Miracle-dz/UniFAR-FTUs huggingface dataset:
Transport Energy.

We introduce the \emph{transport energy} functional $\mathcal E$ acting on Borel measures, a variant of the Bouchitt\'e-Buttazzo-Seppecher shape optimization functional, and we prove that the Evans-Gangbo optimal transport density $\mu^*$ is the unique minimizer of $\mathcal E. $ We study the gradient flow of $\mathcal E$ showing that $\mu^*$ is the unique global attractor of the flow. We introduce a two parameter family $\{\mathcal E_{\lambda,\delta}\}_{\lambda,\delta>0}$ of strictly convex functionals which can be understood as regularizations of $\mathcal E$ and we prove the convergence of the minimizers $\mu_{\lambda,\delta}^*$ of $\mathcal E_{\lambda,\delta}$ to $\mu^*$ as we let $\delta\to 0^+$ and $\lambda\to 0^+. $ We characterize $\mu_{\lambda,\delta}^*$ as global attractors of the gradient flow of $\mathcal E_{\lambda,\delta}. $ In addition, we characterize $\mu^*_{\lambda,\delta}$ by a non-linear system of PDEs.
GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization

Direct SLAM methods have shown exceptional performance on odometry tasks. However, they are susceptible to dynamic lighting and weather changes while also suffering from a bad initialization on large baselines. To overcome this, we propose GN-Net: a network optimized with the novel Gauss-Newton loss for training weather invariant deep features, tailored for direct image alignment. Our network can be trained with pixel correspondences between images taken from different sequences. Experiments on both simulated and real-world datasets demonstrate that our approach is more robust against bad initialization, variations in day-time, and weather changes thereby outperforming state-of-the-art direct and indirect methods. Furthermore, we release an evaluation benchmark for relocalization tracking against different types of weather. Our benchmark is available at https://vision.in. tum.de/gn-net.
Searching for isotropic stochastic gravitational-wave background in the international pulsar timing array second data release

We search for isotropic stochastic gravitational-wave background (SGWB) in the International Pulsar Timing Array second data release. By modeling the SGWB as a power-law, we find very strong Bayesian evidence for a common-spectrum process, and further this process has scalar transverse (ST) correlations allowed in general metric theory of gravity as the Bayes factor in favor of the ST-correlated process versus the spatially uncorrelated common-spectrum process is 30 ± 2. The median and the 90% equal-tail amplitudes of ST mode are ST=1.29−0.44+0.51×10−15 , or equivalently the energy density parameter per logarithm frequency is ΩGWST=2.31−1.30+2.19×10−9 , at frequency of 1 year−1. However, we do not find any statistically significant evidence for the tensor transverse (TT) mode and then place the 95% upper limits as TT<3.95×10−15 , or equivalently ΩGWTT<2.16×10−9 , at frequency of 1 year−1.
Massive spheroids can form in single minor mergers

Understanding how rotationally supported discs transform into dispersion-dominated spheroids is central to our comprehension of galaxy evolution. Morphological transformation is largely merger-driven. While major mergers can efficiently create spheroids, recent work has highlighted the significant role of other processes, like minor mergers, in driving morphological change. Given their rich merger histories, spheroids typically exhibit large fractions of ‘ex situ’ stellar mass, i.e. mass that is accreted, via mergers, from external objects. This is particularly true for the most massive galaxies, whose stellar masses typically cannot be attained without a large number of mergers. Here, we explore an unusual population of extremely massive (M* > 1011M⊙) spheroids, in the Horizon-AGN simulation, which exhibit anomalously low ex situ mass fractions, indicating that they form without recourse to significant merging. These systems form in a single minor-merger event (with typical merger mass ratios of 0.11–0.33), with a specific orbital configuration, where the satellite orbit is virtually co-planar with the disc of the massive galaxy. The merger triggers a catastrophic change in morphology, over only a few hundred Myr, coupled with strong in situ star formation. While this channel produces a minority (∼5 per cent) of such galaxies, our study demonstrates that the formation of at least some of the most massive spheroids need not involve major mergers – or any significant merging at all – contrary to what is classically believed.
Properties of the Null Distance and Spacetime Convergence

The null distance for Lorentzian manifolds was recently introduced by Sormani and Vega. Under mild assumptions on the time function of the spacetime, the null distance gives rise to an intrinsic, conformally invariant metric that induces the manifold topology. We show when warped products of low regularity and globally hyperbolic spacetimes endowed with the null distance are (local) integral current spaces. This metric and integral current structure sets the stage for investigating convergence analogous to Riemannian geometry. Our main theorem is a general convergence result for warped product spacetimes relating uniform, Gromov–Hausdorff, and Sormani–Wenger intrinsic flat convergence of the corresponding null distances. In addition, we show that nonuniform convergence of warping functions in general leads to distinct limiting behavior, such as limits that disagree.
Prediction of water content, sucrose and invert sugar of sugarcane using bioelectrical properties and artificial neural network

The study aimed to predict moisture content, sucrose and invert sugar of sugarcane (Saccharum officinarum L.) using artificial neural network (ANN) prediction model. The ANN model was developed based on the bioelectrical properties of the sugarcane. Bioelectrical properties were measured using LCR meter within 0.1 to 10 kHz range of frequency. The researchers then correlated the result of measurement with chemical content of sugarcane to develop an ANN prediction model. The best ANN topology (3-20-40-3) consisted of 3 nodes of input layer (inductance, capacitance and resistance), 20 nodes in hidden layer 1, 40 nodes in hidden layer 2 and 3 nodes of output layer (water content, sucrose and invert sugar) with training algorithm (trainlm), activation function of hidden layer (logsig), activation function of output layer (purelin), learning rate 0.1 and momentum 0.5. Based on the best topology, the researchers figured out that the validation of mean square error (MSE) was obtained at 0.0122. These results indicated that an ANN model based on the bioelectrical properties can be used to predict the chemical content of sugarcane.
Firm dynamics in news-driven business cycles: the role of endogenous survival rate

Evidences from the structural vector-error correction model shows that the new business formation and stock prices co-moves with output under news shocks. However, simply incorporating firm dynamics into Jaimovich and Rebelo’s (Jaimovich and Rebelo, 2009) model cannot explain these empirical findings. We show that this problem can be resolved by introducing endogenous survival rates for the new entrants.
DETECTION OF PORNOGRAPHIC IMAGES USING BAG-OF-VISUAL-WORDS AND ARCX 4 OF RANDOM MULTINOMIAL NAIVE BAYES

The paper presents a novel approach to detect pornographic images. At the pre-processing step, we propose to use the Scale-invariant feature transform method (SIFT) which is locally based on the appearance of the object at particular interest points, invariant to image scale, rotation and also robust to changes in illumination, noise, occlusion. And then, the representation of the image that we use for classification is the bag-of-visual-words (BoVW), which is constructed from the local descriptors and the counting of the occurrence of visual words in a histogram like fashion. The pre-processing step brings out datasets with a very large number of dimensions. And then, we propose a new algorithm called Arcx4 of random multinomial naive Bayes (Arcx4-rMNB) that is suited for classifying very-high-dimensional datasets. We do setup experiment with two real datasets to evaluate performances. Our approach has achieved an accuracy of 91.75% for a small dataset and 87.93% for other large one.
A truth that ’ s told with bad intent , beats all the lies you can invent

We study psychological games of cheap talk communication involving players who have misaligned material interests and reciprocity preferences. We find that full and efficient information transmission is often impossible if reciprocity concerns are too high. Furthermore, higher material preference misalignment may facilitate the achievement of full information transmission. A key driver of our results is that truth-telling is not per se a kind action by the sender. We contrast discrete and continuous environments, alternative conceptions of reciprocity preferences and consider one-sided reciprocity models.
Characterization andModeling of DHBT in InP / GaAsSb Technology for the Design and Fabrication of a Ka

This paper presents the design of an MMIC oscillator operating at a 38 GHz frequency. This circuit was fabricated by the III–V Lab with the new InP/GaAsSb Double Heterojunction Bipolar Transistor (DHBT) submicronic technology (We = 700 nm). The transistor used in the circuit has a 15 μm long two-finger emitter. This paper describes the complete nonlinear modeling of this DHBT, including the cyclostationary modeling of its low frequency (LF) noise sources. The specific interest of the methodology used to design this oscillator resides in being able to choose a nonlinear operating condition of the transistor from an analysis in amplifier mode. The oscillator simulation and measurement results are compared. A 38 GHz oscillation frequency with 8.6 dBm output power and a phase noise of −80 dBc/Hz at 100 KHz offset from carrier have been measured.
Characterization of 16 S rRNA 3 ’ Termini Using RNA-Seq Data

Optimizing the production of useful macromolecules from transgenic microorganisms is crucial to biopharmaceutical companies. Improving bacterial growth and replication depends largely on the efficiency of translation, which is rate-limited by initiation. Among the most important interactions between the mRNA translation initiation region (TIR) and the translation machinery is the association between the Shine-Dalgarno (SD) sequence in the TIR and the complementary anti-SD (aSD) sequence which is located within a short unstructured segment that includes the 3’ terminus (3’ TAIL) of the mature 16S rRNA. However, the mature 3’ TAIL has been poorly characterized in the majority of bacteria, rendering optimal SD/aSD pairing unclear in these species. In light of this, we established a novel strategy to characterize the mature 3’ TAILs of bacterial species that leverages the availability of publically stored RNA sequencing (RNA-Seq) data. In chapter 2, we devised a RNA-Seq-based approach to successfully recover the experimentally verified 3’ TAIL in E. coli (5’-CCUCCUUA-3’) and resolve inconsistencies surrounding the identity of the 3’ TAIL in Bacillus subtilis. In chapter 3 we improve the method introduced in chapter 2 to clearly and more reliably define the 3’ TAIL termini for 13 bacterial species with available protein abundance data. Our results reveal considerable heterogeneity in the termini of 3’ TAILs among closely related species and that sites downstream of the canonical CCUCC aSD motif are more important to initiation than previously believed. My research contributes to advance our understanding in microbial translation efficiency in two significant ways: 1) providing an RNA-Seq-based approach to characterize rRNA transcripts, and 2) elucidating optimal recognition between protein-coding genes and the rRNA translation machinery.
ICEMST 2014 : International Conference on Education in Mathematics , Science & Technology ERADICATING MATHEMATICS ANXIETY AMONG SECONDARY SCHOOL STUDENTS USING COGNITIVE BEHAVIOURS THERAPY ( CBT )

Achievement in Mathematics to a large extent, is a function of examination anxiety, teachers’ instructional strategy, among other variables. The Onus of this paper is to empirically document the effectiveness of CBT in curbing mathematics anxiety in students in Nigeria. A sample of 154 students was composed. The instrument used is Mathematics Anxiety Test Scale (MATS). The reliability coefficient of 0.83 was obtained. The 154 students were pretested and those (68) who scored 24 and above were assigned to experimental group. Two research questions and two hypotheses guided the study. Research questions were addressed using mean and standard deviation while hypotheses were tested with t-test, ANCOVA. The result indicates a therapeutic significant difference in reduction of Mathematics anxiety of students and in terms of gender, no score differential. It was recommended that workshops/Seminars on psychological techniques on examination anxiety be organized for mathematics teachers.
Biology of Three ICE Families : SXT / R 391 , ICE Bs 1 , and ICE St 1 / ICE St 3 NICOLAS CARRARO

Integrative and Conjugative Elements (ICEs) are bacterial mobile genetic elements that play a key role in bacterial genomes dynamics and evolution. ICEs are widely distributed among virtually all bacterial genera. Recent extensive studies have unraveled their high diversity and complexity. The present review depicts the general conserved features of ICEs and describes more precisely three major families of ICEs that have been extensively studied in the past decade for their biology, their evolution and their impact on genomes dynamics. First, the large SXT/R391 family of ICEs disseminates antibiotic resistance genes and drives the exchange of mobilizable genomic islands (MGIs) between many enteric pathogens such as Vibrio cholerae. Second, ICEBs1 of Bacillus subtilis is the most well understood ICE of Gram-positive bacteria, notably regarding the regulation of its dissemination and its initially unforeseen extrachromosomal replication, which could be a common feature of ICEs of both Gram-positive and Gram-negative bacteria. Finally, ICESt1 and ICESt3 of Streptococcus thermophilus are the prototypes of a large family of ICEs widely distributed among various streptococci. These ICEs carry an original regulation module that associates regulators related to those of both SXT/R391 and ICEBs1. Study of ICESt1 and ICESt3 uncovered the cis-mobilization of related genomic islands (CIMEs) by a mechanism called accretion-mobilization, which likely represents a paradigm for the evolution of many ICEs and genomic islands. These three major families of ICEs give a glimpse about ICEs dynamics and their high impact on bacterial adaptation.
On the performance parameters of PM 2 . 5 and PM 1 size 1 separators for ambient aerosol monitoring 2

10 The performance of particle size separators that are characterized by their 11 cutpoint (d50) and the steepness of their penetration curves (σg) is a critical feature of 12 measurement methods for ambient PM2.5 and PM1 monitoring. The parameters d50 and 13 σg for PM2.5 size separators are regulated in the official measurement methods of 14 many countries and regions. However, those parameters for PM1 size separators have 15 not been previously specified. The interaction of particle size distributions (PSDs) and 16 the particle size separator performance characteristics has significant influence on the 17 PM sampling results. Atmospheric PSDs for each of the four seasons covering a range 18 of particulate pollution concentrations were measured in urban Beijing. The relative 19 differences (RD) between estimated PM2.5/PM1 sampler concentrations and actual 20 * Corresponding author: Tel/Fax:+86-10-61716674 E-mail: lixinghua@buaa.edu. cn AC CE PT ED M AN US CR IP T 2 concentrations associated with the interaction between performance characteristics of 21 size separator and actually measured urban PSDs, as well as for three idealized 22 ambient PSDs, have been systematically investigated. For the PM2.5 size separator, 23 when tolerance of cutpoint is 2.5 ± 0.2 μm and σg is no greater than 1.3, RD values for 24 most typical urban atmospheric aerosol conditions were within the permissible error 25 range (±5%). For the PM1 size separator, when tolerance of cutpoint and sharpness is 26 1.00 ± 0.02 μm and σg no greater than 1.2, respectively, the RD values for typical 27 urban atmospheric aerosol conditions are within the permissible range. Those 28 parameters could also meet the requirements for sampling of the idealized coarse 29 ambient aerosol distribution. 30
STEGANOGRAPHY ALGORITHMS FOR SECURE DATA COMMUNICATIONS

In the era of information technology, a large amount of digital information is distributed over the Internet in the form of videos, images, text, and audio. The main purpose of widespread distribution enables users to share knowledge between one another. As a result, data transmission and information sharing are effected due to malicious activities. Different techniques exist to protect user authentication, data privacy, and copyrights. Two main techniques that improve security and data protection are Cryptography and Steganography. Cryptographic algorithms convert the secret message from plain text into cipher text. Then the message is sent over the communication channel. Steganography hides a secret message inside the carrier media. This proposal will investigate different Steganography algorithms and present novel algorithms employing text file as a carrier file. The proposed model hides secret data in the text file by applying various properties into file font format by inserting special symbols in the text file. In addition, the suggested model can be applied in both Unicode and ASCII code languages, regardless of the text file format. The proposed system achieves a high degree of the main Steganography attributes like hidden ratio, robustness, and transparency. In addition, this proposal provides guidance for other researchers in text Steganography algorithms.
Inappropriate Use of Agrochemicals Poses Potential Threats to Botswana Vultures : A Call for Research and Legal Instruments

Agrochemicals are widely used across the world to serve different purposes. However, inappropriate use of agrochemicals affects wildlife particularly non-target species such as vultures. In this paper, we discuss the potential threats posed by inappropriate use of agrochemicals to vultures in Botswana. We discuss the ecosystem services provided by vultures, recent incidents of potential vulture poising in Botswana, why vultures are vulnerable to agrochemical poisoning and status of the use of chemicals in Botswana. We show that incidents of vulture mortalities possible due to deliberate and accidental poisoning of livestock and wildlife carcasses by farmers and poachers, respectively, are increasing since 2009 in Botswana. In Botswana, the distribution of agrochemicals is not well regulated although the Agrochemicals Act of 1999 and subsidiary 2003 legislation are in place to assist in this endeavour. In addition, factors contributing to vulture declines are not well documented and researched. The lack of information on factors contributing to vulture poisoning calls for collaborate multidisciplinary research to assess vulture population dynamics and the drivers of their population change, including poisoning to inform policies on use of agrochemicals in Botswana.
The West East Institute 1 THE IMPACT OF BRAND IMAGES ON B 2 B BUYING RELEVANCE

Despite an increased interest in B2B branding in the last decade, academic research on B2B branding has been slower to emerge which makes this field of marketing a relatively under-researched one. In this context, the purpose of the paper is to investigate the influence of brand images on the perceived buying relevance for B2B customers. Gaining insight into if and how brands play a role in establishing perceived buying relevance is expected to be determining subsequent decision-making processes. Through surveying B2B professionals on their emotional responses on brand stimuli, the emotionality of the respective brands was identified. The methodology used was the Self-Assessment Manikin, a pictorial method to measure emotions which has found various applications in both psychological and marketing-related research. Further, through correlation analyses, a relationship between emotionality and buying relevance was identified. The participants of the survey were professionals and managers working in the railway industry, an industry-branch which is characterized by a high degree of specialization, complexity and long-term business relationships which math the long lifecycles of the equipment subject to purchase or lease. The main findings were that, unlike former assumptions, B2B brands can vary in emotionality and that emotionality has an impact on perceived buying relevance. Further, the context in which deciders in heavy railway equipment operate has been empirically established. The research results contribute to a better understanding of the role of brand images in B2B markets, especially in high-risk and high-complexity contexts. The chosen research topic has a high degree of actuality since many investment good markets are increasingly shifting to demand-driven markets where marketers need to gain competitive edge understanding and utilizing intangible, emotional assets and build on their brand equity. This trend is expected to sustain which makes the research topic an interesting and actual one for both marketing scholars and practitioners. Development of a measurement instrument for brand emotions using proven non-verbal rating scales. Empirical testing of brand images using real-world industry brands in the railway industry. Practitioners in B2B markets should dedicate more attention to how their brand is perceived in general and the emotional side of their brand image in particular as this impacts their market success. Neglecting the role brands play in the B2B market place can lead to negative effects in terms of sales success, while building positive and emotionally touching brand images can have a positive impact.