional operative time, enhanced technical complexity, graft spasm with hypoperfusion, competitive flow, increased risk of bleeding, deep sternal wound infection, and most importantly lack of randomized trial data have prevented the universal adoption of total arterial coronary grafting. This review evaluates the currents outcomes of total arterial coronary grafting and summarizes the concerns and controversies associated with this strategy.
DYNAMIC SIMULATIONS IN ELECTRICAL APPARATUS

1 Technical University of Sofia, Kliment Ohridski 8, Sofia 1000, Bulgaria, E-mail: yatchev@tu-sofia.bg Abstract: The paper gives an overview of the models for simulation of dynamics in electrical apparatus. The real problem most often consists of electromagnetic field, electric circuit and meahcnical motion problems. Three types of models are considered – circuit models, coupled models and decoupled models. Circuit models are based on magnetic circuit modelling, in coupled models the electromagnetic field is analysed together with the other two problems, while in decoupled model the field is analysed separately. Methods for the solution of the problems are outlined. Examples of different solved problems are given.
Service Quality , satisfaction and loyalty in gymnasiums A study from India

Purpose: This study attempts to explore the dimensions of co nsumer perceived service quality in the context of fitness services provided by gymnasiums and investigate the relationship among service quality, loyalty and ove rall satisfaction of consumers from the fitness service. Design/methodology/approach : A 16-item instrument (SERVGYM) was developed by modifying SERVPERF instrument to measure service qu ality in gymnasiums in four major cities of India. The scale was validated using conf irmatory factor analysis. Structural equation modeling technique was employed to assess the relat ionship of service quality with loyalty and overall satisfaction of consumers. Findings: Four service quality dimensions were identified n amely, reliability, customerorientedness, convenience, and ambiance. All the se rvice quality dimensions were found to have positive influence on both satisfaction and lo yalty. Positive relationship between satisfaction and loyalty was also established. Originality/value : The scale contextualised to Indian fitness servic (Gym) industry is useful to measure service quality in gymnasiums. Understan ding of the service quality dimensions and their relationship with loyalty and customer sa tisf ction is also significant Paper type: Research paper
Using Simplified Grammar for Voice Commands to Decrease Driver Distraction

Today’s car is considered a Cyber Physical System implying a shift of control and management of the car’s features to complex onboard software. Since the computer has taken control over most of the in-car driving and entertainment (infotainment) activities, driver distraction has become one of the primary reasons for car-related fatal accidents. As a result, we need to decrease driver distraction despite the growing presence of cockpit interactive digital technologies. Using voice-based commands is a potential solution to decrease visual distraction but it causes significant cognitive distraction. In this paper, we present a new method for voice-based commands to decreasing the cognitive distraction while using command based voice inputs.
Innovation, trade and multi‐product firms

This paper contributes to the literature on multi-product exporters by developing a model that emphasizes the role of innovation in explaining heterogeneity in export behavior across both firms and products within the same company. We propose a dynamic model of the Luttmer (2011) type where firms invest to maintain and increase their portfolio of goods: the process of product innovation by incumbent firms is such that the probability to capture new business opportunities at home and abroad is a function of the number of goods already sold. This cumulative growth process gives rise to a heavy tail in the distribution of the number of products exported by each firm, which is consistent with the data. Such a markedly heterogeneous behavior across firms occurs even if we do not assume any heterogeneity in productivity to start with. Differences in export sales across products stem from the demand-side of the model, in the form of a product-specific preference attribute. We show that the model is consistent with several empirical regularities that characterize multi-product firms, such as the strict hierarchy in the sales of products across markets, the weak correlation between export scale and scope within each firm, and the substantial degree of product churning.
Brokered Agreements in Multi-Party Machine Learning

Rapid machine learning (ML) adoption across a range of industries has prompted numerous concerns. These range from privacy (how is my data being used? ) to fairness (is this model's result representative? ) and provenance (who is using my data and how can I restrict this usage? ). Now that ML is widely used, we believe it is time to rethink security, privacy, and incentives in the ML pipeline by re-considering control. We consider distributed multi-party ML proposals and identify their shortcomings. We then propose brokered learning, which distinguishes the curator (who determines the training set-up) from that of the broker coordinator (who runs the training process). We consider the implications of this setup and present evaluation results from implementing and deploying TorMentor, an example of a brokered learning system that implements the first distributed ML training system with anonymity guarantees.
Changing Partnership and Fertility

Family dynamics are changing in Europe , but how cohort completed fertility is affected by partnership behaviours and how this has c nged over time is rarely studied. We use microsimulation techniques to investigate the effect of the increasing prevalence of union dissolution on completed fertility levels in Italy, Norway and Britain, three countries with very different systems of value. We find that the net effect of union instability is to decrease fertility (by about 0.5 children for Italian and 0.2 to 0.4 children for British cohorts , explorations are ongoing for Norway) but the magnitude of the difference depends on the timing of union formation and separation. As expected, re-partner ing produces more children in new partnerships if the separation occurs earlier. Nonetheless, it is only f separation takes place after the second birth and if all women r -partner that additional childbearing would almost compensate for births lost due to union disruption.
Asset Selling Under Debt Obligations

We extend the classical asset-selling problem to include debt repayment obligation, selling capacity constraint, and Markov price evolution. Specifically, we consider the problem of selling a divisible asset that is acquired through debt financing. The amount of asset that can be sold per period may be limited by physical constraints. The seller uses part of the sales revenue to repay the debt. If unable to pay off the debt, the seller must go bankrupt and liquidate the remaining asset. Our analysis reveals that in the presence of debt, the optimal asset-selling policy must take into account two opposing forces: an incentive to sell part of the asset early to secure debt payment and an incentive to delay selling the asset to capture revenue potential under limited liability. We analyze how these two forces, originating from debt financing, will distort the seller’s optimal policy.
Navigating among people in crowded environment : Datasets for localization and human robot interaction

This paper presents a novel set of data for the evaluation of visual place recognition in both indoors and outdoors environment in addition to sensor information to evaluate human-robot interactions in crowded areas. The datasets were recorded in the Royal Alcázar of Seville (Spain), a tourist hotspot that may have more than 5000 visits per day. We recorded a large set of images sequences from a stereo camera and scan measurements from three laser mounted on a moving robot. The datasets are timestamped and stored by means of the well-known Robot Operating System (ROS) log functionality. The robot traveled more than one kilometer in each experiment, and every trial was performed at different time of the day so we could capture the evolution of lighting conditions over the images. The tourist attendance also depends on the hour, providing datasets with a lot of examples to model into a socialway the different places such as corridors, gates, queues, groups of people, etc.