Supplier selection using a hybrid model for 3C industry

Supplier selection is a good strategy for firms that can reduce operating costs and improve competitiveness for computer, communication and consumer electronics (3C) industry. The major aim of this research is to build a systematic approach for establishing a supplier selection model, and then prioritize improvement criteria in order to best supply chain management. The study proposed a hybrid approach by using the interpretive structural modeling (ISM) method to deal with the interrelationship among criteria, and the analytic network process (ANP) method is employed to recognize the criteria of supplier selection and evaluate with respect to environmental competency for the case of Taiwan's 3C industry. The study shows that the proposed model could be an effective and efficient decision-making tool that can be easily extended to other contexts. Especially, it has provided decision-makers and researchers with better understanding of the differences in supplier selection activity needs and specific management interventions by examining these criteria

Observation of superradiance in a phase fluctuating dipolar Bose-Einstein condensate

Despite the extensive study of matter-wave superradiance in a Bose-Einstein condensate (BEC) using its unique coherence property, the controllability of superradiant process has remained limited in the previous studies exploiting a phase-coherent condensate with isotropic contact interactions. Here, we combine tunable s-wave scattering with dipolar interactions in a BEC of $^{168}$Er atoms wherein the asymmetry and threshold of superradiance are independently controlled. By changing the s-wave scattering length near the Feshbach resonance, we tune the superradiance threshold with increasing phase fluctuations. In contrast to collective light scattering from a condensate only with contact interactions, we observe an asymmetric superradiant peak in a dipolar BEC by changing the direction of external magnetic field. This results from the anisotropic excitation spectrum induced by the dipole-dipole interaction. Our observation is expected to bring forth unprecedented application of matter-wave optics leading to controlled emission of matter wave.Comment: 6 pages, 6 figure

Magnetic field regression using artificial neural networks for cold atom experiments

Accurately measuring magnetic fields is essential for magnetic-field sensitive experiments in fields like atomic, molecular, and optical physics, condensed matter experiments, and other areas. However, since many experiments are conducted in an isolated vacuum environment that is inaccessible to experimentalists, it can be challenging to accurately determine the magnetic field. Here, we propose an efficient method for detecting magnetic fields with the assistance of an artificial neural network (NN). Instead of measuring the magnetic field directly at the desired location, we detect magnetic fields at several surrounding positions, and a trained NN can accurately predict the magnetic field at the target location. After training, we achieve a relative error of magnetic field magnitude (magnitude of error over the magnitude of magnetic field) below 0.3$\%$, and we successfully apply this method to our erbium quantum gas apparatus. This approach significantly simplifies the process of determining magnetic fields in isolated vacuum environments and can be applied to various research fields across a wide range of magnetic field magnitudes.Comment: 7 pages, 4 figure

Identification of single nucleotide polymorphism markers associated with resistance to bruchids (Callosobruchus spp.) in wild mungbean (Vigna radiata var. sublobata) and cultivated V. radiata through genotyping by sequencing and quantitative trait locus analysis

Interval mapping of bruchid resistance on physical maps of populations TC1966 x NM94 and V2802. (DOCX 14 kb

Influence of typical environments on quantum processes

We present the results of studying the influence of different environmental states on the coherence of quantum processes. We choose to discuss a simple model which describe two electronic reservoirs connected through tunneling via a resonant state. The model could, e.g., serve as an idealization of inelastic resonant tunneling through a double barrier structure. We develop Schwinger's closed time path formulation of non-equilibrium quantum statistical mechanics, and show that the influence of the environment on a coherent quantum process can be described by the value of a generating functional at a specific force value, thereby allowing for a unified discussion of destruction of phase coherence by various environmental states: thermal state, classical noise, time dependent classical field, and a coherent state. The model allows an extensive discussion of the influence of dissipation on the coherent quantum process, and expressions for the transmission coefficient are obtained in the possible limits.Comment: 46 pages, 11 post script figures. Accepted for publication in Physical Review

Review of phase change emulsions (PCMEs) and their applications in HVAC systems

Phase change material emulsions (PCMEs) are multifunctional fluids consisting of phase change materials (PCMs) and carrier fluids. PCMEs could be potential candidates as heat transfer media in heating, ventilation and air conditioning (HVAC) systems. This is mainly because PCME could take advantage of its high heat capacity to reduce flow rate and thus saving pumping power whilst delivering the same amount of cooling effect. PCME can also simultaneously act as cold storage to shift peak-load to off-peak time and improve the COP of systems. However, the optimum design of integrated system requires a good understanding of flow behaviour and heat transfer characteristics of PCMEs. In this paper, comprehensive reviews of their thermo-physical properties and potential applications as thermal energy storage and as alternative heat transfer fluids in air conditioning systems have been carried out to establish their limitations for future research