Advantages of nonclassical pointer states in postselected weak measurements

We investigate, within the weak measurement theory, the advantages of non-classical pointer states over semi-classical ones for coherent, squeezed vacuum, and Schr\"{o}inger cat states. These states are utilized as pointer state for the system operator $\hat{A}$ with property $\hat{A}^{2}=\hat{I}$, where $\hat{I}$ represents the identity operator. We calculate the ratio between the signal-to-noise ratio (SNR) of non-postselected and postselected weak measurements. The latter is used to find the quantum Fisher information for the above pointer states. The average shifts for those pointer states with arbitrary interaction strength are investigated in detail. One key result is that we find the postselected weak measurement scheme for non-classical pointer states to be superior to semi-classical ones. This can improve the precision of measurement process.Comment: 8 pages, 5 figure

Which Factors Can Contribute to the Success of Environmental and Animal Protection Projects in Donation-based Crowdfunding? A Neural Network Model

The crowdfunding industry has developed rapidly in recent years, the existing research shows that crowdfunding can help in many fields such as entrepreneurship, creative products, or donations. Due to global meteorological issues, more and more people are paying attention to the environment and animal protection. However, fundraising in these areas has been the biggest problem, the emergence of donation crowdfunding (DCF) can alleviate this dilemma. Currently, in academia, there is still less research focused on crowdfunding for environmental and animal protection. This paper aims to study the factors influencing the successful financing of environmental and animal protection projects in the DCF. This paper analyses 700 DCF environmental and animal protection projects in China as samples, and creatively introduces financial transparency scoring indicators. Through binary logistic regression, financial transparency was found to be the most critical positive factor affecting project success. At the same time, donors receive NPO-initiated projects well, and the number of donors can also positively impact the results. However, the excessive description of the projects can have the opposite effect. This study also introduced a neural network model, and found that the neural network model can optimize the discriminant accuracy of the traditional binary logistic regression model

Memories of the future

The year is 2020. Sheffield University’s MSc in Electronic & Digital Library Management has been running for 10 years. What paths have its graduates’ careers taken

Identification Techniques Applied to a Passive Elasto-magnetic Suspension

The paper presents an experimental passive elasto-magnetic suspension based on rare-earth permanent magnets, characterized by negligible dependence on mass of its natural frequency. The nonlinear behaviour of this system, equipped with a traditional linear elastic spring coupled to a magnetic spring, is analysed in time domain, for non-zero initial conditions, and in frequency domain, by applying sweep excitations to the test rig base. The dynamics of the system is very complex in dependence of the magnetic contribution, showing both hardening behaviour in the elasto-magnetic setup, and softening motion amplitude dependent behaviour in the purely magnetic case. Hence it is necessary to adopt nonlinear identification techniques, such as non-parametric restoring force mapping method and direct parametric estimation technique, in order to identify the system parameters in the different configurations. Finally, it is discussed the ability of identified versus analytical models in reproducing the nonlinear dependency of frequency on motion amplitude and the presence of jump phenomen

A Study on the Optimization of High School Buildings for Evacuation Safety: Classroom Layout and Ramps in Korea

This study used the Pathfinder program to evaluate evacuation safety by assuming evacuation training in high school buildings and changing classroom layout. Analysis of the final evacuation requirements for Scenario 2, which currently has a concentration of classrooms on the third floor of the building, showed that Scenario 2 reduced 29.6 seconds to 173.9 seconds compared to Scenario 1's 203.5 seconds. However, the analysis of Scenario 3, in which 10 classrooms and personnel of three grades were placed equally on the left and right sides of the building, showed that the final evacuation requirements were reduced 3.9 seconds to 170.0 seconds compared to Scenario 2, but there was no significant difference. Scenario 3, which has more the efficiency of school year operation by placing classroom layout on the same floor by grade level than Scenario 2, in which more classrooms and students were placed downstairs. In each scenario, an analysis of the final evacuation requirements showed that the evacuation exit T1 on the left side of the building was 28 seconds or more shorter than T3 on the right side of the building. Therefore, it was analyzed that proper classroom layout and ramp facilities in high school buildings ensure evacuation safet

Graph-based Representation of Syntactic Structures of Natural Languages based on Dependency Relations

Deep Learning approach using probability distribution to natural language processing achieves significant accomplishment. However, natural languages have inherent linguistic structures rather than probabilistic distribution. This paper presents a new graph-based representation of syntactic structures called syntactic knowledge graph based on dependency relations. This paper investigates the valency theory and the markedness principle of natural languages to derive an appropriate set of dependency relations for the syntactic knowledge graph. A new set of dependency relations derived from the markers is proposed. This paper also demonstrates the representation of various linguistic structures to validate the feasibility of syntactic knowledge graphs

Dietary glycaemic index, glycaemic load and head and neck cancer risk: A pooled analysis in an international consortium

High dietary glycaemic index (GI) and glycaemic load (GL) may increase cancer risk. However, limited information was available on GI and/or GL and head and neck cancer (HNC) risk. We conducted a pooled analysis on 8 case-control studies (4081 HNC cases; 7407 controls) from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. We estimated the odds ratios (ORs) and 95% confidence intervals (CIs) of HNC, and its subsites, from fixed- or mixed-effects logistic models including centre-specific quartiles of GI or GL. GI, but not GL, had a weak positive association with HNC (O