The influence of marital status on the social dysfunction of schizophrenia patients in community

Objective:Estimate predictive associations of marital status with social dysfunction in schizophrenia patients.Methods:817 schizophrenia patients lived in the community of Dongguan,Guangdong province,China,were investigated with the Social Disability Screening Schedule(SDSS)during a three-month period(1.2010e3.2010).The demographic data were harvested.The c2 test,t test,and fisher's exact were used for comparisons between groups,as appropriate.Multinomial logistic regression(MLR)was used to analyze the predictive associations of demographic variables to the grading of social dysfunctions.Results:The study group consisted of male and female patients aged 16e59 years,407 females,and 410 males with the mean age(40.7±9.5)years.Analysis of the data revealed significant differences in course of disease and marital status among patients(with and without dysfunction).The married patient made a significant difference with divorced/widowed patient in mildlyemoderately social dysfunction.There was a significant difference in married and never-married patient with mildly and profoundly social dysfunction.Significant differences were noticed in the self care and occupational roles of the married patient with that of the never-married.Conclusion:This study confirmed that bad marital status is associated with higher odds of social dysfunction among patients with schizophrenia living in the community.These effects should be included in considerations of public health investments in preventing and treating mental disorders.

High-throughput identification of one-dimensional atomic wires and first principles calculations of their electronic states

Low dimensional materials are suitable candidates applying in next-generation high-performance electronic,optoelectronic,and energy storage devices because of their uniquely physical and chemical properties.In particular,one-dimensional(1D)atomic wires(AWs)exfoliating from 1D van der Waals(vdW)bulks are more promising in next generation nanometer(nm)even sub-nm device applications owing to their width of few-atoms scale and free dandling bonds states.Although several 1D AWs have been experimentally prepared,few 1D AW candidates could be practically applied in devices owing to lack of enough suitable 1D AWs.Herein,367 kinds of 1D AWs have been screened and the corresponding computational database including structures,electronic structures,magnetic states,and stabilities of these 1D AWs has been organized and established.Among these systems,unary and binary 1D AWs with relatively small exfoliation energy are thermodynamically stable and theoretically feasible to be exfoliated.More significantly,rich quantum states emerge,such as 1D semiconductors,1D metals,1D semimetals,and 1D magnetism.This database will offer an ideal platform to further explore exotic quantum states and exploit practical device applications using 1D materials.The database are openly available at http://www.dx.doi.org/10.11922/sciencedb.j00113.00004.

Materials Design on the Origin of Gap States in a High-κ/GaAs Interface

Given the demand for constantly scaling microelectronic devices to ever smaller dimensions, a SiO_2 gate dielectric was substituted with a higher dielectric-constant material, Hf(Zr)O_2, in order to minimize current leakage through dielectric thin film. However, upon interfacing with high dielectric constant(high-κ) dielectrics, the electron mobility in the conventional Si channel degrades due to Coulomb scattering, surface-roughness scattering, remotephonon scattering, and dielectric-charge trapping. III-V and Ge are two promising candidates with superior mobility over Si. Nevertheless, Hf(Zr)O_2/III-V(Ge) has much more complicated interface bonding than Si-based interfaces. Successful fabrication of a high-quality device critically depends on understanding and engineering the bonding conflgurations at Hf(Zr)O_2/III-V(Ge) interfaces for the optimal design of device interfaces. Thus, an accurate atomic insight into the interface bonding and mechanism of interface gap states formation becomes essential. Here, we utilize firstprinciple calculations to investigate the interface between HfO_2 and Ga As. Our study shows that As—As dimer bonding, Ga partial oxidation(between 3+ and 1+) and Ga— dangling bonds constitute the major contributions to gap states. These findings provide insightful guidance for optimum interface passivation.

Multidirectional 3D printed functionally graded modular joint actuated by TCPFL muscles for soft robots

Highly deformable bodies are essential for numerous types of applications in all sorts of environments. Joint-like structures comprising a ball and socket joint have many degrees of freedom that allow mobility of many biomimetic structures. Recently, soft robots are favored over rigid structures for their highly compliant material, high-deformation properties at low forces, and ability to operate in di fficult environments. However, it is still challenging to fabricate complex designs that satisfy application constraints due to the combined e ffects of material properties, actuation method, and structural geometry on the performance of the soft robot. Therefore, a combination of a rigid joint and a soft body can help achieve modular robots with fully functional body morphology. Yet, the fabrication of soft parts requires extensive molding for complex shapes, which comprises several processes and can be time-consuming. In addition, molded connections between extremely soft materials and hard materials can be critical failing points. In this paper, we present a functionally graded 3D-printed joint-like structure actuated by novel contractile actuators. Functionally graded materials (FGMs) via 3D printing allow for extensive material property enhancement and control which warrant tunable functionalities of the system. The 3D-printed structure is made of 3 rigid ball and socket joints connected in series and actuated by integrating twisted and coiled polymer fishing line ( TCPFL) actuators, which are con fined in the FGM accordion-shaped channels. The implementation of the untethered T CPFL actuation system can be highly bene ficial for deployment in environments that require low vibrations and silent actuation. The fishing line TCP actuators produce an actuation strain up to 40% and bend the joint up to 40° in any direction. The T CPFL can be actuated individually or as a group to control the bending trajectory of the modular joint, which is bene ficial when deployed in areas that contain small crevices. Obtaining complex modes of bending, the FGM multidirectional joint demonstrated a great potential to achieve di fferent functionalities such as crawling, rolling, swimming, or underwater exploration.

Coal petrology and genesis of Jurassic coal in the Ordos Basin,China

Multiple sets of thick coal beds characterized by simple structure and shallow burial depth were developed in the Early and Middle Jurassic strata of the Ordos Basin, northwestern China. The huge reserves of this high quality coal have a high commercial value. We studied the coal＇s petrologic characteristics and its maceral distribution to determine the maceral＇s contribution to generation of oil and gas. The results show that the Jurassic coals in the Ordos Basin have special petrological features because of the Basin＇s unique depo- sitional environment which was mainly a series of high-stand swamps in the upper fluvial system. These petro- graphic features are a result of the development of typical inland lakes where some sand bodies were formed by migrating rivers. After burial, the peat continued to undergo oxidizing conditions, this process generated extensive higher inertinite contents in the coals and the vitrinite components were altered to semi-vitrinite. The macroscopic petrographic types of these Jurassic coals are mainly semi-dull coal, dull coal, semilustrous and lustrous coal. The proportions of semi-dull coal and dull coal are higher in the basin margins, especially in the area near the northern margin. The numbers of semilustrous and lustrous coals increase southwards and towards the central basin. This situation indicates that different coal-forming swamp environments have major controlling effects on the coal components. Another observation is that in the Ordos＇ coal sequences, especially in the lower part, some sandstone beds are thick, up to 20 m with a coarse grain size. The higher fusinite content in the macerals accompanies a higher semi-vitrinite content with more complete and regular plant cell structure. The fusinite structure is clear and well preserved. After burial, the lithology of the roof and floor rocks can continue to affect the evolution of coal petrology. The sand bodies in the roof and floor exhibit good physical conditions so that pore water can maintain a long-term state of oxidation, circulation and connection to the coal. So coal components remain in an oxidation environment for a long time. Conversely, in the basin center, lacustrine facies developed and peat was rapidly covered by mudstone after burial and subsequent coal beds rapidly entered a reducing environment. As a result, abundant gelatification occurred and the vitrinite content increased. E^inite often accumulated in a specific position in the coal bed. Although the average exinite content is not high on the whole, it does significantly contribute to the total hydrocarbon generation. The exinite content has been underestimated, especially the amorphous bituminous fluid and its importance is emphasized here. The reason is that the fluid flows easily into fusinite which has strong rigidity, or flows into some fissures, where it is commonly neglected.

Impact Estimation and Filtering of Disturbances in FG5 Absolute Gravimeter Observations

Instrumental and environmental disturbances do affect FG5 absolute gravimeter observations and the estimated gravity values, sometimes to the degree that entire measurement campaigns are discarded. We propose a method which moves towards the re-assessment of previously discarded observations. Once an estimate of the frequency and amplitude of a disturbance in a FG5 data set exists, the proposed method can estimate its impact on the estimated gravity value. This is performed through a Gaussian Bell Summation approach of the functional relationship between disturbance frequency and standard deviation of gravity. The filtering of the identified disturbance is realized through a modification of the functional model of the equation of motion in the least squares adjustment of FG5 observations. The results reveal that the Gaussian Bell Summation approximates the frequency—gravity impact relationship sufficiently well with negligible uncertainties, while the accuracy of the detected disturbance frequency defines a limiting factor for the gravity impact estimation. A realistic disturbance of 15 Hz with an amplitude of 1.5 nm had an impact of ≈48 [μGal] on the gravity estimate. The proposed filter approach reduced the impact to ≈12 [μGal], with the remaining effect being almost entirely associated to the uncertainty in disturbance frequency detection.

Reduced Order Machine Learning Finite Element Methods:Concept,Implementation,and Future Applications Dedicated to Professor Karl Stark Pister for his 95th birthday

This paper presents the concept of reduced order machine learning finite element(FE)method.In particular,we propose an example of such method,the proper generalized decomposition(PGD)reduced hierarchical deeplearning neural networks(HiDeNN),called HiDeNN-PGD.We described first the HiDeNN interface seamlessly with the current commercial and open source FE codes.The proposed reduced order method can reduce significantly the degrees of freedom for machine learning and physics based modeling and is able to deal with high dimensional problems.This method is found more accurate than conventional finite element methods with a small portion of degrees of freedom.Different potential applications of the method,including topology optimization,multi-scale and multi-physics material modeling,and additive manufacturing,will be discussed in the paper.

Computational aesthetics and applications

Computational aesthetics,which bridges science and art,is emerging as a new interdisciplinary field.This paper concentrates on two main aspects of computational aesthetics:aesthetic measurement and quantification,generative art,and then proposes a design generation framework.On aesthetic measurement and quantification,we review different types of features used in measurement,the currently used evaluation methods,and their applications.On generative art,we focus on both fractal art and abstract paintings modeled on well-known artists’styles.In general,computational aesthetics exploits computational methods for aesthetic expressions.In other words,it enables computer to appraise beauty and ugliness and also automatically generate aesthetic images.Computational aesthetics has been widely applied to many areas,such as photography,fine art,Chinese hand-writing,web design,graphic design,and industrial design.We finally propose a design generation methodology,utilizing techniques from both aesthetic measurements and generative art.

Emerging properties of non-crystalline phases of graphene and boron nitride based materials

We review recent developments on the synthesis and properties of two-dimensional materials which, although being mainly of an sp^(2) bonding character, exhibit highly disordered, non-uniform and structurally random morphologies. The emergence of such class of amorphous materials, including amorphous graphene and boron nitride, have shown superior properties compared to their crystalline counterparts when used as interfacial films. In this paper we discuss their structural,vibrational and electronic properties and present a perspective of their use for electronic applications.

Surface-ligand effect on radiosensitization of ultrasmall luminescent gold nanoparticles

Gold nanoparticles(AuNPs)could serve as pot ential radiother apy sensitizers because of their exceptional biocompatibility and high.Z material nature;however,since in vitro and in vivo behaviors of AuNPs are determined not only by their particle size but also by their surface chemistries,whether surface ligands can affect their radiosensitization has seldom been investi-gated in the radiosensitization of AuNPs.By conducting head-to-head comparison on radio-sensitization of two kinds of ultrasmall(~2 nm)near-infrared(NIR)emitting AuNPs that are coated with zwitterionic glutathione and neutr al polyethylene glyol(PEG)ligands,respectively,we found that zwitterionic glut athione coated AuNPs(GS-AuNPs)can reduce survival rates of MCF-7 cells under irr adiation of clinically used megavoltage photon beam at low dosage of~2.25 Gy.On the other hand,PEG-AuNPs can serve as a radiation-protecting agent and enabled MCF-7 cells more resistant to the irradiation,clearly indicating the key role of surface cheistry in radiosensitization of AuNPs.More detailed studies suggested that such difference was inde-pendent of cellular uptake and its eficiency,but might be related to the ligand-induced difference in photoelectron generation and/or inter actions between AuNPs and X-ray triggered reactive oxygen species(ROS).

Size-refinement enhanced flexibility and electrochemical performance of MXene electrodes for flexible waterproof supercapacitors

Increasing mechanical flexibility without sacrificing electrochemical performance of the electrode material is highly desired in the design of flexible electrochemical energy storage devices.In metal-related materials science,decreasing the grain size introduces more grain boundaries;this stops dislocations and crack propagation under deformation,and results in increased strength and toughness.However,such a size refinement effect has not been considered in the mechanical properties,particle stacking,wetting,and electrochemical performances of flexible supercapacitor electrodes.In this paper,MXene was used as an electrode material to study the size refinement effect of flexible supercapacitors.Size refinement improved the strength and toughness of the MXene electrodes,and this resulted in increased flexibility.Finite elemental analysis provided a theoretical understanding of size refinement-increased flexibility.Moreover,the size refinement also improved the specific surface area,electric conductance,ion transportation,and water wetting properties of the electrode,and the size refinement provided highly increased energy density and power density of the MXene supercapacitors.A highly flexible,water-proof supercapacitor was fabricated using size-refined MXene.The current study provides a new viewpoint for designing tough and flexible energy storage electrodes.The size refinement effect may also be applicable for metal ion batteries and electronic and photo devices composed of MXene and other nanoparticles.

New Horizon in stabilization of single atoms on metal-oxide supports for CO_(2) reduction

Elecrochemical CO_(2) reduction is a promising route to convert CO_(2) into the value added chemicals,and to control the increasing accumulation of 002 in the atmosphere.The CO_(2) molecule is stable and chemically inert,so a highly efficient electrocatalyst is required for CO_(2) reduction.The single atoms with metal oxdde support is a new fronder in CO_(2) reduction.The supported single atoms contain disperse isolated atoms with an appropriate support maxcimize the atom efficiency of metals for boosting the catalytc perfomance.In this review,we had discussed state-of-the-art research on the synthestis of single atoms supported on the metal oxdde for boosting catalytic activity for CO_(2) reduction and special emphasis is placed on the influence of single atoms supported on metal oxdde on the CO_(2) reduction.Futhermore,we had discussed the challenges,and opportunities for paving the development of single atoms with metal support and their application in ecrocatalytic CO_(2) reduction.

Graphene Bridge Heterostructure Devices for Negative Differential Transconductance Circuit Applications

Two-dimensional van der Waals(2D vdW)material-based heterostructure devices have been widely studied for high-end electronic applications owing to their heterojunction properties.In this study,we demonstrate graphene(Gr)-bridge heterostructure devices consisting of laterally series-connected ambipolar semiconductor/Gr-bridge/n-type molybdenum disulfide as a channel material for field-effect transistors(FET).Unlike conventional FET operation,our Gr-bridge devices exhibit nonclassical transfer characteristics(humped transfer curve),thus possessing a negative differential transconductance.These phenomena are interpreted as the operating behavior in two series-connected FETs,and they result from the gate-tunable contact capacity of the Gr-bridge layer.Multi-value logic inverters and frequency tripler circuits are successfully demonstrated using ambipolar semiconductors with narrow-and wide-bandgap materials as more advanced circuit applications based on non-classical transfer characteristics.Thus,we believe that our innovative and straightforward device structure engineering will be a promising technique for future multi-functional circuit applications of 2D nanoelectronics.

利用近似解加速求解SAT问题的启发式完全算法

结合DPLL完全算法能够证明可满足性(SAT)问题的不可满足性和局部搜索算法快速的优点,提出利用近似解加速求解SAT问题的启发式完全算法.首先利用局部搜索算法快速地得到一个近似解,并将该近似解作为完全算法的初始输入,用于其中分支变量的相位决策.该算法引导完全算法优先搜索近似解所在的子空间,加速解决器找到可满足解的过程,为SAT问题的求解提供了一种新的有效途径.实验结果表明,该算法有效地提高了决策的精度和SAT解决器的效率,对很多实例非常有效.

On Differential Equations of Integrable Billiard Tables

We introduce a method to find differential equations for functions which define tables,such that associated billiard systems admit a local first integral.We illustrate this method in three situations:the case of(locally)integrable wire billiards,for finding surfaces in R^(3)with a first integral of degree one in velocities,and for finding a piece-wise smooth surface in R^(3)homeomorphic to a torus,being a table of a billiard admitting two additional first integrals.

Parallel machine covering with limited number of preemptions

In this paper, we investigate the/-preemptive scheduling on parallel machines to maximize the minimum machine completion time, i.e., machine covering problem with limited number of preemptions. It is aimed to obtain the worst case ratio of the objective value of the optimal schedule with unlimited preemptions and that of the schedule allowed to be preempted at most i times. For the m identical machines case, we show the worst case ratio is 2m-i-1/m and we present a polynomial time algorithm which can guarantee the ratio for any 0 〈 i 〈2 m - 1. For the /-preemptive scheduling on two uniform machines case, we only need to consider the cases of i = 0 and i = 1. For both cases, we present two linear time algorithms and obtain the worst case ratios with respect to s, i.e., the ratio of the speeds of two machines.

D-Type Anti-Ferromagnetic Ground State in Ca_2Mn_2O_5

We study the electronic and magnetic properties of an oxygen-deficient perovskite Ca2Mn2O5 based on the first principle calculations. The calculations show that the ground state of Ca2Mn2O5 is a D-type anti-ferromagnetic structure with the anti-ferromagnetic spin coupling along the c-direction. The corresponding electronic structure of the D-type state is investigated, and the results display that Ca2Mn2O5 is an insulator with an indirect energy gap of -2.08eV. By the partiM density-of-state analysis, the valence band maximum is mainly contributed to by the 0-213 orbitMs and the conduction band minimum is contributed to by the 0-213 and Mn-3d orbitals. Due to the Coulomb repulsion interaction between electrons, the density of state of Mn-3d is pulled to -6--4.5eV.

Visual order of Chinese ink paintings

Visual order is one of the key factors influencing the aesthetic judgment of artworks.This paper reports the results of evaluating the influence of extracted features on visual order in Chinese ink paintings,using a regression model.We use nine contemporary artists’paintings as examples and extract features related to the visual order of their paintings.A questionnaire survey is conducted to collect people’s rating scores on the visual order.Via regression modeling,our research analyzes the significance of each feature and validates the influences of the features on the visual order.

Some One Parameter Models for Continuous Random Variables Defined on the Interval [0, 1]

The Beta Distribution is almost exclusively used for situations, after range normalization, wherein a continuous random variable is defined on the closed range [0, 1]. Since the beta distribution is intrinsically a two parameter distribution, this creates problems in some applications where specification of more than one parameter is difficult. In this note, two new classes of single parameter continuous probability distributions on a closed interval are introduced. These distributions remove some of the theoretical and practical problems of using the Beta Distribution for applications. The Burr Type XI Distribution has desirable characteristics for many applications especially when there is ambiguity in the definition of the specified parameter.

Multi-Task Learning for Semantic Relatedness and Textual Entailment

Recently, several deep learning models have been successfully proposed and have been applied to solve different Natural Language Processing (NLP) tasks. However, these models solve the problem based on single-task supervised learning and do not consider the correlation between the tasks. Based on this observation, in this paper, we implemented a multi-task learning model to joint learn two related NLP tasks simultaneously and conducted experiments to evaluate if learning these tasks jointly can improve the system performance compared with learning them individually. In addition, a comparison of our model with the state-of-the-art learning models, including multi-task learning, transfer learning, unsupervised learning and feature based traditional machine learning models is presented. This paper aims to 1) show the advantage of multi-task learning over single-task learning in training related NLP tasks, 2) illustrate the influence of various encoding structures to the proposed single- and multi-task learning models, and 3) compare the performance between multi-task learning and other learning models in literature on textual entailment task and semantic relatedness task.