Explore the vast range of titles available.

The exponential distribution has always been prominent in various disciplines because of its wide range of applications. In this work, a generalization of the classical exponential distribution under a neutrosophic environment is scarcely presented. The mathematical properties of the neutrosophic exponential model are described in detail. The estimation of a neutrosophic parameter by the method of maximum likelihood is discussed and illustrated with examples. The suggested neutrosophic exponential distribution (NED) model involves the interval time it takes for certain particular events to occur. Thus, the proposed model may be the most widely used statistical distribution for the reliability problems. For conceptual understanding, a wide range of applications of the NED in reliability engineering is given, which indicates the circumstances under which the distribution is suitable. Furthermore, a simulation study has been conducted to assess the performance of the estimated neutrosophic parameter. Simulated results show that imprecise data with a larger sample size efficiently estimate the unknown neutrosophic parameter. Finally, a complex dataset on remission periods of cancer patients has been analyzed to identify the importance of the proposed model for real-world case studies.

Although numerous studies have explored the effects of various sounds on plants, a comparative understanding of how long-term exposure to low-intensity sound and rhythmic versus non-rhythmic sound impact on plants is still lacking. In this study, we conducted a field experiment to determine the growth, physiological responses, and allelopathic intensity of an invasive plant under prolonged exposure to different sound rhythms and intensities. The results showed that even at low intensity, long-term sound exposure inhibited the growth of while activating its defense mechanisms; these responses intensified with increasing sound intensity. However, the plant could not well distinguish between rhythmic and non-rhythmic sound treatments, although its allelopathic intensity also increased with sound intensity. This study extends the knowledge of plant response to acoustic stimuli, highlights the limited ability of plants to discriminate sound rhythms, and underestimates the negative impacts of prolonged low-intensity sound on plant performance. Therefore, the application of acoustic treatment techniques in future horticulture and agriculture requires a careful trade-off between their potential benefits and adverse effects on plants.

To suppress the swing of the payload, a kind of sling tray anti-swing device was designed, which reduced the length of the lifting rope to reduce the swing of payload. The kinematic equations of the payload were established under the condition of whether anti-swing device was provided, and the dynamic was carried out in Mat lab/Simulink environment. The swing of the payload under different rolling angles was analysed in a comparative manner. The results showed that the in-plane angle reduced 60% and out -plane angle reduced 55% of the payload in the case of the anti-swing device. The simulation results verified the effectiveness of the sling tray anti-swing device.

Platform owners need to manage its internal cash flow as investments on buyer side and on seller side. Investment on buyer side will increase using experiences and investment on seller side can create an atmosphere of innovation. It is much necessary to allocate and optimize the total investment on each side users so as to obtain maximal profit. A three-period game model is developed to find the optimal investment decision. And during the process, we find that platforms can be divided into four kinds as investment non-sensitive platform, Seller-sensitive platform, Buyer-sensitive platform, and Investment sensitive platform. It is also found that the platform system structure influences the distribution of total value on platform owner, buyer side, and seller side.

Uncovering the evolutionary dynamics of economies is helpful for us to design economic policy. This paper develops an economic evolution model by examining the coupled dynamics of industry growth and interindustry structure. For each industry, its economic properties (mainly characterized by price and quantity) are incorporated into the model. The input–output relationships among different industries are described as input–output networks, in which nodes represent industries, and weights represent technological and economic constraints between pairing industries. By measuring the dynamic importance of each node, we find that all the nodes in the input–output networks have the same dynamic importance. On the basis of this empirical regularity and the rational expectation assumption, we show that the coupled dynamics of the economic properties of nodes and input–output networks can explain the evolutionary dynamics of national economies.

Sustainable Development Goals (SDGs) are enforced by a set of instruments, among which environmental regulations, green innovation, and carbon taxes play a central part. This article aims to investigate the mitigation capacity of the above-mentioned elements using a sample of 15 European countries. This study takes CO2 and greenhouse gas emissions (GHG) into account to ensure the consistency and accuracy of the findings. Augmented Dickey–Fuller and CIPS unit root tests, Pesaran CD, Bias-corrected scaled LM are employed to check the cross-sectional dependence. The panel effect is tested using error correction-based modeling along with dynamic approaches, while the Granger causality technique employs country-related outcomes. The results show that innovation and environmental policies help in reducing emissions both in the long and the short run. In addition to this, carbon pricing mitigates emissions in the regions although its effect is more country-specific. We find evidence of both unidirectional and bidirectional causality among the variables. However, in a few cases, they are too a country-specific artifact. As a general conclusion, carbon pricing is an efficient short-run tool to achieve SDGs. At the same time, long-run sustainability relies on green innovation and environmental policy stringency in the region.

A new method and corresponding numerical procedure are introduced to estimate scaling exponents of power-law degree distribution and hierarchical clustering function for complex networks. This method can overcome the biased and inaccurate faults of graphical linear fitting methods commonly used in current network research. Furthermore, it is verified to have higher goodness-of-fit than graphical methods by comparing the KS (Kolmogorov-Smirnov) test statistics for 10 CNN (Connecting Nearest-Neighbor) networks.

Uncovering the evolutionary dynamics of economies is helpful for us to design economic policy. This paper develops an economic evolution model by examining the coupled dynamics of industry growth and interindustry structure. For each industry, its economic properties (mainly characterized by price and quantity) are incorporated into the model. The inputDSoutput relationships among different industries are described as inputDSoutput networks, in which nodes represent industries, and weights represent technological and economic constraints between pairing industries. By measuring the dynamic importance of each node, we find that all the nodes in the inputDSoutput networks have the same dynamic importance. On the basis of this empirical regularity and the rational expectation assumption, we show that the coupled dynamics of the economic properties of nodes and inputDSoutput networks can explain the evolutionary dynamics of national economies. Reprinted by permission of Springer

On-chip Brillouin laser gyroscopes harnessing opto-acoustic interaction are an emerging approach to detect rotation, due to their small footprint, excellent stability and low power consumption. However, previous implementations rely solely on optical readout, leaving the simultaneously generated saser (sound amplification by stimulated emission) undetected due to the lack of capability to access the acoustic output. Here, we propose a gyroscope based on saser detection using a suspension-free chip platform that supports low-loss confinement of both optical and acoustic modes. With experimental feasible parameter with optical and acoustic quality factors of 10^5 and 5000, respectively, sasers show significantly suppressed thermal and frequency noises, leading to gyroscope performance that outperforms its optical counterparts. We predict an angle random walk ~0.1 deg/sqrt(h) by saser gyroscope, while a conventional Brillouin laser gyroscope requires significantly higher pump power and optical quality factor to achieve comparable performance. Our work establishes the foundation for active phononic integrated circuits with Brillouin gain, opening avenues in inertial sensing, quantum transduction, and RF signal processing.

The integrated devices that generate structured optical fields with non-trivial orbital angular momentum (OAM) hold great potential for advanced optical applications, but are restricted to complex nanostructures and static functionalities. Here, we demonstrate a reconfigurable OAM beam generator from a simple microring resonator without requiring grating-like nanostructures. Our approach harnesses Brillouin interaction between confined phonon and optical modes, where the acoustic field is excited through microwave input. The phonon stimulate the conversion from a guided optical mode into a free-space vortex beam. Under the selection rule of the radiation, the OAM order of the emitted light is determined by the acousto-optic phase matching and is rapidly reconfigurable by simply tuning the microwave frequency. Furthermore, this all-microwave control scheme allows for the synthesis of arbitrary high-dimensional OAM superpositions by programming the amplitudes and phases of the driving fields. Analytical and numerical models predict a radiation efficiency over 25\\% for experimentally feasible on-chip microcavities. This work introduces a novel paradigm for chip-to-free-space interfaces, replacing fixed nanophotonic structures with programmable acousto-optic interactions for versatile structured light generation.