Classification of scoliotic deformities from external surface of the trunk by using support vector machines

Scoliosis -- Analysis of internal spinal deformity -- Analysis of external trunk deformity -- Scoliosis assessment -- Machine learning in scoliosis research -- Limitations of Jaremko's approach and another direction -- Research question -- Methods -- Raw data acquisition -- Surface fitting -- Data normalization -- Principal component analysis -- Support vector machine -- Training and testing criteria -- Parameter tuning -- Data sets -- Benchmark test -- Surface fitting resuts -- PCA results -- Parameter tuning results -- Classification results -- Results analysis -- Investigative study : the ensemble of SVMs -- Constructing the ensemble of SVMs -- A futher improvement -- Performance evaluation

First-principles study of adsorption of methanethiol on Co(0001)

Investigation of the resident site and the adsorption phase structure of thiolates is of fundamental importance for understanding the formation of self-assembled organic monolayers on metal substrate surfaces. In the present study, we have investigated adsorption of methanethiol, CH3SH, on the ferromagnetic Co (0001) surface using density functional theory calculations.We find that the dissociative adsorption of CH3SH forming an adsorbed methylthiolate (CH3S) and an adsorbed H atom is energetically favorable, and that the CH3S molecule adsorbed at the threefold fcc and hcp hollow sites is most stable. The adsorption energy at the bridge site is only ~ 0.2 eV smaller than that at the threefold hollow site, and the adsorption of CH3S at the atop site is unstable. For the (√3 × √3)R30°, (2 × 2) and (2 × 3) adsorptions, we find that the S-C bond tends to be normal to the surface, whereas for the s231d adsorption it tilts away from the surface normal direction by ~ 40°. The (2 × 1) adsorption phase is much less stable. The reduction of the adsorption energy with the increasing coverage is attributed to the repulsive interaction between the adsorbates. Our calculations show that the (√3 × √3)R30° structure may form in the process of methylthiolate adsorption on Co (0001) due to its adsorption energy being only 0.1 eV lower than that for the (2 × 2) and (2 × 3) structures. We find that there is a charge transfer from the substrate surface atoms to the S atoms, and that the S-Co bond is strongly polar. The surface Co atoms bound to S have a magnetic moment of ~ 1.66μB, while the surface Co atoms unbound to S have a larger magnetic moment of ~ 1.85μB. The S atom in the adsorbed CH3S acquires a magnetic moment of ~0.08 μB

Boosting on Manifolds: Adaptive Regularization of Base Classifiers

In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the data into base classifier design and selection. On the other hand, we use ADABOOST's efficient learning mechanism to significantly improve supervised and semi-supervised algorithms proposed in the context of manifold learning. Beside the specific manifold-based penalization, the resulting algorithm also accommodates the boosting of a large family of regularized learning algorithms

First-Principles Study of Mo Segregation in MoNi(111): Effects of Chemisorbed Atomic Oxygen

Segregation at metal alloy surfaces is an important issue because many electrochemical and catalytic properties are directly correlated to the surface composition. We have performed density functional theory calculations for Mo segregation in MoNi(111) in the presence of chemisorbed atomic oxygen. In particular, the coverage dependence and possible adsorption-induced segregation phenomena are addressed by investigating segregation energies of the Mo atom in MoNi(111). The theoretical calculated results show that the Mo atom prefers to be embedded in the bulk for the clean MoNi(111), while it segregates to the top-most layer when the oxygen coverage is thicker than 1/9 monolayer (ML). Furthermore, we analyze the densities of states for the clean and oxygen-chemisorbed MoNi(111), and see a strong covalent bonding between Mo d-band states and O p-states. The present study provides valuable insight for exploring practical applications of Ni-based alloys as hydrogen evolution electrodes

Correction: First-Principles Study of Mo Segregation in MoNi(111): Effects of Chemisorbed Atomic Oxygen. Materials 2016, 9, 5

The authors wish to make the following corrections to this manuscript [1].[...

Small molecules for fat combustion: targeting obesity

Obesity is increasing in an alarming rate worldwide, which causes higher risks of some diseases, such as type 2 diabetes, cardiovascular diseases, and cancer. Current therapeutic approaches, either pancreatic lipase inhibitors or appetite suppressors, are generally of limited effectiveness. Brown adipose tissue (BAT) and beige cells dissipate fatty acids as heat to maintain body temperature, termed non-shivering thermogenesis; the activity and mass of BAT and beige cells are negatively correlated with overweight and obesity. The existence of BAT and beige cells in human adults provides an effective weight reduction therapy, a process likely to be amenable to pharmacological intervention. Herein, we combed through the physiology of thermogenesis and the role of BAT and beige cells in combating with obesity. We summarized the thermogenic regulators identified in the past decades, targeting G protein-coupled receptors, transient receptor potential channels, nuclear receptors and miscellaneous pathways. Advances in clinical trials were also presented. The main purpose of this review is to provide a comprehensive and up-to-date knowledge from the biological importance of thermogenesis in energy homeostasis to the representative thermogenic regulators for treating obesity. Thermogenic regulators might have a large potential for further investigations to be developed as lead compounds in fighting obesity. KEY WORDS: Thermogenesis, Brown adipose tissue, Beige cells, Obesity, Uncoupling protein

The interface electronic structure of thiol terminated molecules on cobalt and gold surfaces

The bonding strength and interfacial electronic properties of biphenyldimethyldithiol (HS– CH2–C6H4–C6H4–CH2–SH) adsorbed on Au(111) and polycrystalline cobalt are identified from combined photoemission and inverse photoemission. In order to develop a better understanding of the thiol functional group to metal surface interaction, the stable orientation, bonding site, bonding strength and interfacial electronic properties of methylthiol (S–CH3) adsorbed on Au(111) and Co(0001) have been determined by ab initio density functional calculations. Both experiment and theory suggest that thiol bonding to cobalt surfaces is stronger compared to gold surfaces. The transfer of charge toward the adsorbed sulfur is greater for the thiols on cobalt than on gold

Adsorption and Sensing Properties of Formaldehyde on Chemically Modified Graphene Surfaces

Chemically modifying graphene (such as chemical doping) is a commonly used method to improve its formaldehyde sensing properties, but the microscopic mechanisms of heteroatoms in the adsorption and sensing process are still unclear. In this paper, the adsorption and sensing properties of formaldehyde on graphene surfaces modified by X doping (X = B, N, O, P, S, Mg and Al) were systematically investigated by first-principles calculations. The adsorption geometries, adsorption energies, charge transfers, and electronic structures were obtained and analyzed. The adsorption strengths of HCHO molecule on the Mg- and Al-doped graphene surfaces were stronger than those of non-metal (B, N, O, P and S)-doped cases. These results showed that the Mg- or Al-doped graphene was better for HCHO detecting than the non-metal-doped graphene systems. The sensing properties were simulated by theNEGF method for the two-probe nano-sensors constructed from Al- and Mg-doped graphene. The maximum sensing responses of nano-sensors based on Al- and Mg-doped graphene were obtained to be 107% and 60%, respectively. The present study supplies a theoretical basis for designing superior graphene-based HCHO gas sensors