Pulled by God: Sound and Altered State of Consciousness in the Hälqä-Sohbät Ritual of Uyghur Sufis

In Xinjiang, northwestern China, the Uyghur Sufi Muslims practice a localised samāʿ ritual called hälqä-sohbät, which involves dhikr, singing and dancing. Participants in hälqä-sohbät sometimes enter an altered state of consciousness called jäzba, which literally means pulled by God. The hälqä-sohbät includes various sounds such as the singing of hikmät, muqam and mäshräp, as well as instrument playing. However, Uyghur Sufis often deny the role of sound as a decisive factor in triggering jäzba, but attribute its causation to the practice of dhikr, especially silent dhikr. Based on ethnographic data from Khotan, southern Xinjiang, and inspired by Leman’s research framework for music, gesture and embodied meaning, I study the relationship between sound and jäzba in hälqä-sohbät in three perspectives: a first-person perspective from the point of view of the practitioners; a second-person perspective in which hälqä-sohbät is viewed as a way of social interaction in a “me to you” way; and a third-person perspective in which I, the researcher, try to disclose and analyse the various factors at work in triggering the altered state of consciousness, such as timbre, rhythm, and physical movements.In Xinjiang, northwestern China, the Uyghur Sufi Muslims practice a localised samāʿ ritual called hälqä-sohbät, which involves dhikr, singing and dancing. Participants in hälqä-sohbät sometimes enter an altered state of consciousness called jäzba, which literally means pulled by God. The hälqä-sohbät includes various sounds such as the singing of hikmät, muqam and mäshräp, as well as instrument playing. However, Uyghur Sufis often deny the role of sound as a decisive factor in triggering jäzba, but attribute its causation to the practice of dhikr, especially silent dhikr. Based on ethnographic data from Khotan, southern Xinjiang, and inspired by Leman’s research framework for music, gesture and embodied meaning, I study the relationship between sound and jäzba in hälqä-sohbät in three perspectives: a first-person perspective from the point of view of the practitioners; a second-person perspective in which hälqä-sohbät is viewed as a way of social interaction in a “me to you” way; and a third-person perspective in which I, the researcher, try to disclose and analyse the various factors at work in triggering the altered state of consciousness, such as timbre, rhythm, and physical movements

Analysis on Drivers\u27 Vision-psychology under the Influence of Color Difference after Pavement Pothole Repair

Pavement pothole repair, as one of the commonest methods used in routine road maintenance works, is effective to extend the pavement service life and increase its transport capacity. However, there are significant color differences between the old and new pavements after pothole repair, and there are few studies about the impact of color differences on driving safety. Thus, using multiple typical pavements with the pothole repair, we aim to reveal the impact of the color differences between the old and new materials on the driving safety, and to improve the safety and comfort of drivers. Tobii eye tracker and the ErgoLAB physiological recorder were used to test the driver\u27s visual parameters when the vehicles run under the pothole repair environment, including drivers\u27 gaze frequency, gaze duration, saccade range and heart rate variability. Results show that the color differences of the road after pothole repair have a significant influence on the drivers\u27 vision and psychology, resulting in reduced driving safety and stability. Compared with the unrepaired road section, the gaze frequency and duration of drivers on pothole sections are significantly increased. The speed of saccade is also increased, and the saccade range is reduced. Meanwhile, the average heart rate of drivers on the pothole sections is increased by 10-20%, indicating that drivers\u27 attention and heart rate fluctuate greatly when passing through potholes, which can easily cause emotional tension and misjudgment, and thereby reduce the safety of driving. The obtained conclusions provide a significant reference for subsequent research

VommaNet: an End-to-End Network for Disparity Estimation from Reflective and Texture-less Light Field Images

The precise combination of image sensor and micro-lens array enables lenslet light field cameras to record both angular and spatial information of incoming light, therefore, one can calculate disparity and depth from light field images. In turn, 3D models of the recorded objects can be recovered, which is a great advantage over other imaging system. However, reflective and texture-less areas in light field images have complicated conditions, making it hard to correctly calculate disparity with existing algorithms. To tackle this problem, we introduce a novel end-to-end network VommaNet to retrieve multi-scale features from reflective and texture-less regions for accurate disparity estimation. Meanwhile, our network has achieved similar or better performance in other regions for both synthetic light field images and real-world data compared to the state-of-the-art algorithms. Currently, we achieve the best score for mean squared error (MSE) on HCI 4D Light Field Benchmark

Evidence for Two Gaps and Breakdown of the Uemura Plot in Ba0.6_{0.6}K0.4_{0.4}Fe2_2As2_2 Single Crystals

We report a detailed investigation on the lower critical field $H_{c1}$ of the superconducting Ba$_{0.6}$K$_{0.4}$Fe$_2$As$_2$ (FeAs-122) single crystals. A pronounced kink is observed on the $H_{c1}(T)$ curve, which is attributed to the existence of two superconducting gaps. By fitting the data $H_{c1}(T)$ to the two-gap BCS model in full temperature region, a small gap of $\Delta_a(0)=2.0\pm 0.3$ meV and a large gap of $\Delta_b(0)=8.9\pm 0.4$ meV are obtained. The in-plane penetration depth $\lambda_{ab}(0)$ is estimated to be 105 nm corresponding to a rather large superfluid density, which points to the breakdown of the Uemura plot in FeAs-122 superconductors.Comment: 5 pages, 4 figure

Migrant Resettlement by Evolutionary Multi-objective Optimization

Migration has been a universal phenomenon, which brings opportunities as well as challenges for global development. As the number of migrants (e.g., refugees) increases rapidly in recent years, a key challenge faced by each country is the problem of migrant resettlement. This problem has attracted scientific research attention, from the perspective of maximizing the employment rate. Previous works mainly formulated migrant resettlement as an approximately submodular optimization problem subject to multiple matroid constraints and employed the greedy algorithm, whose performance, however, may be limited due to its greedy nature. In this paper, we propose a new framework MR-EMO based on Evolutionary Multi-objective Optimization, which reformulates Migrant Resettlement as a bi-objective optimization problem that maximizes the expected number of employed migrants and minimizes the number of dispatched migrants simultaneously, and employs a Multi-Objective Evolutionary Algorithm (MOEA) to solve the bi-objective problem. We implement MR-EMO using three MOEAs, the popular NSGA-II, MOEA/D as well as the theoretically grounded GSEMO. To further improve the performance of MR-EMO, we propose a specific MOEA, called GSEMO-SR, using matrix-swap mutation and repair mechanism, which has a better ability to search for feasible solutions. We prove that MR-EMO using either GSEMO or GSEMO-SR can achieve better theoretical guarantees than the previous greedy algorithm. Experimental results under the interview and coordination migration models clearly show the superiority of MR-EMO (with either NSGA-II, MOEA/D, GSEMO or GSEMO-SR) over previous algorithms, and that using GSEMO-SR leads to the best performance of MR-EMO