Miracle-dz/UniFAR-FTUs huggingface dataset:
sktime: A Unified Interface for Machine Learning with Time Series

We present sktime -- a new scikit-learn compatible Python library with a unified interface for machine learning with time series. Time series data gives rise to various distinct but closely related learning tasks, such as forecasting and time series classification, many of which can be solved by reducing them to related simpler tasks. We discuss the main rationale for creating a unified interface, including reduction, as well as the design of sktime's core API, supported by a clear overview of common time series tasks and reduction approaches.
AN ANOMALOUS NON-CONVECTIVE HIGH WIND EPISODE OVER UPPER MICHIGAN

Several stations in northwestern Upper Michigan observed wind gusts over 40 kt behind a well-developed low pressure system during the evening and overnight hours of 6-7 April 1997. Observed data and griddedmodel output show the strong winds occurred in considerable low-level cold advection along and behind a secondary cold front and beneath a strong inversion that decoupled the lower layers from aloft. A comparison between this event and an episode of high winds observed in Lower Michigan and Wisconsin during the afternoon of 6 April 1997 suggests the conditions supporting the high winds observed over Upper Michigan did not fit an established high wind model.
Vergleich zur Verbundfestigkeit von Resin-Nano-Keramikkronen auf einteiligen ZrO 2-und Ti-Implantaten – eine Pilotstudie

Einführung: Resin-Nano-Keramiken haben eine duale Netzwerkstruktur und vereinen potenziell die Vorteile von Keramiken und Kompositen. Sie können nur adhäsiv befestigt werden. Es gibt in der Literatur bislang keine Studien, die sich mit dem Verbund von Komposit-Matrix-Keramiken auf einteiligen Implantaten befassen. Ziel dieser Studie war es, die Wirksamkeit der Vorbehandlung von Implantatoberflächen bezüglich des adhäsiven Verbundes mit einer ResinNano-Keramik zu untersuchen.
Understanding AirBnB in Fourteen European cities

This paper gives an overview of the activities of Airbnb in 14 European cities. Since Airbnb provides an online accommodation platform linking property owners and visitors, it could potentially affect both the hotel market and the domestic rental market in the localities in which it operates. We discuss the structure and the segmentation of the accommodation market, and then present some descriptive statistics on Airbnb activities in the 14 cities. Finally, we present some estimates of the impact of Airbnb on hotels and on rents, among the first estimates for European markets. We find Airbnb’s presence in a market has a negative effect on hotel occupancy rates, but a positive effect on total hotel revenue and the average daily rate they charge. In the two cities we consider, the platform’s impact on the rental market is ambiguous, suggesting local market conditions are important. JEL codes: D22, L83, L88, R31
Food Price Volatility & Political Unrest : The case of the Egyptian “ Arab Spring ”

The “Arab Spring” has always been portrayed in Egypt as politically motivated revolts against decades of dictatorial regimes (Abu Hatab, 2014). From a scientific perspective however, way less attention has so far been paid to the question why the Arab spring movement occurred precisely in early 2011, and not any time earlier, given that the political system had been in power already for decades (Abu Hatab, 2014). Furthermore, it has been pointed out that the Arab spring coincided with a period of volatile global food prices, which is potentially important given that Egypt is a net importer of food and the world largest wheat importer.
University of Groningen Selecting heart failure patients for metabolic interventions

Introduction: Heart failure (HF) has become the cardiovascular epidemic of the century and now imposes an immense burden on health care systems. While our understanding of the pathophysiology of HF has increased dramatically, the translation of knowledge into clinical practice has been disappointing. Metabolic dysfunction in HF has been studied for eight decades, but these efforts have not resulted in effective therapies. This paucity in clinical translation probably results from the variable contribution of metabolic dysfunction to the underlying heart disease. A major unmet need in cardiac drug development is therefore the ability to identify a homogeneous subset of patients in whom HF is driven by a specific mechanism that can be targeted. Areas covered: The available literature was evaluated to describe maladaptive metabolic perturbations that occur in failing hearts and may cause metabolic inflexibility, oxidative stress and cardiac energy depletion. Furthermore, the potential utility of various biomarkers and molecular imaging techniques to detect and quantify specific metabolic dysfunctions in HF were compared. Finally, the authors propose ways to utilize these techniques to select patients for specific metabolic interventions. Expert commentary: Metabolic dysfunction is among the most promising therapeutic targets in HF. Meticulous patient-selection with molecular imaging techniques and specific biomarkers appears indispensable for the effective translation of decades of scientific knowledge into clinical therapeutics. ARTICLE HISTORY Received 23 August 2016 Accepted 28 November 2016
Reading and Deafness: State of the Evidence and Implications for Research and Practice

Over the years, persistently low achievement levels have led scholars to question whether reading skill development is different for deaf readers. Research findings suggest that in order for deaf students to become proficient readers, they must master the same fundamental abilities that are well established for hearing learners, regardless of the degree of hearing loss or communication modality used (e.g., spoken or signed). The simple view of reading (SVR), which hypothesizes the critical role both language abilities and phonological skills play in development of reading comprehension, provides a model for understanding the reading process for a wide range of students and has the potential to shed light on the challenges deaf students have historically experienced in achieving age-appropriate outcomes. Therefore, the purpose of this paper is to review the components of the SVR and use this conceptual model as the basis for exploring and discussing both historical and current research evidence in reading and deafness, with a particular focus on phonological skills. Recommendations for future research and practice based on the existing body of literature will also be provided.
Objectively measured physical activity and psychosocial functioning in young children

The global trend in inactivity in children may be related to psychosocial problems. We investigated the cross-sectional association between physical activity (PA) levels and psychosocial functioning in 3.4– 7.3-year-old children. Children from the Dutch GECKO birth cohort (N = 898; 51.6% boys) had PA levels assessed objectively by accelerometry (ActiGraph GT3X) for at least three days. Linear regression analysis was used for associations with psychosocial functioning (parent report of the Strengths and Difficulties Questionnaire), controlling for gender, age and socio-economic status. Higher total and moderate-to-vigorous PA levels (MVPA) were associated with higher Total Difficulty scores, and sedentary time to lower Total Difficulty scores. More time spent in MVPA was significantly associated to “hyperactivity/inattention” in both boys (Standardized BBOYS = 0.192) and girls (Std.BGIRLS = 0.139) whereas for the time in sedentary behaviour, a reverse association was found only in boys (Std.BBOYS = −0.230). In boys only, more time in MVPA (Std.BBOYS = 0.154) and less time in sedentary behaviour (Std.BBOYS = −0.147), were significant determinants for ‘behavioural problems’. When using objectively measured PA, parents report more hyperactivity/inattention and behavioural problems in the more active children, and less in the more sedentary children, most clearly for boys. High levels of PA might be an indicator of psychosocial problems in young children. ARTICLE HISTORY Accepted 27 April 2019
On Compact Deep Neural Networks for Visual Place Recognition, Object Recognition and Visual Localization

There has been an immense increase in the use of Deep Neural Networks in recent times due to the availability of more data and greater computing power. With their recent success, it has been a trend to use them extensively in real-time applications. However, the size of deep models can render them incapable to be used in devices with memory-constraints. In this thesis, we explore the several neural network compression techniques for three separate tasks namely i) visual place recognition, ii) object recognition and iii) visual localization. We explore explicit compression methods for the visual place recognition task and the object recognition task, achieved by making modifications to the learned weight matrices. Furthermore, we look at compression attained through architectural modifications in the network itself, proposing novel training procedures and new loss functions for object recognition and visual localization. The task of visual place recognition requires us to correctly identify a place given its image, by finding out images of the same place in the world(dataset). Performing this on low memory devices such as mobile phones and robotics systems, is a challenging problem. The state of the art models for this task uses deep learning architectures having close to 100 million parameters which take over 400MB of memory. This makes these models infeasible to be deployed in low memory devices and gives rise to the need of compressing them. Hence, we study the effectiveness of explicit model compression techniques like trained quantization and pruning, on one of the most effective visual place recognition models. We show that a compressed network can be created by starting with a pre-trained model and then fine-tuning it via trained pruning and quantization. Through this training method, the compressed model is able to produce the same mAP as the original uncompressed network. We achieve almost 50% parameter reduction through pruning with no loss in mAP and 70% reduction with close to 2% mAP reduction, while also performing trained 8-bit quantization. Furthermore, together with 5-bit quantization, we perform about 50% parameter reduction by pruning and get only about 3% reduction in mAP. The resulting compressed networks have sizes of around 30 MB and 65 MB which makes them easily usable in memory constrained devices. We next move on to compression through low rank approximation for the task of image classification. Traditional compression algorithms in deep networks involves performing low-rank approximations on the learned weight matrices after the training procedure has been completed. We propose to perform low rank approximation during training itself and make the parameters of the approximated matrix learnable too by using a suitable loss function. We show that by using our method, we are able to compress a
Designing Social Robots for Early Detection of Mental Heath Conditions

Globally, mental health is a growing socio-economic burden and leads to negative ramifications including mortality and poor quality of life. Successful early detection of mental illness will make a significant, positive economic and societal impact. Social robots show potential to be integrated as tools for psychological therapy and early detection. This thesis seeks to design and develop social robots for early detection of mental illness. I explore how multi-modal inputs can be used to infer user's mental state and to direct appropriate robot behaviour. I have employed an iterative design process for the design of robot morphology, personality, and behaviour. Design 1 is a social robot with 6 DOF and exhibits non-verbal behaviours. In this design, I explore audio, video, and haptic inputs to detect user's emotional state. Design 2 is an interactive device that aims to collect audio data for the detection of early signs of depression. In this design, acoustic features are explored for depression detection, and the device uses audio and LEDs to communicate it's internal state. Finally, I have conducted a pilot experiment to investigate how the users interact with the robot. This thesis informs the design of future robots that aim to support early detection of mental illnesses.
Studying the Effect of Conservatism on Accrual-Based Profits Management and Chemical Products and Materials Industry in Tehran Stock Exchange

Managers manage the profit often in order to mislead shareholders about the actual economic performance of the company. So it is not surprising that various stakeholders of the company consider the company profits management inappropriate and try to reduce the authorities and powers of the managers through intensified monitoring. In this regard, the shareholders consider conservatism and corporate governance as a supervisory tool that limits the profits management. This research studies the probability of the effect of conservatism on accrual-based profits management and chemical products and materials industry and to assess the accrual-based profit management and conservatism the Jones modified model was used. The research period was from years 2008 until 2013. The study method is descriptive and correlational, and by using regression model, Eviews7 software and generalized squares method the research hypotheses were examined. The results indicate that by increasing the level of conservatism, the opportunities of profit management are limited, and managers have no incentive to manage accrual-based profits that keeps the reported earnings more accurate and protected from manipulation.
DECENTRALIZED SUPERVISORY CONTROLLER DESIGN FOR DISCRETE-EVENT SYSTEMS USING OVERLAPPING DECOMPOSITIONS AND EXPANSIONS

A decentralized supervisory controller design approach for discrete-event systems (DESs) modeled by automata or formal languages is presented. The controller is designed in order to lead the DES to certain desired marked states, in the sense that, from any state, which is reachable from the initial state, there exists a finite string of events which leads to one of the marked states. The controller design approach is based on overlapping decompositions and expansions. To apply the proposed approach, the automaton of the given DES is first decomposed overlappingly and expanded to obtain disjoint subautomata. Next, a controller is designed for each disjoint subautomaton. These controllers are then combined to obtain a controller for the expanded DES. In the final phase, a controller for the original DES is obtained from the controller determined for the expanded DES. It is proved that this final controller leads the original DES to the desired marked states. The computational complexity of the proposed design approach, relative to the computational complexity of a centralized approach is also discussed.
The Effects of-Differential Privacy on Machine Learning Accuracy

While machine learning algorithms have exploded in popularity in recent years, most take no steps to avoid leaking the privacy of users whose information was used in the training data set. One privacy-enhancing model that is becoming increasingly relevant is -differential privacy, which provides a theoretical way of measuring the effectiveness of a privacy mechanism, with lower values of promising more privacy. In this project, we first examined the privacy guaranteed by randomized response, a privacy mechanism that randomly alters some outputs in a training data set used for classification. We then conducted a series of experiments to see how the privacy mechanism affected the performance of various machine learning algorithms. We found that all algorithms suffered in performance, but logistic regression outperformed SVM for smaller values of even though SVM outperformed logistic regression for higher values. Smaller training data set sizes suffer an even larger penalty to accuracy when incorporating privacy, but the penalty is mostly unaffected by the difficulty of the classification problem as measured by the overlap between the clusters representing the various classes. We also explored two potential privacy mechanisms for bounded, realvalued outputs. The first was adding bounded Gaussian noise, while the second combined bounded Gaussian noise with a form of randomized response that randomly replaced an output value in the training data set with one drawn from the uniform distribution. We calculated the theoretical value of -differential privacy that would be guaranteed by these two schemes by examining their probability density functions.
MATE AND NEST SITE FIDELITY IN A RESIDENT POPULATION OF BALD EAGLES’

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Repolarization Parameters in Patients with Premature Coronary Artery Disease

Amaç: Genç bireylerde koroner arter hastalığı nispeten nadir görülür. Literatürde genç yaşta koroner arter hastalığı ile ilgili sınırlı veri mevcuttur. Bu çalışmada yeni tanı almış prematür koroner arter hastalığı olanlarda repolarizasyon parametreleri değerlendirildi. Gereç ve Yöntem: Çalışmaya toplam 200 hasta [128 erkek, 38,0 (29,3-42,0) yaş] dahil edildi ve bunlardan 100’ü yeni tanı prematür koroner arter hastalığı (yaş ≤45) olan çalışma grubunu oluşturdu. Kalan 100 hasta iyi eşleştirilmiş kontrol grubunu oluşturdu. İki grup arasında DII, V2 ve V6 derivasyonlarında ölçülen, QTc intervali, Tp-e intervali ve Tp-e∕QTc den oluşan repolarizasyon parametreleri karşılaştırıldı. Bulgular: Median QTc intervali D2 derivasyonunda (430,3 ms ve 405,3 ms, p<0,001),V2 derivasyonunda (433,8 ms ve 404,7 ms, p<0,001) V6 derivasyonunda (430,2 ms ve 401,7 ms, p<0,001); median Tp-e intervali D2 derivasyonunda (80 ms ve 64 ms, p<0,001), V2 derivasyonunda (82 ms ve 74 ms, p<0,001), V6 derivasyonunda (88 ms ve 72 ms, p<0,001); ve median Tp-e/QTc oranı; D2 derivasyonunda (0,188 ve 0,158, p<0,001), V2 derivasyonunda (0,190 ve 0,181, p=0,022) ve V6 derivasyonunda (0,196 ve 0,183, p<0,001) olmak üzere sırasıyla prematür koroner arter hastalığı olanlarda kontrol grubuna göre anlamlı olarak daha yüksek saptandı. Sonuç: Sonuç olarak, prematür koroner arter hastalığı anormal repolarizasyon dispersiyonu ve dolayısıyla aritmik risk ile ilişkili olabilir. Anahtar Kelimeler: Dispersiyon, Koroner, Prematür, Repolarizasyon Öz
Effect Of Robot Assisted Training On Hand Function In Stroke Patients

:Background: Robot-assisted therapy is one of the new technologies that used in rehabilitation of stroke patients for improving the process of recovery and enhancing functional activity. Objective: The aim of the current study was to investigate the effect of robotic assisted training on the hand function in stroke patients. Methods: Twenty male patients with stroke were selected from king Fahd hospital in Jeddah participated in this study. The patients were randomly assigned into two equal groups; control group and study group. All patients were assessed for functional performance by manual function test and for pinch and grip strength by hand held dynamometer. Both groups were treated with traditional physical therapy program. Additionally the study group received robotic assisted training. The treatment was given three time per week for eight weeks,. Results: The findings showed a significant increase in the mean values of manual function test, grip and pinch strength after treatment in the study group. For the control group there was a significant increase in the mean values of grip and pinch strength after treatment, but there was non-significant difference in the mean values of the manual function test. Also the results showed significant differences between control and study groups in manual function test and grip strength after treatment. Conclusion: Robotic assisted training, in addition to traditional physical therapy program, is effective in improving functions of the affected hand in stroke patients.
Analytical Design of Robust Control Systems with Desirable Performances

In paper the analytical design method of the systems with control on output and impacts is offered. The resulting system has partially given structure, desirable performances, lowered dimension and increased robustness. Parameters of the system’s controller are the solutions of the linear algebraic equations systems. Standard transfer functions are used for maintenance of the desirable quality parameters such as: the astatic orders to reference input and external disturbances; overshoot and settling time. Increase of the robustness is achieved by a reduction of the plant model and inclusion of a part of its poles and zero in roots of the closed system characteristic polynomial. The suggested method of analytical design can be applied in aggregate with the dynamic decomposition method for creation of the multivariable control systems. Efficiency of the analytical design method and the robustness increase method of the control systems by the reduction of the plant model are shown on the numerical examples. These methods can be used for creation of the systems with less complex, but more robust for plants of chemical, textile, food and other branches of production.
GREEN ECONOMY AND POVERTY

We are at a stage in economic development, where the green economy is not an achieved state of affairs at all. We are not even sure if we are even sincerely committed to achieving it, or if we are honestly striving to achieve it. No doubt concerns have been expressed both in the civil society and in official circles almost all over the world about the trend towards environmental degradation and the urgent need to reverse it. Various apprehensions have been voiced about implications of a green economy, or even achieving a green economy, for aggravation of poverty, or its decline, or for attempts at its removal. My lecture now is addressed to discussing these apprehensions.