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Since the celebrated work by Cartan, distributions with \nobreak{small} growth vector $(2,3,5)$ have been studied extensively. In the holomorphic setting, there is a natural correspondence between holomorphic $(2,3,5)$-distributions and nondegenerate lines on holomorphic contact manifolds of dimension 5. We generalize this correspondence to higher dimensions by studying nondegenerate lines on holomorphic contact manifolds and the corresponding class of distributions of small growth vector $(2m, 3m, 3m+2)$ for any positive integer $m$., Comment: To appear in Nagoya Mathematical Journal

Broiler chickens are traditionally weighed by steelyard or platform scale, which is time-consuming and labor-intensive. Broiler chickens usually exhibit stress-related behavior during weighing. The 3D camera-based weighing system for broiler chickens can only weigh the broiler chicken in the monitoring area. Usually, it makes poor weight prediction due to poor segmentation especially when the broiler chicken is flapping its wings. To solve these issues, we developed one simple and low-cost weighing system with high stability and accuracy. A validity value extraction method from dynamic weighing was proposed. Then, an improved amplitude-limiting filtering algorithm and a BP neural networks model were developed to avoid accidental interference. The BP neural networks model used daily weight gain, day-age, average velocity, and the weight data after filtering algorithm as the input layer. The weighing system was tested in a commercial Beijing Fatty Chickens house with Beijing Fatty Chickens. We tested thirteen groups of Beijing Fatty Chickens of different weights, from 500 g to 1800 g in intervals of 100 g, using the three different methods: no filtering algorithm or BP neural networks, only the improved amplitude-limiting filtering algorithm and a hybrid of the improved amplitude-limiting filtering algorithm and BP neural networks. The results showed that the hybrid algorithm had a better performance in minimizing the error, lowering from the original 6% down to 3%. The accurate weight data was transmitted to the remote service platform for further decision-making, such as activity analysis, feeding management, and health alerts.

Pasquier and Perrin discovered that the ${\rm G}_2$-horospherical manifold ${\bf X}$ of Picard number 1 can be realized as a smooth specialization of the rational homogeneous space parameterizing the lines on the 5-dimensional hyperquadric, in other words, it can be deformed nontrivially to the rational homogeneous space. We show that ${\bf X}$ is the only smooth projective variety with this property. This is obtained as a consequence of our main result that ${\bf X}$ can be recognized by its VMRT, namely, a Fano manifold of Picard number 1 is biregular to ${\bf X}$ if and only if its VMRT at a general point is projectively isomorphic to that of ${\bf X}$. We employ the method the authors developed to solve the corresponding problem for symplectic Grassmannians, which constructs a flat Cartan connection in a neighborhood of a general minimal rational curve. In adapting this method to ${\bf X}$, we need an intricate study of the positivity/negativity of vector bundles with respect to a family of rational curves, which is subtler than the case of symplectic Grassmannians because of the nature of the differential geometric structure on ${\bf X}$ arising from VMRT., Comment: To appear in Transformation Groups

This paper defines a logic model of optimization under uncertainty which optimizes the expectation of a uncertainty-perturbed objective function and subjects to a new type of constraints--the probabilistically robust constraints (PRC). This novel logic model is an alternative to, but more general than, the existing ones like the stochastic, robust, and chance-constrained models. The novelty mainly resides in the newly defined PRC which logically requires that an optimal solution should be feasible to high-probability realizations of the uncertain variables. Given that the existing methods of obtaining deterministic approximations are either inapplicable or inefficient to this new logic model, we propose a novel solution paradigm. First, the logic model is approximated by a data-driven deterministic program following an alpha-process of the input data (scenario) set. A sufficient condition on the relation between the accuracy of deterministic approximation and the needed number of input scenarios is provided. Second, the concept of strategic scenario selection (S^3) is developed to figure out a limited number of active scenarios as the input to the data-driven deterministic approximation. Three S^3 algorithms are designed for the cases of discrete, continuous, and mixed-integer uncertain variables respectively, which are not sensitive to the continuity of the decision variables. Numerical experiments showed that the S^3-based data-driven program can accurately approximate the new logic model with low computational complexity., Comment: 36 pages

The uncertainty of multiple power loads and renewable energy generations (PLREG) in power systems increases the complexity of power flow analysis for decision-makers. The chance-constrained method can be applied to model the optimization problems of power flow under uncertainty. This paper develops a novel solution approach for chance-constrained AC optimal power flow (CCACOPF) problem based on the data-driven convexification of power flow and a fast algorithm for scenario technique (FAST). This method is computationally effective for mainly two reasons. First, the original nonconvex AC power flow (ACPF) constraints are approximated by a set of learning-based quadratic convex ones. Second, FAST is an advanced scenario-based solution method (SSM) that doesn't rely on the pre-assumed probability distribution, using far less scenarios than the conventional SSM. Eventually, the CCACOPF is converted into a computationally tractable convex optimization problem. The simulation results on IEEE test cases indicate that 1) the proposed solution method can outperform the conventional SSM in computational efficiency, 2) the data-driven convexification of power flow is effective in approximating original complex AC power flow.

The anemometer tower cannot be well adapted to wind measurement needs due to its inherent limitations in areas with low wind speeds and complicated offshore terrain, but the advantages of sodar can well meet the prediction research of offshore wind power. In this paper, the results of measuring the wind speed and wind direction by the sodar and the anemometer tower are compared and analyzed while the specific power model is verified using the sodar measurement data. The test results show that the sodar can replace the anemometer tower to complete the preliminary work of power prediction in specific environments.

Framing camera is a powerful tool to investigate the ultrafast phenomena in chemical reaction process. Wavelength framing technique is one of the key technologies in the development of framing cameras. The wavelength resolution of the images generated by wavelength framing system determines the interval time of the wavelength framing camera, that is, the time resolution of the wavelength framing camera. In this paper, a wavelength framing system based on a diffractive optical element (DOE) and a band-pass filter (BPF) was set up. The wavelength characteristics of the wavelength framing system were simulated utilizing the theory of multi-beam interference. The central wavelength of each image got from the system, which varies with the position relationship between DOE and BPF, has been obtained. Experiments were carried out through imaging a target of 6 mm × 6 mm by using the wavelength framing system. The spectral characteristics of each image were also studied experimentally. The result we have got proves that the system we have generated can achieve 16-frame imaging, every image has different spectral properties. For the target with a size of 6 mm × 6 mm, the resolution of a single image got from the system is 610 × 610, and the central wavelength ranges from 784 nm to 814 nm. The average difference in central wavelength between adjacent images is 1.95 nm. If the dispersion of the incident pulse light source is 0.46 ps/nm, the time resolution of the system is 0.9 ps.

This paper presents a practical approach to utilizing emergency response resources (ERRs) and post-disaster available distributed energy resources (PDA-DERs) to improve the resilience of power distribution systems against natural disasters. The proposed approach consists of two sequential steps: first, the minimum amount of ERRs is determined in a pre-disaster planning model; second, a post-disaster restoration model is proposed to co-optimize the dispatch of pre-planned ERRs and PDA-DERs to minimize the impact of disasters on customers, i.e., unserved energy for the entire restoration window. Compared with existing restoration strategies using ERRs, the proposed approach is more tractable since 1) in the pre-disaster stage, the needed EERs are determined based on the prediction of energy shortage and disaster-induced damages using machine learning-based algorithms (i.e., cost-sensitive-RFQRF for prediction of outage customers, random forest for prediction of outage duration, and CART for prediction of disaster-induced damages); 2) in the post-disaster stage, the super-node approximation (SNA) and the convex hull relaxation (CHR) of distribution networks are introduced to achieve the best trade-off between computational burden and accuracy. Tests of the proposed approach on IEEE test feeders demonstrated that a combination of SNA and CHR remarkably reduces the solution time of the post-disaster restoration model., Comment: 8 pages, 7 figures!

Th1/Th2 imbalance to Th2 is of significance in the peripheral immune responses in Tuberculosis (TB) development. However, the mechanisms for Th1/Th2 imbalance are still not well determined. Notch signaling pathway is involved in the peripheral T cell activation and effector cell differentiation. However, whether it affects Th1/Th2 imbalance in TB patients is still not known. Here, we used γ-secretase inhibitor (DAPT) to treat the peripheral blood mononuclear cells (PBMCs) from healthy people or individuals with latent or active TB infection in vitro, respectively. Then, the Th1/Th2 ratios were determined by flow cytometry, and cytokines of IFN-γ, IL-4, IL-10 in the culture supernatant were measured by CBA method. The Notch signal pathway associated proteins Hes1, GATA3 and T-bet were quantitated by real-time PCR or immunoblotting. Our results showed that DAPT effectively inhibited the protein level of Hes1. In TB patients, the Th2 ratio increased in the PBMCs, alone with the high expression of GATA3 and IL-4, resulting in the high ratios of Th2/Th1 and GATA3/T-bet in TB patients. However, Th2 cells ratio decreased after blocking the Notch signaling pathway by DAPT and the Th2/Th1 ratio in TB patients were DAPT dose-dependent, accompanied by the decrease of IL-4 and GATA3. But, its influence on Th1 ratio and Th1 related T-bet and IFN-γ levels were not significant. In conclusion, our results suggest that blocking Notch signaling by DAPT could inhibit Th2 responses and restore Th1/Th2 imbalance in TB patients.

Graphene (Gr) has proved its significant role as a reinforcement material in improving the strength of metal matrix composites due to its excellent mechanical properties. In this paper, Gr/Cu composite film with a layered structure was prepared by layering electrodeposition. The directional distribution of Gr in the Cu film was insured by this method, which gives play to its ultra-high-strength in a two-dimensional plane. In the meantime, the effect of electrodeposition time on the distribution structure of the Gr layer was studied. The structure analysis and mechanical properties test show that the strength of the layered Gr/Cu composite film is greatly improved compared to the pure Cu film. Furthermore, the strength of the composite film increases at the beginning and then decreases with the electrodeposition time of the Gr layer increasing, while the coverage and the degree for the layer stacking of Gr gradually increase in this process. In conclusion, the influence of different Gr distributions on the mechanical properties of the composite film has been studied by combining the experimental results with molecular dynamics simulation, which lays an effective foundation for further optimizing the structure of Gr in the layered composite film and improving the mechanical properties.

This paper develops an ensemble learning-based linearization approach for power flow, which differs from the network-parameter based direct current (DC) power flow or other extended versions of linearization. As a novel data-driven linearization through data mining, it firstly applies the polynomial regression (PR) as a basic learner to capture the linear relationships between the bus voltage as the independent variable and the active or reactive power as the dependent variable in rectangular coordinates. Then, gradient boosting (GB) and bagging as ensemble learning methods are introduced to combine all basic learners to boost the model performance. The fitted linear power flow model is also relaxed to compute the optimal power flow (OPF). The simulating results of standard IEEE cases indicate that (1) ensemble learning methods outperform PR and GB works better than bagging; (2) as for solving OPF, the data-driven model excels the DC model and the SDP relaxation in the computational accuracy, and works faster than ACOPF and SDPOPF., Comment: 5 pages, 9 figures, 3 tables

This paper presents a novel scalable framework to solve the optimization of a nonlinear system with differential algebraic equation (DAE) constraints that enforce the asymptotic stability of the underlying dynamic model with respect to certain disturbances. Existing solution approaches to analogous DAE-constrained problems are based on discretization of DAE system into a large set of nonlinear algebraic equations representing the time-marching schemes. These approaches are not scalable to large size models. The proposed framework, based on LaSalle's invariance principle, uses convex Lyapunov functions to develop a novel stability certificate which consists of a limited number of algebraic constraints. We develop specific algorithms for two major types of nonlinearities, namely Lur'e, and quasi-polynomial systems. Quadratic and convex-sum-of-square Lyapunov functions are constructed for the Lur'e-type and quasi-polynomial systems respectively. A numerical experiment is performed on a 3-generator power network to obtain a solution for transient-stability-constrained optimal power flow., Comment: 10 pages, 7 figures

Let X be a connected family of complex Fano manifolds. We show that if some fiber is the product of two manifolds of lower dimensions, then so is every fiber. Combining with previous work of Hwang and Mok, this implies immediately that if a fiber is (possibly reducible) Hermitian symmetric space of compact type, then all fibers are isomorphic to the same variety., Comment: 5 pages. Comments are welcome

BACKGROUND: Central nervous system (CNS) tumor is the most common solid neoplasm in children. Here we report clinical features of children with CNS tumor treated in our institute during recent 11 years. METHODS: Retrospective study was conducted in children with CNS tumor treated in Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, during 2006 to 2017. Clinical data were collected. Statistical calculation was conduct for characteristic analyses. RESULTS: 1136 cases of CNS tumor in children were collected, with 712 males and 424 females. Age ranges were 9.33% in infants (< 1 y/o), 26.32% in toddler (1 - 3 y/o), 35.30% in preschool children (3 - 7 y/o), 27.11% in school-age children (7 - 15 y/o) and 1.94% in adolescence (> 15 y/o). 437 cases were diagnosed with WHO I-II grades and 392 cases were with WHO III-IV grades. There were 548 supratentorial tumors and 441 subtentorial tumors. The most common tumor type was medulloblastoma (n=168, 14.79%), followed by pilocytic astrocytoma (n=166, 14.61%). CONCLUSION: The gender ratios in different age ranges were stable, with high incidence in male than in female. In total, low grade tumors were more common than high grade tumors. Compare to our previous report, pilocytic astrocytoma was second most common tumor, following medulloblastoma.

Room-temperature self-powered/active humidity sensing has been realized from Sb-doped ZnO nanowire (NW) arrays by coupling their piezoelectric and gas sensing characteristics. The piezoelectric output of the device acts as both the power source and the response signal against relative humidity (RH). Upon exposure to 70% RH, the piezoelectric output of Sb-doped ZnO NWs decreases from 1.35 V (10% RH) to 0.22 V, and the response is 83.70 (much higher than that of undoped ZnO).

Thermosensitive poly[N-isopropylacrylamide(NIPAM)-co-N-acryloyl-L-phenylalanine ethyl ester (NALPE)] microgels were prepared by the free radical polymerization of NIPAM and chiral monomer, NALPE. Such microgels exhibited spherical shape and favorable monodispersity. Increasing the content of NALPE units would enhance the average diameter, but decrease the thermosensitivity and volume-phase transition temperatures of the microgels. Compared with PNIPAM microgels, the microgels containing NALPE units performed chiral recognozable capacities for D-phenylalanine and D-tartaric acid, and the enantioselectivity and adsorption capacity of the microgels improved with increasing the temperature and/or the content of NALPE units.

This paper introduces a micro-nexus of water and energy which can be considered as one of the physical infrastructures of the future building/city/village systems. For the electricity side, an alternating current (AC) power flow model integrated with battery energy storage and renewable generation is adopted. The nonlinear hydraulic characteristics in pipe networks is also considered in the proposed micro water-energy nexus (WEN) model. Integer variables are involved to represent the on/off state of pumps. Base on the proposed nexus model, a co-optimization framework of water and energy networks is developed. The overall co-optimization model is a mixed-integer nonlinear programming problem which is tested on a waterenergy nexus which consists of the IEEE 13-bus distribution system and a 8-node water distribution network. The simulation results demonstrate that the cost-efficiency of the co-optimization framework is higher than optimizing two systems independently., Comment: Submitted to IEEE Power & Energy Society 2018 General Meeting

It is promising that mobile relay nodes (MRNs), i.e., relays mounted on top of transportation vehicles, are deployed in future mobile communication systems in order to improve system performance. In this paper a multi-MRN aided multiuser system is studied. The system performance under direct transmission mode and MRN assisted transmission mode are compared with variable parameter of vehicle penetration loss (VPL). The mobile users are separated into two categories in which the direct transmission mode and the MRN assisted transmission mode are selected to transmit in downlink, respectively. A novel power allocation algorithm is proposed to increase the average system capacity under the constraint of total transmit power. The different power allocation schemes are applied for users in two categories to improve the system performance. It is demonstrated by simulation results that the proposed algorithm outperforms the average power allocation algorithm.

It is of interest for future mobile communication systems that mobile relay nodes (MRNs), i.e., relays mounted on top of transportation vehicles, are deployed in order to improve the system performance. A multi-MRN aided multiuser system is considered in this paper. The performance of the direct transmission mode and the MRN assisted transmission mode under different vehicle penetration loss (VPL) are compared. The users are separated into two categories in which the direct transmission mode and the MRN assisted transmission mode are selected to employ, respectively. A novel power allocation algorithm is proposed to improve the average system capacity under the constraint of total transmit power. The different power allocation schemes are applied for users in two categories to improve the system performance. It is demonstrated by simulation results that the proposed algorithm outperforms the average power allocation algorithm.