Differential diagnosis of attention deficit and conduct disorders using conditional probabilities.

Attention deficit and conduct disorders require an important yet often difficult differential diagnosis. Prior efforts to determine which symptoms are optimal for making this differential diagnosis have been limited by a reliance on statistics that do not supply the probability of the disorders given a symptom's presence (positive predictive power) or the probability that the disorder is not present given the absence of the symptom (negative predictive power). This investigation examined the utility of these latter statistics in the differential diagnosis of childhood attention deficit and conduct disorders. The data consisted of symptoms from a standardized maternal psychiatric interview collected for a sample of 76 clinic-referred boys. Results indicated that some symptoms are optimal as inclusion criteria, some as exclusion criteria, some as neither, and some as both. Furthermore, some symptoms that have been traditionally associated with the diagnosis of one disorder were actually found to be more useful in the diagnosis of the other disorder. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Adherence clustering: an efficient method for mining market-basket clusters

We explore in this paper the efficient clustering of market-basket data. Different from those of the traditional data, the features of market-basket data are known to be of high dimensionality and sparsity. Without explicitly considering the presence of the taxonomy, most prior efforts on clustering market-basket data can be viewed as dealing with items in the leaf level of the taxonomy tree. Clustering transactions across different levels of the taxonomy is of great importance for marketing strategies as well as for the result representation of the clustering techniques for market-basket data. In view of the features of market-basket data, we devise in this paper a novel measurement, called the category-based adherence, and utilize this measurement to perform the clustering. With this category-based adherence measurement, we develop an efficient clustering algorithm, called algorithm k-todes, for market-basket data with the objective to minimize the category-based adherence. The distance of an item to a given cluster is defined as the number of links between this item and its nearest tode. The category-based adherence of a transaction to a cluster is then defined as the average distance of the items in this transaction to that cluster. A validation model based on information gain is also devised to assess the quality of clustering for market-basket data. As validated by both real and synthetic datasets, it is shown by our experimental results, with the taxonomy information, algorithm k-todes devised in this paper significantly outperforms the prior works in both the execution efficiency and the clustering quality as measured by information gain, indicating the usefulness of category-based adherence in market-basket data clustering.     

A D&T roundtable: challenges for low-power and high-performancechips

Microprocessor and other lC performance continues to improve at historic rates, with no visible end in sight for the next 10 years. However, we are starting to encounter a power wall. This is true for high-performance components as well as for low-power chips with a very limited energy budget offered by batteries. We need to find ways to manage power and energy consumption on all fronts-technology, design, and architecture-without compromising performance. Otherwise, we may face discontinuation of Moore's law for the semiconductor industry in the near future. This would be triggered not by any difficulty in the scaling of process technology but by formidable barriers posed by packaging and cooling, inefficacy of power delivery, and energy constraints dictated by battery technology, which is advancing at a very lukewarm pace     

Toward a comprehensive assessment of fundamental motivation: Factor structure of the Reiss Profiles.

Two instruments were developed to provide a comprehensive assessment of the strength of a person's fundamental end goals and motivational sensitivities. One instrument was a self-report inventory for adolescents and adults in general, and the other was an informant-rating scale for adolescents and adults with mental retardation and development disabilities. Exploratory and confirmatory factor analyses and test-retest reliabilities are reported in 7 studies, with independent samples of participants from diverse geographical areas, occupations, and social groups, N?=?2,548. Each instrument was found to have a 15-factor solution, and the 2 solutions were similar to one another. Because the factors assess universal motives that are also seen in animals, a genetics-behavior-cognitive model of fundamental motivation is suggested. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A general class of sliding surface for sliding mode control

In the conventional sliding mode control, the relative degree of the chosen sliding surface is usually one. This paper addresses a general class of sliding surface whose relative degree is no longer restricted to one. We show that when the relative degree is more than two, it is inevitable that there will exist a limit cycle for the nonlinear sign function. And for the case of relative degree two the system possesses poor phase margin. However, these disadvantages can be remedied remarkably by smoothing out the control nonlinearity in a suitable boundary layer with a saturation function that ensures asymptotic stability of the overall system     

Coefficients of dynamic friction and the mechanical melting mechanism for vinylidene chloride copolymers

Previous research and this research indicate that the mechanical melting for poly(vinylidene chloride) copolymers (PVDC) is complex. Mechanical melting is defined as the melting (or devitrification) of a polymer when a significant portion of the thermal energy originates from a mechanical energy dissipative process. PVDC mechanically melted on a moving metal surface at temperatures of the test instrument that were considerably lower than the differential scanning calorimetry (DSC) onset melting temperature. PVDC formulated with low levels of high density polyethylene (HDPE), however, melted at metal temperatures near the DSC onset melting temperature. Two different mechanical melting mechanisms are proposed to explan the data, and the frictional data are discussed with respect to solids conveying in a single-screw, plasticating extruder.     

Psychrotrophic violacein-producing bacteria isolated from Lake Winnipeg,Canada

Violet and purple bacterial pigmentations are uncommon when considering strict aerobes. Here we report discovery of two novel isolates, P102 and P117 from the freshwater Lake Winnipeg, each with violet to deep purple colony colouration. The relationship between pigment production and growth was investigated under different conditions, including a variety of carbon sources, pH, and temperatures. The violet compounds were purified using polar organic solvents, and then structurally characterized via mass spectrometry and nuclear magnetic resonance to be violacein and deoxyviolacein. Strain P117 produced higher concentrations of the darker pigment deoxyviolacein, which resulted in a deeper hue of violet than in cultures of P102. Strain P102, synthesized violacein maximally in liquid rich organic medium at pH 8 and 20 °C, and had 99.3% sequence similarity to the 16S rDNA from Janthinobacterium lividum. Strain P117, related to Massilia violaceinigra sharing 99.2% 16S rDNA sequence similarity, also produced violacein at similar optimal conditions, but developed higher concentrations of pigment at 15 °C. Culture-based methods found that violacein producers composed 0.001% or 0.023% CFU of environmental heterotrophic populations using BG-11 and potato-based media, respectively. Culture-independent high-throughput ribosomal 16S V4 sequencing of environmental DNA was used to detect Gram-negative species known for their production of violacein. Of all bacterial and archaeal sequences present during the fall in littoral waters and sediment of Lake Winnipeg, 5.5% and 6.3%, respectively, belonged to species that have similar pigment, demonstrating the scarcity of violacein producers in this aquatic freshwater system.     

浅谈纳米胶在密云水库输水工程中的应用

密云水库第九水厂输水隧洞为一圆形压力隧洞,安全鉴定发现洞身混凝土表面有较多裂缝,裂缝以环形或半环形为主,裂缝宽度一般在0.5mm以下,存在剥蚀、慢渗等情况.为保证隧洞输水安全和水厂正常供水,采用水利先进实用技术"纳米胶",对隧洞混凝土衬砌表层进行了防护和修复,达到很好的微细裂缝修补、抗渗和防护效果.     

A new spatial IP assignment method for IP-based wireless sensor networks

Wireless sensor networks (WSNs), one of the commercial wireless mesh networks (WMNs), are envisioned to provide an effective solution for sensor-based AmI (Ambient Intelligence) systems and applications. To enable the communications between AmI sensor networks and the most popular TCP/IP networks seamlessly, the best solution model is to run TCP/IP directly on WSNs (Mulligan et al. 2009; Hui and Culler 2008; Han and Mam 2007; Kim et al. 2007; Xiaohua et al. 2004; Dunkels et al. 2004; Dunkels et al. 2004; Dunkels 2001; Dunkels et al. 2004). In this case, an IP assignment method is required to assign each sensor node a unique IP address. SIPA (Dunkels et al. 2004) is the best known IP assignment method that uses spatial relations and locations of sensor nodes to assign their IP addresses. It has been applied in Contiki (Dunkels et al. 2004), a famous WSN operating system, to support the 6LowPAN protocol. In Chang et al. (2009), we proposed the SLIPA (Scan-Line IP Assignment) algorithm to improve the assignment success rate (ASR) obtained by SIPA. SLIPA can achieve a good ASR when sensor nodes are uniformly distributed. However, if sensor nodes are deployed by other distributions, the improvements would be limited. This paper proposes a new spatial IP assignment method, called SLIPA-Q (SLIPA with equal-quantity partition), to improve SLIPA. Experiments show that, by testing the proposed method 1,000 times with 1,000 randomly deployed sensor nodes, the average ASR obtained by SLIPA-Q is over two times of that obtained by SLIPA. Under the same 88% ASR, the average numbers of sensor nodes those can be successfully assigned by SLIPA-Q, SLIPA, and SIPA are 950, 850, and 135, respectively. Comparing to previous spatial IP assignment methods, SLIPA-Q can achieve dramatic improvements in ASR for assigning IP addresses to a large set of sensor nodes.     

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers.