Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Cross-Layer Optimization in Real-Time Networked Control Systems

Networked control system (NCS) refers to a set of control loops that are closed over a communication network. In this article, the joint operation of control and networking for NCS is investigated wherein the network serves the sensor-to-controller communication links for multiple stochastic linear time-invariant (LTI) subsystems. The sensors sample packets based on the observed plant state, which they send over a shared multihop network. The network has limited communication resources, which need to be assigned to competing links to support proper control loop operation. In this setup, we formulate an optimization problem to minimize the weighted-sum linear-quadratic-Gaussian cost of all loops, taking into account the admissible sampling, control, congestion control (CC), and scheduling policies. Under some mild assumptions on the sampling frequencies of the control loops and the communication network, we find the joint optimal solution to be given by a certainty equivalence control with a threshold-based sampling policy, as well as a back-pressure-type scheduler with a simple pass-through CC. The interface between network and control loops is identified to be the buffer state of the sensor node, which can be interpreted as network price for sampling a packet from the control perspective. We validate our theoretical claims by simulating NCSs comprised of multiple LTI stochastic control loops communicating over a two-hop cellular network.
RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension

Recent studies have revealed that reading comprehension (RC) systems learn to exploit annotation artifacts and other biases in current datasets. This prevents the community from reliably measuring the progress of RC systems. To address this issue, we introduce R4C, a new task for evaluating RC systems' internal reasoning. R4C requires giving not only answers but also derivations: explanations that justify predicted answers. We present a reliable, crowdsourced framework for scalably annotating RC datasets with derivations. We create and publicly release the R4C dataset, the first, quality-assured dataset consisting of 4.6k questions, each of which is annotated with 3 reference derivations (i.e. 13.8k derivations). Experiments show that our automatic evaluation metrics using multiple reference derivations are reliable, and that R4C assesses different skills from an existing benchmark.
Increasing the Detectability of Phase-Amplitude Coupling

Background: In electrical brain signals such as Local Field Potential (LFP) and Electroencephalogram (EEG), oscillations emerge as a result of neural network activity. The oscillations extend over several frequency bands. Between their dominant components, various couplings can be observed. Of these, Phase-Amplitude Coupling (PAC) is intensively studied in relation to brain function. In the time-frequency domain, however, PAC measurement faces a dilemma in the choice of filter bandwidth. For a frequency m modulating a frequency n, filters narrowly tuned around the latter frequency will miss the modulatory components at frequencies n+m and n-m; wide band tuning will pass increasing levels of noise. New Method: Our CFC measurement uses three identical narrow band filters with center frequencies located on n-m, n, and n+m. The method therefore is free from the bandwidth dilemma. Comparison with Existing Method(s): The method was tested on diagnostic artificial signals modeled on local field potentials and compared with four established PAC detection algorithms. While the proposed method detected the simulated PAC in high frequency resolution, the other methods detected with poor frequency resolution, or completely missed the PAC. Conclusion: Using the proposed triplet-filter banks instead of wideband filtering allows for high resolution detection of PAC. Moreover, the method successfully detected PAC in wide range of modulation frequency. Finally, bandwidth is not chosen subjectively in our new method which makes the comparison of PAC more convenient among different studies.
Modeling of negative protein-protein interactions: methods and experiments

Protein-protein interactions (PPIs) are of fundamental importance for the human body, and the knowledge of their existence can facilitate very important tasks like drug target developing and therapy design. The high-throughput experiments for detecting new PPIs are costly and time-consuming, stressing the need for new computational systems able to generate high-quality PPIs predictions. These systems have to face two main problems: the high incompleteness of the human interactome and the lack of high-quality negative protein-protein interactions (i.e. proteins that are known to not interact). The latter is usually overlooked by the PPIs prediction systems, causing a significant bias in the performances and metrics. In this work, we compare methods for simulating negative knowledge using highly reliable training and test sets. Moreover, we measure the performances of two state-of-the-art systems when very reliable settings are adopted.
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles

The motion planners used in self-driving vehicles need to generate trajectories that are safe, comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior planner, which handles high-level decisions and produces a coarse trajectory, and trajectory planner that generates a smooth, feasible trajectory for the duration of the planning horizon. These planners, however, are typically developed separately, and changes in the behavior planner might affect the trajectory planner in unexpected ways. Furthermore, the final trajectory outputted by the trajectory planner might differ significantly from the one generated by the behavior planner, as they do not share the same objective. In this paper, we propose a jointly learnable behavior and trajectory planner. Unlike most existing learnable motion planners that address either only behavior planning, or use an uninterpretable neural network to represent the entire logic from sensors to driving commands, our approach features an interpretable cost function on top of perception, prediction and vehicle dynamics, and a joint learning algorithm that learns a shared cost function employed by our behavior and trajectory components. Experiments on real-world self-driving data demonstrate that jointly learned planner performs significantly better in terms of both similarity to human driving and other safety metrics, compared to baselines that do not adopt joint behavior and trajectory learning.
Spectral and temporal properties of Compton scattering by mildly relativistic thermal electrons

We have obtained new solutions and methods for the process of thermal Comptonization. We modify the solution to the kinetic equation of Sunyaev and Titarchuk to allow its application up to mildly relativistic electron temperatures and optical depths $\gtrsim {1}$. The solution can be used for spectral fitting of X-ray spectra from astrophysical sources. We also have developed an accurate Monte Carlo method for calculating spectra and timing properties of thermal Comptonization sources. The accuracy of our kinetic equation solution is verified by comparison with the Monte Carlo results. We also compare our results with those of other publicly available methods. Furthermore, based on our Monte Carlo code, we present distributions of the photon emission times and the evolution of the average photon energy for both up and down scattering.
Electrically driven photon emission from individual atomic defects in monolayer WS2

Electron-stimulated photon emission from individual point defects in monolayer WS2 could be visualized with atomic resolution. Quantum dot–like single-photon sources in transition metal dichalcogenides (TMDs) exhibit appealing quantum optical properties but lack a well-defined atomic structure and are subject to large spectral variability. Here, we demonstrate electrically stimulated photon emission from individual atomic defects in monolayer WS2 and directly correlate the emission with the local atomic and electronic structure. Radiative transitions are locally excited by sequential inelastic electron tunneling from a metallic tip into selected discrete defect states in the WS2 bandgap. Coupling to the optical far field is mediated by tip plasmons, which transduce the excess energy into a single photon. The applied tip-sample voltage determines the transition energy. Atomically resolved emission maps of individual point defects closely resemble electronic defect orbitals, the final states of the optical transitions. Inelastic charge carrier injection into localized defect states of two-dimensional materials provides a powerful platform for electrically driven, broadly tunable, atomic-scale single-photon sources.
hlslib: Software Engineering for Hardware Design

High-level synthesis (HLS) tools have brought FPGA development into the mainstream, by allowing programmers to design architectures using familiar languages such as C, C++, and OpenCL. While the move to these languages has brought significant benefits, many aspects of traditional software engineering are still unsupported, or not exploited by developers in practice. Furthermore, designing reconfigurable architectures requires support for hardware constructs, such as FIFOs and shift registers, that are not native to CPU-oriented languages. To address this gap, we have developed hlslib, a collection of software tools, plug-in hardware modules, and code samples, designed to enhance the productivity of HLS developers. The goal of hlslib is two-fold: first, create a community-driven arena of bleeding edge development, which can move quicker, and provides more powerful abstractions than what is provided by vendors; and second, collect a wide range of example codes, both minimal proofs of concept, and larger, real-world applications, that can be reused directly or inspire other work. hlslib is offered as an open source library, containing CMake files, C++ headers, convenience scripts, and examples codes, and is receptive to any contribution that can benefit HLS developers, through general functionality or examples.
K-Potent Matrices-Construction and Applications in Digital Image Encryption

A k-potent matrix is any matrix A, the kth power of which is a linear combination of the identity matrix and A, for example, unipotent, idempotent, and involutary matrices are special k-potent matrices. Such matrices have values in applications to digital image encryption. In order to achieve lossless image decryption, all arithmetic operations are restricted over the integer field. Therefore, algorithms are sought to construct integral k-potent matrices. It turns out that the unique eigenstructure of these matrices provides the key for constructing k-potent matrices systematically. In this paper, we explore the spectral properties of k-potent matrices and applications to digital image encryption. Key-Words: Nilpotent, Idempotent, Involutary, Unipotent, Skewed k-potent Matrix, Diagonalizability, Image Encryption
Diseño de algoritmos inteligentes aplicados a interfaces humano-computador e internet de las cosas

Actualmente dentro del campo de la informática existen diversas aplicaciones que se diseñan para funcionar en ambientes conectados al mundo exterior. Tal característica obliga a reenfocar el análisis y diseño de sistemas desde una perspectiva mas amplia que la convencional. Bajo este entorno el escenario se ha extendido hacia el diseño de aplicaciones sensibles al contexto (Context Aware). Esta amplitud exige que tanto los investigadores como los diseñadores incorporen nuevos elementos (sensores) para que efectivamente una aplicación pueda funcionar conectada tanto al medio ambiente como a las personas. Si bien existen desde hace varias décadas aplicaciones que toman señales del exterior a través de sensores hacia sistemas embebidos, dichas aplicaciones no cuentan en su gran mayoría con algoritmos inteligentes (Artificial Intelligence) y menos aun con acceso a Internet (Cloud Computing y Fog Computing). El proyecto propone la investigación y el desarrollo de aplicaciones híbridas orientadas al uso de sensores, actuadores e interfaces mediante algoritmos y técnicas de inteligencia artificial. La implementación de este tipo de aplicaciones proporcionará mejoras en los sistemas sensibles al contexto actuales gracias al uso de técnicas basadas en IA y además constituirá un primer acercamiento hacia otros ámbitos tales como la robótica, el control de actuadores, brain computer interface, human computer interface, smartcities, smarthome, smartcar, smartgrid, artificial vision, augmented reality, internet of things, internet of mobile things, entre otros.
A case study for e-democracy in Palestine

The world at present is facing a number of real challenges in the face of persistent economic crisis, local conflicts and huge waves of refugees. All of the above are affecting secure access to and completion of peoples voting rights. The relevant technological solutions appear to have matured and have successfully responded to rigorous testing. The need for digital access to election events is probably higher than ever in digital age. The question that remains to be answered is whether all this enough to inspire people to trust the systems and participate amass in e-voting particularly in areas where the political climate might be volatile. Palestinian have been scattered across the world since the late 1940s. This forced diaspora creates particular challenges as the Palestinian Authority (PA) continues to gain international recognition as an emerging state. The PA is experiencing a huge difficulty in enabling its citizens to elect their representative. According to PA officials many countries who are hosting Palestinians as refugees don’t accept the facilitation of elections for representatives to the PA government. Using e-voting systems could offer a solution to overcoming this problem and the PA has been evaluating such systems since 2011. The inspiration for this paper is taken from the results of an extensive survey conducted by the authors to evaluate the response amongst Palestinians around the world to the Palestinian Authority’s decision to fully
STRUCTURES AND THEIR INTEGRAL STOKES DATA

In [16] a description was given of all smooth solutions of the two-function tt*-Toda equations in terms of asymptotic data, holomorphic data, and monodromy data. In this supplementary article we focus on the holomorphic data and its interpretation in quantum cohomology, and enumerate those solutions with integral Stokes data. This leads to a characterization of quantum Dmodules for certain complete intersections of Fano type in weighted projective spaces. 1. The tt*-Toda equations The tt* (topological—anti-topological fusion) equations were introduced by S. Cecotti and C. Vafa in their work on deformations of quantum field theories with N=2 supersymmetry (section 8 of [3], and also [4],[5]). This has led to the development of an area known as tt* geometry ([3],[11],[19]), a generalization of special geometry. Solutions of the tt* equations can be interpreted as pluriharmonic maps with values in the noncompact real symmetric space GLnR/On, or as pluriharmonic maps with values in a certain classifying space of variations of polarized (finite or infinite-dimensional) Hodge structure. Frobenius manifolds with real structure, e.g. quantum cohomology algebras, provide a very special class of solutions “of geometric origin” (see [11]). These special solutions lie at the intersection of p.d. e. theory, integrable systems, and (differential, algebraic, and symplectic) geometry. However, very few concrete examples have been worked out in detail, and their study is just beginning. It is relatively straightforward to obtain local solutions, but these special solutions have (or are expected to have) global properties, and these properties are hard to establish. In [17], [16] a family of global solutions was constructed by relatively elementary p.d. e. methods. In this article we shall describe the special solutions in terms of their holomorphic data. This allows us to obtain — in a very restricted situation — an a fortiori characterization of 2000 Mathematics Subject Classification. Primary 81T40; Secondary 53D45, 35J60.
ORGANIZATIONAL LEARNING AND CONTINUOUS IMPROVEMENT AMONG COMMERCIAL BANKS IN KENYA A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT FOR THE REQUIREMENTS OF THE DEGREE OF MASTER OF BUSINESS ADMINISTRATION, AT THE UNIVERSITY OF NAIROBI

The purpose of this research is to determine the factors that influence organizational learning and the impact of organizational learning on continuous improvement among commercial banks in Kenya. The research addresses the immediate need to explore ways to design organizations so that they fulfill their function effectively and encourage people to reach their full potential. Extensive research was contacted among 44 commercial banks operating in Kenya by administering questionnaires to one person from each bank. This research will provide valuable information regarding how organizations are coming up with systems thinking, team learning, shared visions, personal mastery and organizational corporate culture. The analysis shows that organizational learning influences continuous improvement. Further research can be contacted to find out what influences continuous improvement.
Equilibrium and Thermodynamics Studies of Fe 3 + Ion Removal from Aqueous Solutions Using Periwinkle Shell Activated Carbon

Iron (III) adsorption from aqueous solutions unto periwinkle shell carbon (PSC) was studied using batch experiments. Activated periwinkle shell carbon was prepared (pyrolysed at 300 ̊C and activated with nitric acid) and characterized to determine its physiochemical properties. Batch adsorption experiments were conducted to investigate the effects of process parameters (contact time, particle size, carbon dosage and pH of stock solution) on adsorption rate. Adsorption kinetics was tested using pseudo first and second order models. Adsorption Isotherms were analyzed using the Langmuir, Freundlich and Temkin isotherms while Thermodynamics parameters such as Enthalpy change (∆H ̊), Entropy change (∆S ̊) and Gibbs-free energy change (∆G ̊) were determined. Results showed that adsorption rate increase with increase in contact time, adsorbent dose and pH and decreased with increase in particle size. Batch adsorption Kinetics experiments revealed that the mechanism of adsorption followed pseudo-second-order kinetic model. Isotherm data showed that the Langmuir isotherm accurately described the adsorption data indicating that adsorption process was mainly monolayer on a homogeneous adsorbent surface. Thermodynamic parameters results showed that adsorption process was endothermic with Enthalpy change (∆H ̊): 222.91 kJ/mol; a positive Entropy change (∆S ̊) of 19.19 kJ/mol, indicating an increase in the degree of freedom (or disorder) of the adsorbed species and a negative Gibb’s free energy (∆G ̊) at all temperature indicating that the adsorption process was spontaneous and favorable at high temperature.
RUNNING TITLE: EFFECTS OF ACTIVITY INTERRUPTIONS BY PAIN

a Research Group Health Psychology, University of Leuven, Tiensestraat 102 box 3726, 3000 Leuven, Belgium b Clinical Psychological Science, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands c Centre for Health and Medical Psychology, Örebro University, Fakultetsgatan 1, 701 82 Örebro, Sweden d Department of Experimental-Clinical and Health Psychology, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium.
The the determinants of office rents in accra , ghana By noah

In Ghana, real estate is one of the largest components of wealth. Housing in particular is a major motivation for household saving and significantly influences household consumption (Karley 2008). The ratio of commercial real estate is also growing gradually within this sector. Many of the office buildings available before the 1980’s economic restructuring were state owned. However, these buildings were not able to meet users’ demand and in many cases fell short of users’ requirements. The increased demand for office space led to sharp increases in rents. In the short term, residential buildings were converted into other uses including offices, retailing and even for industrial purposes. Yet, this did not slow down rising rents, and in some cases the premises posed health and safety hazards for users.
Success or Failure: Selectivity and Reasons of Return Migration in Sichuan and Anhui, China

a research Abstract: In this paper we examine urban ^ rural return migration in China. We argue that the traditional success ^ failure dichotomy approach used for analyzing return migration is inadequate and that it must be expanded to address better the institutional context of the transitional economy. Using an empirical study of Sichuan and Anhui provinces, we analyze the selectivity of return migrants and their reasons for return, focusing not only on how returnees compare with continuing migrants, but also on their decisionmaking. The analysis indicates that returnees are negatively selected among migrants and suggests that failure migrants are more prevalent than are typically portrayed in the literature. The results also highlight family demand as an important reason for return. These findings suggest that migrants' institutional and social inferiority in the city undermines their likelihood to succeed in the destination and reinforces their desire to return when family needs arise. Our analysis raises questions about the optimism of existing studies about the contribution of return migrants in China's countryside. Abstract. In this paper we examine urban^rural return migration in China. We argue that the tradi- tional success^failure dichotomy approach used for analyzing return migration is inadequate and that it must be expanded to address better the institutional context of the transitional economy. Using an empirical study of Sichuan and Anhui provinces, we analyze the selectivity of return migrants and their reasons for return, focusing not only on how returnees compare with continuing migrants, but also on their decisionmaking. The analysis indicates that returnees are negatively selected among migrants and suggests that failure migrants are more prevalent than are typically portrayed in the literature. The results also highlight family demand as an important reason for return. These findings suggest that migrants’ institutional and social inferiority in the city undermines their likelihood to succeed in the destination and reinforces their desire to return when family needs arise. Our analysis raises questions about the optimism of existing studies about the contribution of return migrants in China’s countryside.
INTEGRATION OF MIGRANTS IN THE EUROPEAN UNION WITH REFERENCE TO CROATIA : POSITION PAPER OF THE INSTITUTE FOR MIGRATION AND ETHNIC STUDIES INTEGRATION OF MIGRANTS – DEFINITION OF THE CONCEPT

Due to the increased migration and particularly refugee flows in 2015, the issue of integration imposes itself as key in all European countries, and particularly in those that have accepted the greatest number of immigrants.1 Despite the fact that the prevailing perception in the majority of Western European countries is that they do not fall into the category of being immigration countries, the share of immigrants in the total population in some of them is even higher than their share in those that are regarded as classical cases of being immigration countries.2 Therefore, apart from managing migration flows, growing emphasis is being placed on the integration of (im)migrant groups, which has recently been becoming a part of the public policy and strategic documents of the European Union.