Miracle-dz/UniFAR-FTUs huggingface dataset:
Crystal Chemistry and Thermoelectric Properties of Type-I Clathrate Ba8Ni∼3.8SixGe42.2−x (x = 0, 10, 20, 42.2)

Thermoelectric materials are actively considered for waste heat recovery applications. To improve the heat to electricity conversion efficiency, fundamental understanding on composition, crystal structure, and interrelation with the thermoelectric properties is necessary. Here, we report the chemical and thermoelectric properties of type-I clathrates Ba8Ni3.8SixGe42.2−x (x = 0, 10, 20, 42.2), to show that the Si substitution can retain the low lattice thermal conductivity as in pure Ge-based clathrates by adding defects (cage distortion) scattering and/or alloying effect, and the charge carrier concentration can be optimized and thus the electronic properties can be improved by tailoring the vacancy content. We demonstrate the vacancies in the pure Ge-based compound by Rietveld refinement, and possible vacancies in the quaternary compound by transport property measurements. We also show that, for intrinsic property studies in these compounds with such a complex crystal structure, a heat treatment for as cast alloys is necessary for phase purity and composition homogeneity. The highest ZT value of 0.19 at 550 °C is reached in the compound with x=10.
Cerebrovascular-Reactivity Mapping Using MRI: Considerations for Alzheimer’s Disease

Alzheimer’s disease (AD) is associated with well-established macrostructural and cellular markers, including localized brain atrophy and deposition of amyloid. However, there is growing recognition of the link between cerebrovascular dysfunction and AD, supported by continuous experimental evidence in the animal and human literature. As a result, neuroimaging studies of AD are increasingly aiming to incorporate vascular measures, exemplified by measures of cerebrovascular reactivity (CVR). CVR is a measure that is rooted in clinical practice, and as non-invasive CVR-mapping techniques become more widely available, routine CVR mapping may open up new avenues of investigation into the development of AD. This review focuses on the use of MRI to map CVR, paying specific attention to recent developments in MRI methodology and on the emerging stimulus-free approaches to CVR mapping. It also summarizes the biological basis for the vascular contribution to AD, and provides critical perspective on the choice of CVR-mapping techniques amongst frail populations.
Automatic Clustering of a Network Protocol with Weakly-Supervised Clustering

Abstraction is a fundamental part when learning behavioral models of systems. Usually the process of abstraction is manually defined by domain experts. This paper presents a method to perform automatic abstraction for network protocols. In particular a weakly supervised clustering algorithm is used to build an abstraction with a small vocabulary size for the widely used TLS protocol. To show the effectiveness of the proposed method we compare the resultant abstract messages to a manually constructed (reference) abstraction. With a small amount of side-information in the form of a few labeled examples this method finds an abstraction that matches the reference abstraction perfectly.
Empirical Comparisons and Evaluation of Univariate Time series Models for Forecasting Sales of Internet Browsing Tickets in a Typical Nigerian University

: The purpose of this research paper is to carry out comparative analysis and evaluation of some univariate time series forecasting methods and their application for forecasting sales of internet browsing ticket. Applying weekly data spreading over October2014 to November 2015 on the amount of money generated from the sales of internet browsing ticket in the Federal University of Technology, Akure, Nigeria. The forecasting performance of various forecasting methods were measured through the use of the following forecast accuracy criteria: Mean Absolute Percentage Error (MAPE), Mean Forecast Error (MFE), Mean Absolute Error (MAE), Mean Square Error (MSE) and Root Mean Square Error (RMSE). The forecasting methods analyzed included; naïve method, moving average, double moving average and exponential smoothing. Among these methods, the moving average method performed better than other competing methods in the sales of Internet Browsing ticket. The moving average method produced the most accurate forecasting based on the data obtained in the ranking table, therefore, as a matter of policy implication, the moving average method is therefore recommended for use in the process of forecasting of sales of internet browsing ticket in Nigeria’s Higher Educational Institutions where internet browsing tickets are sold .
Program Synthesis from Visual Specification

Program synthesis is the process of automatically translating a specification into computer code. Traditional synthesis settings require a formal, precise specification. Motivated by computer education applications where a student learns to code simple turtle-style drawing programs, we study a novel synthesis setting where only a noisy user-intention drawing is specified. This allows students to sketch their intended output, optionally together with their own incomplete program, to automatically produce a completed program. We formulate this synthesis problem as search in the space of programs, with the score of a state being the Hausdorff distance between the program output and the user drawing. We compare several search algorithms on a corpus consisting of real user drawings and the corresponding programs, and demonstrate that our algorithms can synthesize programs optimally satisfying the specification.
Longwave Band-by-band Cloud Radiative Effect and its Application in GCM Evaluation

AbstractThe cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM’s radiation code is uniquely valuable for GCM evaluation because 1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and 2) the fractional contribution of each band to the LW broadband CRE (fCRE) is sensitive to cloud-top height but largely insensitive to cloud fraction, thereby presenting a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band-by-band quantities from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations. A study is presented here that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs—the GFDL Atmospheric Model version 2 (GFDL AM2), NASA Goddard Earth Observing System version 5 (GEOS-5), and the fourth-generation AGCM of the Canad.
An SDE approximation for stochastic differential delay equations with colored state-dependent noise

We consider a general multidimensional stochastic differential delay equation (SDDE) with colored state-dependent noises. We approximate it by a stochastic differential equation (SDE) system and calculate its limit as the time delays and the correlation times of the noises go to zero. The main result is proven using a theorem about convergence of stochastic integrals by Kurtz and Protter. It formalizes and extends a result that has been obtained in the analysis of a noisy electrical circuit with delayed state-dependent noise, and may be used as a working SDE approximation of an SDDE modeling a real system, where noises are correlated in time and whose response to noise sources is delayed.
OpenSpace: Changing the Narrative of Public Dissemination in Astronomical Visualization from What to How

We present the development of an open-source software called OpenSpace that bridges the gap between scientific discoveries and public dissemination and thus paves the way for the next generation of science communication and data exploration. We describe how the platform enables interactive presentations of dynamic and time-varying processes by domain experts to the general public. The concepts are demonstrated through four cases: Image acquisitions of the New Horizons and Rosetta spacecraft, the dissemination of space weather phenomena, and the display of high-resolution planetary images. Each case has been presented at public events with great success. These cases highlight the details of data acquisition, rather than presenting the final results, showing the audience the value of supporting the efforts of the scientific discovery.
Characterizing and Predicting Users’ Behavior on Local Search Queries

The use of queries to find products and services that are located nearby is increasing rapidly due mainly to the ubiquity of internet access and location services provided by smartphone devices. Local search engines help users by matching queries with a predefined geographical connotation (“local queries”) against a database of local business listings. Local search differs from traditional Web search because, to correctly capture users’ click behavior, the estimation of relevance between query and candidate results must be integrated with geographical signals, such as distance. The intuition is that users prefer businesses that are physically closer to them or in a convenient area (e.g., close to their home). However, this notion of closeness depends upon other factors, like the business category, the quality of the service provided, the density of businesses in the area of interest, the hour of the day, or even the day of the week. In this work, we perform an extensive analysis of online users’ interactions with a local search engine, investigating their intent, temporal patterns, and highlighting relationships between distance-to-business and other factors, such as business reputation, Furthermore, we investigate the problem of estimating the click-through rate on local search (LCTR) by exploiting the combination of standard retrieval methods with a rich collection of geo-, user-, and business-dependent features. We validate our approach on a large log collected from a real-world local search service. Our evaluation shows that the non-linear combination of business and user information, geo-local and textual relevance features leads to a significant improvements over existing alternative approaches based on a combination of relevance, distance, and business reputation [1].
An analysis of the effect of gravity compensation on compliant biped walking controllers

This paper presents and compares three distinct control schemes aimed at the endowment of compliant humanoid robots, with locomotion capabilities. It is demonstrated that the aforementioned control methods share a common foundation composed of linear state feedback elements, although they distinguish themselves from one another through their utilization of different forms of gravity compensation terms. The controller analysed herein exploits the direct motor position feedback, while the benchmarking schemes revolve around the use of link position feedback and desired link position gravity compensation. Additionally, it is demonstrated that the application of the motor­position-based gravity compensation schemes on the various dynamical models, leads to asymptotically stable closed-loop systems for regulation, whilst delineating the extension to trajectory tracking. The practical results generated from a series of experiments involving the COmpliant huMANoid (COMAN), corroborate the controllers' abilities to permit the successful execution of walking trajectories. Furthermore, they reveal the superior efficacy of the two feedback-dependent gravity compensation control techniques in terms of tracking walking trajectories, in comparison to the feedforward controller.
Optimizing Bootstrap method to improve forecasting accuracy in business jet spare parts supply chains

Having products available when customer wants them keeps customers satisfied and businesses more competitive, especially in business aircrafts industry where clients are paying considerably higher for flying than in a commercial airliner. So, all parts needed for normal operation and maintenance must be readily available to ensure business flights. As there are business-aircrafts' spare parts which have lead times of up to three years, to ensure that the right parts are available at the right time in the right volume and at the right location, forecasts must be made of anticipated customer demand. The overestimated demand results in holding costs as storage, rent utilities and product obsolescence costs whereas underestimated demand leads to back order and stock out. The demand in business aircrafts industry is volatile so traditional forecasting methods are not efficient. This give rise of interest in data driven forecasting methods e.g. Bootstrap, Neural Network etc. have compared existing traditional and data driven methods and proposed an extension to Bootstrap through sliding window concept as best performing forecasting method. In this paper, optimization methodology for the sliding window bootstrap is proposed to improve forecasting accuracy. Results are validated using data from Dassault Falcon Business Jet. USA, world renowned Business Aircraft manufacturer.
A Value Ordering Heuristic for Weighted CSP

In this paper, we propose a new value ordering heuristic for weighted constraint satisfaction problems (WCSP) based on the quality of solutions. The H-quality of an assignment estimates its capacity at occurring in solutions of "good" quality. Experiments using limited discrepancy search on random WCSP instances and CELAR benchmarks show that our value ordering always outperforms MinAC in a significant way.
Regulation and Evolution of NLR Genes: A Close Interconnection for Plant Immunity

NLR (NOD-like receptor) genes belong to one of the largest gene families in plants. Their role in plants’ resistance to pathogens has been clearly described for many members of this gene family, and dysregulation or overexpression of some of these genes has been shown to induce an autoimmunity state that strongly affects plant growth and yield. For this reason, these genes have to be tightly regulated in their expression and activity, and several regulatory mechanisms are described here that tune their gene expression and protein levels. This gene family is subjected to rapid evolution, and to maintain diversity at NLRs, a plethora of genetic mechanisms have been identified as sources of variation. Interestingly, regulation of gene expression and evolution of this gene family are two strictly interconnected aspects. Indeed, some examples have been reported in which mechanisms of gene expression regulation have roles in promotion of the evolution of this gene family. Moreover, co-evolution of the NLR gene family and other gene families devoted to their control has been recently demonstrated, as in the case of miRNAs.
The Prognostic Value of Histopathologic Lesions in Native Kidney Biopsy Specimens: Results from the Boston Kidney Biopsy Cohort Study.

Background Few studies have evaluated whether histopathologic lesions on kidney biopsy provide prognostic information beyond clinical and laboratory data.Methods We enrolled 676 individuals undergoing native kidney biopsy at three tertiary care hospitals into a prospective, observational cohort study. Biopsy specimens were adjudicated for semiquantitative scores in 13 categories of histopathology by two experienced renal pathologists. Proportional hazards models tested the association between histopathologic lesions and risk of kidney disease progression (≥40% eGFR decline or RRT). Results Mean baseline eGFR was 57.5±36.0 ml/min per 1.73 m2 During follow-up (median, 34.3 months), 199 individuals suffered kidney disease progression. After adjustment for demographics, clinicopathologic diagnosis, and laboratory values, the following lesions (hazard ratio; 95% confidence interval) were independently associated with progression: inflammation in nonfibrosed interstitium (0.52; 0.32 to 0.83), moderate and severe versus minimal interstitial fibrosis/tubular atrophy (2.14; 1.24 to 3.69 and 3.42; 1.99 to 5.87, respectively), moderate and severe versus minimal global glomerulosclerosis (2.17; 1.36 to 3.45 and 3.31; 2.04 to 5.38, respectively), moderate and severe versus minimal arterial sclerosis (1.78; 1.15 to 2.74 and 1.64; 1.04 to 2.60, respectively), and moderate and severe versus minimal arteriolar sclerosis (1.63; 1.08 to 2.46 and 2.33; 1.42 to 3.83, respectively). An 11-point chronicity score derived from semiquantitative assessments of chronic lesions independently associated with higher risk of kidney disease progression (hazard ratio per one-point increase, 1.19; 95% confidence interval, 1.12 to 1.27). Conclusions Across a diverse group of kidney diseases, histopathologic lesions on kidney biopsy provide prognostic information, even after adjustment for proteinuria and eGFR.
Asymptotically Optimal Algorithms for Running Max and Min Filters on Random Inputs

Given a <inline-formula><tex-math notation="LaTeX">$d$</tex-math></inline-formula>-dimensional array of size <inline-formula><tex-math notation="LaTeX">$n^d$</tex-math></inline-formula> and an integer <inline-formula> <tex-math notation="LaTeX">$p$</tex-math></inline-formula>, the running max (or min) filter is the set of maximum (or minimum) elements within a <inline-formula><tex-math notation="LaTeX">$d$</tex-math></inline-formula>-dimensional sliding window of edge length <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula> inside the array. This problem is useful in many signal processing applications such as pattern analysis, adaptive signal processing, and morphological analysis. The current best algorithm for computing the one-dimensional (1-D) max (or min) filter, due to the work of [H. Yuan and M. J. Atallah, “Running max/min filters using 1+o(1) comparisons per sample,” <italic>IEEE Trans. Pattern Anal. Mach. Intell. </italic>, vol. 33, no. 12, pp. 2544–2548, Dec. 2011], uses <inline-formula><tex-math notation="LaTeX">$1+o(1)$</tex-math></inline-formula> comparisons per sample in the worst case. As a direct consequence, the <inline-formula><tex-math notation="LaTeX">$d$ </tex-math></inline-formula>-dimensional max (or min) filter (max and min filters, respectively) can be computed in <inline-formula><tex-math notation="LaTeX">$d+o(1)$</tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$2d+o(1)$</tex-math></inline-formula>, respectively) comparisons per sample. In this paper, we first present an algorithm for computing <inline-formula><tex-math notation="LaTeX">$d$</tex-math></inline-formula> -dimensional max and min filters simultaneously on i.i. d. inputs that uses <inline-formula><tex-math notation="LaTeX"> $1.5+o(1)$</tex-math></inline-formula> expected comparisons per sample. This is the first algorithm (on i.i.d. inputs) that gets rid of the dependence on <inline-formula><tex-math notation="LaTeX">$d$</tex-math></inline-formula> in the dominating term, with respect to <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula>, of the (expected) number of comparisons needed. It is also asymptotically optimal (when <inline-formula><tex-math notation="LaTeX">$d$</tex-math> </inline-formula> is a fixed constant as <inline-formula><tex-math notation="LaTeX">$n \rightarrow \infty$</tex-math> </inline-formula> and <inline-formula><tex-math notation="LaTeX">$p \rightarrow \infty$</tex-math></inline-formula>). We also consider the dynamic version of the problem of <inline-formula><tex-math notation="LaTeX">$d$</tex-math> </inline-formula>-dimensional max and min filters simultaneously on i.i. d. inputs where we want to maintain the filters after changes in the input array. We design a linear-sized data structure that stores precomputed information for efficient update using <inline-formula><tex-math notation="LaTeX">$O(p^{d-1}\log _2 p)$</tex-math></inline-formula> expected comparisons per update.
The follicular placenta of the viviparous fish, Heterandria formosa. I. Ultrastructure and development of the embryonic absorptive surface

Embryos of the poeciliid Heterandria formosa develop to term in the ovarian follicle in which they establish a placental association with the follicle wall (follicular placenta) and undergo a 3,900% increase in embryonic dry weight. This study does not confirm the belief that the embryonic component of the follicular placenta is formed only by the surfaces of the pericardial and yolk sacs; early in development the entire embryonic surface functions in absorption. The pericardial sac expands to form a hood‐like structure that covers the head of the embryo and together with the yolk sac is extensively vascularized by a portal plexus derived from the vitelline circulation. The hood‐like pericardial sac is considered to be a pericardial amnion‐serosa. Scanning and transmission electron microscopy reveal that during the early and middle phases of development (Tavolga's stages 10–18 for Xiphophorus maculatus) the entire embryo is covered by a bilaminar epithelium whose apical surface is characterized by numerous, elongate microvilli and coated pits and vesicles. Electron‐lucent vesicles in the apical cytoplasm appear to be endosomes while a heterogeneous group of dense‐staining vesicles display many features characteristic of lysosomes. As in the larvae of other teleosts, cells resembling chloride cells are also present in the surface epithelium. Endothelial cells of the portal plexus lie directly beneath the surface epithelium of the pericardial and yolk sacs and possess numerous transcytotic vesicles. The microvillous surface epithelium becomes restricted to the pericardial and yolk sacs late in development when elsewhere on the embryo the non‐absorptive epidermis differentiates. We postulate that before the definitive epidermis differentiates, the entire embryonic surface constitutes the embryonic component of the follicular placenta. The absorptive surface epithelium appears to be the principle embryonic adaptation for maternal‐embryonic nutrient uptake in H. formosa, suggesting that a change in the normal differentiation of the surface epithelium was of primary importance to the acquisition of matrotrophy in this species. In other species of viviparous poeciliid fishes in which there is little or no transfer of maternal nutrients, the embryonic surface epithelium is of the non‐absorptive type.
Prediction of Emotion Change From Speech

The fact that emotions are dynamic in nature and evolve across time has been explored relatively less often in automatic emotion recognition systems to date. Although within-utterance information about emotion changes recently has received some attention, there remain open questions unresolved, such as how to approach delta emotion ground truth, how to predict the extent of emotion change from speech, and how well change can be predicted relative to absolute emotion ratings. In this article, we investigate speech-based automatic systems for continuous prediction of the extent of emotion changes in arousal/valence. We propose the use of regression (smoothed) deltas as ground truth for emotion change, which yielded considerably higher inter-rater reliability than first-order deltas, a commonly used approach in previous research, and represent a more appropriate approach to derive annotations for emotion change research, findings which are applicable beyond speech-based systems. In addition, the first system design for continuous emotion change prediction from speech is explored. Experimental results under the Output-Associative Relevance Vector Machine framework interestingly show that changes in emotion ratings may be better predicted than absolute emotion ratings on the RECOLA database, achieving 0.74 vs 0.71 for arousal and 0.41 vs 0.37 for valence in concordance correlation coefficients. However, further work is needed to achieve effective emotion change prediction performances on the SEMAINE database, due to the large number of non-change frames in the absolute emotion ratings.