Supply chain management (SCM) has become an important management paradigm. As supply chain members are often separate and independent economic entities, a key issue in SCM is to develop mechanisms ...that can align their objectives and coordinate their activities so as to optimize system performance. In this paper, we provide a review of coordination mechanisms of supply chain systems in a framework that is based on supply chain decision structure and nature of demand. This framework highlights the behavioral aspects and information need in the coordination of a supply chain. The identification of these issues points out several directions of future research in this area.
Abstract
We analyze pre-explosion near- and mid-infrared (IR) imaging of the site of SN 2023ixf in the nearby spiral galaxy M101 and characterize the candidate progenitor star. The star displays ...compelling evidence of variability with a possible period of ≈1000 days and an amplitude of Δ
m
≈ 0.6 mag in extensive monitoring with the Spitzer Space Telescope since 2004, likely indicative of radial pulsations. Variability consistent with this period is also seen in the near-IR
J
and
K
s
bands between 2010 and 2023, up to just 10 days before the explosion. Beyond the periodic variability, we do not find evidence for any IR-bright pre-supernova outbursts in this time period. The IR brightness (
M
K
s
=
−
10.7
mag) and color (
J
−
K
s
= 1.6 mag) of the star suggest a luminous and dusty red supergiant. Modeling of the phase-averaged spectral energy distribution (SED) yields constraints on the stellar temperature (
T
eff
=
3500
−
1400
+
800
K) and luminosity (
log
L
/
L
⊙
=
5.1
±
0.2
). This places the candidate among the most luminous Type II supernova progenitors with direct imaging constraints, with the caveat that many of these rely only on optical measurements. Comparison with stellar evolution models gives an initial mass of
M
init
= 17 ± 4
M
⊙
. We estimate the pre-supernova mass-loss rate of the star between 3 and 19 yr before explosion from the SED modeling at
M
̇
≈
3
×
10
−
5
to 3 × 10
−4
M
⊙
yr
−1
for an assumed wind velocity of
v
w
= 10 km s
−1
, perhaps pointing to enhanced mass loss in a pulsation-driven wind.
Abstract Developing devices with a wide-temperature range persistent photoconductivity (PPC) and ultra-low power consumption remains a significant challenge for optical synaptic devices used in ...neuromorphic computing. By harnessing the PPC properties in materials, it can achieve optical storage and neuromorphic computing, surpassing the von Neuman architecture-based systems. However, previous research implemented PPC required additional gate voltages and low temperatures, which need additional energy consumption and PPC cannot be achieved across a wide temperature range. Here, we fabricated a simple heterojunctions using zinc(II)-meso-tetraphenyl porphyrin (ZnTPP) and single-walled carbon nanotubes (SWCNTs). By leveraging the strong binding energy at the heterojunction interface and the unique band structure, the heterojunction achieved PPC over an exceptionally wide temperature range (77 K-400 K). Remarkably, it demonstrated nonvolatile storage for up to 2×10 4 s, without additional gate voltage. The minimum energy consumption for each synaptic event is as low as 6.5 aJ. Furthermore, we successfully demonstrate the feasibility to manufacture a flexible wafer-scale array utilizing this heterojunction. We applied it to autonomous driving under extreme temperatures and achieved as a high impressive accuracy rate as 94.5%. This tunable and stable wide-temperature PPC capability holds promise for ultra-low-power neuromorphic computing.
Abstract
Gamma-ray bursts produce afterglows that can be observed across the electromagnetic spectrum and can provide insight into the nature of their progenitors. While most telescopes that observe ...afterglows are designed to rapidly react to trigger information, the Transiting Exoplanet Survey Satellite (TESS) continuously monitors sections of the sky at cadences between 30 minutes and 200 s. This provides TESS with the capability of serendipitously observing the optical afterglow of GRBs. We conduct the first extensive search for afterglows of known GRBs in archival TESS data reduced with the
TESSreduce
package, and detect 11 candidate signals that are temporally coincident with reported burst times. We classify three of these as high-likelihood GRB afterglows previously unknown to have been detected by TESS, one of which has no other afterglow detection reported on the Gamma-ray Coordinates Network. We classify five candidates as tentative and the remainder as unlikely. Using the
afterglowpy
package, we model each of the candidate light curves with a Gaussian and a top-hat model to estimate burst parameters; we find that a mean time delay of 740 ± 690 s between the explosion and afterglow onset is required to perform these fits. The high cadence and large field of view make TESS a powerful instrument for localising GRBs, with the potential to observe afterglows in cases when no other backup photometry is possible, and at timescales previously unreachable by optical telescopes.
The advantages of e-commerce and information technology play an extremely important role in enhancing the competitiveness of the tourism industry and adapting to the needs of global economic ...integration. The development of e-commerce has played a huge role in all walks of life. For the tourism industry, the role of e-commerce is even more important. This article analyzes the influence of e-commerce on tourism production factors, such as optimizing tourism production factors, optimizing industrial structure, improving the competitiveness of tourism enterprises and playing the leading role of the government. This article attempts to find out the fundamental reason why e-commerce can enhance the competitiveness of China’s tourism industry, so as to find a better way for e-commerce to promote the development of China’s tourism industry. In order to accurately predict the scale and quantity of domestic tourism, an optimized neural network model is proposed to analyze and predict tourism data, and then analyze and research the data. Tourism development factors such as tourism development factors, changes in tourism demand and the optimization of industrial structure have effectively promoted the development of China’s tourism industry.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cutting force is one of the most basic signals that can reflect the information of the cutting process, so it is very necessary to study the strain elastic element of strain gauge wireless rotating ...dynamometers. This paper proposes a strain elastic element with a double-layer cross floating beam that can be applied to the strain gauge wireless rotating dynamometer, which can simultaneously obtain the four-component cutting force/torque information of FX, FY, FZ, and MZ. Based on the proposed strain elastic element, a compact strain gauge wireless rotating dynamometer is designed, which is composed of a tool holder, upper connection flange, strain elastic element, lower connection flange, tool base, and data acquisition and wireless transmission system. The static model of the double-layer cross floating beam on the strain elastic element is established by the segmented rigid body method, and the relationships between the material, force, structural parameters, and the strain and deformation of the floating beam are obtained. The static model is consistent with the finite element solution, which proves the rationality of the static model. Based on the established static model, the sequential quadratic programming algorithm is used to optimize the structural parameters of the double-layer cross floating beam to maximize the sensitivity of the floating beam. The overall structure of the strain elastic element is analyzed by finite element software, and the strain of the structure under simulation conditions is obtained, which provides a reference for subsequent calibration tests and circuit design. The calibration matrix and dynamic performance of the strain elastic element are obtained by the static calibration test, dynamic calibration test, and cutting test. The results show that the proposed strain elastic element has high sensitivity and low cross-sensitivity error, and can be applied to the strain gauge wireless rotating dynamometer to measure medium- and low-speed cutting forces.
•We consider a centralized distribution system consisting of one warehouse and multiple nonidentical retailers.•The system adopts a fixed-interval order-up-to policy and myopic optimal stock ...allocation.•We develop methods to evaluate and optimize the inventory control system.•We demonstrate that myopic optimal stock allocation can significantly reduce system cost compared to virtual allocation.
We consider a centralized two-level distribution system that consists of one warehouse and multiple retailers. The retailers are non-identical and face independent Poisson demand. The system adopts a fixed-interval order-up-to policy, in which the warehouse and retailers each order in a fixed interval to raise the echelon inventory position to a fixed base stock level. Shortages in the system are fully backlogged but transshipments between retailers are not allowed. The fixed-interval order-up-to policy has been studied in the literature under virtual allocation that reserves a unit of warehouse stock immediately after a unit of demand occurs. We consider an inventory control system that is different in two aspects. First, the warehouse implements myopic optimal allocation that allocates stock to retailers only at points of delivery to minimize system cost. Second, the warehouse adopts a non-stationary base stock policy to order stock for retailers according to their replenishment schedules. We develop methods to exactly evaluate and fully optimize this inventory control system. In a numerical study, we demonstrate that myopic optimal allocation reduces system cost by an average of 5.89% with a range from 1.45% to 10.13% as compared to virtual allocation. In addition, we develop an iterative procedure to alleviate the problem of dimensionality for myopic optimal warehouse stock allocation and a close-to-optimal heuristic solution that can significantly reduce computation.
ABSTRACT We report on 0.3-10 keV observations with the Chandra X-ray Observatory of eight hard X-ray sources discovered within 8° of the Galactic plane by the International Gamma-ray Astrophysics ...Laboratory satellite. The short (∼5 ks) Chandra observations of the IGR source fields have yielded very likely identifications of X-ray counterparts for three of the IGR sources: IGR J14091-6108, IGR J18088-2741, and IGR J18381-0924. The first two have very hard spectra in the Chandra band that can be described by a power law with photon indices of Γ = 0.6 0.4 and - , respectively (90% confidence errors are given), and both have a unique near-IR counterpart consistent with the Chandra position. IGR J14091-6108 also displays a strong iron line and a relatively low X-ray luminosity, and we argue that the most likely source type is a cataclysmic variable (CV), although we do not completely rule out the possibility of a high mass X-ray binary. IGR J18088-2741 has an optical counterpart with a previously measured 6.84 hr periodicity, which may be the binary orbital period. We also detect five cycles of a possible 800-950 s period in the Chandra light curve, which may be the compact object spin period. We suggest that IGR J18088-2741 is also most likely a CV. For IGR J18381-0924, the spectrum is intrinsically softer with , and it is moderately absorbed, NH = (4 1) × 1022 cm−2. There are two near-IR sources consistent with the Chandra position, and they are both classified as galaxies, making it likely that IGR J18381-0924 is an active galactic nucleus. For the other five IGR sources, we provide lists of nearby Chandra sources, which may be used along with further observations to identify the correct counterparts, and we discuss the implications of the low inferred Chandra count rates for these five sources.
Spiking neural networks (SNNs) have immense potential due to their utilization of synaptic plasticity and ability to take advantage of temporal correlation and low power consumption. The leaky ...integration and firing (LIF) model and spike-timing-dependent plasticity (STDP) are the fundamental components of SNNs. Here, a neural device is first demonstrated by zeolitic imidazolate frameworks (ZIFs) as an essential part of the synaptic transistor to simulate SNNs. Significantly, three kinds of typical functions between neurons, the memory function achieved through the hippocampus, synaptic weight regulation and membrane potential triggered by ion migration, are effectively described through short-term memory/long-term memory (STM/LTM), long-term depression/long-term potentiation (LTD/LTP) and LIF, respectively. Furthermore, the update rule of iteration weight in the backpropagation based on the time interval between presynaptic and postsynaptic pulses is extracted and fitted from the STDP. In addition, the postsynaptic currents of the channel directly connect to the very large scale integration (VLSI) implementation of the LIF mode that can convert high-frequency information into spare pulses based on the threshold of membrane potential. The leaky integrator block, firing/detector block and frequency adaptation block instantaneously release the accumulated voltage to form pulses. Finally, we recode the steady-state visual evoked potentials (SSVEPs) belonging to the electroencephalogram (EEG) with filter characteristics of LIF. SNNs deeply fused by synaptic transistors are designed to recognize the 40 different frequencies of EEG and improve accuracy to 95.1%. This work represents an advanced contribution to brain-like chips and promotes the systematization and diversification of artificial intelligence.
Machine learning has emerged as a powerful tool in studying the behavior of stock movement. However, it has yet to be highly accurate due to market randomness. This article aims to improve stock ...movement classification accuracy by addressing macroeconomic factors, which have been neglected in previous machine learning stock prediction studies. Hence, we propose a Risk Adapting Stock Trading System (RAST) using both technical and macroeconomic indicators. The simulated trading result of the system presented here proves that a combination of these two types of indicators is more effective than only using technical indicators when associated with machine learning.
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