Miracle-dz/UniFAR-FTUs huggingface dataset:
Prototype instruments for determination of aroma and flavor quality of brewed black tea

Black tea is one of Indonesia's major leading export products. In terms of trading, quality of black tea, especially flavor and aroma, will determine its selling price. The purpose of this research is to design a prototype of electronic nose, which integrated gas sensors, data acquisition, and computer, to detect the aroma of brewed black tea. This electronic nose consists of four gas sensors (TGS 822, TGS 825, TGS 826, and TGS 2620) MOS type with SnO2 as sensing element. The response of sensor is processed by using power spectral estimation method and the result is being used as an input for Artificial Neural Network (ANN) to classify the quality of brewed black tea. ANN is trained by varying 4 sets of data input for each quality classes: 31, 35, 37, and 39, which are being used as an ANN inputs. The performance of ANN that has been developed is tested by using 9 sets of brewed black tea aroma data which are different from trained data. The results of the test show that the system is able to recognize the aroma with 11,11% errors.
Age-Dependent Decline in β-Cell Proliferation Restricts the Capacity of β-Cell Regeneration in Mice

OBJECTIVE The aim of this study was to elucidate whether age plays a role in the expansion or regeneration of β-cell mass. RESEARCH DESIGN AND METHODS We analyzed the capacity of β-cell expansion in 1.5- and 8-month-old mice in response to a high-fat diet, after short-term treatment with the glucagon-like peptide 1 (GLP-1) analog exendin-4, or after streptozotocin (STZ) administration. RESULTS Young mice responded to high-fat diet by increasing β-cell mass and β-cell proliferation and maintaining normoglycemia. Old mice, by contrast, did not display any increases in β-cell mass or β-cell proliferation in response to high-fat diet and became diabetic. To further assess the plasticity of β-cell mass with respect to age, young and old mice were injected with a single dose of STZ, and β-cell proliferation was analyzed to assess the regeneration of β-cells. We observed a fourfold increase in β-cell proliferation in young mice after STZ administration, whereas no changes in β-cell proliferation were observed in older mice. The capacity to expand β-cell mass in response to short-term treatment with the GLP-1 analog exendin-4 also declined with age. The ability of β-cell mass to expand was correlated with higher levels of Bmi1, a polycomb group protein that is known to regulate the Ink4a locus, and decreased levels of p16Ink4aexpression in the β-cells. Young Bmi1−/− mice that prematurely upregulate p16Ink4afailed to expand β-cell mass in response to exendin-4, indicating that p16Ink4alevels are a critical determinant of β-cell mass expansion. CONCLUSIONS β-Cell proliferation and the capacity of β-cells to regenerate declines with age and is regulated by the Bmi1/p16Ink4apathway.
SemKer: Syntactic/Semantic Kernels for Recognizing Textual Entailment

In this paper we describe the SemKer system participating to the fifth Recognizing of Textual Entailment (RTE5) challenge. The major novelty with respect to the systems with which we participated to the previous challenges is the use of semantic knowledge based on Wikipedia. More specifically, we used it to enrich the similarity measure between pairs of text and hypothesis (i.e. the tree kernel for text and hypothesis pairs), with a lexical similarity (i.e. the similarity between the leaves of the trees. The results show the benefit of this added semantic information.
Interest and investment in fictional romances.

Shipping, which refers to emotional investment in fictional relationships, has been occurring for decades yet has not received much theoretical or any empirical attention. In light of it becoming more recognized in mainstream culture, we wanted to establish whether interest in fictional relationships is a relevant, intriguing, and meaningful form of media engagement. To do this we ran one exploratory study, one preregistered confirmatory replication, and one preregistered extension. Together, these three studies answered several questions: (a) Are people interested in fictional relationships? ; (b) Who is likely to be interested? ; (c) Why are individuals interested? ; and (d) Is interest in fictional relationships a distinct form of media engagement? We found that emotional investment in fictional couples is somewhat common and occurs across a number of media platforms. Being more inclined to think about relationships and have more romantic beliefs was linked to interest in fictional relationships, which reflects a general inclination to focus on relationships. We were also able to demonstrate moderate correlations between relationship interest and other media engagement variables—namely parasocial relationships, narrative transportation, character identification, and celebrity worship—in addition to showing that interest in fictional relationships provides incremental prediction after controlling for these other types of media engagement. These three studies support the notion that relationship interest is a unique and important form of media engagement that is related to individuals’ romantic cognition.
Strategic Voting in Slovak Regional Elections of 2013 and 2017: Evidence for Duverger’s Law in Elections of Presidents of Regional Self-Government?

Strategic Voting in Slovak Regional Elections of 2013 and 2017: Evidence for Duverger’s Law in Elections of Presidents of Regional Self-Government? This article tests Duverger’s law through an analysis of the 2017 elections of Slovakian regional presidents which were held under the new first-past-the-post (or single-member plurality) system, and comparison with results of the previous election of 2013 which used a tworound system (absolute majority run-off). The main aim of the article is to test the expectations of strategic voting in the context of the so-called second-order elections, under which regional elections can be classified. The results show that strategic voting was not a universal phenomenon under the plurality rule in 2017, as indicated by electoral results and party competition at the level of electoral precincts. In most electoral precincts, the character of electoral competition was not in compliance with theoretical expectations and two-party competition. More importantly, the introduction of FPTP, instead of TRS, should lead to increasing two-party competition and strategic voting, but the opposite was true. Competition at precinct level in 2017 went far away from the Duvergerian equilibrium, as two-party competition increased in only one out of eight regions, Trnava, compared to 2013. Finally, segmented Nagayama diagrams likely proved as the most suitable indicator of competitiveness and strategic behaviour, helping us identify the patterns, but above all, changes to the patterns, of electoral competitiveness between elections. Our research thus confirmed that the effect of electoral institutions (institutional structure) is contingent upon and (at the district, or precinct, level) inhibited by country-specific conditions, with potentially strong influence of the second-order character of the Slovak regional elections. Sociológia 2018, Vol. 50 (No. 6: 697-726) https://doi.org/10.31577/sociologia.2018. 50.6. 26
Linear precoding in MISO cognitive channels with degraded message sets

In this work, the coexistence of a single-input single-output (SISO) primary link and a multiple-input single-output (MISO) secondary link is considered, where the secondary transmitter has non-causal knowledge of primary message and transmits both primary and secondary messages. The optimal beamforming vectors and power allocation at the secondary transmitter are derived to maximize the achievable secondary rate while satisfying the primary rate requirement. Moreover, the optimal linear precoding is obtained by semidefinite relaxation and rank-one decomposition, when the number of antennas at the secondary transmitter is larger than two. Finally, the performance of the proposed scheme is evaluated through numerical simulations.
Technology Mapping into General Programmable Cells

Field-Programmable Gate Arrays (FPGA) implement logic functions using programmable cells, such as K-input lookup-tables (K-LUTs). A K-LUT can implement any Boolean function with K inputs and one output. Methods for mapping into K-LUTs are extensively researched and widely used. Recently, cells other than K LUTs have been explored, for example, those composed of several LUTs and those combining LUTs with several gates. Known methods for mapping into these cells are specialized and complicated, requiring a substantial effort to evaluate custom cell architectures. This paper presents a general approach to efficiently map into single-output K-input cells containing LUTs, MUXes, and other elementary gates. Cells with to 16 inputs can be handled. The mapper is fully automated and takes a logic network and a symbolic description of a programmable cell, and produces an optimized network composed of instances of the given cell. Past work on delay/area optimization during mapping is applicable and leads to good quality of results.
Crossmodal affective context and emotional attention 1 Running head : CROSSMODAL AFFECTIVE CONTEXT AND EMOTIONAL ATTENTION

48 Prior evidence has shown that a person’s affective context influences attention to 49 emotional stimuli. The present study investigated w hether a crossmodal affective context that is 50 induced by remembering an emotional sound modulates tt ntion to visual emotional stimuli. 51 One group of participants had to remember a positiv e, negative, or neutral sound during each trial 52 of a dot probe paradigm. A second group of particip ants also had to encode the valence of the 53 sound. The results revealed that attention was pref erentially deployed to stimuli that were 54 emotionally congruent to the affective context. How ever, this effect was only evident when 55 participants had to encode the valence of the affec tive context. These findings suggest that a 56 crossmodal affective context modulates the deployme nt of attention to emotional stimuli 57 provided that the affective connotation of the cont ext is task-relevant. 58 59 60
Optimized Reduce for Mesh-Based NoC Multiprocessors

Future processors are expected to be made up of a large number of computation cores interconnected by fast on-chip networks (Network-on-Chip, NoC). Such distributed structures motivate the use of message passing programming models similar to MPI. Since the properties of these networks, like e.g. the topology, are known and fixed after production, this knowledge can be used to optimize the communication stack. We describe two schemes that take advantage of this to accelerate the (All-)Reduce operation defined in MPI, namely a contention avoiding rank-to-core mapping and a way of interleaving communication and computation by means of pipelining. Simulations show that the combination of both schemes can accelerate (All-)Reduce operations by more than 60%.
Microstrip lateral RF MEMS switch integrated with multistep CPW transition

A new type of microstrip lateral metal‐contacting micro‐electromechanical systems (MEMS) series switch using an enhanced transition‐design technology is proposed and demonstrated. It uses a conductor‐backed coplanar waveguide (CBCPW) connected to a microstrip back‐to‐back MEMS transmission line without any via holes or bonded wires. The RF measurements of this switch show an off‐state isolation of 18 dB and an on‐state insertion loss of less than 2 dB at 6–27 GHz. In addition, the simplicity of this fabrication process is achieved using deep reactive‐ion etching (DRIE), micromachining technology, and silicon‐on‐insulator (SOI) substrate. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 93–95, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20557
What Can We Learn From Movie Colors ?

We applied supervised learning methods to classify movies into one of four genres based solely on colors present in the film. Data was obtained from screen captures of the Netflix preview window at 10 second intervals. Our final feature was X = {512-color histogram, avg. color change}. Our genre classes were Y = {Action, Animation, Horror, Romance}. We attempted Multinomial Naive Bayes and 1-v-all SVM to predict the genres of a film based on its color features. We also attempted Unsupervised Learning K-Means Clustering algorithm on our movies to observe patterns across movies.
DC-DC converter design for power distribution systems in electric vehicles using calorimetric loss measurements

In this contribution, a uni-directional converter is proposed which supplies the EV's safety-low voltage grid of 14 V DC directly from the drive battery voltage level of Vbatt = 250.370 V. The converter consists of two power stages which are a hard-switching SiC boost converter and a softswitching resonant converter. Special attention is paid to the accurate loss modelling of the converter, where frequency-depending winding losses, magnetic core losses, and semiconductor switching losses are considered. The core and winding losses were validated by calorimetric measurements, which results are in good accordance with the simulations. As final result, a converter peak efficiency of 98.2% was achieved.
Efficient Approximate Inference for Online Probabilistic Plan Recognition

We present a new general framework for online probabilistic plan recognition called the Abstract Hidden Markov Memory Model (AHM M). The new model is an extension of the existing Abstract Hidden Markov Model to allow the policy to have internal memory which can be updated in a Markov fashion. We show that the AHM M can represent a richer class of probabilistic plans, and at the same time derive an efficient algorithm for plan recognition in the AHM M based on the Rao-Blackwellised Particle Filter approximate inference method.
How should public health professionals engage with lay epidemiology?

“Lay epidemiology” is a term used to describe the processes through which health risks are understood and interpreted by laypeople. It is seen as a barrier to public health when the public disbelieves or fails to act on public health messages. Two elements to lay epidemiology are proposed: (a) empirical beliefs about the nature of illness and (b) values about the place of health and risks to health in a good life. Both elements have to be dealt with by effective public health schemes or programmes, which would attempt to change the public’s empirical beliefs and values. This is of concern, particularly in a context in which the lay voice is increasingly respected. Empirically, the scientific voice of standard epidemiology should be deferred to by the lay voice, provided a clear distinction exists between the measurement of risk, which is empirical, and its weighting, which is based on values. Turning to engagement with values, health is viewed to be an important value and is discussed and reflected on by most people. Public health professionals are therefore entitled and advised to participate in that process. This view is defended against some potential criticisms.
Improving Electric Fraud Detection using Class Imbalance Strategies

Improving nontechnical loss detection is a huge challenge f or lectric companies. The great number of clients and the diversity of the different types of fraud makes this a very complex task. In this paper we present a fraud detection strategy based on class imbalance research . An automatic detection tool combining classification strategies is proposed. Individual classifiers such as One Class SVM, Cost Sensitive SVM (CS-SVM), Optimum Path Forest (OPF) and C4.5 Tree, and combination fun ctions are designed taken special care in the data’s class imbalance nature. Analysis over consumers his torical kWh load profile data from Uruguayan Electric Company (UTE) shows that using combination and balanci ng techniques improves automatic detection performance.
Semi-automatic enhancement of very low quality fingerprints

In this paper we propose a semi-automatic approach for the enhancement of very low quality fingerprints such as latent fingerprints. A specific markup tool is designed to allow fingerprint examiners to simply and quickly provide sparse estimates of local orientations and frequencies. These estimates are then interpolated though Delaunay triangulation and fed to a contextual Gabor-based enhancement algorithm that significantly improves the image quality, thus making the successive automatic feature extraction much more reliable. Experimental results (both qualitative and quantitative) confirm the effectiveness of this method over a fully-automatic state-of-the-art approach.
A practical method for exact computation of subtree prune and regraft distance

MOTIVATION Subtree prune and regraft (SPR) is one kind of tree rearrangements that has seen applications in solving several computational biology problems. The minimum number of rooted SPR ((r)SPR) operations needed to transform one rooted binary tree to another is called the (r)SPR distance between the two trees. Computing the (r)SPR distance has been actively studied in recent years. Currently, there is a lack of practical software tools for computing the (r)SPR distance for relatively large trees with large (r)SPR distance. RESULTS In this article, we present a simple and practical method that computes the exact (r)SPR distance with integer linear programming. By applying this new method on several simulated and real biological datasets, we show that our new method outperforms existing software tools in term of accuracy and efficiency. Our experimental results indicate that our method can compute the exact (r)SPR distance for many large trees with large (r)SPR distance.
Multi-robot path planning for budgeted active perception with self-organising maps

We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has polynomial-bounded runtime independent of the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Simulations were performed using a 3D point cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for budgeted active perception tasks with continuous sets of candidate viewpoints and long planning horizons.
Accuracy enhancement of omnidirectional camera calibration for structure from motion

This paper presents a technique to enhance accuracy of omnidirectional camera calibration which is applied structure from motion. We use two omnidirectional images of a predefined trihedron with checker board taken by a calibrate camera at an arbitrary location. Then, several point matches were picked manually from both views of the object. After that, compute and perform a 3D metric reconstruction of a real object from both images, by using the geometrical approach model estimated by single view calibration method. Then improved by the minimization error the distances among trihedral object use our proposed method. The overall experimental results show our proposed method gave smaller distance error.
Automating formal modular verification of asynchronous real-time embedded systems

Most verification tools and methodologies such as model checking, equivalence checking, hardware verification, software verification, and hardware-software co-verification often flatten out the behavior of a target system before verification. Inherent modularities, either explicit or implicit, functional or structural, are not exploited by these tools and algorithms. In this work, we show how assume-guarantee reasoning (AGR) can be used for such exploitations by integrating AGR into a verification tool. Targeting at real-time embedded systems, we propose procedures to automatically generate assumptions, guarantees, and time constraints, which otherwise require manual efforts and human creativity. Through a complex but comprehensible real-time embedded system example such as a Vehicle Parking Management System (VPMS), we illustrate the feasibility of the AGR approach and the extremely large reduction possible in state-space sizes when AGR is applied. Due to AGR, we also found five errors in the VPMS design using much lesser CPU time and memory space than possible without AGR.
Watching high-risk sports on television: the reversal theory’s concept of protective frame

Abstract The study explored the psychological links that may exist between the feeling of being threatened and the perceived risk of sports situations, the interest for television sports programs, and the interest for conversations about these television sports reports. One hundred ninety-nine participants were presented with a series of questionnaires to assess: a) the degree of threat, the perceived risk as well as the amount of personal experience associated with certain sports situations, b) the degree of interest and the viewing habits associated with the same sports situations, c) the degree of interest shown for participating in conversations about these sports programs. The more the sports were considered threatening and perceived as risky, the more the participants were interested in watching these sports on television and to talk about these television programs. The concept of protective frame explained this finding.
Application and adaptation of Genetic Algorithm in optimal Eco-friendly reservoir operation

Optimal reservoir operation is a complex problem that involves multiple objectives, multiple constraints as well as considerable risk and uncertainty. Eco-friendly reservoir operation makes it more complicated by taking into account a conflicting objective or highly nonlinear constraint related to ecosystem requirement. The study developed a model to optimize reservoir operation in an Eco-friendly manner by using Genetic Algorithm(GA) and applied it to two cascade reservoirs of Yalongjiang River in the Southwest of China. In order to improve its performance, GA was adapted in transferring objective function and operating mutation dynamically. In addition, a time-nested model was proposed to optimize monthly-based data to daily one, thereby avoiding too much state variables being involved when reservoir require daily operation policy. It is shown that the adapted GA can certainly fulfill the goal of eco-friendly reservoir operation and it was enhanced in search accuracy and global searching ability with objective function transfer and dynamic mutation operator. Moreover, the time-nested model was greatly help to build a daily-based optimization model which can cut computing times dramatically and improve the GA efficiency.