Comparison of noise reduction results for fit-testing and continuous observations during coal mining for selected earplug and earmuff

It is not clear how effective hearing protective devices are during actual use, including during coal mining. A proposed solution is individual fit-testing, which is usually done in an office environment. However, it is not clear that fit-testing accurately represents protection while actually working. This research investigates both issues for coal miners for two hearing protectors (E-A-R earplug and Peltor earmuff). It consists of two related studies: lab studies of fit-testing and field studies relating fit-testing at coal mine offices to the actual noise reductions provided for the same coal miners during work.;The effects of several variables on fit-testing results were investigated in the lab studies. First, the necessity of using a reverberatory chamber for fit-testing was investigated by testing the same individuals in both a chamber and an ordinary university laboratory room. The overall A-weighted noise reduction (NRA) difference was found to be about 1 dBA, a modest difference of little practical importance, indicating that an ordinary room can be used as a substitute for a reverberatory chamber for fit-testing. As part of this study, each subject was tested while oriented at 0, 180, and 90 degrees to the noise source. The fit-testing results showed modest effects of orientation to the source on NRA values. Likewise, having each subject do various body movements during testing produced only modest differences from results found while sitting still. Finally, the effect of re-fitting was tested by having each of five subjects remove and then re-don his or her Peltor(TM) ear muff or E-A-R(TM) earplugs twelve times. The twelve refittings produced NRA variations of 10 to 34 dBA, suggesting that the average of multiple fit-tests may be required to determine a representative value for each individual. Finally, by comparing noise levels measured concurrently the study demonstrated that there were negligible differences due to the use of the dosimeters.;For the field study, the investigator fit tested seventeen coal miners in ordinary coal mine offices while they wore either their own cap-mounted muffs or investigator-supplied E-A-R ear plugs, depending on whether they normally used cap-mounted muffs or earplugs while working prior to the study. The fit-test setup and apparatus was identical to the fit-testing done in the university lab room, with the exceptions that an analyzer and two dosimeters were employed. The fit-testing results showed that the coal miners\u27 NRA was highly variable among the twelve different fitting measurements. Most subjects\u27 NRA values varied over a range of more than 10 dBA, suggesting that the average of many fit-testings are necessary to adequately represent the NRA for each miner, agreeing with the results of the lab study.;Either earlier or later the same day for the same fit-tested miners, NRA values were determined continuously during full shifts of work using two dosimeters, one measuring at the shoulder and the other measuring proximal to the ear plug or muff. The field study also showed that the minute-by-minute NRA values of the tested coal miners fluctuated widely (ranges = -15.9 to 44.6 dBA) during their tested work shifts. Using observations of HPD use and non-use during each miner\u27s work shift, investigators developed an algorithm to determine whether an HPD was worn during unobserved periods. These determinations made it possible to estimate the total fraction of the work shift and of exposure dose for each worker that were attributable to failure to wear the HPD. The results showed that the percentage of the noise dose measured in the ear attributable to failure to wear the HPD ranged from 0 to 98% with an average across subjects of 58%. The fraction of minutes in which the HPD were not worn ranged from 0 % to 78%, with an average of 26% minutes across all subjects. Broken down by HPD type, the comparable figures for dose and time were 60% and 29% for the earmuff, and 57% and 24% for the earplug.;The correlation between fit-testing and work NRA average values for these miners differed between earplugs and ear muffs. For the earplug, there was a modest linear relationship (R2=0.53) between fit-testing and work experience. For the earmuff, a linear relationship was not found when all subject results were included.;In conclusion, failure to wear the HPD was a main cause of the low mean NRA values during work for these subjects. The relationship between the average of twelve fit-tests and the same worker\u27s work NR A would be moderately strong only if a pair of invalid results were arbitrarily omitted and did not show prediction relationship for earmuff

China-Africa Relations from the Perspective of the Belt and Road Initiative: Motivations, Characteristics and Prospects

The Belt and Road Initiative is a major diplomatic strategy implemented by the Chinese government and a public good of worldwide significance. Africa has unique advantages such as abundant strategic resources and considerable market potential, and has become the focus of major countries. Strengthening China-Africa cooperation is of great significance to building a new type of international relations and building a community with a shared future for mankind. In recent years, China has become a major force in promoting Africa’s development. With its huge size and increasing strategic influence, China is playing an increasingly important role in global development with global development initiatives and the Belt and Road Initiative as its starting point. This is especially true in Africa: activities such as Chinese investment in Africa, as well as cooperation with other countries such as the United States, will enhance the capacity of low-income African countries to achieve sustainable development

Does adoption mean the same to every user? A study of active and passive usage of mobile instant messaging applications

This research-in-progress paper studies the active and passive usage of mobile instant messaging (MIM) applications. Grounded on two-factor theory and three-factor theory, we propose the features of MIM applications influence the active/passive usage of MIM applications through users’ satisfaction and dissatisfaction. The proposed features are categorized into three factors: exciting factors which contain design aesthetics, customization and enjoyment, performance factors which include sociability, convenience and privacy assurance, and basic factors which are application costs and technical functionality. To test hypothetical relationships in this study, we plan to use a survey method. The potential implications to both literature and practice are discussed

Assessing Prompt Injection Risks in 200+ Custom GPTs

In the rapidly evolving landscape of artificial intelligence, ChatGPT has been widely used in various applications. The new feature: customization of ChatGPT models by users to cater to specific needs has opened new frontiers in AI utility. However, this study reveals a significant security vulnerability inherent in these user-customized GPTs: prompt injection attacks. Through comprehensive testing of over 200 user-designed GPT models via adversarial prompts, we demonstrate that these systems are susceptible to prompt injections. Through prompt injection, an adversary can not only extract the customized system prompts but also access the uploaded files. This paper provides a first-hand analysis of the prompt injection, alongside the evaluation of the possible mitigation of such attacks. Our findings underscore the urgent need for robust security frameworks in the design and deployment of customizable GPT models. The intent of this paper is to raise awareness and prompt action in the AI community, ensuring that the benefits of GPT customization do not come at the cost of compromised security and privacy

Hybrid algorithms to solve linear systems of equations with limited qubit resources

The solution of linear systems of equations is a very frequent operation and thus important in many fields. The complexity using classical methods increases linearly with the size of equations. The HHL algorithm proposed by Harrow et al. achieves exponential acceleration compared with the best classical algorithm. However, it has a relatively high demand for qubit resources and the solution $\left| x \right\rangle$ is in a normalized form. Assuming that the eigenvalues of the coefficient matrix of the linear systems of equations can be represented perfectly by finite binary number strings, three hybrid iterative phase estimation algorithms (HIPEA) are designed based on the iterative phase estimation algorithm in this paper. The complexity is transferred to the measurement operation in an iterative way, and thus the demand of qubit resources is reduced in our hybrid algorithms. Moreover, the solution is stored in a classical register instead of a quantum register, so the exact unnormalized solution can be obtained. The required qubit resources in the three HIPEA algorithms are different. HIPEA-1 only needs one single ancillary qubit. The number of ancillary qubits in HIPEA-2 is equal to the number of nondegenerate eigenvalues of the coefficient matrix of linear systems of equations. HIPEA-3 is designed with a flexible number of ancillary qubits. The HIPEA algorithms proposed in this paper broadens the application range of quantum computation in solving linear systems of equations by avoiding the problem that quantum programs may not be used to solve linear systems of equations due to the lack of qubit resources.Comment: 22 pages, 6 figures, 6 tables, 48 equation

Current Sheet Flapping Motions in the Tailwind Flow of Magnetic Reconnection

The feature and origin of current sheet flapping motions are one of most interesting issues of magnetospheric dynamics. In this paper we report the flapping motion of the current sheet detected in the tailward flow of a magnetic reconnection event on 7 February 2009. This flapping motion with frequency about 12 mHz was accompanied by magnetic turbulence. The observations by the tail‐elongated fleet of five Time History of Events and Macroscale Interactions during Substorms probes indicate that these flapping oscillations were rather confined within the tailward flow than were due to a global process. This flapping motion could be due to the instability driven by the free energy associated with the ion temperature anisotropy in the tailward flow. Our observations indicate that the flapping motion in the tailward flow could have a different generation mechanism with that in the earthward flow

Doubly Robust Self-Training

Self-training is an important technique for solving semi-supervised learning problems. It leverages unlabeled data by generating pseudo-labels and combining them with a limited labeled dataset for training. The effectiveness of self-training heavily relies on the accuracy of these pseudo-labels. In this paper, we introduce doubly robust self-training, a novel semi-supervised algorithm that provably balances between two extremes. When the pseudo-labels are entirely incorrect, our method reduces to a training process solely using labeled data. Conversely, when the pseudo-labels are completely accurate, our method transforms into a training process utilizing all pseudo-labeled data and labeled data, thus increasing the effective sample size. Through empirical evaluations on both the ImageNet dataset for image classification and the nuScenes autonomous driving dataset for 3D object detection, we demonstrate the superiority of the doubly robust loss over the standard self-training baseline