Miracle-dz/UniFAR-FTUs huggingface dataset:
Shaping the future for primary care education & training project. Education and training needs analysis (ETNA) toolkit:a resource kit and users’ guide

The Education and Training Needs Analysis (ETNA) Toolkit that has been developed as part of an inter university collaboration in the North West of England entitled the ‘Shaping the Future for Primary Care Education and Training’ project. The tool has been developed by the University of Bolton and Lancaster University in collaboration with key stakeholders including representatives from Primary Care Trusts and Social Services across the North West
An enhanced reactive power dispatch with finest location of dg using PSO algorithm

In the safety and economic point of view, Reactive Power is the most problematic thing during the operation of the electrical power system network. Reactive Power supply completion is a nonlinear and has both equality and inequality constraints. In this work, to find the solution of reactive power supply issue, Particle Swarm Optimization (PSO) algorithm and MATPOWER 5.1 toolbox are utilized. PSO is an excellent optimization technique that is also having effective finding ability. One of the best asset of PSO is that the ability of PSO is less sensitive to the complication of the objective function. MAT POWER 5.1 is an open source MATLAB toolbox concentrating on finding the power flow issues. The proposed method in this paper diminishes the active power loss in the conventional power system and determines the optimal location of a new installed Distributed Generator (DG). The IEEE 14 bus system is utilized to find the performance and test results show the perfectness of the proposed method.
A Fast Chaos-Based Colour Image Encryption Algorithm Using a Hash Function

This paper suggests a new fast colour image cipher to meet the increasing demand for secure online image communication applications. Unlike most other existing approaches using a permutation-substitution network, the proposed algorithm consists of only a single substitution part. The keystream sequence is generated from a 4-D hyperchaotic system, whose initial conditions are determined by both the secret key and the SHA-224 cryptographic hash value of the plain-image. Favoured by the avalanche effect of hash functions, totally different keystream sequences will be generated for different images. Consequently, desired diffusion effect can be achieved after only a single round of substitution operation, whereas at least two encryption rounds are required by the state-of-the-art permutation-substitution type image ciphers. We also demonstrate the computational efficiency of the proposed algorithm by comparing it with the AES encryption algorithm. A thorough security analysis is carried out in detail, demonstrating the satisfactory security of the proposed algorithm.
Elderly People Fall Detection System Using Skeleton Tracking and Recognition

The fall detection systems use a variety of technologies like sensors, wearable devices, color camera, thermal camera etc. With the use of Microsoft Kinect camera for non-gaming purposes, depth images have started being utilized for fall detection. Various authors have made an attempt at using Kinect for fall detection in combination with a variety of techniques like ellipse analysis, bounding box analysis etc. However, most of these attempts fail to differentiate between human subjects and other inanimate objects and fail to identify the person who has fallen while assuming that there is only one person who needs to be monitored. This paper proposes a new system that is based on the depth images captured by Microsoft Kinect, skeleton tracking and bounding box analysis. The key novelty of this system is that it wraps the moving object into the bounding box and determines the change of size of the moving object by analysis the motion over the time to distinguish the human moving object and non-human moving object. The system stores the joint measurements of the known people in a database and compares the joint measurements of the detected person with the values in the database to identify the person. The proposed solution provides a significantly higher accuracy rate as compared to the current best solution and especially when the person carrying an object, sweeping the floor, dropping an object and picking an object from the floor.
External fixation of femoral fractures in children : clinical, radiological and functional outcome and cost analysis.

The overall aim of this thesis was to evaluate the outcome when treating children for displaced femoral fractures with external fixation.In a consecutive and prospective study during the period 1993-2000, 96 children aged 3-15 years with 98 displaced femoral fractures were treated with external fixation and early mobilisation. The mean age was 8.1 years, the mean hospital stay was 8.7 days and the mean treatment time was 61 days. All fractures healed. Minor complications included pin tract infections (18%), clinical insignificant malunions, heterotopic ossification and two re-reductions. Major complications (6%) included two re-fractures after significant trauma and three plastic deformations after premature fixator removal leading to an osteotomy.Radiological evaluation was performed up to one year for the whole group and for a subgroup up to two years. The evaluation showed that malunions were few and prone to remodelling almost completely. Although the fractures were fixated without shortening, as recommended earlier, the overgrowth was far less than expected.Isokinetic muscle strength was measured in both hamstrings and quadriceps in 31 of the patients and compared with 31 matched children without previous injury to the legs. Early mobilisation seems to prevent residual muscle weakness previously shown after treatment with traction or cast for femoral fractures in children.A cost analysis was performed, comparing three different treatment modalities of femoral shaft fractures: traction in hospital, traction in hospital/at home and external fixation. The analysis included both total medical costs and costs for the care provider. The most important factors were days spent at the hospital and the sick leave for the care provider. Treatment that can minimise these factors will contribute strongly to a lowering of health care costs.Conclusion: External fixation of displaced femoral fractures in children can be used as standard treatment in children aged 3-15 years. The treatment provides satisfactory results with a low rate of major complications. Early mobilisation seems to prevent residual muscle weakness. The treatment reduce the number of days in hospital and the number of days of sick leave for the care provider and contributes strongly to lowering health care costs.
An Endfire Circularly Polarized Complementary Antenna Array for 5G Applications

An endfire circularly polarized (CP) complementary antenna array is proposed for 5G applications. The proposed antenna is realized using a single-layered printed circuit board (PCB) with plated-through-hole technology and metal blocks. The antenna element consists of an open-ended substrate-integrated waveguide (SIW), an electric dipole, a double-sided parallel-strip line (DSPSL), and two metal blocks. It is simple in configuration and can achieve wide impedance and axial ratio (AR) bandwidths, stable gain and radiation patterns, and low back radiation. To increase the gain, a $1 \times 8$ antenna array is formed by integrating eight antenna elements with a planar 1–8 SIW feed network. The measurement results show that the proposed array can achieve an overlapping impedance and AR bandwidth of 23.8% from 56.3 to 71.5 GHz with an endfire left-handed CP (LHCP) gain from 14 to 15.3 dBic. The proposed array possesses all the salient features of the complementary source in symmetric and stable radiation patterns, low back radiation, and wide bandwidth.
Machine learning in algorithmic trading strategy optimization - implementation and efficiency

The main aim of this paper was to formulate and analyze the machine learning methods, fitted to the strategy parameters optimization specificity. The most important problems are the sensitivity of a strategy performance to little parameter changes and numerous local extrema distributed over the solution space in an irregular way. The methods were designed for the purpose of significant shortening of the computation time, without a substantial loss of a strategy quality. The efficiency of methods was compared for three different pairs of assets in case of moving averages crossover system. The methods operated on the in sample data, containing 20 years of daily prices between 1998 and 2017. The problem was presented for three sets of two assets portfolios. In the first case, a strategy was trading on the SPX and DAX index futures, in the second on the AAPL and MSFT stocks and finally, in the third case on the HGF and CBF commodities futures. The major hypothesis verified in this thesis is that machine learning methods select strategies with evaluation criterion near to the highest one, but in significantly lower execution time than the Exhaustive Search.
Curved Path Following for Unmanned Surface Vehicles With Heading Amendment

This article presents two interrelated problems-along tracking and cross tracking-in guidance design for curved path following for unmanned surface vehicles. Since these two types of directional tracking are interactively constrained in most research work, an iteration mechanism is first put forward to optimize the path parameter in each closed loop such that along tracking will not affect cross tracking in the subsequent time period. An extended line-of-sight (ELOS) guidance principle is then proposed by varying the look-ahead distance with the cross-track error such that sideslip in cross tracking can be promptly compensated through vehicle heading amendment. Both simulation and experimental results verify the effectiveness of the proposed methods, which perform better than the conventional line-of-sight (LOS) and integral LOS (ILOS) guidance laws.
How Excitation Conditions Alter the Afterglow Characteristics of CsI:Tl,Sm Microcolumnar Films

Combining high light output with the microcolumnar structure, the CsI:Tl films significantly reduce the need for painful tradeoff between thickness (hence, stopping power) and spatial resolution. But both films and monocrystals share two important deficiencies that hinder their use in many high-speed imaging and computed tomography applications: a persistent afterglow and hysteresis. These properties receive the primary attention of this investigation. In our earlier work, we reported that codoping with Sm2+ brings about a significant reduction in the afterglow of CsI:Tl. Here, focusing on the microcolumnar films, we examine this afterglow-suppressive effect over a wide range of exposure times, from milliseconds to seconds, and at temperatures between 0 °C and 60 °C. Our measurements reveal well-defined dependences on both parameters. At room temperature (20 °C), defined as the normal operating condition, a 10-ms X-ray pulse leaves an afterglow from the standard (Sm-free) CsI:Tl of about 1% at 2 ms after the end of the pulse, changing little as a function of pulselength. Doping with Sm2+, however, reduces that afterglow by at least an order of magnitude, although somewhat less so after longer (100 and 1000 ms) pulses. When we change the temperature, however, we find markedly different behavior. Here, we find that a temperature increase of only 60°, without changing the pulselength, cuts the afterglow of standard CsI:Tl films by a factor of 20. However, films of codoped CsI:Tl,Sm, whose afterglow has already been suppressed by the presence of Sm2+, show much less change as a function of either temperature or pulse duration. It is the presence of Sm2+ that makes the biggest difference. As for hysteresis, we again see an improvement, with the performance of the codoped CsI:Tl,Sm films bettering that of the standard (Sm-free) films. After an exposure of 300 mR, the change in light output falls to within 1% of the original after 1 min, whereas standard CsI:Tl films require 30 min to reach the same level.
Distributed Stochastic Subgradient Projection Algorithms Based on Weight-Balancing over Time-Varying Directed Graphs

We consider a distributed constrained optimization problem over graphs, where cost function of each agent is private. Moreover, we assume that the graphs are time-varying and directed. In order to address such problem, a fully decentralized stochastic subgradient projection algorithm is proposed over time-varying directed graphs. However, since the graphs are directed, the weight matrix may not be a doubly stochastic matrix. Therefore, we overcome this difficulty by using weight-balancing technique. By choosing appropriate step-sizes, we show that iterations of all agents asymptotically converge to some optimal solutions. Further, by our analysis, convergence rate of our proposed algorithm is O(ln Γ/Γ) under local strong convexity, where Γ is the number of iterations. In addition, under local convexity, we prove that our proposed algorithm can converge with rate O(ln Γ/Γ). In addition, we verify the theoretical results through simulations.
The Merck Manual of Diagnosis and Therapy

The world's most widely used medical reference now features expanded clinical focus on each category of disorder, as well as more specific guidance on patient examinations. The thoroughly revised and updated 18th Edition is packed with essential information on diagnosing and treating medical disorders to help medical professionals deliver the best care to their patients. This handy, compact guide was written by a team of clinicians for everyday use. Designed for maximum clinical utility, the new Merck Manual of Diagnosis and Therapy makes it easy to find the right information, right when it is needed. It is a must-have for medical students, residents, practicing physicians, nurses, and allied health professionals. Featuring: * All new "approach" chapters * All-new abstract summaries *341 total chapters *34 completely new chapters *69 new illustrations * New cross-referencing * Two-color presentation * Brand new content on: critical care medicine, metabolic syndrome, acute lung injury, biological warfare and terrorism, SARS, smallpox, and more
Handling negative mentions on social media channels using deep learning*

ABSTRACT Social media channels such as social networks, forum or online blogs have been emerging as major sources from which brands can gather user opinions about their products, especially the negative mentions. This kind of task, popular known as sentiment analysis, has been addressed recently by many deep learning approaches. However, negative mentions on social media have their own language characteristics which require certain adaptation and improvement from existing works for better performance. In this paper, we propose a new architecture for handling negative mentions on social media channels. As compared to the architecture published in our previous work, we expose substantial change in the combination manner of deep neural network layers for better training and classification performance on social-oriented messages. We also propose the way to re-train the pre-trained embedded words for better reflect sentiment terms, introducing the resultant sentimentally-embedded word vectors. Finally, we introduce the concept of a penalty matrix which incurs more reasonable loss function when handling negative mentions. Our experiments on real datasets demonstrated significant improvement.
Quantum Integral Inequalities of Simpson-Type for Strongly Preinvex Functions

In this paper, we establish a new q-integral identity, the result is then used to derive two q-integral inequalities of Simpson-type involving strongly preinvex functions. Some special cases of the obtained results are also considered, it is shown that several new and previously known results can be derived via generalized strongly preinvex functions and quantum integrals.
Towards Optimization of Boosting Models for Formation Lithology Identification

Lithology identification is an indispensable part in geological research and petroleum engineering study. In recent years, several mathematical approaches have been used to improve the accuracy of lithology classification. Based on our earlier work that assessed machine learning models on formation lithology classification, we optimize the boosting approaches to improve the classification ability of our boosting models with the data collected from the Daniudi gas field and Hangjinqi gas field. Three boosting models, namely, AdaBoost, Gradient Tree Boosting, and eXtreme Gradient Boosting, are evaluated with 5-fold cross validation. Regularization is applied to the Gradient Tree Boosting and eXtreme Gradient Boosting to avoid overfitting. After adapting the hyperparameter tuning approach on each boosting model to optimize the parameter set, we use stacking to combine the three optimized models to improve the classification accuracy. Results suggest that the optimized stacked boosting model has better performance concerning the evaluation matrix such as precision, recall, and f1 score compared with the single optimized boosting model. Confusion matrix also shows that the stacked model has better performance in distinguishing sandstone classes.
Opening Remarks ∼ Prospects of very high energy cosmic ray interactions for astroparticle physics

Hadronic interactions of very high energy cosmic rays have been studied in various aspects of motivation. In recent decades, mainly motivated by air shower experiments, modelling of very high energy cosmic ray interactions have been greatly improved together with new data obtained from high energy colliders such as the LHC. Regarding recent rapid progress of multi-messenger astronomy, a precise knowledge on secondary particle production by cosmic rays at very high energy is largely indispensable. This would give us a new insight and new motivation to study minimum bias hadronic interactions of very high energy cosmic rays.
Estimating the parameters in mixtures of circular and spherical distributions

In this thesis we compare various methods for estimating the unknown parameters in mixtures of circular and spherical distributions. We study the von Mises distribution on the circle and the Fisher distribution on the sphere. We propose a new method of estimation based on the characteristic function and compare it with the classical methods based on maximum likelihood and moments. Thus far these methods have only been successfully applied to distributions on the line. Here we show that the extension to circular and spherical distributions is reasonably straightforward and convergence to the final estimates is fairly rapid. We apply these methods to various simulated and real data sets and show that the results obtained for the mixture of two von Mises distributions are satisfactory but generally depend on the sample size and method of estimation used. However, results obtained for the mixture of two Fisher distributions show that maximum likelihood performs best overall.
Broadband Wilkinson power divider based on chebyshev impedance transform method

Broadband impedance matching techniques widely used in microwave circuits. In this study, we proposed a 2-way multi-layer micro strip Wilkinson Power Divider (WPD) circuit matched by Chebyshev Impedance matching technique. The design was chosen at 1 GHz center frequency and as four layers. The design was carried out as 3 dimensions on Advanced Design tool (ADS 2009) which is 3D microwave circuits’ simulation tool. For -20 dB return loss reference level, while the reflection bandwidth was 25% in the basic quarter wave matched WPD, it could be increased up to 132% in the Chebyshev matching. Additionally, for the reference power transmission of -4.3 dB, the transmission bandwidth raised up to %160. In the range, the proposed design could transfer 75% of the input power to both output ports.
Supplementary Material for "The Sonified Music Stand - An Interactive Sonification System for Musicians"

This paper presents the sonified music stand, a novel interface for musicians that provides real-time feedback for professional musicians in an auditory form by means of interactive sonification. Sonifications convey information by using non-speech sound and are a promising means for musicians since they (a) leave the visual sense unoccupied, (b) address the sense of hearing which is already used and in this way further trained, (c) allow to relate feedback information in the same acoustic medium as the musical output, so that dependencies between action and reaction can be better understood. This paper presents a prototype system together with demonstrations of applications that support violinists during musical instrument learning. For that a pair of portable active loudspeaker has been designed for the music stand and a small motion sensor box has been developed to be attached to the bow, hand or hand wrist. The data are sonified in real-time according to different training objectives. We sketch several sonification ideas with sound examples and give a qualitative description of using the system.
Water Use Efficiency and Water Production Function of Corn under Full and Deficit Irrigation in a Cold Semi-arid Environment

Bu calismada, tarla kosullarinda 2005-2006‘dan 2012-2013 yillari arasinda sekiz yilda olculen misir (Zea mays L.) verimleri soguk yari kurak kosullarda Tarimsal Ekolojik Bolge yontemi tarafindan simule edilen verilerle karsilastirilmistir. Misirin potansiyel verimi (Ym), 618 m 3 /da net sulama suyu icin 1 043 kg/da olmustur. Misir icin su uretim fonksiyonu, % 100 ile% 40 arasinda uygulama verimliligi senaryolariyla elde edilmistir. Potansiyel bir misir verimi uretmek icin, sulama suyu gereksinimi, Sirasiyla % 100, 90, 80, 70, 60, 50 ve 40 su uygulama etkinligi altinda 618, 686.7, 772.5, 882.9, 1 030, 1 236, 1 545 m 3 /da bulunmustur. Sonuclar, olculen verimin da basina ortalama 640.4 kg/da oldugu ve 578.4 ila 702.6 kg/da arasinda degistigini gostermistir. Misir uretimi icin uygulanan su ortalama 1056.7 m 3 /da olmustur. Misir ciftliklerinde su kullanim etkinligi (SKE) sekiz yil boyunca ortalama 0.61 kg/m 3 ve su uygulama verimliligi % 51.2 olarak bulunmustur. Soguk yari kurak ortamda misir uretiminde su kullanim verimliligini artirmak icin kisintili sulamanin uygulanabilecegi onerilmektedir.
Noise reinforcement for Lévy processes

In a step reinforced random walk, at each integer time and with a fixed probability p ∈ (0, 1), the walker repeats one of his previous steps chosen uniformly at random, and with complementary probability 1 − p, the walker makes an independent new step with a given distribution. Examples in the literature include the so-called elephant random walk and the shark random swim. We consider here a continuous time analog, when the random walk is replaced by a Levy process. For sub-critical (or admissible) memory parameters p < p c , where p c is related to the Blumenthal-Getoor index of the Levy process, we construct a noise reinforced Levy process. Our main result shows that the step-reinforced random walks corresponding to discrete time skeletons of the Levy process, converge weakly to the noise reinforced Levy process as the time-mesh goes to 0.