Unknown Degree Research Articles

Bolt looseness localization with connection-stiffness-varying flange

Electromechanical impedance analysis is a traditional method to identify the occurrence of bolt looseness, but accurate localization of blot looseness is hard to realize on the flange. In this study, a flange model with bolt connection stiffness varying with position is proposed. The location of bolt looseness can be then determined from the impedance spectrum of the model since the uniformity and symmetry of the flange are broken. The analytic model is established to reveal the distinguishability of the eigenfrequency shifting characteristics when the connection stiffness at different positions changes. The frequency shifting sequence is extracted from the coupling impedance spectrum as a feature, and the correlation between the sequences corresponding to bolt looseness at different positions is low. The relationship between the sequence and the degree of looseness is highly related so that the unknown degree of looseness can be matched with the calibrated sequence to realize the localization of the looseness. Based on the distinguishability of the frequency shifting sequence, the connection-stiffness-varying model shows great potential in the field of flanges or other connecting structures for structural health monitoring and damage localization.

Bone and Soft Tissue Sarcoma Epidemiology in Iranian Elderly Population; an Analysis of the Iranian National Registry for Cancer (2009-2014 Years).

We aimed to investigate the patterns of incidence and prevalence of bone sarcoma (BS) and soft tissue sarcoma (STS), morphology as well as geographical distribution in the elderly in Iran. By the primary site of the tumor and the morphological types, whole cases of cancer were classified. Then, the WHO classification (2018) and the third revision of the standard International Classification of Diseases for Oncology (ICD-O-3) were used to assign a code to them. The estimated incidence rates were obtained as the frequency of the newly-diagnosed cases within one year divided by the calculated population of the mid-year Iranian residents as estimated by the Iranian Bureau of Statistics. The age-standardized incidence rates were also estimated for both bone and soft tissue sarcoma. The annual crude incidence rates of sarcomas in males (0.80 per 100,000) were more than in females (0.55 per 100,000) in all years. The total combined crude incidence in 2014 years was obtained at 0.67 per 100,000 people. In terms of disease grade majority of the patients were of grade 3 (11.5 %). In terms of tumor location, the Lower extremity was 16.8%, the Visceral (including gastrointestinal & uterus) 15.8%, the Thoracic 12.8%, and the Pelvic & abdominal wall 9.7%. Even though such sarcoma is more prevalent in elderly men, its incidence was also observed in lower-aged female groups. In addition, the incidence rate of BS was lower in comparison with that of STS, and the patients often exhibited an unknown degree of sarcoma.

Effects of Exercise on Frailty in Older People Based on ACSM Recommendations: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Objectives: The objective of the study was to carry out an analysis of the methodological quality of clinical trials (effects of exercise on frailty in older people) based on ACSM recommendations. Methods: The search scope included PubMed, Embase, Web of Science, Cochrane, and literature that cannot be retrieved from the database. The topic was the impact of exercise on frailty in elderly people. Changes in five outcome measures (FP, BI, SPPB, GS, and BMI) were assessed using mean differences (MD) and 95% confidence intervals (95% CI). A random effects model (RE) was used to conduct a meta-analysis and compare the results between subgroups. Results: The intervention effects of exercise on the five outcome indicators of frailty in elderly people were all significant (p < 0.05). The effect of a high-consistency subgroup on outcome indicators FP and GS was more significant than that of the low- or uncertain-consistency subgroup (MD: -1.09 < -0.11, MD: 2.39 >1.1). There was no significant difference in the intervention effect as reflected in the outcome measures SPPB and BMI in the high-consistency subgroup (p = 0.07, p = 0.34). There was no significant difference in the impact of the intervention on the outcome measure BI between the two subgroups (p = 0.06, p = 0.14). Conclusions: Exercise prescriptions with high consistency with ACSM recommendations may be more effective in both FP and GS interventions than those with uncertain or low consistency. However, it is essential to note that the data derived from the meta-analysis is still subject to the small number of studies, the unknown degree of consistency of participants in individual studies, and the different mix of cases in the studies.

Decision algorithm for picture fuzzy sets and Aczel Alsina aggregation operators based on unknown degree of wights

Aggregation operators (AOs) are well-known and efficient mathematical tools that are utilized to overcome the impact of imprecise and vague information during the aggregation process. The theoretical concepts of Aczel Alsina aggregation expressions are an extension of triangular norms and become a hot research topic in the environment of the fuzzy framework. The power operators provide a smooth approximation and are used to mitigate the influence of redundant or insufficient information on the attributes or criteria. Some robust aggregation approaches are developed by combining two different theories, like power operators and Aczel Alsina aggregation tools. This article aims to explore the theory of picture fuzzy sets (PFSs), an extended version of fuzzy sets, and intuitionistic fuzzy sets. Some robust operations of Aczel Alsina aggregation tools are also present in light of the picture fuzzy environment. We established a class of new methodologies in the light of picture fuzzy information, including picture fuzzy Aczel Alsina power weighted average (PFAAPWA) and picture fuzzy Aczel Alsina power ordered weighted average (PFAAPOWA) operators. We also developed an appropriate approach like picture fuzzy Aczel Alsina power weighted geometric (PFAAPWG) and picture fuzzy Aczel Alsina power ordered weighted geometric (PFAAPOWG) operators. Notable properties and characteristics of proposed methodologies are also demonstrated. Our invented approaches not only aggregate complicated information but can clearly define interrelationships among several arguments. Moreover, we establish an algorithm for the multi-attribute group decision-making (MAGDM) problem to handle the impact of redundant and vague information on human opinions. Finally, we study an experimental case study to evaluate an appropriate optimal option from available options. To reveal consistency and effectiveness of developed approaches, influence study by changing various parametric values and comparative study by comparing results of existing approaches.

IMPLICATIONS OF TREATING PARASITIC INFECTION IN NORTHERN BOBWHITE (COLINUS VIRGINIANUS) ON OVERALL HELMINTH LIFE CYCLE.

This study was conducted to determine how reducing the parasite burden in a definitive host may affect the prevalence in intermediate hosts. Here we used the eyeworm Oxyspirura petrowi and cecal worm Aulonocephalus pennula as model species. Northern bobwhite quail (Colinus virginianus) were provided an anthelmintic medicated feed in wild systems because of convincing evidence that these parasites were suppressing their populations. Eyeworm and cecal worm prevalence were measured in Orthopterans, which act as intermediate hosts, using polymerase chain reaction. Individuals were collected from a control site, a site treated for 2 yr, and a site treated for 5 yr. Orthopteran community composition was significantly different among the sites; however, an interaction between subfamily and site was not significant for the eyeworm. There was a significant reduction in eyeworm-infected Orthopterans on the 5-yr site compared with the other 2, suggesting that treatment of a definitive host may indeed affect the prevalence of eyeworms during other life-cycle stages. There was an interaction between the Orthopteran subfamily and the site for the cecal worm, so results were analyzed within each subfamily. A significant reduction in the prevalence of cecal worms was only found in the Cyrtacanthacridinae subfamily on the 5-yr site when compared with the other sites. However, the greatest prevalence in the Gomphocerinae and Oedipodinae subfamilies across all 3 sites was 4.1%. This indicates an unknown degree of cecal worm host specificity. Therefore, conclusions could not be made through the simple assessment of prevalence.

Joint regression analysis of multiple traits based on genetic relationships.

Polygenic scores (PGSs) are widely available and employed in genomic data analyses for predicting and understanding genetic architectures. Existing approaches either require information on SNP level, do not infer clusters of traits sharing genetic characteristic, or do not have any immediate predictive properties. Here, we present geneJAM, which is a novel clustering and estimation method using PGSs for inferring a genetic relationship among multiple, simultaneously measured and potentially correlated traits in a multivariate GWAS.Using graphical lasso, we estimate a sparse covariance matrix of the PGSs and obtain clusters of traits sharing genetic characteristics. We use the clusters to specify the structure of the error covariance matrix of a generalized least squares (GLS) model and use the feasible GLS estimator for estimating a linear regression model with a certain unknown degree of correlation between the residuals.The method suits many biology studies well with traits embedded in some genetic functioning groups and facilitates development of the PGS research. We compare the method with fully parametric techniques on simulated data and illustrate the utility of the methods by examining a heterogeneous stock mouse data set from the Wellcome Trust Centre for Human Genetics. We demonstrate that the method successfully identifies clusters of traits and increases precision, power, and computational efficiency. GeneJAM is implemented in R and available at: https://github.com/abuchardt/geneJAM.

FACTORIZATION OF DEGREE k-ALMOST SIMPLE POLYNOMIALS

In this work, we introduce the notion of k-almost prime polynomials formed by the product over a Galois field of an arbitrary characteristic p of exactly k irreducible polynomials. The study aims to develop an effective algorithm for factorizing the degree of such composite polynomials providing a minimum of computational complexity. The proposed algorithm is based on the solution of a system of two equations functionally related to the a priori unknown degree of the components of the compound polynomial. One of these equations reflects that the degree of the composite polynomial equals the sum of degrees of elements of this polynomial. The second equation is based on the so-called cycle period of the compound polynomial, which coincides with the least common multiple of the unknown degrees of the components of the compound polynomial. It is found that the expansion of the cycle period contains all the degrees of the factorizable compound polynomial. The computational volume reduction is achieved by switching from the linear scale of the multiplicative group of subtractions generated by the cycle period of the compound polynomial to the logarithmic scale.

Elucidating polymorphs of crystal structures by intensity-based hierarchical clustering analysis of multiple diffraction data sets.

In macromolecular structure determination using X-ray diffraction from multiple crystals, the presence of different structures (structural polymorphs) necessitates the classification of the diffraction data for appropriate structural analysis. Hierarchical clustering analysis (HCA) is a promising technique that has so far been used to extract isomorphous data, mainly for single-structure determination. Although in principle the use of HCA can be extended to detect polymorphs, the absence of a reference to define the threshold used to group the isomorphous data sets (the `isomorphic threshold') poses a challenge. Here, unit-cell-based and intensity-based HCAs have been applied to data sets for apo trypsin and inhibitor-bound trypsin that were mixed post data acquisition to investigate the efficacy of HCA in classifying polymorphous data sets. Single-step intensity-based HCA successfully classified polymorphs with a certain `isomorphic threshold'. In data sets for several samples containing an unknown degree of structural heterogeneity, polymorphs could be identified by intensity-based HCA using the suggested `isomorphic threshold'. Polymorphs were also detected in single crystals using data collected using the continuous helical scheme. These findings are expected to facilitate the determination of multiple structural snapshots by exploiting automated data collection and analysis.

Multiway Spherical Clustering Via Degree-Corrected Tensor Block Models

We consider the problem of multiway clustering in the presence of unknown degree heterogeneity. Such data problems arise commonly in applications such as recommendation system, neuroimaging, community detection, and hypergraph partitions in social networks. The allowance of degree heterogeneity provides great flexibility in clustering models, but the extra complexity poses significant challenges in both statistics and computation. Here, we develop a degree-corrected tensor block model with estimation accuracy guarantees. We present the phase transition of clustering performance based on the notion of angle separability, and we characterize three signal-to-noise regimes corresponding to different statistical-computational behaviors. In particular, we demonstrate that an intrinsic statistical-to-computational gap emerges only for tensors of order three or greater. Further, we develop an efficient polynomial-time algorithm that provably achieves exact clustering under mild signal conditions. The efficacy of our procedure is demonstrated through two data applications, one on human brain connectome project, and another on Peru Legislation network dataset.

Chitin oligomers promote lymphoid innate and adaptive immune cell activation.

Chitin is a highly abundant N-acetylglucosamine polysaccharide that has been linked to immune responses in the context of fungal infections and allergic asthma, especially to T helper 2 immune responses. Unfortunately, due to the frequent use of crude chitin preparations of unknown purity and degree of polymerization, there is still great uncertainty about how chitin activates different parts of the human immune system. We recently identified chitin oligomers of 6 N-acetylglucosamine units as the smallest immunologically active chitin motif and the innate immune receptor TLR2 as a primary chitin sensor on human and murine myeloid cells, but the response of further immune cells (e.g. lymphoid cells) to oligomeric chitin has not been investigated. Our analysis of primary human immune cells now shows that chitin oligomers activate immune responses of both innate and adaptive lymphocytes: notably, chitin oligomers activated natural killer cells but not B lymphocytes. Moreover, chitin oligomers induced maturation of dendritic cells and enabled potent CD8+ T-cell recall responses. Our results suggest that chitin oligomers not only trigger immediate innate responses in a limited range of myeloid cells but also exert critical activities across the entire human immune system. This highlights chitin oligomer immune activation as an interesting and broadly applicable potential target for both adjuvant development and therapeutic interference in chitin-mediated pathologies.

Simultaneous quantum estimation of phase and indistinguishability in a two-photon interferometer

With the rapid development of quantum technologies in recent years, the need for high-sensitivity measuring techniques has become a key issue. In particular, optical sensors based on quantum states of light have proven to be optimal resources for high-precision interferometry. Nevertheless, their performance may be severely affected by the presence of noise or imperfections. In this work, we derive the quantum Fisher information matrix associated with the simultaneous estimation of an interferometric phase and the indistinguishability characterizing the probe state consisting of an even number of photons. We find the optimal measurement attaining the ultimate precision for both parameters in a single setup and perform an experiment based on a pair of photons with an unknown degree of indistinguishability entering a two-port interferometer.

The availability of gonadotropin therapy from FDA-approved pharmacies for men with hypogonadism and infertility.

Recent changes to the Biologics Price Competition and Innovation Act of 2009 have created barriers to accessing therapy for men utilizing gonadotropins for hypogonadism and infertility. In this study we sought to investigate ways to decrease disparities in the treatment of male hypogonadism by increasing access to gonadotropin therapy by identifying 503b outsourcing pharmacies which currently provide gonadotropin therapy. A review of 503b compounding pharmacies was performed using the online published registry available from the US Food and Drug Administration (FDA). Each pharmacy was contacted regarding their ability to provide gonadotropin therapy. Pharmacies were also queried regarding the impact of FDA-related legal changes and cost considerations. The study outcomes were the number and location of FDA-approved 503b compounding pharmacies supplying human chorionic gonadotrophin (hCG) and/or follicle-stimulating hormone (FSH) for the treatment of male hypogonadism and infertility. The 81 503b-compounding pharmacies approved by the FDA to produce hCG and FSH therapy were identified using the FDA registry. Seventy-five of the 81 pharmacies responded to the survey (response rate92.6%). Of the contacted pharmacies, 5 provided hCG (6.67%). Of the pharmacies offering compounded hCG, 4 offered FSH. No additional pharmacies offered compounded FSH. Eight pharmacies had previously provided hCG and FSH. Six of the 8 pharmacies that stopped making hCG and FSH cited the 2020 FDA mandate as the reason for halting compounding services. Of the 75 pharmacies that responded, only 1 pharmacy provided the cost for FSH ($287 per 100-IU vial), and 3 pharmacies provided the cost for hCG ($50-$83 per 10 000-IU vial). There are few FDA-approved outsourcing pharmacies currently providing male gonadotropin therapy, and increasing awareness of these pharmacies may decrease barriers to care for patients with male hypogonadism and infertility. The strengths of this article are the clinical utility of the data presented, as this article may serve as a tool for clinicians to increase patient access to therapy. All FDA-approved 503b outsourcing pharmacies were contacted, and 92.6% participated in this project. Limitations of this article were the following: no non-FDA-approved compounding pharmacies such as 503a pharmacies were contacted, participant-reported outcomes were utilized, and only 3 contacted outsourcing pharmacies provided a cost for FSH or hCG, allowing for an unknown degree of cost variability between outsourcing pharmacies. There currently exists limited access to FDA-approved compounded gonadotropin therapies for hypogonadism and male infertility, and these results demonstrate the barriers to hCG and FSH access and the need for additional treatment options for this vulnerable patient population.

Spatial inequality of shopping opportunities under the boom of express deliveries in China

The orderly spatial structure of cities promotes city vitality and human well-being. The spatial mismatch between traditional shops and population causes spatial inequality in shopping opportunities along urban‒rural gradients. This spatial inequality has been deconstructed. The rapid expansion of express delivery outlets linked to online shopping reduces the spatial inequality of shopping opportunities to an unknown degree. This study focused on the spatial patterns of shops and express delivery outlets in cities. The Gini coefficient was used to quantify the spatial inequality of shopping opportunities in 18 Chinese cities. This study further compared the ecosystem services of the two types of shopping facilities. The results show that (1) the net ecosystem services provided by express delivery outlets are 3-fold those of shops; (2) the environmental impact of online shopping are lower than those of traditional shopping; (3) express delivery outlets show more spatial dispersion than shops; (4) the spatial inequality of shops is higher than that of express delivery outlets; and (5) the supplement of express delivery outlets to shops reduces spatial inequality by 35%. These findings show that online shopping promotes ecosystem services, reduces the spatial inequality of city structure and improves human well-being and the sustainability of cities.

Graph Theory Measures and Their Application to Neurosurgical Eloquence.

Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.

Compressive Detection of Stochastic Sparse Signals With Unknown Sparsity Degree

Compressive Detection of Stochastic Sparse Signals With Unknown Sparsity Degree

General model-free weighted envelope estimation

Envelope methodology is succinctly pitched as a class of procedures for increasing efficiency in multivariate analyses without altering traditional objectives [5, first sentence of page 1]. This description comes with the additional caveat that efficiency gains obtained by envelope methodology are mitigated by model selection volatility to an unknown degree. Recent strides to account for model selection volatility have been made on two fronts: 1) development of a weighted envelope estimator to account for this variability directly in the context of the multivariate linear regression model; 2) development of model selection criteria that facilitate consistent dimension selection for more general settings. We unify these two directions and provide weighted envelope estimators that directly account for the variability associated with model selection and are appropriate for general multivariate estimation settings. Our weighted estimation technique provides practitioners with robust and useful variance reduction in finite samples. Theoretical and empirical justification is given for our estimators and validity of a nonparametric bootstrap procedure for estimating their asymptotic variance are established. Simulation studies and a real data analysis support our claims and demonstrate the advantage of our weighted envelope estimator when model selection variability is present.

Unknown College Retention and Degree Completion: Spring Starters at Four-Year Institutions

Unknown College Retention and Degree Completion: Spring Starters at Four-Year Institutions

Adaptive regulation for minimum phase systems with unknown relative degree and uncertain exosystems

This paper investigates the adaptive error feedback regulation problem for unknown minimum phase, single-input, single-output linear systems with uncertain exosystems. The design problem of a feedback control which is capable of driving the output tracking error exponentially to zero, on the basis of the output tracking error only, is locally solved by an adaptive controller which continuously updates the frequency estimates and requires only two informations on the uncertain linear system: (i) an upper bound for the relative degree; (ii) the sign of the high-frequency gain. The proposed adaptive controller contains two gains to be tuned: an adaptation gain which should be chosen sufficiently small and a control gain which should be chosen sufficiently large. Extensions to single-input single-output nonlinear systems affected by uncertain biased multisinusoidal disturbances are outlined.

Low functional vulnerability of fish assemblages to coral loss in Southwestern Atlantic marginal reefs

Marginal reefs sustain coral assemblages under conditions considered suboptimal for most corals, resulting in low coral abundance. These reefs are inhabited by numerous fishes with a generally unknown degree of association with corals that might lead to the assumption that corals play minor roles in determining fish occurrence, when corals could be actually sustaining diverse and resilient assemblages. Using site-occupancy models fitted to data of 113 reef fish species of different life stages (adults and juveniles) from 36 reefs distributed across the Southwestern Atlantic (0.87–27.6°S) we first assessed fish assemblage’s response to coral and turf algal cover, and identified coral-associated fish. Then, we simulated the loss of coral-associated fishes and contrasted it with random losses, providing inferences on the resilience of fish assemblage’s functional trait space to species loss. The entire fish assemblage responded more positively to coral than to turf algae, with 42 (37%) species being identified as coral-associated fish. The simulated loss of coral-associated fish reduced up to 5% the functional trait space and was not different from the random loss. These results reveal that marginal reefs of Southwestern Atlantic reefs host resilient fish assemblages that might preserve fundamental ecological functions and ecosystem services even with coral declines.

Uniform inference in linear panel data models with two-dimensional heterogeneity

This paper studies uniform inference in a linear panel data model when the slope coefficients may exhibit heterogeneity over both the individual and time dimensions and they can be correlated with the regressors. We propose a generalized two-way fixed effects (GTWFE) estimation procedure to estimate the model. To establish the asymptotic properties of the GTWFE estimators, we invert a number of large dimensional square matrices by approximating them with quasi-Kronecker structured matrices. We establish the asymptotic normality of our GTWFE estimators and show that their convergence rates depend on the unknown degree of parameter heterogeneity. To make a uniform inference on the common slope component, we propose a novel triple-bootstrap procedure to estimate the asymptotic variance. Simulations show the superb performance of our estimators and inference procedure. We apply our method to study the relationship between savings and investments, and find significant parameter heterogeneity along both the individual and time dimensions.