Design research on systems thinking approach in veterinary education

The purpose of this study was to investigate the application of a newly designed systems approach to the problem of students\u27 lack of big-picture experience in the College of Veterinary Medicine. To determine whether students\u27 performance on problem-solving for various scenarios improved after intervention , a design research methodology was adopted to develop a systems-approach teaching and learning environment. Three iterations were conducted, with improvements to the instructional approach following each of the first two iterations. The results supported the hypothesis that instructional intervention led to modest but statistically significant increases in students\u27 use of system thinking across the three experimental studies. However, the instructor indicated the need for faculty systems-approach training, whereas students tended to request hands-on practice to understand and retain systems thinking skills. Furthermore, there was a significant improvement from pretest to posttest for the beef scenario, demonstrating transfer of systems thinking to a topic for which systems-approach instruction was not provided. The qualitative data suggested that most students found systems thinking was beneficial for macro systems, such as food production, but not for micro systems such, as individual small-animal biological systems

Weak measurement combined with quantum delayed-choice experiment and implementation in optomechanical system

Weak measurement [1,19] combined with quantum delayed-choice experiment that use quantum beam splitter instead of the beam splitter give rise to a surprising amplification effect, i.e., counterintuitive negative amplification effect. We show that this effect is caused by the wave and particle behaviours of the system to be and can't be explained by a semiclassical wave theory, due to the entanglement of the system and the ancilla in quantum beam splitter. The amplification mechanism about wave-particle duality in quantum mechanics lead us to a scheme for implementation of weak measurement in optomechanical system

Customer Acceptance of Biometric Technology

Information intensive industries, such as the hospitality industry, are attempting to turn back the customer service clock by creating more personalized experiences for their guests. Customer Relationship Management (CRM) systems have enabled organizations to record and gain insight into the relationship it has with each one of its clients. The act of face and name recognition continues to remain an essential ingredient in creating positive customer service experiences. A biometric recognition system could assist hotel employees by providing an on-demand history of customers’ behaviors and preferences. A prototype was developed to simulate a hotel facial recognition system with a fingerprint identification application. The experiment also included a survey instrument to measure the likelihood of customer acceptance of biometric technology. This study concluded that user intention to adopt depended on the attractiveness of the innovation and new product attributes

N′-(3-Eth­oxy-2-hydroxy­benzyl­idene)-3-hydroxy­naphthalene-2-carbohydrazide

In the mol­ecule of the title compound, C20H18N2O4, the dihedral angle between the benzene ring and the naphthyl ring system is 8.5 (2)°. In the crystal structure, mol­ecules are linked through inter­molecular O—H⋯O hydrogen bonds, forming chains running along the b axis

SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

As an important and challenging problem in computer vision, PAnoramic Semantic Segmentation (PASS) gives complete scene perception based on an ultra-wide angle of view. Usually, prevalent PASS methods with 2D panoramic image input focus on solving image distortions but lack consideration of the 3D properties of original $360^{\circ}$ data. Therefore, their performance will drop a lot when inputting panoramic images with the 3D disturbance. To be more robust to 3D disturbance, we propose our Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation (SGAT4PASS), considering 3D spherical geometry knowledge. Specifically, a spherical geometry-aware framework is proposed for PASS. It includes three modules, i.e., spherical geometry-aware image projection, spherical deformable patch embedding, and a panorama-aware loss, which takes input images with 3D disturbance into account, adds a spherical geometry-aware constraint on the existing deformable patch embedding, and indicates the pixel density of original $360^{\circ}$ data, respectively. Experimental results on Stanford2D3D Panoramic datasets show that SGAT4PASS significantly improves performance and robustness, with approximately a 2% increase in mIoU, and when small 3D disturbances occur in the data, the stability of our performance is improved by an order of magnitude. Our code and supplementary material are available at https://github.com/TencentARC/SGAT4PASS.Comment: Accepted by IJCAI 202