Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-temporal multi-granularity : modelling and implementation challenges

Multiple spatial and temporal granularities are essential to extract signicant knowledge from datasets at dierent levels of detail: they enable to zoom-in and zoom-out a dataset, enhancing the data modelling exibility and being instrumental to boost the analysis of information. Implementing granularities poses several interesting problems. Specically, in this paper we analyse the issues involved by enhancing a data model and a query language with spatio-temporal multi-granularity, and we gure out ecacious solutions to address all of them. In our exposition, we investigate proper representa- tions for the spatial and the temporal domains; then we conceive an appropriate design for granules and granularities, and for multi-granular values. In particular, mutual relationships among granular- ities and how they aect granularities design is discussed according to their inuence on data access and considering the application of multi-granular conversions. Afterward, we dedicated to the design of multi-granular spatio-temporal conversions, discussing the multiple ways in which they aect data usability and envisaging how the design of a multi-granular model and query language may guarantee such an fundamental property, reducing uncertainty on the represented values, combining concepts like topologically consistent transformation, probability distributions, invertibility and quasi-invertibility properties. In our discussion, we are inuenced
Current Understanding on Antihepatocarcinoma Effects of Xiao Chai Hu Tang and Its Constituents

Xiao Chai Hu Tang (XCHT), a compound formula originally recorded in an ancient Chinese medical book Shanghanlun, has been used to treat chronic liver diseases for a long period of time in China. Although extensive studies have been demonstrated the efficacy of this formula to treat chronic hepatitis, hepatic fibrosis, and hepatocarcinoma, how it works against these diseases still awaits full understanding. Here, we firstly present an overview arranging from the entire formula to mechanism studies of single herb in XCHT and their active components, from a new perspective of “separation study,” and we tried our best to both detailedly and systematically organize the antihepatocarcinoma effects of it, hoping that the review will facilitate the strive on elucidating how XCHT elicits its antihepatocarcinoma role.
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing

The alternating direction method of multipliers (ADMM) is an important tool for solving complex optimization problems, but it involves minimization sub-steps that are often difficult to solve efficiently. The Primal-Dual Hybrid Gradient (PDHG) method is a powerful alternative that often has simpler sub-steps than ADMM, thus producing lower complexity solvers. Despite the flexibility of this method, PDHG is often impractical because it requires the careful choice of multiple stepsize parameters. There is often no intuitive way to choose these parameters to maximize efficiency, or even achieve convergence. We propose self-adaptive stepsize rules that automatically tune PDHG parameters for optimal convergence. We rigorously analyze our methods, and identify convergence rates. Numerical experiments show that adaptive PDHG has strong advantages over non-adaptive methods in terms of both efficiency and simplicity for the user.
The effects of improved survival on fertility: A reassessment

The purpose of this chapter is to reassesses mortality-fertility links in the context of less developed countries. In the first section the author examines the nature of pretransitional reproductive regimes. He then describes the massive disruption to these regimes caused by the mortality declines in the early half of the 20th century and follows this account by distilling explanatory lessons from the evidence about fertility transitions in the second half of that century. He then assembles these building blocks in support of the conclusion that demographer Kingsley Davis who states that large mortality declines will stimulate corresponding adjustments in fertility was essentially correct. Mortality decline is indeed the common underlying cause – both necessary and sufficient – of the fertility declines that have swept across most of the developing world in the past 40 years. (excerpt modified)
Optical Properties of Metal Nanoparticles with Arbitrary Shapes

We have studied the optical properties of metallic nanoparticles with arbitrary shape. We performed theoretical calculations of the absorption, extinction, and scattering efficiencies, which can be directly compared with experiments, using the discrete dipole approximation (DDA). In this work, the main features in the optical spectra have been investigated depending of the geometry and size of the nanoparticles. The origin of the optical spectra are discussed in terms of the size, shape, and material properties of each nanoparticle, showing that a nanoparticle can be distinguish by its optical signature.
A survey of Cyber Attack Detection Strategies

Homeland security field deals with diverse subjects, audio processing, video surveillance, image detection, geolocation determination, and cyber attack detection. Audio processing and video surveillance area are significant for public places safety and land border area. However the big threat for homeland security is cyber attacks. Cyber terror attacks and cyber crime attacks may move over virtual networks and can get every home. Nowadays, we consider the homeland security field however we set the cyber attack detection area the highest priority in our research. This paper introduces the overview of the state of the art in cyber attack detection strategies.
Event-driven transient error propagation: A scalable and accurate soft error rate estimation approach

Fast and accurate soft error vulnerability assessment is an integral part of cost-effective robust system design. The de facto approach is expensive fault simulation or emulation in which the error is injected in random bits and cycles, and then the effect is simulated for millions of cycles. In this paper, we propose a novel alternative approach to obtain the soft error vulnerability by integrating transient error propagation in an event-driven gate-level logic simulator which captures the combined effect of various masking factors. By carefully combining various generated errors at different cycles, in one pass all the error generation and propagation effects across all bits and all cycles are analyzed. This enables us to drastically reduce the runtime while maintaining the accuracy compared to statistical fault injection.
Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

A simple measure of the uncertainty associated with using radar-derived rainfall estimates as “truth” has been introduced to the Numerical Weather Prediction (NWP) verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radarcomposite were used. The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.
Turning an interactive tool implemented in Haskell into a web application – An experience report

At the Open University, The Netherlands, we are developing interactive exercise assistants that give good feedback to students trying to solve mathematical or logical exercises. To simplify installing, maintaining, and adapting the tools, and to improve reporting facilities, we have turned our tools into web applications. Since our tools are implemented in Haskell, this implies that we have to be able to connect an interactive Haskell application to the web. We have developed an architecture that makes it possible to change an application written in Haskell into a light-weight webservice for an Ajax-style web-based application. In this paper, we discuss the various possibilities to combine Haskell and a web-based application. We investigate the advantages and disadvantages of the chosen architecture with respect to changes in the interface of the tool written in Haskell. Figure 1: The equation solver
New Bounds on the Expected Length of Optimal One-to-One Codes

In this correspondence, we consider one-to-one encodings for a discrete memoryless source, which are "one-shot" encodings associating a distinct codeword with each source symbol. Such encodings could be employed when only a single source symbol rather than a sequence of source symbols needs to be transmitted. For example, such a situation can arise when the last message must be acknowledged before the next message can be transmitted. We consider two slightly different types of one-to-one encodings (depending on whether the empty codeword is used or not) and obtain lower and upper bounds on the expected length of optimal one-to-one codes. We first give an extension of a known tight lower bound on the expected length of optimal one-to-one codes for the case that the the size of the source alphabet is finite and partial information about the source symbol probabilities is available. As expected, our lower bound is no less than the previously known lower bound obtained without side information about the source symbol probabilities. We then consider the case that the source entropy is available and derive arbitrarily tight lower bounds on the expected length of optimal one-to-one codes. We also derive arbitrarily tight lower bounds for the case that the source entropy and the probability of the most likely source symbol are available. Finally, given that the probability of the most likely source symbol is available, we obtain an upper bound on the expected length of optimal one-to-one codes. Our upper bound is tighter than the best upper bound known in the literature
A robust recognition approach in eye-based dwell-free typing

Alternative form of text entry is a tremendous benefit for a subset of physically challenged people, spurning the development of many assistive technologies. However, speed of text entry with these methods is still a critical problem. Eye gaze technologies have potential for text entry, but still tend to relatively slow. Recently dwell-free eye-typing systems have been proposed, but can be vulnerable to some common text entry problems, such as selection of the wrong character. In this paper, we propose a recognition approach for inferring the words which the user intends to type. The method is robust to missing letters and even when a neighboring character on the keyboard is incorrectly selected. Simulation and experiments results suggest that our proposed approach has better accuracy and more resilience to text entry errors than currently proposed dwell-free systems.
Semi-Supervised Learning for Quantitative Structure-Activity Modeling

In this study, we compare the performance of semi-supervised and supervised machine learning methods applied to various problems of modeling Quantitative Structure Activity Relationship (QSAR) in sets of chemical compounds. Semi-supervised learning utilizes unlabeled data in addition to labeled data with the goal of building better predictive models than can be learned by using labeled data alone. Typically, labeled QSAR datasets contain tens to hundreds of compounds, while unlabeled data are easily accessible via public databases containing thousands of chemical compounds: this makes QSAR modeling an attractive domain for the application of semi-supervised learning. We tested four different semi-supervised learning algorithms on three different datasets and compared them to five commonly used supervised learning algorithms. While adding unlabeled data does help for certain pairings of dataset and method, semi-supervised learning is not clearly superior to supervised learning across the QSAR classification problems addressed by this study. Povzetek: Metode delno-nadzorovanega ucenja smo testirali na razlicnih podatkih iz domene kvantitativnega modeliranja razmerja med strukturo in aktivnostjo kemicnih spojin (angl. Quantitative Structure Activity Relationship, oziroma QSAR).
Solution of Differential - Algebraic Equation Systems Using Neural Networks

In this paper, the solution of differential algebraic equations (DAES) is obtained using neural networks. The goal is to obtain accurate solution with reduced calculus effort by comparing the solution of the DAES obtained from Pade approximation and neural network method, the solution of DAE system is computed by feedforward neural network (FFNN). The solution of the neural network approach to this problem is very close to the exact solution. An illustrative numerical method is presented for the proposed method.
On the transmission capacity of wireless multi-channel ad hoc networks with local FDMA scheduling

The problem of the capacity of multi-channel interference-limited ad hoc networks with local frequency planning is examined in the transmission capacity framework. Bounds on outage and transmission capacity are given. If local frequency planning, i.e., frequency domain orthogonalization of neighbors in the communication range, is employed, transmission capacity can be significantly improved. The gain on the transmission capacity depends on the node density and is found to be a factor of 1.35 to 13 for a path loss attenuation α = 4 and outage probability greater than 0.01. A design insight is, that, if frequency planning in the communication range of nodes is employed, low node densities call for lower spectral efficiencies, while at high node densities higher spectral efficiencies increase the capacity of the network.
A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem

cheduling problems are difficult types of production arrangement problems that enumerated among NP-Complete problems. Some of evolutionary algorithms such as Genetic Algorithm, Ant Colony Optimization etc. have been used to solve this problem. In new years, Artificial Immune Algorithm is used to solve optimization problems such as routing and scheduling. One of complex scheduling problems is Job-shop Scheduling problem. In this article we use immune system concepts of human body, to implement a new artificial immune algorithm for solving Job-shop scheduling problem. A new population generation method was proposed based on G&T algorithm. We use two mutation methods, namely Shift Change method and Inverse method in Job-shop scheduling for first time. Moreover, we describe a vaccination method named MCV, to make maximum advance in solutions, and then achieve to more than one optimal solution concurrently and release from local optimum. Finally, we test our method on the very famous benchmark of JSP, namely FT06, then show experimental results and get some conclusions.
The fossilization of non-current English pronunciation in German EFL teaching1

The German term Handy is a neat and singular creation, referring to the ‘mobile phone’ (British English) or ‘cell phone’ (American English), in itself a unique and most useful invention – handy, indeed! What is even more remarkable is the pronunciation of this term: /hεndi:/. While the second vowel mirrors the pronunciation of word-final ‘i’ sounds in German (cf. Gabi, Salami, Müsli), the ‘a’ does not. Instead, it appears to reflect a socially generalized view of what a short ‘a’ in English is supposed to sound like. And this is not the front, near-open ‘ash’ vowel [æ], the ‘standard lexical set TRAP’, as defined by Wells (1982: 129), but rather a cardinal [ε], the ‘standard lexical set DRESS’ (128), as found in German in other English borrowings: Jetlag or Jet-Lag /jεtlεg/, Gag /gεg/, relaxen /relεksn/, scannen /skεnǝn/, etc.
Speech and Language Resources for LVCSR of Russian

A syllable-based language model reduces the lexicon size by hundreds of times. It is especially beneficial in case of highly inflective languages like Russian due to the abundance of word forms according to various grammatical categories. However, the main arising challenge is the concatenation of recognised syllables into the originally spoken sentence or phrase, particularly in the presence of syllable recognition mistakes. Natural fluent speech does not usually incorporate clear information about the outside borders of the spoken words. In this paper a method for the syllable concatenation and error correction is suggested and tested. It is based on the designed co-evolutionary asymptotic probabilistic genetic algorithm for the determination of the most likely sentence corresponding to the recognized chain of syllables within an acceptable time frame. The advantage of this genetic algorithm modification is the minimum number of settings to be manually adjusted comparing to the standard algorithm. Data used for acoustic and language modelling are also described here. A special issue is the preprocessing of the textual data, particularly, handling of abbreviations, Arabic and Roman numerals, since their inflection mostly depends on the context and grammar.
SELECTING CHEMOTHERAPY SCHEDULES FOR ADJUVANT TREATMENT OF EARLY STAGE BREAST CANCER, WHAT IS THE RATIONALE BEHIND?

Breast cancer is one of the most prevalent cancers that oncologists are faced with in their clinics. The varieties of clinical features of the disease result to very different scenarios in the processes of treatment decision making. While classic factors of stage, grade, age and hormone receptor status are still the criterion for choosing treatment, a very delicate list of other prognostic and predictive factors have been entered to this field over recent two decades. The evidence-based medicine rules to treat patients based on the best evidences that have been found by powered randomized clinical trials. Different panels and guidelines gathering these evidences try to help oncologists to find the best treatment methods through the variable and sometimes contradicting results. As it is always the main objective, increasing the survival rates in addition to the ideal aim of curing the disease is usually the target. Finding the best and the most practical chemotherapy regimen against breast cancer needs to notice the biology of this disease and its varieties along with each individual patient condition. It is clear that not all patients need the most complicated and expensive treatment.
Modelling Competing Endogenous RNA Networks

MicroRNAs (miRNAs) are small RNA molecules, about 22 nucleotide long, which post-transcriptionally regulate their target messenger RNAs (mRNAs). They accomplish key roles in gene regulatory networks, ranging from signaling pathways to tissue morphogenesis, and their aberrant behavior is often associated with the development of various diseases. Recently it has been experimentally shown that the way miRNAs interact with their targets can be described in terms of a titration mechanism. From a theoretical point of view titration mechanisms are characterized by threshold effect at near-equimolarity of the different chemical species, hypersensitivity of the system around the threshold, and cross-talk among targets. The latter characteristic has been lately identified as competing endogenous RNA (ceRNA) effect to mark those indirect interactions among targets of a common pool of miRNAs they are in competition for. Here we propose a stochastic model to analyze the equilibrium and out-of-equilibrium properties of a network of miRNAs interacting with mRNA targets. In particular we are able to describe in detail the peculiar equilibrium and non-equilibrium phenomena that the system displays in proximity to the threshold: (i) maximal cross-talk and correlation between targets, (ii) robustness of ceRNA effect with respect to the model's parameters and in particular to the catalyticity of the miRNA-mRNA interaction, and (iii) anomalous response-time to external perturbations.
Sentinel-1 radar mission: Status and performance

The ESA Sentinels constitute the first series of operational satellites responding to the Earth Observation needs of the EU-ESA Global Monitoring for Environment and Security (GMES) programme. The GMES space component relies on existing and planned space assets as well as on new complementary developments by ESA. This describes the Sentinel-1 mission, as imaging synthetic aperture radar (SAR) satellite constellation at C-band. It provides an overview of mission requirements, its applications and the technical concepts for the system.
Mixing in manipulated turbulence

A numerical investigation of turbulent flow, subject to deterministic broadband forcing, is presented. Explicit forcing procedures are included that represent the simultaneous agitation of a wide spectrum of length scales, including both large scales and a band of much smaller scales. Such forcing induces a multiscale modulation of turbulent flow that is motivated by flow through complex objects and along irregular boundaries. Two types of forcing procedures are investigated; with reference to the collection of forced modes these procedures are classified as ‘constant energy’ or ‘constant-energy input rate’. It is found that a considerable modulation of the traditional energy cascading can be introduced with a specific forcing strategy. In spectral space, forcing yields strongly localized deviations from the common Kolmogorov scaling law, directly associated with the explicitly forced scales. In addition, the accumulated effect of forcing induces a significant non-local alteration of the kinetic energy including the spectrum for the large scales. Consequently, a manipulation of turbulent flow can be achieved over an extended range, well beyond the directly forced scales. Compared to flow forced in the large scales only, the energy in broadband forced turbulence is found to be transferred more effectively to smaller scales. The turbulent mixing of a passive scalar field is also investigated, in order to quantify the physical-space modifications of transport processes in multiscale forced turbulence. The surface area and wrinkling of level sets of the scalar field are monitored as measures of the influence of explicit forcing on the local and global mixing efficiency. At small Schmidt numbers, the values of surface area are mainly governed by the large-scale sweeping effect of the flow while the wrinkling is influenced mainly by the agitation of the smaller scales.