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Even though tuning electronic effect of chiral ligands has proven to be a promising method for designing efficient catalysts, the potential to achieve highly selective reactions by this strategy remains largely unexplored. Here, we report a palladium-catalyzed enantioselective ring-closing aminoalkylative amination of aminoenynes enabled by rationally tuning the remote electronic property of 1,1'-binaphthol-derived phosphoramidites. With a tailored 6,6'-CN-substituted 1,1'-binaphthol-derived phosphoramidite as a ligand, a broad range of aromatic amines are compatible with this reaction, allowing the efficient synthesis of a series of enantioenriched exocyclic allenylamines bearing saturated N-heterocycles with up to >99% enantiomeric excess. Remarkably, a one-pot aminoalkylative amination/hydroamination process for the rapid synthesis of chiral spirodiamines promoted by this catalytic system is also established. Detailed mechanistic studies provide solid evidence to support that the remote electronic character of these chiral ligands can efficiently tuning the enantioselectivity by altering the length of the allylic C-Pd bond of the key catalytic intermediate. The potential applications of remote electronic effect in Pd-catalyzed asymmetric transformations have remained largely unexplored. Here, the authors report a Pd-catalyzed enantioselective ring-closing aminoalkylative amination of aminoenynes enabled by rationally tuning the remote electronic property of BINOL-derived phosphoramidites. [ABSTRACT FROM AUTHOR]

Differential evolution (DE) has attracted widespread attention due to its outstanding optimization performance and ease of operation, but it cannot avoid the dilemmas of premature convergence or stagnation when faced with complex optimization problems. To reduce the probability of such difficulties for DE, we sort out the factors that influence the balance between global exploration and local exploitation in the DE algorithm, and we design a novel DE variant (abbreviated as PISRDE) by integrating the corresponding influence factors through a periodic intervention mechanism and a systematic regulation mechanism. The periodic intervention mechanism divides the optimization operations of PISRDE into routine operation and intervention operation, and it balances global exploration and local exploitation at the macro level by executing the two operations alternately. The systematic regulation mechanism treats the involved optimization strategies and parameter settings as an organic system for targeted design, to balance global exploration and local exploitation at the meso or micro level. To evaluate and verify the optimization performance of PISRDE, we employ seven DE variants with excellent optimization performance to conduct comparison experiments on the IEEE CEC 2014 and IEEE CEC 2017 benchmarks. The comparison results indicate that PISRDE outperforms all competitors overall, and its relative advantage is even more significant when dealing with high-dimensional and complex optimization problems. Schematic design philosophy of PISRDE [ABSTRACT FROM AUTHOR]

Multidimensional Floquet-driven alignment systems with dynamical symmetry present various exotic phenomena and applications. However, there are challenges in directly characterizing large-spin dynamical symmetry from spectra. Here, we first observe the symmetry-protected selection rules of dynamical high-dimensional parity in a large-spin (F = 4) system. We theoretically construct a Floquet-driven alignment system that can be used to reveal high-dimensional spatiotemporal symmetry. In the experiment, the system is implemented in Cs atomic gas subjected to two-dimensional Floquet-modulated magnetic resonance driving. By developing Floquet detection protocols of alignment double-sided spectra, we directly verify symmetry-protected selection rules of dynamical high-dimensional parity for large-spin systems. This work advances the exploration of dynamical symmetry to large spins, and unravels a universal Floquet scheme for the investigation of symmetry-protected selection rules. [ABSTRACT FROM AUTHOR]

Based on the actual operation scenario of metro, this paper proposes an uneven parameter stray current distribution model. The model combines the calculation method of multi-section traction power supply of metro and establishes an uneven parameter stray current distribution model in different calculation domains with the metro operation position and the traction substation position as the boundary points. The improved dynamic boundary conditions were used to calculate the model. Compared with the experimental data, the average maximum deviation between the two was 0.677. Meanwhile, the dynamic space–time distribution characteristics of stray current and the change law of rail-to-ground voltage were obtained through simulation analysis. In addition, the calculation model for ground potential gradient distribution under stray current interference was established by discretizing stray currents within each calculation domain, and the characteristics of ground potential gradient distribution were simulated and analyzed. The results showed that the distribution period of stray current was approximately equal to the headway, and the waveform change lagged behind the rail-to-ground voltage. The fluctuation degree of ground potential gradient was obviously affected by the length of power supply interval and train operation conditions. [ABSTRACT FROM AUTHOR]

By partially substituting water molecules in polymer hydrogel electrolytes with organic solvents, the-low temperature tolerance of supercapacitors can be significantly improved. However, the low conductivity resulting from the organic solvents inevitably influences the energy storage behavior of the supercapacitor. To address this issue, a new strategy is employed by embedding glycerin (Gly)-Mo into both the electrolyte and electrode materials, resulting in a supercapacitor that exhibits outstanding conductivity and resistance to subzero temperatures. The introduction of Gly-Mo enhances the mechanical properties and conductivity of hydrogel under freezing conditions. The in situ growth of an electrode containing Gly-Mo lowers the interface resistance between the electrode and electrolyte. When the temperature decreases from room temperature to − 40 °C, the supercapacitor retains 63.36% of its specific capacitance. Furthermore, the flexible supercapacitor is capable of withstanding punching damage, maintaining a specific capacitance of 140.75 mF cm−2 at 1 mA cm−2 with 300 holes cm−2. The supercapacitor also exhibits remarkable capacitance retention after being bent at a 90° angle for 400 cycles. [ABSTRACT FROM AUTHOR]

The emerging information and communication technologies (ICT) related to Industry 4.0 play a critical role to enhance supply chain performance. Employing the smart technologies has led to so-called smart supply chains. Understanding how Industry 4.0 and related ICT affect smart supply chains and how smart supply chains evolve with the support of the advanced technologies are vital to practical and academic communities. Existing review works on smart supply chains with ICT mainly rely on the academic literature alone. This paper presents an integrated approach to explore the effects of Industry 4.0 and related ICT on smart supply chains, by combining introduction of the current national strategies in North America, the research status analysis on ICT assisted supply chains from the major North American national research councils, and a systematic literature review of the subject. Besides, we introduce a smart supply chain hierarchical framework with multi-level intelligence. Furthermore, the challenges faced by supply chains under Industry 4.0 and future research directions are discussed as well. [ABSTRACT FROM AUTHOR]

An enhancing terahertz radiation scheme, in which a linearly polarized laser pulse irradiates a double-layer target consisting of a near-critical density plasma and an overdense density plasma, is proposed and studied by using the two-dimensional Particle-In-Cell simulations. Compared with that in the single-layer target only containing an overdense density plasma, the results show that the electric field intensity of the terahertz wave passing through the probe point is increased by an order of magnitude in the double-layer target. We find that the electrons coming from the interaction of laser with near-critical density plasma are the origin of enhancing terahertz radiation. These electrons gain high energy through the direct laser acceleration mechanism, leading to the maximum cut-off energy being more than 5 times higher than that in the single-layer target. Besides, the influence of the parameters of the near-critical density plasma on the terahertz radiation is also scanned through a series of numerical simulations, and the robustness of this scheme is verified. This scheme may provide a theoretical and parametric guidance for the generation of strong-field terahertz waves based on the relativistic femtosecond laser irradiation of structural targets. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the clinical characteristics, endocrinological function, and etiology of bilateral adrenal lesions in hospitalized patients. Methods: A retrospective study of 777 patients with bilateral adrenal lesions was conducted at the Chinese People's Liberation Army General Hospital between January 2013 and January 2018. Patients' demographic features, hormonal profiles, imaging findings, and histopathological findings were reviewed from database records. Results: Of the 777 patients with bilateral adrenal lesions, 495 were men. The mean age at diagnosis was 52.0 ± 13.0 years. Overall, 511 (65.8%) cases were benign, followed by adrenal metastases (n = 224, 28.8%), pheochromocytoma (n = 26, 3.3%), adrenal lymphoma (n = 9, 1.2%), and adrenal corticocarcinoma (ACC; n = 7, 0.9%). Hormonal evaluation revealed that 34.3% of bilateral adrenal lesions were functional. The primary etiologies of functional lesions were primary aldosteronism (16.6%, 129/777), and primary bilateral macronodular adrenocortical hyperplasia (PBMAH; 8.8%, 68/777). Patients with lymphoma and metastases were significantly older than those with benign nonfunctional lesions (60.4 ± 11.0 years vs. 54.5 ± 10.4 years and 57.9 ± 10.8 years vs. 54.5 ± 10.4 years, respectively; both P < 0.001). Lesions in patients with adrenal lymphoma, ACC, pheochromocytoma, metastases, congenital adrenal hyperplasia, tuberculosis, and Cushing's syndrome were significantly larger than benign nonfunctional lesions (all P < 0.001). Conclusion: Benign adrenal lesions and metastases from the lungs are the most common causes of bilateral adrenal lesions. Primary aldosteronism and PBMAH are the most prevalent functional lesions. Moreover, patients with lymphoma or metastases are older and their masses are larger. [ABSTRACT FROM AUTHOR]

Natural disasters not only inflict massive life and economic losses but also result in psychological damage to survivors, at times even causing social unrest. It is necessary to design a sustainable last mile relief network for distributing relief supplies regarding social factors, disaster relief efficiency as well as the economic cost of three perspectives in terms of sustainability. We establish a multi-objective distributionally robust optimization model for a sustainable last mile relief network problem that maximizes the equitable distribution of relief supplies and simultaneously minimizes the transportation time and operation cost. Under the partial probability information of uncertainties, such as the disaster situation, transportation time, freight, road capacity, and demand, we characterize the uncertain variables in an ambiguity set incorporating the bounds, means and the mean absolute deviations. Then, the bounds on the objective values and the safe approximations of the chance constraints are deduced under the ambiguity sets. Based on a revised multi-choice goal programming approach, we obtain a computationally tractable framework of the multi-objective model. To verify the effectiveness of the model and methods, a case study of the Banten tsunami is illustrated. The results demonstrate our proposed model can obtain a trade-off between the equitability, timeliness and economics for relief distribution in a relief network. [ABSTRACT FROM AUTHOR]

The optical scattering coefficient (μs) in the dermis layer of human skin obtained with optical coherence tomography (OCT) has shown to have a strong correlation with the blood glucose concentration (BGC), which can be used for noninvasive BGC monitoring. Unfortunately, the nonhomogeneity in the skin may cause inaccuracies for the BGC analysis. In this paper, we propose a 2D correlation analysis method to identify 2D regions in the skin with μs sensitive to BGC variations and only use data in these regions to calculate μs for minimizing the inaccuracy induced by nonhomogeneity and therefore improving the accuracy of OCT-based BGC monitoring. We demonstrate the effectiveness of the 2D method with OCT data obtained with in vivo human forearm skins of nine different human subjects. In particular, we present a 3D OCT data set in a two-dimensional (2D) map of depth vs. a lateral dimension and calculate the correlation coefficient R between the μs and the BGC in each region of the 2D map with the BGC data measured with a glucose meter using finger blood. We filter out the μs data from regions with low R values and only keep the μs data with R values sufficiently high (R-filter). The filtered μs data in all the regions are then averaged to produce an average μs data. We define a term called overall relevancy (OR) to quantify the degree of correlation between the filtered/averaged μs data and the finger-blood BGC data to determine the optimal R value for such an R-filter with the highest obtained OR. We found that the optimal R for such an R-filter has an absolute value (|R|) of 0.6 or 0.65. We further show that the R-filter obtained with the 2D correlation method yields better OR between μs and the BGC than that obtained with the previously reported 1D correlation method. We believe that the method demonstrated in this paper is important for understanding the influence of BGC on μs in human skins and therefore for improving the accuracy of OCT-based noninvasive BGC monitoring, although further studies are required to validate its effectiveness. [ABSTRACT FROM AUTHOR]

Spermatogenesis is usually accompanied throughout mammalian lifetime, transmitting genetic information to the next generation, which is mainly dependent on the self-renewal and differentiation of spermatogonial stem cells (SSCs). With further investigation on profiles of SSCs, the previous prevailing orthodoxy that SSCs are unipotent stem cells to differentiate into spermatids only, has been challenged. More notably, accumulating evidence has demonstrated that SSCs are capable of giving rise to cell lineages of the three germ layers, highlighting potential important applications of SSCs for regenerative medicine. Nevertheless, it is unknown how the proliferation and stemness maintenance of SSCs are regulated intrinsically and strictly controlled in a special niche microenvironment in the seminiferous tubules. Based on the special niche microenvironment for SSCs, it is of vital interest to summarize the recent knowledge regarding several critical bioactive molecules in the self-renewal and stemness maintenance of SSCs. In this review, we discuss most recent findings about these critical bioactive factors and further address the new advances on the self-renewal and stemness maintenance of SSCs. [ABSTRACT FROM AUTHOR]

Abnormal excessive production and deposition of β-amyloid (Aβ) peptides in selectively susceptible brain regions are thought to be a key pathogenic mechanism underlying Alzheimer's disease (AD), resulting in memory deficits and cognitive impairment. Genistein is a phytoestrogen with great promise for counteracting diverse Aβ-induced insults, including oxidative stress and mitochondrial dysfunction. However, the exact molecular mechanism or mechanisms underlying the neuroprotective effects of genistein against Aβ-induced insults are largely uncharacterized. To further elucidate the possible mechanism(s) underlying these protective effects, we investigated the neuroprotective effects of genistein against Aβ-induced oxidative stress mediated by orchestrating α7 nicotinic acetylcholine receptor (α7nAChR) signaling in rat primary hippocampal neurons. Genistein significantly increased cell viability, reduced the number of apoptotic cells, decreased accumulation of reactive oxygen species (ROS), decreased contents of malondialdehyde (MDA) and lactate dehydrogenase (LDH), upregulated BCL-2 expression, and suppressed Caspase-3 activity occurring after treatment with 25 μM Aβ25-35. Simultaneously, genistein markedly inhibited the decreases in α7nAChR mRNA and protein expression in cells treated with Aβ25-35. In addition, α7nAChR signaling was intimately involved in the genistein-mediated activation of phosphatidylinositol 3-kinase (PI3K)/Akt and Nrf2/keap1 signaling. Thus, α7nAChR activity together with the PI3K/Akt/Nrf2 signaling cascade likely orchestrates the molecular mechanism underlying the neuroprotective effects of genistein against Aβ-induced oxidative injury. [ABSTRACT FROM AUTHOR]

Since natural disasters often cause the loss of lives and property, it is necessary to design a reasonable relief network to distribute relief supplies after a disaster. The shortage of relief supplies and timely transportation are the main difficulties in the whole relief network. To overcome these difficulties, we introduce a three-level humanitarian relief network design problem with resource reallocation of relief supplies. Based on the existing relief network system before a disaster, this problem determines the positions of candidate local distribution centers and points of distribution, while considering the relief distribution in the network under an uncertain post-disaster environment. For the uncertain variables, we consider a distributionally robust model with mean absolute semi-deviation (MASD) as a risk measure taken into the transportation time function. Under the partial probability distribution information of the uncertainties, we deduce a tractable framework of the distributionally robust model. Specifically, we derive the worse case form of the MASD objective under an ambiguity set and the safe approximations of the chance constraints under a box + ellipsoid + generalized budget perturbation set. Finally, we demonstrate the efficacy of the model by a real case in Anambra flood. [ABSTRACT FROM AUTHOR]

Proper production planning is significantly for enhancing revenue and productivity of manufacturing companies. This paper focuses on multi-channel supply chain multi-factory collaborative production planning problem, considering uncertain customer demand. The decision-making process is divided into strategic and operational decisions aimed at maximizing company profits. To meet customer demand, the collaboration between multiple factories is crucial. However, customer demand is often uncertain, unobservable, and difficult accurately describe. To address this challenge, we propose a data-driven adaptive distributionally robust optimization model. Specifically, we utilize K-means clustering to tackle the unobservability of customer demand and construct a distributional ambiguity set described by divergence to handle the distributional ambiguity of customer demand. Subsequently, the formulated optimization model is transformed into a mixed integer program. In numerical experiments, we demonstrate the efficacy of our proposed adaptive distributionally robust optimization model in mitigating customer demand unobservability and distributional ambiguity. We verify the impact of cluster number on the model solution. Moreover, we compare our constructed adaptive distributionally robust model with the stochastic average approximation model, demonstrating that our model better reduces uncertainty compared to the stochastic average approximation model. [ABSTRACT FROM AUTHOR]

Redundancy allocation is a direct way of enhancing the series-parallel system lifetime and reliability. Since it is difficult to obtain the exact probability distributions about the lifetimes of components, fuzzy random variables are used to characterize them. Under the given system weights and cost constraints, we maximize the equilibrium optimistic system lifetime of redundant elements. This paper proposes an equilibrium optimization model for the standby redundancy system. Since the exact analytical expressions of the equilibrium optimistic system lifetimes are unavailable in general case, the proposed model cannot be analytically solved. Under mild assumptions, the new equilibrium model can be divided into its equivalent stochastic programming subproblems. Moreover, a new approximation method is proposed to solve the general equilibrium model. For the equivalent stochastic programming subproblems, sample average approximation (SAA) is adapted to gain their SAA problems. A hybrid particle swarm optimization algorithm with local search is designed to solve the SAA problems. Several numerical experiments are conducted to investigate the effectiveness of proposed model and designed solution method. The comparative studies indicate the randomness, and fuzziness cannot be ignored in the equilibrium standby redundancy optimization problem. [ABSTRACT FROM AUTHOR]

To investigate the relationship between managerial compensation and research and development (R&D) investment under asymmetric information, this paper establishes a two-period principal-agency model, in which the firm owner hires a risk-averse manager to operate the firm and to make the R&D investment decision. The manager has private information regarding the profitability of the R&D investment. Firstly, we present an R&D investment problem under symmetric information as the benchmark. Then, we discuss the scenario with asymmetric information about the profitability, and the firm owner offers new optimal incentive contact. We compare the differences of the company’s R&D investment decisions and choices of the compensation contract under symmetric and asymmetric information cases by numerical experiments. We find that the manager receives an upward distortion in the first-period bonus share rate, and a downward distortion in the second-period bonus share rate. Meanwhile, the R&D investment is less than the symmetric information case. At last, the variable outside option has no effect on the optimal manager’s compensation contract when the marginal cost of R&D investment is relatively small or under symmetric information case. [ABSTRACT FROM AUTHOR]

To investigate the effect of employees' job satisfaction on the firm's workforce planning, this paper builds a multi-period uncertain workforce planning model with job satisfaction level, where the labor demands and operation costs are characterized as uncertain variables. The job satisfaction level is defined as the employees' psychological satisfaction about overtime through prospect theory. The proposed uncertain model can be transformed into an equivalent deterministic form, which contains complex nonlinear constraints and cannot be solved by conventional optimization methods. Thus, a hybrid joint operations algorithm (JOA) integrated with LINGO software is designed to solve the proposed workforce planning problem. Consequently, several numerical experiments are conducted to compare our proposed JOA with a hybrid particle swarm optimization algorithm to verify the effectiveness of the JOA algorithm. The results demonstrate that the firm's total operation cost increases with the employees' job satisfaction level, the loss averse degree and outside firms' overtime level, respectively. Meanwhile, the firm would overpay in bounded rational cases with job satisfaction, and the overpayment can be seen as the value of bounded rationality, which ensures the firm's normal operation. [ABSTRACT FROM AUTHOR]

To investigate how the loss averse customer's psychological satisfaction affects the company's furniture production planning, we establish a furniture production planning model under uncertain environment, where customer demand and production costs are characterized by mutually independent uncertain variables. Based on prospect theory, customer's psychological satisfaction about stockout performance is measured by cumulative service levels in our model. In the framework of uncertainty theory, the proposed uncertain model can be transformed into an equivalent deterministic form. However, the transformed model is a nonlinear mixed integer programming problem, which cannot be solved by conventional optimization algorithms. To cope with this difficulty, a chemical reaction optimization algorithm integrated with LINGO software is designed to solve the proposed production planning problem. In order to verify the effectiveness of the designed hybrid chemical reaction optimization (CRO) algorithm, we conduct several numerical experiments via an application example and compare with a spanning tree-based genetic algorithm (hst-GA). The computational results show that our proposed CRO algorithm achieves better performance than hst-GA, and the results also provide several interesting managerial insights in production planning problems. [ABSTRACT FROM AUTHOR]

This paper investigates the hybrid time- and random event-triggered systems wherein sensors are scheduled and actuators are triggered by a random event modeled as a Markov chain. The system is built as a group of Markov jump linear systems (MJLS) switching with each other. Then, a design condition for scheduling sequences is obtained. With the scheduling sequence, some sufficient conditions for stability are obtained, which tie together the sensor switching properties (such as switching frequency and activation rate) and the probability of the random event driving the actuators. In particular, a feedback controller design algorithm and constraint conditions for the average dwell time are given. A numerical example has shown the usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: Our purpose was to explore pupil light response (PLR) with respect to the change in sensitivity of photoreceptors during various dark adaptation phases and to determine the optimal duration of dark adaptation time before the PLR. Methods: The PLR was recorded in 15 healthy subjects and three patients with neural or retinal vision loss after 1-sec blue and red light stimuli of 1, 10, and 100 cd/m. The PLR was repeated nine times at different checkpoints during the 40-minute dark adaptation. The transient contraction amplitude, sustained contraction amplitude, and relative sustained contraction ratio of the PLR were analyzed. Results: The increase in the transient contraction amplitude during the entire dark adaptation process was significant (changing up to 45.1 %) in the initial phase of dark adaptation under different stimulus conditions. The changes in the sustained contraction amplitude and the relative sustained contraction ratio were substantial (changing up to 71.0 % and 37.2 % from 1 to 20 minutes of dark adaptation, respectively) under high-intensity blue illumination. The inflection point of the contraction curves in the dark adaptation was 15 or 20 minutes. The patients' PLR results changed in a similar manner. Conclusions: The changes in the sensitivity of different photoreceptors occurred at different rates, and the contraction amplitude of the PLR was significantly affected by the dark adaptation duration. So 20 minutes of dark adaptation before PLR testing was suggested to achieve a consistent and stable pupil response. The dark adaptation effect should be put into consideration when comparing the results from different phases of the PLR test. [ABSTRACT FROM AUTHOR]

In many practical supply chain network design (SCND) problems, the critical parameters such as customer demands, transportation costs and resource capacities are quite uncertain. The significance of uncertainty motivates us to develop a new mean-risk fuzzy optimization method for SCND problem, in which the standard semivariance is suggested to gauge the risk resulted from fuzzy uncertainty. To demonstrate the advantages of the proposed optimization method, we define a new concept about the value of fuzzy solution for our SCND problem. When the transportation costs and the demands of customers have continuous possibility distributions, we approximate the continuous fuzzy vector by a sequence of discrete fuzzy vectors. On the basis of the approximation scheme, we obtain an approximating optimization model, which is a nonlinear mixed-integer programming problem. Furthermore, we design a hybrid memetic algorithm (MA) to solve the approximating optimization problem. The designed hybrid MA incorporates the reduced variable neighborhood search to act as the local search procedure. Finally, we conduct some numerical experiments via an application example to demonstrate the effectiveness of the designed hybrid MA. [ABSTRACT FROM AUTHOR]

In order to ascertain the invasive mechanism and control strategy of the invasive Crofton weed, Ageratina adenophora, its ecological adaptability and population differentiation, the formation of single dominant population, displacement of native plants and sustainable management strategies were investigated. The present results helped to clarify and explain such issues as the adaptability post invasion, interaction and competition between inter- and intra-species and community resistance, thereby providing important references to researches on other invasive alien species. [ABSTRACT FROM AUTHOR]

This paper discusses admissibilities of estimators in a class of linear models, which include the following common models: the univariate and multivariate linear models, the growth curve model, the extended growth curve model, the seemingly unrelated regression equations, the variance components model, and so on. It is proved that admissible estimators of functions of the regression coefficient β in the class of linear models with multivariate t error terms, called as Model II, are also ones in the case that error terms have multivariate normal distribution under a strictly convex loss function or a matrix loss function. It is also proved under Model II that the usual estimators of β are admissible for p ⩽ 2 with a quadratic loss function, and are admissible for any p with a matrix loss function, where p is the dimension of β. [ABSTRACT FROM AUTHOR]

This study investigated the role of homocysteine thiolactone (HcyT) in the development of macrovascular complications in Chinese patients with type 2 diabetes. HcyT has been proposed as a possible molecular basis for homocysteine (Hcy)-induced vascular damage. One hundred and sixty subjects were recruited into this study: 40 healthy controls and 120 patients with type 2 diabetes. Plasma Hcy levels were measured by polarization immunoassay and HcyT concentrations were monitored using high-performance liquid chromatography on a reversephase C18 column with ultraviolet detection. Plasma folic acid and vitamin B12 levels were measured using radioimmunoassay methods. Plasma Hcy and HcyT concentrations in patients with type 2 diabetes were significantly higher than in healthy controls (Hcy [25th and 75th quartiles]: 9.28 [7.51–11.82] vs. 5.64 [5.17–8.00] μmol/L, P=0.01; HcyT: 3.38 [2.94–4.73] vs. 2.91 [2.77–3.08] nmol/L, P<0.05). Plasma Hcy and HcyT levels in patients with macrovasculopathy (MAVP) were significantly higher compared with patients without MAVP (Hcy: 10.36 [7.67–12.45] vs. 7.85 [6.76–10.52] μmol/L, P<0.05; HcyT: 4.27 [3.02–5.11] vs. 3.12 [2.63–3.77] nmol/L, P<0.05). Plasma HcyT concentrations were positively correlated with urinary excretion of albumin/creatinine (Alb/Cr; r=0.285, P=0.007), duration of diabetes ( r=0.249, P=0.019), age ( r=0.233, P=0.028), and fibrinogen levels ( r=0.289, P=0.034). Plasma HcyT concentrations were negatively correlated with high-density lipoprotein levels ( r=−0.223, P=0.037). Binary logistic regression showed that HcyT, Hcy, smoking, serum triglyceride, and urine Alb/Cr were significantly associated with the risk of diabetic MAVP ( P<0.05). Hcy and HcyT levels were associated with the development and progression of diabetic MAVP. HcyT may provide a plausible chemical mechanism for explaining Hcy toxicity in the human vascular endothelium. [ABSTRACT FROM AUTHOR]

In this paper, we study the existence of the uniformly minimum risk equivariant (UMRE) estimators of parameters in a class of normal linear models, which include the normal variance components model, the growth curve model, the extended growth curve model, and the seemingly unrelated regression equations model, and so on. The necessary and sufficient conditions are given for the existence of UMRE estimators of the estimable linear functions of regression coefficients, the covariance matrix V and (tr V)α, where α > 0 is known, in the models under an affine group of transformations for quadratic losses and matrix losses, respectively. Under the (extended) growth curve model and the seemingly unrelated regression equations model, the conclusions given in literature for estimating regression coefficients can be derived by applying the general results in this paper, and the sufficient conditions for non-existence of UMRE estimators of V and tr( V) are expanded to be necessary and sufficient conditions. In addition, the necessary and sufficient conditions that there exist UMRE estimators of parameters in the variance components model are obtained for the first time. [ABSTRACT FROM AUTHOR]