Sign-based Stochastic Gradient Descents (Sign-based SGDs) use the signs of the stochastic gradients for communication costs reduction. Nevertheless, current convergence results of sign-based SGDs ...applied to the finite sum optimization are established on the bounded assumption of the gradient, which fails to hold in various cases. This paper presents a convergence framework about sign-based SGDs with the elimination of the bounded gradient assumption. The ergodic convergence rates are provided only with the smooth assumption of the objective functions. The Sign Stochastic Gradient Descent (signSGD) and its two variants, including majority vote and zeroth-order version, are developed for different application settings. Our framework also removes the bounded gradient assumption used in the previous analysis of these three algorithms.
Carbon dioxide emissions (CO
2
es) are presently a hot topic of worldwide concern. It is of great significance for lessening CO
2
es to wholly understand the transformation pattern of CO
2
es among ...countries, industries, and the main factors (i.e., emission effect, energy intensity, economic development, population size, carbon per unit of land, land per capita, and environmental impact per capita effects) influencing CO
2
es. Thus, to mitigate the country’s CO
2
es efficiently, it is necessary to determine the driving factors of its emissions and damage variations. For this, we use the logarithmic mean Divisia index method. This research decomposes the major two dimensions, such as carbon sources and carbon damage variations from 1986 to 2020, into eight factors. The results show that Pakistan’s CO
2
es increased continuously during the period, with an average annual growth rate of 4.76%. Growing the country’s CO
2
es over 1986–2020, the key influencing factors are economic development, population, and land, while energy intensity and emission factors are the main forces in mitigating CO
2
es. The carbon source and carbon damage dimensions reached 68.75 Mt and 208.56 Mt, respectively, which led to a rise in CO
2
e. The entire set of factors is averagely moving around the major outcomes that provide significant policy measures. Finally, to efficiently reduce CO
2
e, Pakistan should concentrate on specific industrial paths and implement challenging, comprehensive governance to attain a low-carbon chain throughout the process. Thus, based on empirical results, this research put forward policy suggestions for cleaner production to reduce CO
2
emissions further, and environmental policies must be tailored to local conditions.
construction of the Schottky-junction is considered to be a valid route to boost the spatial charge separation and transfer of the photocatalytic system. Herein, two-dimensional (2D) O-doped g-C3N4 ...nanosheets were prepared by an annealing route, and then a 2D/2D Ti3C2 MXene/O-doped g-C3N4 Schottky-junction was fabricated using an in-situ electrostatic assembly of negatively charged Ti3C2 MXene and positively charged O-doped g-C3N4 nanosheets. The as-prepared Ti3C2 MXene/O-doped g-C3N4 Schottky-junction exhibited almost two times enhanced hydrogen evolution (25124 μmol/g/h) in comparison to pristine O-doped g-C3N4 (13745 μmol/g/h) and Ti3C2 MXene/pristine C3N4 (15573 μmol/g/h). Based on fully characterizations and theory calculation, the enhanced photocatalytic performance could be attributed to the synergy effect of intimate 2D/2D interfacial contact and the construction of Schottky-junction, which result in the short charge transport distance from HCN to Ti3C2 MXene and efficient separation of the photo-generated charge. This study will provide new insight into developing 2D/2D Schottky-junction photocatalysts for the solution of the energy crisis.
Angle-resolved XPS combined with argon ion etching was used to characterize the surface functional groups and the chemical structure of Ti3C2Tx MXene. Survey scanning obtained on the sample surface ...showed that the sample mainly contains C, O, Ti and F elements, and a little Al element. Analyzing the angle-resolved narrow scanning of these elements indicated that a layer of C and O atoms was adsorbed on the top surface of the sample, and there were many O or F related Ti bonds except Ti–C bond. XPS results obtained after argon ion etching indicated staggered distribution between C–Ti–C bond and O–Ti–C, F–Ti bond. It is confirmed that Ti atoms and C atoms were at the center layer of Ti3C2Tx MXene, while O atoms and F atoms were located at both the upper and lower surface of Ti3C2 layer acting as surface functional groups. The surface functional groups on the Ti3C2 layer were determined to include O2−, OH−, F− and O−–F−, among which F atoms could also desorb from Ti3C2Tx MXene easily. The schematic atomic structure of Ti3C2Tx MXene was derived from the analysis of XPS results, being consistent with theoretical chemical structure and other experimental reports. The results showed that angle-resolved XPS combing with argon ion etching is a good way to analysis 2D thin layer materials.
Behaving efficiently and flexibly is crucial for biological and artificial embodied agents. Behavior is generally classified into two types: habitual (fast but inflexible), and goal-directed ...(flexible but slow). While these two types of behaviors are typically considered to be managed by two distinct systems in the brain, recent studies have revealed a more sophisticated interplay between them. We introduce a theoretical framework using variational Bayesian theory, incorporating a Bayesian intention variable. Habitual behavior depends on the prior distribution of intention, computed from sensory context without goal-specification. In contrast, goal-directed behavior relies on the goal-conditioned posterior distribution of intention, inferred through variational free energy minimization. Assuming that an agent behaves using a synergized intention, our simulations in vision-based sensorimotor tasks explain the key properties of their interaction as observed in experiments. Our work suggests a fresh perspective on the neural mechanisms of habits and goals, shedding light on future research in decision making.
This paper presents a multi-algorithm fusion model (StackingGroup) based on the Stacking ensemble learning framework to address the variable selection problem in high-dimensional group structure ...data. The proposed algorithm takes into account the differences in data observation and training principles of different algorithms. It leverages the strengths of each model and incorporates Stacking ensemble learning with multiple group structure regularization methods. The main approach involves dividing the data set into K parts on average, using more than 10 algorithms as basic learning models, and selecting the base learner based on low correlation, strong prediction ability, and small model error. Finally, we selected the grSubset + grLasso, grLasso, and grSCAD algorithms as the base learners for the Stacking algorithm. The Lasso algorithm was used as the meta-learner to create a comprehensive algorithm called StackingGroup. This algorithm is designed to handle high-dimensional group structure data. Simulation experiments showed that the proposed method outperformed other R2, RMSE, and MAE prediction methods. Lastly, we applied the proposed algorithm to investigate the risk factors of low birth weight in infants and young children. The final results demonstrate that the proposed method achieves a mean absolute error (MAE) of 0.508 and a root mean square error (RMSE) of 0.668. The obtained values are smaller compared to those obtained from a single model, indicating that the proposed method surpasses other algorithms in terms of prediction accuracy.
We used the Laplace transform method to investigate the time periodic pulse electroosmotic flow (EOF) of linear viscoelastic fluids through a circular microchannel driven by pulse. Among them, the ...viscoelastic fluids and pulse are described by Jeffrey fluids and rectangle pulse, respectively. In addition, we focus on the depletion effect caused by the interaction of Jeffrey fluids macro-molecules with the channel surface. The overall flow is divided into two layers: the depletion layer (noted as layer I) and the bulk flow outside the depletion layer (noted as layer II). And the velocity expressions of the above two layers are obtained by calculation respectively. The research results show that for any pulse width
ā
, the velocity in different layers will tend to a steady state with time. The larger the pulse width
ā
, the longer it takes to reach a steady state. In the layer II, longer retardation time
λ
¯
2
will result in the fluid taking a short time from a static state to a flowing state. The time required for the fluid in layer II to reach the flowing state is longer than that in layer I. Increasing the density ratio
ρ
and viscosity ratio
γ
will lead to the velocity amplitude to decrease. The effect of these two parameters on the velocity amplitude will gradually weaken with the passage of time. The above conclusions have certain theoretical guiding significance for the transportation of biological fluids in microfluidic systems driven by pulses.
Natural frequencies of structures are usually convenient to acquire with a high precision in engineering. However, it is still difficult and faces challenges to apply the frequencies in the area of ...structural health monitoring. One of the main reasons is the natural frequency’s sensitivity to the variation of environmental conditions, such as temperature, which often disturbs the frequency based identification and even results in the false evaluation of the structural health condition. To overcome this problem, a novel frequency-based co-integration technique is proposed in this paper. The main principle is that the non-stationarity of the acquired frequencies caused by the variation of environmental temperature, can be transformed to stationary sequence by linear combining two non-stationary frequencies using the co-integration algorithm. The calculated stationary relationship between two frequencies series is insensitive to the influence of environmental variation, and can be employed to detect structural damage. In the study, ADF (Augmented Dickey-Fuller) test and EG (Engle-Granger) test are first introduced to check the non-stationary order and calculate the co-integration coefficients of the frequency series. Subsequently, the theoretical derivation of frequency co-integration based technique is developed using a simply supported beam as an example, and the procedure of damage detection based on frequency co-integration technique under the influence of environmental temperature is introduced in detail. At last, the validity and robustness of the proposed method are illustrated and verified through a numerical simulation of a steel truss bridge and a real cable-stayed bridge under the influence of changing environmental temperature. Both the numerical simulation and the practical application demonstrate that the proposed frequency co-integration technique can effectively eliminate the influence of the changing environmental temperature and identify the structural damage accurately.
The configuration of user-side energy storage can effectively alleviate the timing mismatch between distributed photovoltaic output and load power demand, and use the industrial user electricity ...price mechanism to earn revenue from peak shaving and valley filling. The configuration of photovoltaic & energy storage capacity and the charging and discharging strategy of energy storage can affect the economic benefits of users. This paper considers the annual comprehensive cost of the user to install the photovoltaic energy storage system and the user’s daily electricity bill to establish a bi-level optimization model. The outer model optimizes the photovoltaic & energy storage capacity, and the inner model optimizes the operation strategy of the energy storage. And calculate the actual life of the energy storage through the rain flow counting method. Use the fmincon function in the optimization toolbox to solve the problem on the matlab platform. The result of the calculation example verifies the improvement effect of the bi-level optimization model proposed in this paper on user economy.
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