Truncation Level Research Articles

Минеральные ассоциации золоторудных проявлений Берентальского рудного поля (Северо-Восток России)

Berental prospective ore cluster (Magadan region) hosts a many ore occurrences, which differ in mineral composition, ore productivity, features of secondary and primary dispersion halos. As a result of the study of ores, mineral associations have been characterized, the stages of formation of ore occurrences and the alteration of the ore cluster have been established. The interrelation of five genetic types of native gold with mineral associations is revealed. Key ore occurrences have formed during several stages of ore formation associated with the evolution of a common hydro-thermal system. The earliest mineral association (arsenopyrite-lellingite), which contains the first generation of gold, was formed in the quartz-sericite facies in marginal parts of Berental stock and refers to the lower level of erosion truncation. After that, arsenopyrite-telluride association was formed in the marginal granites and arsenopyrite-galenobismutite association was formed in the exomorfic zone, they contain gold of the second - fourth generations with signs of recrystallization and diffusion transformations. Arsenopyrite-silver and pyrite-silver ore associations are localized at the upper level of the erosion trancation in calcium-containing birch with quartz veins, these associations contain low-fineness gold of the fourth and fifth generations. Pay gold mineralization of the Berental ore field is associated with arsenopyrite-telluride and arsenopyrite-galenobismutite associations, contains gold with a fineness of 750-945 %. The spatial placement of mineral associations is consistent with the placement of secondary and prima-ry scattering halos: complex Au-Bi-As halos accompany arsenopyrite-lellingite, arsenopyrite-telluride and arsenopy-rite-galenobismutite associations; for Au-As-Ag and Au-Ag-Pb-Zn association there is a spatial conjugation with ar-senopyrite-silver and pyrite-silver associations, respectively.

The Eshelby problem of the confocal N-layer spheroid with imperfect interfaces and the notion of equivalent particle in thermal conduction

The solution to the generalized conduction Eshelby problem of a confocal N-layer spheroid with low or highly conducting interfaces between isotropic layers is provided thanks to a decomposition in series of harmonics. A generic workflow is detailed for practical numerical implementation including a fine analysis to assess the influence of the level of truncation of the infinite series. The case of perfect interfaces presents a particular interest insofar as it is characterized by an equivalent conductivity tensor obtained from a recursive procedure. The notion of equivalent conductivity is then investigated and applied to a uniform spheroid surrounded by an imperfect interface. Some approximated models are developed, either based on a surface description of the interface or on a thin interphase, casting a new light on published models and proposing a unified framework for new ones. These approximated models are finally analyzed by comparison to the exact solution.

Introduction of Developing Fatigue Load Spectrum for Full-Scale Fatigue Test of Composite Aircraft

This is a study on the loading spectrum for full-scale fatigue testing of composite aircraft structures. Fatigue tests are performed to confirm the durability and damage tolerance of a composite aircraft structure. In particular, as composite materials have fatigue life variance larger than that of metallic materials, it takes a considerable amount of time to complete the aforementioned tests. Investigation of key factors such as spectrum truncation and load enhancement is required to create a load spectrum that can reasonably shorten the test time. In other words, criteria for removing the loads that have little effect on the fatigue life and applying factors for the severe load spectrum should be studied to produce the optimal load spectrum, which depends on the fatigue characteristics of the composite material. In this study, coupon tests and statistical analyses of carbon fiber/epoxy composites were performed to analyze the key elements and establish the criteria for the reliable truncation level and load factor for an optimal loading spectrum.

Topologic and Hemodynamic Characteristics of the Human Coronary Arterial Circulation.

BackgroundMany processes contributing to the functional and structural regulation of the coronary circulation have been identified. A proper understanding of the complex interplay of these processes requires a quantitative systems approach that includes the complexity of the coronary network. The purpose of this study was to provide a detailed quantification of the branching characteristics and local hemodynamics of the human coronary circulation.MethodsThe coronary arteries of a human heart were filled post-mortem with fluorescent replica material. The frozen heart was alternately cut and block-face imaged using a high-resolution imaging cryomicrotome. From the resulting 3D reconstruction of the left coronary circulation, topological (node and loop characteristics), topographic (diameters and length of segments), and geometric (position) properties were analyzed, along with predictions of local hemodynamics (pressure and flow).ResultsThe reconstructed left coronary tree consisted of 202,184 segments with diameters ranging from 30 μm to 4 mm. Most segments were between 100 μm and 1 mm long. The median segment length was similar for diameters ranging between 75 and 200 μm. 91% of the nodes were bifurcations. These bifurcations were more symmetric and less variable in smaller vessels. Most of the pressure drop occurred in vessels between 200 μm and 1 mm in diameter. Downstream conductance variability affected neither local pressure nor median local flow and added limited extra variation of local flow. The left coronary circulation perfused 358 cm3 of myocardium. Median perfused volume at a truncation level of 100 to 200 μm was 20 mm3 with a median perfusion of 5.6 ml/min/g and a high local heterogeneity.ConclusionThis study provides the branching characteristics and hemodynamic analysis of the left coronary arterial circulation of a human heart. The resulting model can be deployed for further hemodynamic studies at the whole organ and local level.

Clinical evaluation of thrombus molecular markers in patients with malignant tumor

Objective To explore the early diagnostic value of thrombus molecular markers in thrombosis ofpatients with malignant tumors and to evaluate their risk factors. Methods Diagnostic research.A total of 1366 patients (including lung cancer, breast cancer and colorectal cancer,) were randomly selected in the Red Flag Hospital of Mudanjiang Medical College and Mudanjiang Cancer Hospitalfrom September 2009 to February 1919. Among them, 562 were males and 804 were females with average age (59.45±15.10) years old. The control group consisted of 70healthy donors (35 males and 35 females, with an average age of (49.60±19.12) years old), including 69 cases of venous thrombosis (thrombotic group, 32 males and37 females, with an average age of (61.20±15.71) years old).Chemoluminescent enzyme immunoassay was used to detect thromboregulatory proteins(TM), thrombin-antithrombin complexes(TAT), tissue plasminogen activators/inhibitors -1 complexes(t-PAIC), plasminase-anti-fibrinolysis complexes(PIC) in venous plasma. According to the sensitivity and specificity of each marker, the receiver′s work characteristic curve was drawn to evaluate its diagnostic performance. Cox regression analysis was used for single-factor and multi-factor risk analysis. Results The incidence of venous thromboembolism(VTE) in patients with different types of malignant tumors was statistically significant, with lung cancer being the highest, followed by colorectal cancer and breast cancer(P<0.05). The levels of TM, TAT, t-PAIC and PIC were significantly higher in the lung, breast and colorectal thrombosis group than in the control group. The differences were statistically significant(all P<0.05). The optimal cut-off level for TM is 10.57 IU/ml(sensitivity 50.30%, specificity 75.50%, AUC=0.671), and the optimal cut-off level for TAT is 4.16 ng/ml(sensitivity is 80.30%, specificity is 62.80%, AUC=0.757).The optimal truncation level for t-PAIC is 11.44 ng/ml(sensitivity 52.50%, specificity 84.00%, AUC=0.682), and the optimal truncation level for PIC is 1.18μg/ml(sensitivity 67.20%, specificity is 79.50%, AUC=0.790). The combined detection of the four molecular markers has the best sensitivity and diagnostic performance(86.90%, AUC=0.807). Age, stage, metastasis, surgery, tumor diameter, and PIC levels are independent factors that affect the occurrence of VTE in malignant tumors (all P<0.05). Conclusions Different types of malignant tumors have different rates of thrombosis. The combined detection ofTM, TAT, t-PAIC and PIC have the best diagnostic performance, and can be used as a new early diagnosis method for VTE in malignant tumors. Age, stage, metastasis, surgery, and tumor diameter are risk factors for VTE in malignant tumors. PIC levels can be used as a reliable markerfor the risk of VTE in patients with malignant tumors within 6 months. Key words: Neoplasms; Venous thromboembolism; Biomarkers

Multireference Stochastic Coupled Cluster.

We describe a modification of the stochastic coupled cluster algorithm that allows the use of multiple reference determinants. By considering the secondary references as excitations of the primary reference and using them to change the acceptance criteria for selection and spawning, we obtain a simple form of stochastic multireference coupled cluster which preserves the appealing aspects of the single-reference approach. The method is able to successfully describe strongly correlated molecular systems using few references and low cluster truncation levels, showing promise as a tool to tackle strong correlation in more general systems. Moreover, it allows simple and comprehensive control of the included references and excitors thereof, and this flexibility can be taken advantage of to gain insight into some of the inner workings of established electronic structure methods.

Complex Neutrosophic Hypergraphs: New Social Network Models

A complex neutrosophic set is a useful model to handle indeterminate situations with a periodic nature. This is characterized by truth, indeterminacy, and falsity degrees which are the combination of real-valued amplitude terms and complex-valued phase terms. Hypergraphs are objects that enable us to dig out invisible connections between the underlying structures of complex systems such as those leading to sustainable development. In this paper, we apply the most fruitful concept of complex neutrosophic sets to theory of hypergraphs. We define complex neutrosophic hypergraphs and discuss their certain properties including lower truncation, upper truncation, and transition levels. Furthermore, we define T-related complex neutrosophic hypergraphs and properties of minimal transversals of complex neutrosophic hypergraphs. Finally, we represent the modeling of certain social networks with intersecting communities through the score functions and choice values of complex neutrosophic hypergraphs. We also give a brief comparison of our proposed model with other existing models.

Practical thresholds to distinguish erosive and rill rainfall events

In this paper, 1017 rainfall events from 2008 to 2017 are used to identify the rainfall threshold that produces upland erosion at the Masse (central Italy) and Sparacia (southern Italy) experimental stations. The rainfall events are classified into three classes: non-erosive, interrill-only and rill. The threshold values for separating as correctly as possible the erosive rains (case I) and the rill rains (case II) are derived solely from the hyetograph. Each threshold value is obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events (case I) or only rill events (case II). The performances of selective criteria based on 31 threshold variables are compared, and those most effective in separating erosive and rill events are identified. The identification of the best criterion depends on the aim of the analysis. It could be required to provide the greatest accuracy for separating erosive and rill events or the lowest error in the prediction of long-term erosivity. In general, the results clearly show that the best variables are those that quantify the characteristics of rainfall patterns, such as rain showers (periods of continuous rain) and the deviations in the rain records over a truncation level. These results are especially significant for the operational estimation of rainfall erosivity and for identifying the trigger of the erosion process and rill development by using only a hyetograph. This is obtained by relatively simple field measurements and is also widely available on a global scale. The most effective variables are potentially usable in water erosion prediction models as proxies of variables that are more rarely available and/or more difficult to measure.

Data-Driven Acceleration of the Coupled-Cluster Singles and Doubles Iterative Solver.

Solving the coupled-cluster (CC) equations is a cost-prohibitive process that exhibits poor scaling with system size. These equations are solved by determining the set of amplitudes (t) that minimize the system energy with respect to the coupled-cluster equations at the selected level of truncation. Here, a novel approach to predict the converged coupled-cluster singles and doubles (CCSD) amplitudes, thus the coupled-cluster wave function, is explored by using machine learning and electronic structure properties inherent to the MP2 level. Features are collected from quantum chemical data, such as orbital energies, one-electron Hamiltonian, Coulomb, and exchange terms. The data-driven CCSD (DDCCSD) is not an alchemical method because the actual iterative coupled-cluster equations are solved. However, accurate energetics can also be obtained by bypassing solving the CC equations entirely. Our preliminary data show that it is possible to achieve remarkable speedups in solving the CCSD equations, especially when the correct physics are encoded and used for training of machine learning models.

C-terminal α-synuclein truncations are linked to cysteine cathepsin activity in Parkinson’s disease

A pathological feature of Parkinson's disease (PD) is Lewy bodies (LBs) composed of α-synuclein (α-syn) amyloid fibrils. α-Syn is a 140 amino acids–long protein, but truncated α-syn is enriched in LBs. The proteolytic processes that generate these truncations are not well-understood. On the basis of our previous work, we propose that these truncations could originate from lysosomal activity attributable to cysteine cathepsins (Cts). Here, using a transgenic SNCAA53T mouse model, overexpressing the PD-associated α-syn variant A53T, we compared levels of α-syn species in purified brain lysosomes from nonsymptomatic mice with those in age-matched symptomatic mice. In the symptomatic mice, antibody epitope mapping revealed enrichment of C-terminal truncations, resulting from CtsB, CtsL, and asparagine endopeptidase. We did not observe changes in individual cathepsin activities, suggesting that the increased levels of C-terminal α-syn truncations are because of the burden of aggregated α-syn. Using LC-MS and purified α-syn, we identified C-terminal truncations corresponding to amino acids 1–122 and 1–90 from the SNCAA53T lysosomes. Feeding rat dopaminergic N27 cells with exogenous α-syn fibrils confirmed that these fragments originate from incomplete fibril degradation in lysosomes. We mimicked these events in situ by asparagine endopeptidase degradation of α-syn fibrils. Importantly, the resulting C-terminally truncated fibrils acted as superior seeds in stimulating α-syn aggregation compared with that of the full-length fibrils. These results unequivocally show that C-terminal α-syn truncations in LBs are linked to Cts activities, promote amyloid formation, and contribute to PD pathogenesis.

Directional regression for functional data

We propose a method of sufficient dimension reduction for functional data based on directional regression. Functional principal component analysis with truncation acting as the regularization mechanism is used in the development. We establish optimal convergence rate for the estimation of the dimension reduction directions, in both L2 estimation error and prediction risk. Somewhat surprisingly, the optimal rates for both error measures are achieved at the same truncation level. Effect of discrete sampling of functional predictor on a dense grid is also considered. Simulations and a real data application illustrate the favorable finite sample performance of the method.

Many-body quantum metrology with scalar bosons in a single potential well

We theoretically investigate the possibility of performing high precision estimation of an externally imposed acceleration using scalar bosons in a single-well trap. We work at the level of a two-mode truncation, valid for weak to intermediate two-body interaction couplings. The splitting process into two modes is in our model entirely caused by the interaction between the constituent bosons and is hence neither due to an externally imposed double-well potential nor due to populating a spinor degree of freedom. The precision enhancement gained by using various initial quantum states using a two-mode bosonic system is well established. Here we therefore instead focus on the effect of the intrinsic dynamics on the precision, where, in a single well, the Hamiltonian assumes a form different from that of the typical double-well case. We demonstrate how interactions can significantly increase the quantum Fisher information maximized over initial states as well as the quantum Fisher information for a fragmented or a coherent state, the two many-body states that can commonly represent the ground state of our system.

On the Optimal Design of the Randomized Unbiased Monte Carlo Estimators

In recent literature, a new class of unbiased Monte Carlo estimators have been proposed, which is based on truncating a telescopic representation of the expectation of a functional of the stochastic process at an independent random level. The generality of the method lies in that it can translate any sequence of asymptotically unbiased estimators into a truly unbiased estimator. However, since any independent truncation level can lead to an unbiased estimator, its optimal choice is crucial for the successful implementation of this unbiased Monte Carlo method in financial engineering applications. We develop a novel efficient algorithm to locate the optimal distribution of the random truncation level in general, which answers positively an open question posted in Rhee and Glynn (2015), and we rigorously establish the convergence and optimality of the algorithm and derive its exact complexity. Our algorithm has a much lower complexity as compared to the literature, and numerical examples confirm our findings. The proposed algorithm is shown to be also applicable to optimization problems arising in contextual areas of supply chain management.

Truncation level selection in nonparametric regression using Padé approximation

This paper introduces a Padé-type approximation for an unknown regression function in a nonparametric regression model. This newly introduced approximation provides a linear model with multi-collinearities and errors in all its variables. To deal with these issues, we used the truncated total least squares (TTLS) method. The efficient implementation of a Padé-type method using TTLS depends on choosing a truncation level. To provide an optimum truncation level for this method, we update the conventional parameter selection methods, including the generalized cross validation (GCV), improved version of the Akaike information criterion (AICc), restricted maximum likelihood (REML), Bayesian information criterion (BIC), and Mallows’ Cp criterion. The primary aim of this study is to compare the performances of these level selection methods. A Monte Carlo simulation and a real data example are performed to illustrate the ideas in the paper. The results confirm that the GCV and AICc slightly outperform the other methods, especially when sample sizes are small and large, respectively.

Study of Conical Aerospike Nozzles with Base-Bleed and Freestream Effects

Conical aerospike nozzles are advanced rocket nozzles suitable for altitude compensation. A spike nozzle has geometry that resembles a conventional bell nozzle turned inside out. Lack of a solid outer surface ensures the variation of gas expansion to match the prevailing atmospheric pressure at different altitudes. This study focuses on flow characteristics within conical aerospike nozzles with different levels of truncation and flow conditions. Full spike and truncated aerospike nozzles are numerically simulated using two-dimensional axisymmetric and full three-dimensional models. Reynolds-averaged Navier–Stokes equations are solved with the shear stress transport turbulence model. Computational results of 20, 40, and 60% truncated nozzles are studied in comparison. Base bleed is implemented at two different locations of the base in 20% aerospike nozzle. Base bleed is taken as 2% of the inlet mass flow. The freestream effect is applied to 40% aerospike nozzle for validation purpose and 20% aerospike nozzle with different base-bleed cases for evaluation. Comparison of results establishes that the introduction of base bleed assists in compensating performance loss due to truncation, with the location of bleeding playing a major role in performance improvement. Effects of freestream on the base pressure characteristics of the nozzle are also demonstrated in comparison to nozzles without freestream.

Combined effects of 17β-estradiol and exercise training on cardiac apoptosis in ovariectomized rats.

BackgroundThe purpose of this study was to investigate the combined 17β-estradiol (E2) and exercise training on cardiac pro-survival and anti-apoptotic pathways in ovariectomized rats.MethodsFifty-six female Sprague–Dawley rats were divided into a sham-operated (Sham), a bilaterally ovariectomized (OVX), an OVX treated with E2 (OVX-E2; 10μg/kg/day), and an OVX with E2 and treadmill exercise training (OVX-E2-EX; 60 min/day, 5 days/week) for 10 weeks. Following 10 weeks of exercise training, rat hearts were isolated for the evaluation of Histopathological analysis, TUNEL assay, and Western blotting.ResultsThe protein levels of estrogen receptor α (ERα), estrogen receptor β (ERβ), insulin-like growth factor 1 (IGF-1), IGF-1 receptor (IGF-1R), phospho-phosphatidylinositol 3-kinase (p-PI3K) (estrogen receptors/IGF-1-related survival pathway) were significantly increased in either the OVX-E2 or OVX-E2-EX group when compared with the OVX group. The protein levels of B-cell lymphoma 2 (Bcl-2), B-cell lymphoma-extra-large (Bcl-xL) and phosphorylated-Bad (p-Bad) (Bcl-2 family survival pathway) were significantly increased in the OVX-E2-EX group when compared with the OVX group. Only the p-Bad was significantly increased in the OVX-E2 group when compared with the OVX group. The protein levels of truncation of Bid (t-Bid), Bcl-2-associated death promotor (Bad), Bcl-2-associated X protein (Bax), Cytochrome c, caspases-9, and caspases-3 (mitochondria-dependent apoptotic pathway), as well as the protein levels of tumor necrosis factor-α (TNF-α), Fas ligand, Fas receptors, Fas-associated death domain (FADD), activated caspase-8 and activated caspase-3 (Fas receptor–dependent apoptotic pathway) were significantly decreased in either the OVX-E2 or OVX-E2-EX group when compared with the OVX group. Furthermore, when compared with the OVX-E2 group, the protein levels of ERβ, IGF-1, IGF-1R, Bcl-2 and Bcl-xL were further enhanced in the OVX-E2-EX group as well as the protein levels of Cytochrome c, Fas receptors, FADD, activated caspase-8, activated caspase-9 and activated caspase-3 were further decreased in the OVX-EX-E2 group.ConclusionsCombined E2 and exercise training exhibited a positive effect of protection on ovariectomy-induced cardiac apoptosis by enhancing ERβ-related survival pathways, which might provide a more effective therapeutic effect on cardiac protection in bilaterally oophorectomized or menopausal women than E2 treatment only.

Somatic growth contributes to population variation in marine fishes.

Understanding population fluctuations is a major goal of population ecology. In unpredictable marine environments, population variation is thought to be caused primarily by varying survival rates through a critical early life-history stage. However, there is increasing evidence that somatic growth variation is common and causes population fluctuations. We examine the relative effects of empirically validated variability in somatic growth and recruitment on two response metrics across eight different life-history archetypes of marine fish. We evaluate how much variation is propagated into mature biomass (MB), a proxy for population resilience, and population production, a measure of population rebuilding capacity. Production is defined as the biomass produced by the stock above what is needed to sustain the population at a constant level. We used empirical estimates of reproductive success and somatic growth rate, coupled with a population model, to evaluate the relative role of both types of variation in population fluctuations. The effects of this variation on population production and MB were examined across three variation scenarios, in which somatic growth only, reproduction only or both processes varied temporally. We also examined three levels of age truncation to explore whether modified population age structure altered these dynamics. The contribution of somatic growth to biomass variability exceeded that of recruitment for some species (2/8), while in others (5/8 species), recruitment variation was more influential. When population production was examined, somatic growth variation contributed more to population variation for three species. The relative importance of the two processes was not clearly correlated with key life-history traits (i.e., growth and mortality rates), but instead was determined by time-series characteristics of growth and recruitment variation. Increasing age truncation slightly increased the relative effect of recruitment variation on MB variation for three species. These results suggest somatic growth variation can be as important as early life-history survival in driving population fluctuations in some marine fish species. This analysis provides a counterexample to the commonly held assumption of many marine population dynamics models: That population variability is induced primarily through variation in reproductive success.

Large scale parallelization in stochastic coupled cluster.

Coupled cluster theory is a vital cornerstone of electronic structure theory and is being applied to ever-larger systems. Stochastic approaches to quantum chemistry have grown in importance and offer compelling advantages over traditional deterministic algorithms in terms of computational demands, theoretical flexibility, or lower scaling with system size. We present a highly parallelizable algorithm of the coupled cluster Monte Carlo method involving sampling of clusters of excitors over multiple time steps. The behavior of the algorithm is investigated on the uniform electron gas and the water dimer at coupled-cluster levels including up to quadruple excitations. We also describe two improvements to the original sampling algorithm, full non-composite, and multi-spawn sampling. A stochastic approach to coupled cluster results in an efficient and scalable implementation at arbitrary truncation levels in the coupled cluster expansion.

Non-integrated defect of meromorphic maps on Kähler manifolds

The purpose of this article is twofold. The first is to establish a truncated non-integrated defect relation for meromorphic mappings from a complete Kahler manifold quotien of a ball into a projective variety intersecting hypersurfaces in subgeneral position. We also apply it to the Gauss mapping from a closed regular submanifold of $${\mathbb {C}}^m$$ . The second aim is to establish an above type theorem with truncation level 1 for differentiably nondegenerate meromorphic mappings.

Critical Wess-Zumino models with four supercharges in the functional renormalization group approach

We analyze the $\mathcal{N}=1$ supersymmetric Wess-Zumino model dimensionally reduced to the $\mathcal{N}=2$ supersymmetric model in three Euclidean dimensions. As in the original model in four dimensions and the $\mathcal{N}=(2,2)$ model in two dimensions the superpotential is not renormalized. This property puts severe constraints on the non-trivial fixed-point solutions, which are studied in detail. We admit a field-dependent wave function renormalization that in a geometric language relates to a K\"ahler metric. The K\"ahler metric is not protected by supersymmetry and we calculate its explicit form at the fixed point. In addition we determine the exact quantum dimension of the chiral superfield and several critical exponents of interest, including the correction-to-scaling exponent $\omega$, within the functional renormalization group approach. We compare the results obtained at different levels of truncation, exploring also a momentum-dependent wave function renormalization. Finally we briefly describe a tower of multicritical models in continuous dimensions.