Mixed Set Research Articles

Addressing overdispersion and zero-inflation for clustered count data via new multilevel heterogenous hurdle models

ABSTRACT Unobserved heterogeneity causing overdispersion and the excessive number of zeros take a prominent place in the methodological development on count modeling. An insight into the mechanisms that induce heterogeneity is required for better understanding of the phenomenon of overdispersion. When the heterogeneity is sourced by the stochastic component of the model, the use of a heterogenous Poisson distribution for this part encounters as an elegant solution. Hierarchical design of the study is also responsible for the heterogeneity as the unobservable effects at various levels also contribute to the overdispersion. Zero-inflation, heterogeneity and multilevel nature in the count data present special challenges in their own respect, however the presence of all in one study adds more challenges to the modeling strategies. This study therefore is designed to merge the attractive features of the separate strand of the solutions in order to face such a comprehensive challenge. This study differs from the previous attempts by the choice of two recently developed heterogeneous distributions, namely Poisson–Lindley (PL) and Poisson–Ailamujia (PA) for the truncated part. Using generalized linear mixed modeling settings, predictive performances of the multilevel PL and PA models and their hurdle counterparts were assessed within a comprehensive simulation study in terms of bias, precision and accuracy measures. Multilevel models were applied to two separate real world examples for the assessment of practical implications of the new models proposed in this study.

Functional sets with typed symbols: Mixed zonotopes and Polynotopes for hybrid nonlinear reachability and filtering

Verification and synthesis of Cyber–Physical Systems (CPS) are challenging and still raise numerous issues so far. In this paper, based on a new concept of mixed sets defined as function images of symbol type domains, a compositional approach combining eager and lazy evaluations is proposed. Syntax and semantics are explicitly distinguished. Both continuous (interval) and discrete (signed, boolean) symbol types are used to model dependencies through linear and polynomial functions, so leading to mixed zonotopic and polynotopic sets. Polynotopes extend sparse polynomial zonotopes with typed symbols. Polynotopes can both propagate a mixed encoding of intervals and describe the behavior of logic gates. A functional completeness result is given, as well as an inclusion method for elementary nonlinear and switching functions. A Polynotopic Kalman Filter (PKF) is then proposed as a hybrid nonlinear extension of Zonotopic Kalman Filters (ZKF). Bridges with a stochastic uncertainty paradigm are briefly outlined. Finally, several discrete, continuous and hybrid numerical examples including comparisons illustrate the effectiveness of the theoretical results.

Diversity and Depth Distribution of Modern Benthic Foraminifera Offshore Brunei Darussalam

ABSTRACT The distribution of modern benthic foraminifera is studied from offshore mixed carbonate-siliciclastic settings of Brunei Darussalam located in northwestern Borneo (South China Sea). The sediments were collected from 17 sites (i.e., shallow reefs, sunken wrecks, and two depth transects). A total of 231 species were identified from 8 to 63 m water depth. We conducted several analyses to understand the patterns of faunal composition, including: (1) Cluster analysis and Principal Component Analysis together with correlation to define relation among the sites; (2) Diversity indices, such as Shannon Index and Fisher's Alpha Index to assess diversity patterns at sites; and (3) Foram Index (FI) to determine whether the water quality indicates conditions that support reef growth. The most abundant foraminiferal groups from the reef and most wreck samples are larger benthic foraminifera (LBF), especially Calcarinidae and Amphisteginidae, whereas in the muddier sites the most abundant are smaller benthic foraminifera (SBF) with the genera Pseudorotalia and Asterorotalia. Certain species from the groups have shown patterns that do or do not correlate with depth and clay content.

DEEPFAKE DETECTION USING EYE-BLINKING PATTERN

Deep learning algorithms have become so potent due to increased computing power that it is now relatively easy to produce human-like synthetic videos, sometimes known as & quot; deep fakes. & quot; It is simple to imagine scenarios in which these realistic face switched deep fakes are used to extort individuals, foment political unrest, and stage fake terrorist attacks. This paper provides a deep learning strategy novel for the efficient separation of fraudulent films produced by AI from actual ones. Automatically spotting replacement and recreation deep fakes is possible with our technology. To combat artificial intelligence, we are attempting to deploy artificial intelligence. The framelevel characteristics are extracted by our system using a Res-Next Convolution neural network, and later these features are applied to train an LSTM-based recurrent neural network to determine if those submitted video is being altered in any way or not, i.e. whether it is a deep fake or authentic video. We test our technique on a sizable quantity of balanced and mixed data sets created by combining the different accessible data sets, such as Face-Forensic++[1], Deep fake detection challenge[2], and Celeb-DF[3], in order to simulate real-time events and improve the model's performance on real-time data.

Differential equation for partition functions and a duality pseudo-forest

We consider finite quantum systems defined by a mixed set of commutation and anti-commutation relations between components of the Hamiltonian operator. These relations are represented by an anti-commutativity graph that contains necessary and sufficient information for computing the full quantum partition function. We derive a second-order differential equation for an extended partition function z[β, β′, J] that describes a transformation from a “parent” partition function z[0, β′, J] (or anti-commutativity graph) to a “child” partition function z[β, 0, J] (or anti-commutativity graph). The procedure can be iterated, and then one forms a pseudo-forest of duality transformations between quantum systems, i.e., a directed graph in which every vertex (or quantum system) has at most one incoming edge (from its parent system). The pseudo-forest has a single tree connected to a constant partition function, many pseudo-trees connected to self-dual systems, and all other pseudo-trees connected to closed cycles of transformations between mutually dual systems. We also show how the differential equation for the extended partition function can be used to study disordered systems.

Extraction of Aquaculture Pond Region in Coastal Waters of Southeast China Based on Spectral Features and Spatial Convolution

To control the negative effects resulting from the disorderly development of aquaculture ponds and promote the development of the aquaculture industry, rapid and accurate identification and extraction techniques are essential. An aquaculture pond is a special net-like water body divided by complex roads and dikes. Simple spectral features or spatial texture features are not sufficient to accurately extract it, and the mixed feature rule set is more demanding on computer performance. Supported by the GEE platform, and using the Landsat satellite data set and corresponding DEM combined with field survey data, we constructed a decision-making model for the extraction of aquaculture ponds in the coastal waters, and applied this method to the coastal waters of Southeast China. This method combined the image spectral information, spatial features, and morphological operations. The results showed that the total accuracy of this method was 93%, and the Kappa coefficient was 0.86. The overlapping proportions of results between the automated extraction and visual interpretation for test areas were all more than 90%, and the average was 92.5%, which reflected the high precision and reliability of this extraction method. Furthermore, in 2020, the total area of coastal aquaculture ponds in the study area was 6348.51 km2, which was distributed primarily in the cities of Guangdong and Jiangsu. Kernel density analysis suggested that aquaculture ponds in Guangdong and Jiangsu had the highest degree of concentration, which means that they face higher regulatory pressure in the management of aquaculture ponds than other provinces. Therefore, this method can be used to extract aquaculture ponds in coastal waters of the world, and holds great significance to promote the orderly management and scientific development of fishery aquaculture.

Multispecies Probiotic for the Prevention of Antibiotic-Associated Diarrhea in Children

The efficacy of multispecies probiotic formulations in the prevention of antibiotic-associated diarrhea (AAD) remains unclear. To assess the effect of a multispecies probiotic on the risk of AAD in children. This randomized, quadruple-blind, placebo-controlled trial was conducted from February 2018 to May 2021 in a multicenter, mixed setting (inpatients and outpatients). Patients were followed up throughout the intervention period. Eligibility criteria included age 3 months to 18 years, recruitment within 24 hours following initiation of broad-spectrum systemic antibiotics, and signed informed consent. In total, 646 eligible patients were approached and 350 patients took part in the trial. A multispecies probiotic consisting of Bifidobacterium bifidum W23, Bifidobacterium lactis W51, Lactobacillus acidophilus W37, L acidophilus W55, Lacticaseibacillus paracasei W20, Lactiplantibacillus plantarum W62, Lacticaseibacillus rhamnosus W71, and Ligilactobacillus salivarius W24, for a total dose of 10 billion colony-forming units daily, for the duration of antibiotic treatment and for 7 days after. The primary outcome was AAD, defined as 3 or more loose or watery stools per day in a 24-hour period, caused either by Clostridioides difficile or of otherwise unexplained etiology, after testing for common diarrheal pathogens. The secondary outcomes included diarrhea regardless of the etiology, diarrhea duration, and predefined diarrhea complications. A total of 350 children (192 boys and 158 girls; mean [range] age, 50 [3-212] months) were randomized and 313 were included in the intention-to-treat analysis. Compared with placebo (n = 155), the probiotic (n = 158) had no effect on risk of AAD (relative risk [RR], 0.81; 95% CI, 0.49-1.33). However, children in the probiotic group had a lower risk of diarrhea regardless of the etiology (RR, 0.65; 95% CI, 0.44-0.94). No differences were observed between the groups for most of the secondary outcomes, including adverse events. A multispecies probiotic did not reduce the risk of AAD in children when analyzed according to the most stringent definition. However, it reduced the overall risk of diarrhea during and for 7 days after antibiotic treatment. Our study also shows that the AAD definition has a significant effect on clinical trial results and their interpretation. ClinicalTrials.gov Identifier: NCT03334604.

A game theoretic approach to a problem in polymatroid maximization

We consider the problem of maximizing the minimum (weighted) value of all components of a vector over a polymatroid. This is a special case of the lexicographically optimal base problem introduced and solved by Fujishige. We give an alternative formulation of the problem as a zero-sum game between a maximizing player whose mixed strategy set is the base of the polymatroid and a minimizing player whose mixed strategy set is a simplex. We show that this game and three variations of it unify several problems in search, sequential testing and queuing. We give a new, short derivation of optimal strategies for both players and an expression for the value of the game. Furthermore, we give a characterization of the set of optimal strategies for the minimizing player and we consider special cases for which optimal strategies can be found particularly easily.

Benchmark Density Functional Theory Approach for the Calculation of Bond Dissociation Energies of the M-O2 Bond: A Key Step in Water Splitting Reactions.

A very fascinating aspect in quantum chemical research is to determine the accurate and cost-effective methods for the calculation of electronic and structural properties through a benchmark study. The current study focuses on the performance evaluation of density functional theory methods for the accurate measurement of bond dissociation energies (BDEs) of chemically important M–O2 bonds in water splitting reactions. The BDE measurement has got noteworthy attention due to its importance in all areas of chemistry. For BDE measurements of M–O2 bonds in five metal complexes with oxygen molecules, 14 density functionals (DFs) are chosen from seven classes of DFs with two series of mixed basis sets. A combination of pseudopotential and Pople basis sets [LANL2DZ & 6-31G(d) and SDD & 6-31+G(d)] are used as a series of mixed basis sets. The B3LYP-GD3BJ functional with LANL2DZ & 6-31G(d) gives outstanding results due to low deviations, error, and the best Pearson’s correlation (R) between the experimental and theoretical data. Our study suggested an efficient, low-cost, precise, and accurate B3LYP-GD3BJ/LANL2DZ & 6-31G(d) level of theory for BDE of the M–O2 bond, which may be useful for chemists working in the field of energy generation and utilization.

Systematic review and meta-analysis to examine intrapartum interventions, and maternal and neonatal outcomes following immersion in water during labour and waterbirth

ObjectivesWater immersion during labour using a birth pool to achieve relaxation and pain relief during the first and possibly part of the second stage of labour is an increasingly popular...

Friction Characteristics of Open Graded Asphalt Friction Courses with BOF and EAF Steel Slag Aggregates

Friction properties of open graded asphalt friction course (OGAFC) mixtures play an essential role in ensuring traffic safety, especially under wet weather conditions. This study evaluated the friction characteristics of basic oxygen furnace (BOF) and electric-arc furnace (EAF) steel slag aggregate incorporated OGAFC mixes. Nine sets of OGAFC mixes were fabricated using five percentage replacements (0%, 25%, 50%, 75%, and 100%) of the coarse natural aggregate fraction by BOF and EAF steel slags. The effect of modified binder type (polymer and crumb-rubber modified) on the frictional characteristics of OGAFC mixes was also examined. The principal friction test devices used were the British pendulum tester and dynamic friction tester. Multiple friction performance aspects were studied: (1) effect of surface condition (dry, wet, and ponding) on the measured friction coefficient; (2) separate evaluation of adhesion and hysteresis friction components; (3) variation of friction coefficient with varying slip speeds, and (4) friction performance later in the OGAFC service life using artificially polished aggregates, and comparison of the performance with unpolished aggregates. Results revealed that the use of steel slags in OGAFC mixes considerably enhanced the frictional characteristics and that the skid resistance of OGAFC-BOF mixes was better than that of OGAFC-EAF mixes. Frictional resistance of the mixes was found to increase with an increase in steel slag content. OGAFC mixes comprising polished steel slag aggregates also showed promising results with the increment in steel slag content. The findings also indicated that OGAFC-CRMB mixes perform better than OGAFC-PMB mixes.

Density functional calculations of atomic structure, charging effect, and static dielectric constant of two-dimensional systems based on B-splines

We have implemented a total-energy minimization scheme to allow for relaxation of atomic positions in density functional calculations for two-dimensional (2D) materials using a mixed basis set. The basis functions consist of products of 2D plane waves in the plane of the material and localized B-splines along the perpendicular direction. By using the mixed basis approach (MBA), we have studied the atomic relaxation and charge polarization of 2D systems under an applied electric field. In contrast to the conventional super-cell approach (SCA) which adopts repeated slabs sandwiched between vacuum regions, MBA makes no requirement of compensating background charge for treating electrically charged 2D systems due to carrier injection. With MBA we can avoid using a periodic sawtooth potential for systems under the applied field as commonly adopted in SCA. Furthermore, we introduced a simple method to determine the out-of-plane dielectric constants of 2D materials without the ambiguity of defining their effective thickness. This is achieved by calculating the linear response in charge polarization to the applied field. Selected 2D systems, including graphene and transition-metal dichalcogenides are tested. Our MBA results are consistent with previous SCA calculations when both approaches are equally applicable. However, for charged systems with high carrier density, we find significant deviation from SCA results obtained by imposing artificial charge neutrality condition.

Impact of Using A Mixed Data Collection Modality on Statistical Inferences in Decentralized Clinical Trials.

BackgroundDecentralized clinical trials offer the promise of reduced patient burden, faster and more diverse recruitment, and have received regulatory support during the COVID-19 pandemic. However, lack of data accuracy or data validation poses a challenge for fully decentralized trials. A mixed data collection modality where onsite measurements are collected at key time points and decentralized measurements are taken at intermediate time points is attractive operationally. To date, the impact of decentralized measurements (which could presumably be less accurate) taken at intermediate time points on statistical inference on the primary or other key time points has not been evaluated.MethodsIn this article we evaluate the estimation and statistical inference for three scenarios: (1) all onsite measurements, (2) a mixture of onsite and decentralized measurements, and (3) all decentralized measurements, in the setting of a chronic weight management trial. We consider scenarios where decentralized measurements have additional within- and between-subject variabilities and/or bias.ResultsIn the mixed modality setting, simulation studies showed that the estimation and inference for the key time points with onsite measurements have good properties and are not impacted by the additional variability and bias from intermediate decentralized measurements. However, estimates for intermediate decentralized time points for the mixed modality and estimates for the all decentralized modality measurements have increased variability and bias.ConclusionMixed modality trials can help achieve the benefits of decentralized clinical trials by reducing the number of onsite visits with little impact on statistical inferences for various estimands, compared to traditional (all onsite) clinical trials.Supplementary InformationThe online version contains supplementary material available at 10.1007/s43441-022-00416-x.

Object Pose Detection to Enable 3D Interaction from 2D Equirectangular Images in Mixed Reality Educational Settings

In this paper, we address the challenge of estimating the 6DoF pose of objects in 2D equirectangular images. This solution allows the transition to the objects’ 3D model from their current pose. In particular, it finds application in the educational use of 360° videos, where it enhances the learning experience of students by making it more engaging and immersive due to the possible interaction with 3D virtual models. We developed a general approach usable for any object and shape. The only requirement is to have an accurate CAD model, even without textures of the item, whose pose must be estimated. The developed pipeline has two main steps: vehicle segmentation from the image background and estimation of the vehicle pose. To accomplish the first task, we used deep learning methods, while for the second, we developed a 360° camera simulator in Unity to generate synthetic equirectangular images used for comparison. We conducted our tests using a miniature truck model whose CAD was at our disposal. The developed algorithm was tested using a metrological analysis applied to real data. The results showed a mean difference of 1.5° with a standard deviation of 1° from the ground truth data for rotations, and 1.4 cm with a standard deviation of 1.5 cm for translations over a research range of ±20° and ±20 cm, respectively.

Ambiguous Positionings: The Politics and Experiences of Moral Learning at Gülen Movement Schools in Urban Tanzania

Abstract This article examines the ambiguous positionings of the Gülen Movement (gm) in the religiously mixed setting of urban Tanzania, particularly in education. It argues that the gm has capitalised on its identity as a not-explicitly-Muslim minority group within the privatised educational market in Tanzania, making its schools an option for Muslim and Christian families alike. Against the backdrop of Tanzania’s larger histories of religious inequalities and sentiments of injustice among the Muslim population, gm schools fill a significant gap through their elite orientation and inclination towards Islam. The article further argues that the moral education offered by gm schools binds them to the broader ideological mission of the movement. Foregrounding the experiences of female students, it shows that moral education at gm schools is a highly gendered and open-ended process that entails the embodiment of different and at times contradictory understandings of femininity, modesty, and shame.

Multidimensional Analysis and Evaluation of College English Teaching Quality Based on an Artificial Intelligence Model

In view of the lack of teaching resources and the impossibility of real-time sharing and application of teaching resources in English teaching, this paper proposes a multidimensional analysis and application of English teaching quality based on an artificial intelligence model. This paper analyzes the basic framework and application of the Internet of Things technology and puts forward the corresponding hierarchical classification and teaching quality monitoring mode. Secondly, the monitoring framework of the Internet of Things to achieve the quality of English teaching and then the basic theory of the Internet of Things is analyzed. Finally, the experiment shows that the average score of English has been greatly improved by comparing the traditional teaching mode and the new classroom quality monitoring mode under the Internet of Things technology. The main dimensions of teaching quality, such as teachers’ quality, teaching attitude, teaching content, and teaching methods, are analyzed in depth, and the coefficient of most sample data is more than 0.7, which has a good application effect. Whether running on the test set or the mixed test set, the accuracy of the new classroom quality monitoring model proposed in this paper is the highest among the three models. The correct rate on the test set can reach 99.71%, the correct rate on the mixed test set can reach 98.01%, and the correct rate can reach 98.67%, which shows the superiority of the performance of the new classroom quality monitoring model.

Single crystal, a lead-free hybrid organic-inorganic perovskite material: {[(C6H5)NH3]+}4.I.[BiI6]3-.H2O with optical and third-order nonlinear properties

A lead-free organic–inorganic halide perovskite (LFHP) single crystal, tetrakis(phenylammonium) iodide hexaiodidebismuthate monohydrate (TIHM): {[(C6H5)NH3]+}4.I.[BiI6]3-.H2O, was successfully synthesized by a simple condensation reaction method in ambient environment. The bismuth iodide-based crystal compound was grown by using methanol solvent. The crystal lattice comprised of a discrete (BiI6)3− anion surrounded by tetrakis(phenylammonium) cations, iodide anion, and a water molecule. The structure related to monoclinic crystal system with P21/c space group: a ​= ​21.921 (4) Å, b ​= ​8.5521 (15) Å, c ​= ​21.105 (4) Å, β ​= ​102.398 (3) °, and Z ​= ​4. The full geometry optimization was performed by density functional theory (DFT) calculation at B3LYP functional with 6–311++G(d,p) and LanL2DZ mixed basis sets by using GAUSSIAN software. The gaussian predicted peak emission at 479 ​nm with bandgap of 2.97 ​eV. The HRTEM analysis reveals that the titled LFHP nanocrystal has a size below 5 ​nm. The centrosymmetric crystal exhibit third-order nonlinear optical susceptibility of 1.0228 ​× ​10-5 ​esu with Im χ3 response higher than Reχ3, and, hence, it can be concluded that the hybrid perovskite has promising optical limiting properties.

Mental Health and Positive Development Prevention Interventions: Overview of Systematic Reviews.

Previous reviews of mental health interventions have focused on adolescents (10-19 years), with a paucity of comprehensive evidence syntheses on preventive interventions for school-aged children (5-10 years). To summarize and synthesize the available evidence from systematic reviews of mental health and positive development interventions for children aged 5-14.9 years in both high-income (HIC) and low- and middle-income countries (LMIC), with a focus on preventive and promotive strategies. This overview includes all relevant reviews from OVID Medline, The Cochrane Library, and Campbell Systematic Reviews through December 2020. We included systematic reviews that synthesized empirical studies using experimental or quasi-experimental designs to evaluate the effectiveness of interventions in children aged 5-14.9 years. Data extraction and quality assessment were completed independently and in duplicate by two review authors. The AMSTAR2 tool was used to assess methodological quality. We included 162 reviews. The greatest evidence was found in support of school-based universal and anti-bullying interventions in predominantly HIC. Moderate evidence was found for the use of substance abuse prevention, and early learning and positive development interventions in mixed settings. In LMIC-only contexts, the most promising evidence was found for positive youth development programs. The review was primarily limited by paucity of high-quality research due to methodological issues and high heterogeneity. This overview of reviews highlights the need for further research to consolidate findings and understand the specific criteria involved in creating positive mental health and development outcomes from the various interventions considered.

A novel bearing fault diagnosis method with feature selection and manifold embedded domain adaptation

Traditional fault diagnosis models assume that the training and test data sets have the same feature distribution, but in practice the distribution between the training and test sets varies considerably, making it difficult to achieve the desired fault diagnosis performance. Thus, a diagnosis method based on feature selection and manifold embedding domain adaptation is proposed in this paper. First, the signal is decomposed by variational modal decomposition to obtain multiple modal components, and the entropy, time domain and frequency domain features of each modal component are extracted to form a mixed feature set. Second, it proposes a feature evaluation index based on Fisher scores and feature domain differences to select features that are conducive to cross-domain fault diagnosis and transfer learning. Then, the geodesic flow core is constructed to learn the transformation feature representation in the Grassmann manifold space to avoid features are distorted. Finally, the domain adaptation is performed by minimizing the discrepancy in the joint probability distribution between the same category and maximizing the discrepancy between the different categories. Based on the results of multi-index experiments, the method in this paper is superior to other existing methods.

Measuring the diffusion of conspiracy theories in digital information ecologies

Digital platforms and media are fertile breeding grounds for disinformation and conspirational views. They provide a variety of communication venues for a mixed set of actors and foster the diffusion of content between actor groups, across platforms and media, and across languages and geographical spaces. Understanding those diffusion processes requires approaches to measure the prevalence and spread of communicative acts within and across digital platforms. Given the increasing access to digital data, computational methods provide new possibilities to capture this spread and do justice to the interrelated nature and hybridity of online communication. Against this background, the paper focuses on the spread of conspiracy theories in digital information ecologies. It provides a review of recent methodological approaches to measuring conspiracy-related content online regarding the (a) prevalence and (b) diffusion of conspiracy theories. To that end, the paper differentiates between social network analysis approaches and computational techniques of automated text classification. It further discusses how far these and related computational approaches could facilitate studying the diffusion of conspiracy theories across different actor types, languages, topics and platforms. In doing so, it takes the specific nature of online communication and challenges in the field of conspiracy-related content into account.