Maximum Likelihood Analysis Methods Research Articles

Towards detecting super-GeV dark matter via annihilation to neutrinos

The next generation of neutrino telescopes will feature unprecedented sensitivities in the detection of neutrinos. Here we study the capabilities of a large-scale neutrino telescope, like the fully-operating KM3NeT experiment in the near future, for detecting dark matter annihilation signals from the Galactic Centre.We consider both ORCA and ARCA detectors, covering dark matter masses from a few GeV to 100 TeV. We obtain the sensitivities with a maximum-likelihood analysis method and present them as upper limits in the thermally averaged annihilation cross-section into Standard Model fermions. Our projections show that the sensitivity of such a neutrino telescope can reach the thermal relic line for mχ ≳ 1 TeV and for mχ ≃ few GeV, for the NFW dark matter density profile. This demonstrates that ORCA- and ARCA-like detectors will be able to perform competitive dark matter searches in a wide range of masses. The implications of these striking projections are investigated in a few selected dark matter particle models, where we show that neutrino telescopes are able to probe new parameter space.

I, me, and my everything: Self conceptual traits and compulsive buying behavior

Compulsive buying behavior is detrimental to the well-being of the consumers, brands, and the economy. Therefore, the current study aims to understand how the self-conceptual traits and values underline the corridors to the compulsive buying behavior of fashion apparel products. We collected self-administered data from systematically selected 744 young shopping mall consumers and employed structural equation modeling (SEM) via maximum likelihood method for analysis. Self-conceptual traits (physical and achievement vanity), materialism, and brand consciousness play a pivotal role in the development of compulsive buying behavior in young consumers of Pakistan. Furthermore, the presence of materialistic attitude and brand consciousness in consumers firmly explains vanity-driven consumer's excessive, chronic, and unneeded purchasing of fashion appeal products. Policymakers and fashion apparel marketers should limit the excessive use of self-oriented and self-defining appeals in their marketing campaigns and focus on strategies that build consumer relationships with brands based on mutual benefits and welfare.

University lecturers acceptance of moodle platform in the context of the COVID-19 pandemic

PurposeThis study aimed at determining factors which affect university lecturers’ adoption of the Moodle platform under the conditions of COVID-19. In considering the condition of the COVID-19 pandemic, the unified theory of acceptance and use of technology (UTAUT) model was applied and extended by adding two additional variables of learning demand and time pressure to assess their influence on Moodle platform adoption.Design/methodology/approachData were obtained from the 226 participants through an online structured questionnaire. The covariance-based approach of structural equation modeling was used to examine the proposed model. The structural model was tested using the maximum likelihood method of analysis of a moment structures to analyze the study’s hypotheses.FindingsResults suggest that performance expectations have a substantial influence on behavioral intent. The effort expectancy, social effect and facilitative factors have no effects on behavioral intentions. Facilitating conditions directly and significantly affect the actual use of Moodle. The results also reveal that learning demands, which is a salient predictor of perceived time pressure, in turn directly and significantly affects the actual use of Moodle. Finally, the behavioral intention has a strong influence on Moodle’s actual usage.Originality/valueAlthough the UTAUT 2 model is considered to be a new and updated version of UTAUT, it has not been used since newly added variables, namely, price, habit and hedonic motivations, are less related to the context and to avoid respondents’ paradox. Moreover, using the Moodle platform in the researched context is compulsory for both students and instructors. Discussion, insights, limitations and recommendations for future studies are suggested.

Normal Tissue Complication Probability Modeling of Radiation-Induced Hypothyroidism After Head-and-Neck Radiation Therapy

To determine the dose-response relationship of the thyroid for radiation-induced hypothyroidism in head-and-neck radiation therapy, according to 6 normal tissue complication probability models, and to find the best-fit parameters of the models. Sixty-five patients treated with primary or postoperative radiation therapy for various cancers in the head-and-neck region were prospectively evaluated. Patient serum samples (tri-iodothyronine, thyroxine, thyroid-stimulating hormone [TSH], free tri-iodothyronine, and free thyroxine) were measured before and at regular time intervals until 1 year after the completion of radiation therapy. Dose-volume histograms (DVHs) of the patients' thyroid gland were derived from their computed tomography (CT)-based treatment planning data. Hypothyroidism was defined as increased TSH (subclinical hypothyroidism) or increased TSH in combination with decreased free thyroxine and thyroxine (clinical hypothyroidism). Thyroid DVHs were converted to 2 Gy/fraction equivalent doses using the linear-quadratic formula with α/β = 3 Gy. The evaluated models included the following: Lyman with the DVH reduced to the equivalent uniform dose (EUD), known as LEUD; Logit-EUD; mean dose; relative seriality; individual critical volume; and population critical volume models. The parameters of the models were obtained by fitting the patients' data using a maximum likelihood analysis method. The goodness of fit of the models was determined by the 2-sample Kolmogorov-Smirnov test. Ranking of the models was made according to Akaike's information criterion. Twenty-nine patients (44.6%) experienced hypothyroidism. None of the models was rejected according to the evaluation of the goodness of fit. The mean dose model was ranked as the best model on the basis of its Akaike's information criterion value. The D(50) estimated from the models was approximately 44 Gy. The implemented normal tissue complication probability models showed a parallel architecture for the thyroid. The mean dose model can be used as the best model to describe the dose-response relationship for hypothyroidism complication.

Analysis of Welded Structures with Failed and Non-Failed Welds Based on Maximum Likelihood

A maximum likelihood analysis method allowing for random censoring has been developed for statistical evaluation of fatigue data. The method is shown to be especially useful when analysing welded structures that have two or more potential failure locations. In those cases where fatigue cracking is observed at only one location, the method allows the non-failures to also be statistically considered. The method is illustrated using a fatigue data set from spectrum loaded welds made from 10 mm thick HTS 390 and VHTS 690 high tensile strength steel with three fabrication procedures. Each of the specimens tested had two or more failure locations and only a few of them showed significant fatigue cracking at both locations. As compared to the “usual” quality welded specimens from high strength steel, the use of a second weld pass followed by TIG dressing improved fatigue strength by about 25%. Full penetration and grinded welds from very high strength steel showed fatigue strength improvement of about 30% at 1×106 cycles to failure but significantly more at longer lives. For both “usual” quality and grinded welds, spectrum loading with alternating tension and compressive mean stresses resulted in about twice the fatigue life as compared to spectrum loading with constant tensile mean stress. This indicates that the portion of the spectrum with compressive cycles was non-damaging.

A radiation hybrid map of human chromosome 11q22-q23 containing the ataxia-telangiectasia disease locus.

We describe a high-resolution radiation hybrid map of human chromosome 11q22-q23 containing the ataxia-telangiectasia (AT) disease gene loci. The order and intermarker distances of 32 chromosome 11q22-q23 markers were determined by a multipoint maximum likelihood method of analysis of the cosegregation of markers in 100 radiation hybrids. The radiation hybrid map of polymorphic loci was consistent with genetic linkage maps of common markers. Several genes, including alpha B-crystallin, adrenal ferrodoxin, CBL2, collagenase, dopamine receptor type 2, neural cell adhesion molecule, progesterone receptor, and stromelysins 1 and 2, were placed in relation to previously ordered, genetically mapped polymorphic loci. Five new markers (alpha B-crystallin, adrenal ferrodoxin, CJ52.114, CJ52.3, and D11S535) were ordered within the current published flanking markers for the AT group A and group C disease loci. A candidate AT group D gene (ATDC) identified by Kapp et al. (1992, Am. J. Hum. Genet. 51: 45-54) was mapped telomeric to THY1, outside the flanking markers identified by multipoint linkage analysis for the major AT locus.

Dynamic identification of the cooling system in a fluidized-bed combustor

The experimental identification of a dynamic model of the cooling system in a fluidized-bed combustor pilot-scale unit using the maximum likelihood method of analysis is described. The aim of the study was to obtain a model of the process which can be used for the design of a controller for the system, possibly an adaptive controller. As the mechanism of the cooling system is rather complex to model using physical analysis, the empirical method chosen was the only way to get reasonable results in a short time. Data were processed using an interactive identification program package. A first-order dynamic model has been found to describe the process adequately.