Miracle-dz/UniFAR-FTUs huggingface dataset:
Semiparametric Reinforcement Learning

We introduce a semiparametric approach to deep reinforcement learning inspired by complementary learning systems theory in cognitive neuroscience. Our approach allows a neural network to integrate nonparametric, episodic memory-based computations with parametric statistical learning in an end-to-end fashion. We give a deep Q network access to intermediate and final results of a differentiable approximation to k-nearest-neighbors performed on a dictionary of historic state-action embeddings. Our method displays the early-learning advantage associated with episodic memory-based algorithms while mitigating the asymptotic performance disadvantage suffered by such approaches. In several cases we find that our model learns even more quickly from few examples than pure kNN-based approaches. Analysis shows that our semiparametric algorithm relies heavily on the kNN output early on and less so as training progresses, which is consistent with complementary learning systems theory.
Improved Genetic Algorithm to Solve Asymmetric Traveling Salesman Problem

The asymmetric traveling salesman problem (ATSP) is a combinatorial problem of great importance where the cost matrix is not symmetric, which complicates its resolution. The genetic algorithms (GAs) are a meta-heuristics methods used to solve transportation problems that have proved their effectiveness to obtain good results. However, improvements can be made by adapting the crossover operator as a primordial operator in GAs. In this work, we propose an adapted XIM crossover operator for the ATSP in order to improve the optimal solution obtained by GAs. Numerical simulations are performed and discussed for different series of standard instances showing the improvement of the optimal solution by the proposed genetic operator.
Stabilization of nonlinear RLC circuits: power shaping and passivation

In this paper we prove that for a class of RLC circuits with convex energy function and weak electromagnetic coupling it is possible to "add a differentiation" to the port terminals preserving passivity - with a new storage function that is directly related to the circuit power. The result is of interest in circuit theory, but also has applications in control problems as it suggests the paradigm of power shaping stabilization as an alternative to the well-known method of energy shaping. We show in the paper that, in contrast with energy shaping designs, power shaping is not restricted to systems without pervasive dissipation and naturally allows to add "derivative" actions in the control. These important features, that stymie the applicability of energy shaping control, make power shaping very practically appealing, as illustrated with examples in the paper. To establish our results we exploit the geometric property that voltages and currents in RLC circuits live in orthogonal spaces, i.e., Tellegen's theorem, and heavily rely on the seminal paper of Brayton and Moser in 1964.
The Lyman alpha bulge of Jupiter: Effects of non-thermal velocity field

In this preliminary study, we outline for the first time the effect of non-thermal line broadening processes (turbulence, random waves, convection ,.) on the shape and intensity of the H Ly-α line resonance scattered from the atmosphere of Jupiter and we show how a non-thermal velocity field, confined to the bulge region, in the upper atmosphere of Jupiter, may account for most of the H Ly-α bulge features. Both the shape and the brightness of the Ly-α line from the bulge region as reported by the IUE instrument and the Voyager UV Spectrometer can be recovered assuming resonant scattering with a total atomic hydrogen [H]∼ 4 × 1017 cm−2, and a non-thermal component [H]∼ 2 × 1015 cm−2 above the thermopause.
Business Model Ecosystem Analysis Case Study of Alphabet’s IoT Strategy

Alphabet Inc., the holding company of companies like Google or Nest, stands for a rather secretive public relations strategy, with limited informational value of public announced statements and interviews of executives, especially when it comes to the strategy of its investments in the field of the Internet of Things. One of these investments is the company Nest, a developer of intelligent devices for private households and of the associated platform. This business case will be utilized as the centerpiece of the performed study, with the aim to describe and analyze the strategic approach of Alphabet’s Internet of Things strategy. Different architectural and business model frameworks will be discussed and applied for the in-depth study of the chosen case. The secondary focus will be on the other initiatives of Alphabet in the internet of things and how these may affect the development of Nest in its function of the holding structure. Ethics and sustainability will be discussed in terms of the security and privacy of users and the data they share through the use of intelligent and interconnected devices and applications. It will be pointed out, which issues and concerns arise with the spread of novel concepts in the Internet of Things. The findings of this thesis are of a tentative nature and need to be treated with caution, due to the lack of reliable information and the use of secondary data as reports of company insiders. This paper has been written as the degree project in the course Entrepreneurship and Innovation Management. With this thesis the author intends to obtain a Master of Science degree at the university KTH Royal Institute of Technology, Stockholm.
In Vitro Effects of Ascorbic Acid and Alpha-tocopherol on Serum Malondialdehyde formation in Diabetic Patients

Free radicals are responsible for onset and progression of diabetes. The link between oxidative stress and secondary complications of diabetes has been also documented. In present study we have studied In vitro effect of ascorbic acid and alpha tocopherol in terms of Malondialdehyde (MDA) formation in blood serum from diabetic as well as non-diabetic persons. Total 60 blood samples from average age group of 48.12 + 11.60 years were studied. Each sample is fractionated into control and experimental group for ascorbic acid and alpha tocopherol respectively. Given fractions were incubated for 1 hr, 6 hr and 24 hr duration for studying time dependent results. There was a time dependent increase in malondialdehyde (MDA) in all control as well as experimental groups. But there found highly significant (p<0.001) decline in rate of malondialdehyde (MDA) formation in both experimental group as compared to their respective controls. In conclusion in vitro supplementation of antioxidant vitamins has a potential to minimize the oxidative stress hence recommended for their use in invitro systems.
Packing of flexible 2D materials in vesicles

To understand the mechanics of cellular packing of two-dimensional (2D) materials, we perform systematic molecular dynamics simulations and theoretical analysis to investigate the packing of a flexible circular sheet in a spherical vesicle and the 2D packing problem of a strip in a cylindrical vesicle. Depending on the system dimensions and the bending rigidity ratio between the confined sheet and the vesicle membrane, a variety of packing morphologies are observed, including a conical shape, a shape of three-fold symmetry, a cylindrically curved shape, an axisymmetrically buckled shape, as well as the initial circular shape. A set of buckling analyses lead to phase diagrams of the packing morphologies of the encapsulated sheets. These results may have important implications on the mechanism of intracellular packing and toxicity of 2D materials.
Text to Image Synthesis Using Stacked Generative Adversarial Networks

Motivation. Human beings are quickly able to conjure and imagine images related to natural language descriptions. For example, when you read a story about a sunny field full of flowers, an image of a beautiful field with blossoming flowers might pop into your head. Artificial synthesis of images using text descriptions or human cues could have profound applications in visual editing, animation, and digital design. Related Work. In order to tackle this problem, we utilize the stacked Generative Adversarial Network (S-GAN) architecture proposed by (ZXL+16). Stacked GANs improve upon an earlier DC-GAN architecture for text-to-image synthesis proposed by (RAY+16), which described how to utilize GANs to generate images by conditioning on text descriptions. However, the synthesized images from DCGANs did not great fidelity or the ability to produce output at high-resolution. Stack-GANs attempt to improve the synthesis process by using a two-stage procedure, each of which is it’s own manageable GAN implementation. The first stage, stage-I, learns to produce the rough shape and primary colors of the synthesized object conditioned on a given text description, and generates background regions from a random noise vector sampled from a prior distribution. The generated low resolution image is coarse and of lower fidelity than provided texts description. It may eve have entire objects or segments missing. However, to improve fidelity, a second GAN is stacked on top: a stage-II GAN, which aims to generate realistic high resolution images conditioned on both the low resolution image as well as the provided text description.
GEOACOUSTIC MATCHED-FIELD INVERSION USING A VERTICA L VECTOR SENSOR ARRAY

Vector sensors measure the acoustic pressure and the particle velocity components. This type of sensor has the ability to provide information in both vertical and azimuthal direction allowing increased directivity. These characteristics have been explored by many authors and most of the studies on vector sensors found in literature are related to direction of arrival (DOA) estimation. However, assembled into an array, a Vector Sensor Array (VSA) improves spatial filtering capabilities and can be used with advantage in other applications such as geoacoustic inversion. In this paper it will be shown that a reliable estimation of ocean bottom parameters, such as sediment compressional speed, density and compressional attenuation, can be obtained using high-frequency signals and a small aperture vertical VSA. The introduction of particle velocity on matched-field processing (MFP) techniques is going to be presented. It will be seen how MFP, usually done with acoustic pressure, can be adapted in order to incorporate the three components of the particle velocity. Comparisons between several processors based either in individual particle velocity components or using all the VSA outputs, are made for simulated and experimental data. The quaternion model, which is founded on hypercomplex algebra, thus more appropriate to represent the 4 dimensional VSA data, is also presented in the MFP context. A novel ray tracing model is used to generate field replicas that include both the acoustic pressure and the particle velocity outputs. The data considered herein was acquired by a four element vertical VSA in the 8-14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I. , Hawaii (USA). The results shows that, when the particle velocity is included it can significantly increase the resolution of bottom properties estimation and in some cases a similar result is obtained using only the vertical component of the particle velocity.
Derivation of extended Maxwell Garnett formula for carbon-nanotube-doped nematic liquid crystal

A numerical effort for modelling the dielectric behaviour of the novel binary mixture of nematic liquid crystal and carbon nanotube (NLC:CNT) has been carried out using the Maxwell Garnett theory. The CNTs are treated as conductive anisotropic inclusions while the NLCs as dielectric isotropic or anisotropic matrix depending on temperature. Thus, the numerical expressions for the dielectric anisotropy for the scenarios of aligned CNTs in the NLC matrix of either nematic or isotropic phases have been derived, and the results show that the Debye parameter of CNT at optic limit seems to be the decisive factor in the enhancement of the dielectric anisotropy of the nematic system.
Asteroseismic modelling of the two F-type hybrid pulsators KIC 10080943A and KIC 10080943B

Context. Pulsating binary stars are ideal targets for testing the theory of stellar structure and evolution. Fundamental parameters can be derived to high precision from binary modelling and provide crucial constraints for seismic modelling. High-order gravity modes are sensitive to the conditions near the convective core and therefore allow for a determination of parameters describing interior physics, especially the convective-core overshooting parameter. KIC 10080943 is a binary system that contains two gravity- and pressure-mode hybrid pulsators. A detailed observational study has provided fundamental and seismic parameters for both components. Aims. We aim to find a model that is able to predict the observed g -mode period spacings and stellar parameters of both components of KIC 10080943. Methods. By calculating model grids with the stellar evolution code MESA and the seismic code GYRE, we can compare theoretical properties to the observed mean period spacing and position in the Hertzsprung-Russell diagram. Results. The masses of our best models are somewhat below the values estimated from binarity, which is a consequence of the low observed mean g -mode period spacing. We find that the amount of core overshooting and diffusive mixing can be well constrained by the equal-age requirement for the two stars, however, we find no significant difference for different shapes of core overshooting. The measured rotation rates are within the limit of validity for the first-order perturbation approximation. We can find a good fit by using the traditional approximation for the pulsations, when taking slightly younger models with a higher asymptotic period spacing. This is because the zonal modes experience a slight shift due to the Coriolis force, which the first-order perturbation approximation ignores.
FINITE DIMENSIONS DEFINED BY MEANS OF m-COVERINGS

We introduce and investigate finite dimensions (m, n)-dim defined by means of m-coverings. These dimensions generalize the Lebesgue dimension: dim = (2, 1)-dim. If n < m and (m, n)-dimX < ∞, then X is weakly infinite-dimensional in the sense of Smirnov. Introduction In [7] there were introduced classes of G-C-spaces and m-G-C-space, where G is a class of simplicial complexes and m ≥ 2 is an integer. Partial cases of these classes were considered in [8], where (m,n)-C-spaces were defined (m ≥ n ≥ 1). Let (m,n)-C be the class of all (m,n)-C-spaces. Then all classes (m,n)-C are intermediate between the class wid = (2, 1)-C = (n + 1, n)-C of all weakly infinitedimensional spaces in the sense of Smirnov and the class C of all C-spaces in the sense of Haver [9], Addis and Gresham [1]. For example, wid = (2, 1)-C ⊃ (3, 1)-C ⊃ · · · ⊃ (m, 1)-C ⊃ · · · ⊃ C. Here we define new dimension functions: (m,n)-dim (Definition 2.8). From definitions it follows that (m,n)-dimX < ∞⇒ X ∈ (m,n)-C. (0.1) For every normal space X we have (2, 1)-dimX = dimX (0.2) in view of the partition theorem. For every metrizable space we have (Theorem 3.7) (m,n)-dimX ≤ dimX (0.3) 2010 AMS Subject Classification: 54F45
Non-Linear Matters: Auxetic Surfaces

Auxetic structures exhibiting non-linear buckling are a prevalent research topic in the material sciences due to the ability to tune their reversible actuation, porosity, and negative Poisson’s ratio. However, the research is limited to feature sizes at scales below 10 mm2, and to date, there are no available efficient design and prototyping methods for architectural designers. Our study develops design principles and workflow methods to transform standard materials into auxetic surfaces at an architectural scale. The auxetic behavior is accomplished through buckling and hinging by subtracting from a homogeneous material to create perforated patterns. The form of the perforations, including shape, scale, and spacing, determines the behavior of multiple compliant "hinges" generating novel patterns that include scaling and tweening transformations. An analytical method was introduced to generate hinge designs in four-fold symmetric structures that approximate non-linear buckling. The digital workflow integrates a parametric geometry model with non-linear finite element analysis (FEA) and physical prototypes to rapidly and accurately design and fabricate auxetic materials. A robotic 6-axis waterjet allowed for rapid production while maintaining needed tolerances. Fabrication methods allowed for spatially complex shaping, thus broadening the design scope of transformative auxetic material systems by including graphical and topographical biases. The work culminated in a large-scale fully actuated and digitally controlled installation. It was comprised of auxetic surfaces that displayed different degrees of porosity, contracting and expanding while actuated electromechanically. The results provide a promising application for the rapid design of non-linear auxetic materials at scales complimentary to architectural products.
APPLYING DISTRIBUTIONAL SEMANTICS TO ENHANCE CLASSIFYING EMOTIONS

Most of the recent researches have been carried out to analyse sentiment and emotions found in English texts, where few studies have been conducted on Arabic contents, which have been focused on analysing the sentiment as positive and negative, instead of the different emotions’ classes. Therefore this paper has focused on analysing different six emotions’ classes in Arabic contents, especially Arabic tweets which have unstructured nature that make it challenging task compared to the formal structured contents found in Arabic journals and books. On the other hand, the recent developments in the distributional sematic models, have encouraged testing the effect of the distributional measures on the classification process, which was not investigated by any other classification-related studies for analysing Arabic texts. As a result, the model has successfully improved the average accuracy to more than 86% using Support Vector Machine (SVM) compared to the different sentiments and emotions studies for classifying Arabic texts through the developed semi-supervised approach which has employed the contextual and the co-occurrence information from a large amount of unlabelled dataset. In addition to the different remarkable achieved results, the model has recorded a high average accuracy, 85.30%, after removing the labels from the unlabelled contextual information which was used in the labelled dataset during the classification process. Moreover, due to the unstructured nature of Twitter contents, a general set of pre-processing techniques for Arabic texts was found which has resulted in increasing the accuracy of the six emotions’ classes to 85.95% while employing the contextual information from the unlabelled dataset.
ALGORITHMIC ASPECTS OF RESOURCE ALLOCATION IN COGNITIVE RADIO WIRELESS NETWORKS

Wireless networking is a critical component of today’s internet infrastructure. Two examples of important wireless internet infrastructure are long distance network backbone links and last-mile solutions to remote areas. Wireless technology already supplies a wide variety of consumer solutions including analog television channels (TVWS), cellular infrastructure for massive scale real-time communication, and computer networking for seamless global connectivity. Worldwide, there are an estimated 2.5B internet users and 6B cellular phone subscribersand those numbers are steadily growing. Sufficient capacity for divergent wireless applications, along with their growing users, calls for a more efficient use of bandwidth. We present multiple resource allocation algorithms to address this challenge in various aspects of wireless networking. Each algorithm focuses on a single resource of wireless networking: antenna beam sector activation, directional antenna beam bearings and duration, joint routing and channel selection, and link-channel allocation. In terms of computation and memory, our topology control algorithms provide near optimal performance with significantly lower cost. For each algorithm, a rich set of simulation scenarios is presented that compare our novel algorithms performance to the optimal solution. Ultimately, we present a topology control algorithm that provides an efficient solution to the channel rental problem: finding the most cost-effective set of communication channels (for a wireless mesh network) at a minimum performance guarantee. This problem occurs in high-density traditional wireless networking, cellular networking, and rural sparse networking with last mile internet connectivity; topology control algorithms are well suited for all applications of wireless technology. These algorithms are shown to be robust against various network challenges including topology, frequency availability, and interference.
Left Lower Quadrant Pain-Suspected Diverticulitis

Procedure Appropriateness Category Relative Radiation Level CT abdomen and pelvis with IV contrast Usually Appropriate ☢☢☢ CT abdomen and pelvis without IV contrast May Be Appropriate ☢☢☢ MRI abdomen and pelvis without and with IV contrast May Be Appropriate O MRI abdomen and pelvis without IV contrast May Be Appropriate O US abdomen transabdominal May Be Appropriate O CT abdomen and pelvis without and with IV contrast Usually Not Appropriate ☢☢☢☢ Fluoroscopy contrast enema Usually Not Appropriate ☢☢☢ Radiography abdomen and pelvis Usually Not Appropriate ☢☢☢ US pelvis transvaginal Usually Not Appropriate O
sprocket: Open-Source Voice Conversion Software

Statistical voice conversion (VC) is a technique to convert spe-ciﬁc non-or paralinguistic information while keeping linguistic information unchanged, and speaker conversion has been studied as a typical application of VC for a few decades. To better understand various VC techniques using a freely available common dataset, the Voice Conversion Challenge (VCC) was launched in 2016 and the 2nd challenge was held in 2018. As one of the baseline systems for VCC 2018, we developed open-source VC software called “sprocket”, in which not only conventional techniques, such as a trajectory-based conversion method using a Gaussian mixture model (GMM) and a vocoder-based conversion framework but also recently developed techniques, such as a vocoder-free VC framework, have been implemented. Using sprocket, it is possible to 1) easily reproduce converted voices using the VCC datasets and 2) develop VC systems using other parallel speech datasets with fundamental VC functions, such as acoustic feature extraction, time alignment between the source and target features, GMM training, feature conversion, and waveform generation. In this paper, we describe 1) the technical details and use of sprocket, 2) the development of the baseline systems for the HUB and SPOKE tasks of VCC 2018 using sprocket, and 3) the performance of sprocket as a VC system by demonstrating results for our developed baseline systems in VCC 2018.
Hepato-preventive Activity of Camel Milk Against CCl4-Induced Lesions in Mice

This study was aimed at evaluating the potential effects of a mice exposure to CCl4 single dose on liver tissue and potent preventive effects of camel milk (CM) orally treated by gavage. Additionally, CCl4 was administered by intra-peretonial injection at day 14. Administration of CCl4 caused an increase in lipid peroxidation and a decrease in superoxide dismutase, catalase, glutathione peroxidase activities and GSH levels in liver. Moreover, CCl4 caused a distinguished rise of liver level markers (AST, ALT, ALP, LDH, E¤-GT), TG, TC, and LDL-Ch but a reduced levels of HDL-Ch. In contrast, no such harms or biochemical changes were found in mice treated with camel milk against typically observed changes in CCl4-treated animals. These findings strongly prove that beneficial effects of Camel Milk clearly shown through the reduction of the CCl4 induced related damages and oxidative stress.