Miracle-dz/UniFAR-FTUs huggingface dataset:
THE NUMERICAL EVALUATION OF THE MAXIMUM-LIKELIHOOD ESTIMATE OF A SUBSET OF MIXTURE PROPORTIONS*

In this note, we give necessary and sufficient conditions for a maximum-likelihood estimate of a subset of the proportions in a mixture of specified distributions. From these conditions, we derive likelihood equations satisfied by the maximum-likelihood estimate and discuss a successive-approximations procedure suggested by these equations for numerically evaluating the maximum-likelihood estimate. It is shown that, with probability 1 for large samples, this procedure converges locally to the maximum- likelihood estimate whenever a certain step-size lies between 0 and 2. Furthermore, optimal rates of local convergence are obtained for a step-size which is bounded below by a number between 1 and 2. 1. Introduction. Let x be an n-dimensional random variable whose density function is a convex combination of density functions po, P1,i. , Pm on Ri. In parti- cular, suppose that the density function of x is p(x, do), a member of the parametric family of density functions m p (x, a)= aipi (x) + (1 - j)po(x) i=l The results given here generalize those of (2), in which a restricted iterative procedure is considered in the special case /3 = 1. We also remark that our results apply to the problem of numerically evaluating a maximum-likelihood estimate of a
Sweet As Honey: A Content Analysis Of How Beekeeping Is Reflected In Romanian Mass Media

Apiculture is an activity with multiple ramifications, as it is approached from an economic, biologic, social or ecologic perspective in the attempt to tackle its contributions to biodiversity, a healthy eating style, the sustainable growth of agricultural production or community development. In this material we will study apiculture from a sociologic perspective, focusing on the way the field is reflected in mass media. The aim of the paper is to show the way in which the experts, the legislation and the institutions involved contribute to the construction of a particular image and to its traits. The exploratory research is based primarily on content analysis, but also on data mining and semantic network visualization. These methods are applied to a number of 2,248 articles published between 2010 and 2014 in digital format on the websites of news agencies and news aggregators such as Agerpres, Hotnews, Mediafax and Ziare.com. The results point to an image in which the dominant dimension is natural, ecologic, health and medicine oriented, with secondary aspects concerning the way in which the bees and their products connect the people and the environment.
Toral rank conjecture for moment-angle complexes

We consider an operation K \to L(K) on the set of simplicial complexes, which we call the "doubling operation". This combinatorial operation has been recently brought into toric topology by the work of Bahri, Bendersky, Cohen and Gitler on generalised moment-angle complexes (also known as K-powers). The crucial property of the doubling operation is that the moment-angle complex Z_K can be identified with the real moment-angle complex RZ_L(K) for the double L(K). As an application we prove the toral rank conjecture for Z_K by estimating the lower bound of the cohomology rank (with rational coefficients) of real moment-angle complexes RZ_K$. This paper extends the results of our previous work, where the doubling operation for polytopes was used to prove the toral rank conjecture for moment-angle manifolds.
Tacrolimus in pancreas transplant: a focus on toxicity, diabetogenic effect and drug–drug interactions

Introduction: With further reduction in surgical complications and improvement in immunosuppressive protocols, pancreas transplant offers excellent outcomes for patients with diabetes. However, long-term survival of pancreas allograft is affected not only by rejection but also by immunosuppressive regimen toxicity. Areas covered: This article reviews the existing literature and knowledge of tacrolimus toxicity and focuses on its diabetogenic effect after pancreas transplant. Some clinically relevant drug–drug interactions with glucocorticoids and sirolimus are also highlighted. This review also summarizes the diabetogenic mechanisms of tacrolimus, the alternatives to minimize these effects, and the main differential diagnosis of hyperglycemia after pancreas transplant. Expert opinion: Tacrolimus is a potent calcineurin inhibitor, an important pathway that regulates pancreatic development. Tacrolimus can induce β-cell apoptosis, decrease insulin exocytosis and reduce insulin gene transcription, which ultimately lead to impaired functional β-cell mass after pancreas transplant. Furthermore, insulin resistance can exacerbate the diabetogenic effect of tacrolimus due to inhibition of insulin gene transcription and β-cell proliferation. It is important to critically analyze the results of clinical studies and investigate new immunosuppressive drugs and/or novel drug combinations. It is equally important to comprehend and interpret experimental data. Therefore, minimization of side effects, based on safe approaches, can prolong pancreas allograft survival.
Beamforming Transmission in IEEE 802.11ac under Time-Varying Channels

The IEEE 802.11ac wireless local area network (WLAN) standard has adopted beamforming (BF) schemes to improve spectral efficiency and throughput with multiple antennas. To design the transmit beam, a channel sounding process to feedback channel state information (CSI) is required. Due to sounding overhead, throughput increases with the amount of transmit data under static channels. Under practical channel conditions with mobility, however, the mismatch between the transmit beam and the channel at transmission time causes performance loss when transmission duration after channel sounding is too long. When the fading rate, payload size, and operating signal-to-noise ratio are given, the optimal transmission duration (i.e., packet length) can be determined to maximize throughput. The relationship between packet length and throughput is also investigated for single-user and multiuser BF modes.
Analogical inference over a common sense database

This paper shows that by applying analogical inference techniques to a large natural language common sense database, we can generate new, plausible common sense facts. Two systems that do this are described. Being able to generate new facts in this manner allows quick augmentation of the common sense database. The role of analogical inference in common sense reasoning has been discussed before (Carbonell 1983), but only recently have large common sense databases become publicly available. We used the Open Mind Common Sense (OMCS) database, which contains several hundred thousand English common sense statements (Singh 2002). The OMCS database is built by internet users who are prompted to enter common sense facts at a website. The reason we use the OMCS database instead of the CYC common sense database (Lenat and Guha 1994) is because this analogical inference work is concurrently being integrated into OMCS's data collection mechanism. The idea is that an internet user can enter a fact at the OMCS website, then the system uses techniques described by this paper to respond with 30 plausible deductions based off the fact. Then, the user decides whether each deduction is true or false. True deductions become additional database facts, while false ones become negative expertise. Doing this allows for much faster data input by users. To carry out the analogical inference, we first represent the OMCS database as a set of concepts and a set of relations. A concept is a noun phrase or an adjective. A relation looks like “A ? is for playing ? ”. Each original sentence becomes a relation after its concepts are replaced by question marks.
Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition

Recognizing facial action units (AUs) during spontaneous facial displays is a challenging problem. Most recently, Convolutional Neural Networks (CNNs) have shown promise for facial AU recognition, where predefined and fixed convolution filter sizes are employed. In order to achieve the best performance, the optimal filter size is often empirically found by conducting extensive experimental validation. Such a training process suffers from expensive training cost, especially as the network becomes deeper. This paper proposes a novel Optimized Filter Size CNN (OFS-CNN), where the filter sizes and weights of all convolutional layers are learned simultaneously from the training data along with learning convolution filters. Specifically, the filter size is defined as a continuous variable, which is optimized by minimizing the training loss. Experimental results on two AU-coded spontaneous databases have shown that the proposed OFS-CNN is capable of estimating optimal filter size for varying image resolution and outperforms traditional CNNs with the best filter size obtained by exhaustive search. The OFS-CNN also beats the CNN using multiple filter sizes and more importantly, is much more efficient during testing with the proposed forward-backward propagation algorithm.
Feasibility study of Improvement Experimental Measurement and Thermodynamic Modelling of Contaminants Effect on the Thermo-Mechanical Properties of Industrial Petroleum recycled plastics wastes

The recycled plastics (RHDPE and RLDPE) were exposed to environment conditions for many years. Also the chemical contaminants had effects on the thermo-mechanical and other properties of these wastes. Then a weathering effect data is examined for both Iraqi and Foreign wastes on the thermo-mechanical and chemical properties (Tensile strength, modulus, elongation, impact and permeability). The different mathematical software model were applied to analysis these weathering – properties data in order to estimate which one or several among these properties had more effective by these weathering conditions such as (concentration of contaminant, time, temperature, thickness of specimen, length of spectra, basic property). The results shows that a multi-polynomial model has a best fit for most or several of properties to active weathering variables, also gave a vary residual and deviation than experimental analyzed data for both sources of wastes Iraqi and Foreign RHDPE and RLDPE. Also the results for thermo-mechanical and chemical properties prove that both tensile strength and modulus of elasticity thermo-mechanical properties and permeability / length of spectra chemical property were given a high quality of correction and fitting factor from 93-99 %, with less deviation and residual function was produced. And the results of RHDPE gave a best fit than RLDPE for most of checked analysis properties (thermo-mechanical and chemical properties).
Looking after the teachers: exploring the emotional labour experienced by teachers of looked after children

Abstract Whilst outcomes for looked after children (LAC) have been extensively discussed, less attention has been paid to the experiences of teachers of this group of children. It is accepted that Emotional Labour (EL) is commonplace in the teaching profession but no research has investigated how, and to what extent, teachers experience emotional labour during interactions with LAC. Fourteen Key Stage Two teachers of LAC participated in the current study by completing semi-structured interviews. Results indicate that participants experience emotional labour during interactions with LAC and that this may be mediated, to a degree, by factors including role constructions, perceptions of support and self-perceived role facilitators such as perception of a professional duty. The potential benefit of educational psychologists understanding better, and supporting, the impact of emotional labour on teachers of LAC is subsequently discussed.
VIRAPOPS: a forward simulator dedicated to rapidly evolved viral populations

SUMMARY Daily, mutability and recombination of RNA viruses result in the production of million variants. All these rapid genomic changes directly influence the functional sites of the protein, its 3D structure or its drug resistances. Therefore, it is important to simulate these drastic switches to determine their effects on virus populations. Many computer programs are able to simulate specific variations in DNA genomes, but are generally non-adapted to RNA viruses. They simulate site-specific selection pressures, but rarely pressures on covariant or on higher order correlated sites and no at all on synthetic lethal groups. That is why we felt it important to create VIRAPOPS, a forward simulator that models specific RNA virus functions. It was designed for computational biologists, biologists and virologists. AVAILABILITY AND IMPLEMENTATION Free binaries are available through a software repository at http://petitjeanmichel.free. fr/itoweb.petitjean. freeware.html.
Loop detection in robotic navigation using MPEG CDVS

The choice for image descriptor in a visual navigation system is not straightforward. Descriptors must be distinctive enough to allow for correct localization while still offering low matching complexity and short descriptor size for real-time applications. MPEG Compact Descriptor for Visual Search is a low complexity image descriptor that offers several levels of compromises between descriptor distinctiveness and size. In this work we describe how these trade-offs can be used for efficient loop-detection in a typical indoor environment.
In vivo reflectance of blood and tissue as a function of light wavelength

The reflectance of light from in vivo tissue is described for wavelengths in the range from 420 to 940 nm, based on photon diffusion theory and on experimental results from studies of 17 subjects. The results show a minimum reflectance and a peak sensitivity to the blood pulsations in the wavelength range from 510 to 590 nm. Skin pigmentation is seen to attenuate reflectance rather than altering the character of the modulation spectra. Based on the model presented, the dependence of modulation spectra on mean blood fractional volume as well as wavelength is described theoretically and corroborated by further experimental data at 570 and 630 nm. At these latter wavelengths, the signal-to-noise ratio is calculated for the blood volume pulsation signal in the presence of physiological noise. The median for calculated ratios of reflectance modulation by blood pulsation and ratios of signal to noise between the two wavelengths are 13.1 and 7.5, respectively, for 93 sites in nine subjects. These results are seen to be consistent with the theory. <<ETX>>
Piecewise linear image coding using surface triangulation and geometric compression

The provably NP-hard problem of finding optimal piecewise linear approximation for images is extended from 1D curve fitting to 2D surface fitting by a dual-agent algorithm. The results not only yield a storage-efficient codec for range, or intensity, images but also a surface triangulation technique to generate a succinct, accurate and visually pleasant 3D visualization model. Compared with the traditional piecewise linear image coding (PLIC) algorithms, triangulation of a range image is more adaptive due to conformity of the shape, orientation and size of triangles with the image contents. The triangularization algorithm presented here differs from previous approaches in that it strives to minimize the total number of triangles (or vertices) needed to approximate the image surface while keeping the deviation of any intensity value to within a prescribed error tolerance. Unlike most methods of bottom-up triangularization, which could bog down before any mesh simplification even begins, this algorithm fits the surface in a top-down manner, avoiding the generation of most unnecessary triangles. When combined with an efficient 3D triangulation-encoding scheme, the algorithm achieves compact code length with guaranteed error bound, thus providing a more faithful representation of all image features. A variety of benchmark test images have been experimented with and compared.
Sound Ranking Using Auditory Sparse-Code Representations

The task of ranking sounds from text queries is a good test application for machine-hearing techniques, and particularly for comparison and evaluation of alternative sound representations in a large-scale setting. We have adapted a machine-vision system, “passive-aggressive model for image retrieval” (PAMIR) [2], which efficiently learns, using a ranking-based cost function, a linear mapping from a very large sparse feature space to a large query-term space. Using this system allows us to focus on comparison of different auditory front ends and different ways of extracting sparse features from high-dimensional auditory images. In addition to two main auditory-image models, we also include and compare a family of more conventional Mel-Frequency Cepstral Coefficients (MFCC) front ends. The experimental results show a significant advantage for the auditory models over vector-quantized MFCCs. The two auditory models tested use the adaptive polezero filter cascade (PZFC) auditory filterbank and sparse-code feature extraction from stabilized auditory images via multiple vector quantizers. The models differ in their implementation of the strobed temporal integration used to generate the stabilized image. Using ranking precision-at-top-k performance measures, the best results are about 72% top-1 precision and 35% average precision, using a test corpus of thousands of sound files and a query vocabulary of hundreds of words.
A journey through the "desert" of unemployment : pastoral responses to people "between jobs"

In this research project the research participants and I embarked on a journey through the “desert” of unemployment. I was introduced to the research participants at Jacob’s Well, a ministry for people “between jobs” The effects of unemployment on a male’s identity were explored, as well as the pastoral response of caregivers to people “between jobs”. A phenomenological study was undertaken in which interviews with the participants formed the basis of the research. The structured section of the interviews was guided by the research questions, but the largest part of the interviews was about the participants’ personal journeys “between jobs. ” The role of a ministry like Jacob’s Well, catering for people “between jobs”, was highlighted and recommendations for practical theology and pastoral praxis were made.
Non-Gaussian Statistical Interconnect Timing Analysis

This paper focuses on statistical interconnect timing analysis in a parameterized block-based statistical static timing analysis tool. In particular, a framework for performing timing analysis of RLC networks with step inputs, under both Gaussian and non-Gaussian sources of variation, is presented. In this framework, resistance, inductance, and capacitance of the RLC line are modeled in a canonical first order form and used to produce the corresponding propagation delay and slew (time) in the canonical first-order form. To accomplish this step, mean, variance, and skewness of delay and slew distributions are obtained in an efficient, yet accurate, manner. The proposed framework can be extended to consider higher order terms of the various sources of variation. Experimental results show average errors of less than 2% for the mean, variance and skewness of interconnect delay and slew while achieving orders of magnitude speedup with respect to a Monte Carlo simulation with 104 samples
Borderline Personality Traits, Rumination, and Self-Injurious Behavior: An Empirical Test of the Emotional Cascades Model in Adult Male Offenders

This study examined the Emotional Cascade Model in adult male offenders with borderline personality traits. Participants were 179 adults detained in a medium-secure prison, all of whom completed a battery of questionnaire measures and self-reported their actual prison behavior. The results support the application of the model to this population, suggesting that emotional cascades (measured in terms of rumination) may play an important role in non-suicidal self-injury (NSSI) and suicidality in adult male offenders, although this needs further exploration. These findings highlight the benefits of targeting rumination to manage risk of NSSI and suicidality within custodial settings.
Taxonomic status of Kitasatosporia, and proposed unification with Streptomyces on the basis of phenotypic and 16S rRNA analysis and emendation of Streptomyces Waksman and Henrici 1943, 339AL.

Species classified within the genus Kitasatosporia share many of the phenotypic characteristics typical of streptomycetes. By using a probabilistic identification scheme, they were identified with Streptomyces exfoliatus cluster 5, a species group within Streptomyces. The four species studied hybridized with a 16S rRNA genus probe for Streptomyces spp. , indicating a close relationship between the two genera. The kitasatosporias were resistant to selected polyvalent streptomycete phages tested. Quantitative analysis showed that meso-diaminopimelic acid varied from 49 to 89% in Kitasatosporia species and from 1 to 16% in Streptomyces species depending on growth conditions. On the basis of 16S rRNA analysis, it is proposed to reduce Kitasatosporia to synonymy with Streptomyces. As a result, the new names proposed are Streptomyces mediocidicus comb. nov., Streptomyces phosalacineus comb. nov., Streptomyces setae comb. nov., and Streptomyces griseolosporeus comb. nov., nom. nov.
The challenge of working with racially motivated offenders: An exercise in ambivalence?

A Probation Circular published in 2005 announced that accredited one-to-one programmes should be developed for Racially Motivated Offenders (RMOs). This article reviews a number of existing literatures written by both practitioners and academics which have focused on the problems and opportunities that arise during interventions with RMOs. At the same time, in this article, insights derived from the latter literatures are contextualized within poststructuralist and discursive psychological literatures. The outcome of this is an attempt to forge common ground between practitioner-derived insights on racism, racists, identity, locality and shared `communities of prejudice' with poststructuralist approaches to identity and the advancement of specific therapeutic/correctionalist techniques (especially the motivational interviewing technique pioneered by Miller and Rollnick, 1991) for facilitating change processes in RMOs.
The Cytomegaloviral Protein pUL138 Acts as Potentiator of Tumor Necrosis Factor (TNF) Receptor 1 Surface Density To Enhance ULb′-Encoded Modulation of TNF-α Signaling

ABSTRACT Human cytomegalovirus is a ubiquitous herpesvirus that establishes lifelong latent infection. Changes in immune homeostasis induce the reactivation of lytic infection, which is mostly inapparent in healthy individuals but often causes overt disease in immunocompromised hosts. Based on discrepant tumor necrosis factor receptor 1 surface disposition between human cytomegalovirus AD169 variants differing in the ULb′ region, we identified the latency-associated gene product pUL138, which also is expressed during productive infection, as a selective potentiator of tumor necrosis factor receptor 1, one of the key receptors of innate immunity. Ectopically expressed pUL138 coprecipitated with tumor necrosis factor receptor 1, extended the protein half-life, and enhanced its signaling responses, thus leading to tumor necrosis factor receptor 1 hyperresponsiveness. Conversely, the targeted deletion of UL138 from the human cytomegaloviral genome strongly reduced tumor necrosis factor receptor 1 surface densities of infected cells. Remarkably, the comparison of UL138 deficiency to ULb′ deficiency revealed the presence of further positive modulators of tumor necrosis factor alpha signal transduction encoded within the human cytomegalovirus ULb′ region, identifying this region as a hub for multilayered tumor necrosis factor alpha signaling regulation.