Toward Collinearity-Avoidable Localization for Wireless Sensor Network

In accordance with the collinearity problem during computation caused by the beacon nodes used for location estimation which are close to be in the same line or same plane, two solutions are proposed in this paper: the geometric analytical localization algorithm based on positioning units and the localization algorithm based on the multivariate analysis method. The geometric analytical localization algorithm based on positioning units analyzes the topology quality of positioning units used to estimate location and provides quantitative criteria based on that; the localization algorithm based on the multivariate analysis method uses the multivariate analysis method to filter and integrate the beacon nodes coordinate matrixes during the process of location estimation. Both methods can avoid low estimation accuracy and instability caused by multicollinearity

Effects of diet and/or exercise in enhancing spinal cord sensorimotor learning.

Given that the spinal cord is capable of learning sensorimotor tasks and that dietary interventions can influence learning involving supraspinal centers, we asked whether the presence of omega-3 fatty acid docosahexaenoic acid (DHA) and the curry spice curcumin (Cur) by themselves or in combination with voluntary exercise could affect spinal cord learning in adult spinal mice. Using an instrumental learning paradigm to assess spinal learning we observed that mice fed a diet containing DHA/Cur performed better in the spinal learning paradigm than mice fed a diet deficient in DHA/Cur. The enhanced performance was accompanied by increases in the mRNA levels of molecular markers of learning, i.e., BDNF, CREB, CaMKII, and syntaxin 3. Concurrent exposure to exercise was complementary to the dietary treatment effects on spinal learning. The diet containing DHA/Cur resulted in higher levels of DHA and lower levels of omega-6 fatty acid arachidonic acid (AA) in the spinal cord than the diet deficient in DHA/Cur. The level of spinal learning was inversely related to the ratio of AA:DHA. These results emphasize the capacity of select dietary factors and exercise to foster spinal cord learning. Given the non-invasiveness and safety of the modulation of diet and exercise, these interventions should be considered in light of their potential to enhance relearning of sensorimotor tasks during rehabilitative training paradigms after a spinal cord injury

Breakdown of Three-dimensional Dirac Semimetal State in pressurized Cd3As2

We report the first observation of a pressure-induced breakdown of the 3D-DSM state in Cd3As2, evidenced by a series of in-situ high-pressure synchrotron X-ray diffraction (XRD) and single crystal transport measurements. We find that Cd3As2 undergoes a structural phase transition from a metallic tetragonal (T) phase in space group I41/acd to a semiconducting monoclinic (M) phase in space group P21/c at critical pressure 2.57 GPa, above this pressure, an activation energy gap appears, accompanied by distinct switches in Hall resistivity slope and electron mobility. These changes of crystal symmetry and corresponding transport properties manifest the breakdown of the 3D-DSM state in pressurized Cd3As2.Comment: 17 pages, 4 figure

Toward Understanding the Isomeric Stability of Fullerenes with Density Functional Theory and the Information-Theoretic Approach

For a given size of one fullerene molecule, there could exist many different isomers and their energy landscape is remarkably complex. To have a better understanding of the nature and origin of their isomeric stability, as a continuation of our previous endeavors, we systematically dissect the molecular stability of four fullerene systems, C44, C48, C52, and C60, with a total of 2547 structures, using density functional theory and the information-theoretic approach. The total energy decomposition analysis is beneficial to understand the origin and nature of isomeric stability. Our results showcase that the electrostatic potential is the dominant factor contributing to the isomeric stability of these fullerenes, and other contributions such as steric and quantum effects play minor but indispensable roles. This study also finds that the origin of the isomeric stability of these species is due to the spatial delocalization of the electron density. Our work should provide novel insights into the isomeric stability of fullerene molecules, which have found tremendous applications in solar-energy studies and nanomaterial sciences

Laboratory Evaluation and Field Application of a Gas-Soluble Plugging Agent: Development of Bottom Water Plugging Fracturing Technology

The currently reported bottom water sealing materials and fracturing technologies can hardly simultaneously achieve the high production and low water cut of gas reservoirs due to the complexity of various formation conditions. Therefore, without controlling the fracturing scale and injection volume, a kind of polylactide polymer water plugging material with a density of 1.15–2.0 g/cm3 is developed, which can be used to seal the bottom water of a gas–water differential layer by contact solidification with water and automatic degradation with natural gas. This technology can not only fully release the production capacity of the gas reservoir but also effectively control water production and realize the efficient fracturing development of the target gas reservoir. Laboratory test results show that the smart plugging agent has a bottom water plugging rate of 100%, and the low-density plugging agent has a dissolution rate of 96.7% in methane gas at 90 °C for 4 h and a dissolution rate of 97.6% in methane gas at 60 °C for 6 h, showing remarkable gas degradation performance. In addition, settlement experiments show that the presence of a proppant can increase the settlement rate of a plugging agent up to many times (up to 21 times) in both water and guanidine gum solution. According to the actual conditions of well J66-8-3, a single-well water plugging fracturing scheme was prepared by optimizing the length of fracture, plugging agent dosage, and plugging agent sinking time, and a post-evaluation method was proposed. It has guiding significance to the development of similar gas reservoirs

A Combined Model Incorporating Improved SSA and LSTM Algorithms for Short-Term Load Forecasting

To address the current difficulties and problems of short-term load forecasting (STLF), this paper proposes a combined forecasting method based on the improved sparrow search algorithm (ISSA), with fused Cauchy mutation and opposition-based learning (OBL), to optimize the hyperparameters of the long- and short-term-memory (LSTM) network. For the sparrow-search algorithm (SSA), a Sin-chaotic-initialization population, with an infinite number of mapping folds, is first used to lay the foundation for global search. Secondly, the previous-generation global-optimal solution is introduced in the discoverer-location update way, to improve the adequacy of the global search, while adaptive weights are added to reconcile the ability of the local exploitation and global search of the algorithm as well as to hasten the speed of convergence. Then, fusing the Cauchy mutation arithmetic and the OBL strategy, a perturbation mutation is performed at the optimal solution position to generate a new solution, which, in turn, strengthens the ability of the algorithm to get rid of the local space. After that, the ISSA-LSTM forecasting model is constructed, and the example is verified based on the power load data of a region, while the experimental comparison with various algorithms is conducted, and the results confirm the superiority of the ISSA-LSTM model

A Combined Model Incorporating Improved SSA and LSTM Algorithms for Short-Term Load Forecasting

To address the current difficulties and problems of short-term load forecasting (STLF), this paper proposes a combined forecasting method based on the improved sparrow search algorithm (ISSA), with fused Cauchy mutation and opposition-based learning (OBL), to optimize the hyperparameters of the long- and short-term-memory (LSTM) network. For the sparrow-search algorithm (SSA), a Sin-chaotic-initialization population, with an infinite number of mapping folds, is first used to lay the foundation for global search. Secondly, the previous-generation global-optimal solution is introduced in the discoverer-location update way, to improve the adequacy of the global search, while adaptive weights are added to reconcile the ability of the local exploitation and global search of the algorithm as well as to hasten the speed of convergence. Then, fusing the Cauchy mutation arithmetic and the OBL strategy, a perturbation mutation is performed at the optimal solution position to generate a new solution, which, in turn, strengthens the ability of the algorithm to get rid of the local space. After that, the ISSA-LSTM forecasting model is constructed, and the example is verified based on the power load data of a region, while the experimental comparison with various algorithms is conducted, and the results confirm the superiority of the ISSA-LSTM model

Laboratory Evaluation and Field Application of a Gas-Soluble Plugging Agent: Development of Bottom Water Plugging Fracturing Technology

The currently reported bottom water sealing materials and fracturing technologies can hardly simultaneously achieve the high production and low water cut of gas reservoirs due to the complexity of various formation conditions. Therefore, without controlling the fracturing scale and injection volume, a kind of polylactide polymer water plugging material with a density of 1.15–2.0 g/cm3 is developed, which can be used to seal the bottom water of a gas–water differential layer by contact solidification with water and automatic degradation with natural gas. This technology can not only fully release the production capacity of the gas reservoir but also effectively control water production and realize the efficient fracturing development of the target gas reservoir. Laboratory test results show that the smart plugging agent has a bottom water plugging rate of 100%, and the low-density plugging agent has a dissolution rate of 96.7% in methane gas at 90 °C for 4 h and a dissolution rate of 97.6% in methane gas at 60 °C for 6 h, showing remarkable gas degradation performance. In addition, settlement experiments show that the presence of a proppant can increase the settlement rate of a plugging agent up to many times (up to 21 times) in both water and guanidine gum solution. According to the actual conditions of well J66-8-3, a single-well water plugging fracturing scheme was prepared by optimizing the length of fracture, plugging agent dosage, and plugging agent sinking time, and a post-evaluation method was proposed. It has guiding significance to the development of similar gas reservoirs