Coal desulfurization by aqueous chlorination

A method of desulfurizing coal is described in which chlorine gas is bubbled through an aqueous slurry of coal at low temperature below 130 degrees C., and at ambient pressure. Chlorinolysis converts both inorganic and organic sulfur components of coal into water soluble compounds which enter the aqueous suspending media. The media is separated after chlorinolysis and the coal dechlorinated at a temperature of from 300 C to 500 C to form a non-caking, low-sulfur coal product

Anti-ISI Demodulation Scheme and Its Experiment-based Evaluation for Diffusion-based Molecular Communication

In diffusion-based molecular communication (MC), the most common modulation technique is based on the concentration of information molecules. However, the random delay of molecules due to the channel with memory causes severe inter-symbol interference (ISI) among consecutive signals. In this paper, we propose a detection technique for demodulating signals, the increase detection algorithm (IDA), to improve the reliability of concentration-encoded diffusion-based molecular communication. The proposed IDA detects an increase (i.e., a relative concentration value) in molecule concentration to extract the information instead of detecting an absolute concentration value. To validate the availability of IDA, we establish a real physical tabletop testbed. And we evaluate the proposed demodulation technique using bit error rate (BER) and demonstrate by the tabletop molecular communication platform that the proposed IDA successfully minimizes and even isolates ISI so that a lower BER is achieved than the common demodulation technique

Identification of the plastic behavior of aluminum plates under free air explosions using inverse methods and full-field measurements

AbstractThis article describes an inverse method for the identification of the plastic behavior of aluminum plates subjected to sudden blast loads. The method uses full-field optical measurements taken during the first milliseconds of a free air explosion and the finite element method for the numerical prediction of the blast response. The identification is based on a damped least-squares solution according to the Levenberg–Marquardt formulation. Three different rate-dependent plasticity models are examined. First, a combined model based on linear strain hardening and the strain rate term of the Cowper–Symonds model, secondly, the Johnson–Cook model and finally, a combined model based on a bi-exponential relation for the strain hardening term and the strain rate term of the Cowper–Symonds model. A validation of the method and its sensitivity to measurement uncertainties is first provided according to virtual measurements generated with the finite element method. Next, the plastic behavior of aluminum is identified using measurements from real free air explosions obtained from a controlled detonation of C4. The results show that inverse methods can be successfully applied for the identification of the plastic behavior of metals subjected to blast waves. In addition, the material parameters identified with inverse methods enable the numerical prediction of the material’s response with increased accuracy

A Novel Definition of Equivalent Uniform Dose Based on Volume Dose Curve

© 2013 IEEE. With the improvement of mobile device performance, the requirement of equivalent dose description in intensity-modulated radiation therapy is increasing in mobile multimedia for healthcare. The emergence of mobile cloud computing will provide cloud servers and storage for intensity-modulated radiotherapy (IMRT) mobile applications, thus realizing visualized radiotherapy in a real sense. Equivalent uniform dose (EUD) is a biomedical indicator based on the dose measure. In this paper, the dose volume histogram is used to describe the dose distribution of different tissues in target and nontarget regions. The traditional definition of EUD, such as the exponential form and the linear form, has only a few parameters in the model for fast calculation. However, there is no close relationship between this traditional definition and the dose volume histogram. In order to establish the consistency between the EUD and the dose volume histogram, this paper proposes a novel definition of EUD based on the volume dose curve, called VD-EUD. By using a unique organic volume weight curve, it is easy to calculate VD-EUD for different dose distributions. In definition, different weight curves are used to represent the biological effects of different organs. For the target area, we should be more careful about those voxels with a low dose (cold point); thus, the weight curve is monotonically decreasing. While for the nontarget area, the curve is monotonically increasing. Furthermore, we present the curves for parallel, serial, and mixed organs of nontarget areas separately, and we define the weight curve form with only two parameters. Medical doctors can adjust the curve interactively according to different patients and organs. We also propose a fluence map optimization model with the VD-EUD constraint, which means that the proposed EUD constraint will lead to a large feasible solution space. We compare the generalized EUD (gEUD) and the proposed VD-EUD by experiments, which show that the VD-EUD has a closer relationship with the dose volume histogram. If the biological survival probability is equivalent to the VD-EUD, the feasible solution space would be large, and the target areas can be covered. By establishing a personalized organic weight curve, medical doctors can have a unique VD-EUD for each patient. By using the flexible and adjustable EUD definition, we can establish the VD-EUD-based fluence map optimization model, which will lead to a larger solution space than the traditional dose volume constraint-based model. The VD-EUD is a new definition; thus, we need more clinical testing and verification

Towards Bayesian-Based Trust Management for Insider Attacks in Healthcare Software-Defined Networks

© 2004-2012 IEEE. The medical industry is increasingly digitalized and Internet-connected (e.g., Internet of Medical Things), and when deployed in an Internet of Medical Things environment, software-defined networks (SDNs) allow the decoupling of network control from the data plane. There is no debate among security experts that the security of Internet-enabled medical devices is crucial, and an ongoing threat vector is insider attacks. In this paper, we focus on the identification of insider attacks in healthcare SDNs. Specifically, we survey stakeholders from 12 healthcare organizations (i.e., two hospitals and two clinics in Hong Kong, two hospitals and two clinics in Singapore, and two hospitals and two clinics in China). Based on the survey findings, we develop a trust-based approach based on Bayesian inference to figure out malicious devices in a healthcare environment. Experimental results in either a simulated and a real-world network environment demonstrate the feasibility and effectiveness of our proposed approach regarding the detection of malicious healthcare devices, i.e., our approach could decrease the trust values of malicious devices faster than similar approaches

Picking winners: An empirical analysis of the determinants of educational outcomes in India

We use data from the Young Lives longitudinal survey to analyse the effect of socioeconomic conditions and gender on the educational performance of young children in India. In particular, we use data for standardised scores on two cognitive tests: the Peabody Picture Vocabulary Test (PPVT) and a maths test. Our results show that there are significant gender differences in the way that household wealth affects the educational performance of children. Specifically, boys born into wealthier households perform significantly better in maths than those from worse‐off economic backgrounds. The effect of wealth on the PPVT is stronger for girls than it is for boys. The results are robust across a range of specifications. The effect of household wealth on performance differed between the genders, even when we focused our analysis on the bottom 10% and top 10% of the performance distribution. One possible explanation for these differences is parental aspirations. We tested this hypothesis and found that boys from wealthier households with higher parental educational aspirations are positively and significantly associated with higher maths scores. Further analysis showed that the moderating role of parents’ educational aspirations was more pronounced at the top of the test score distribution, an indication that more able children are associated with wealthier and more ambitious parents

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles.

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction

Receiver-Side TCP Countermeasure in Cellular Networks.

Cellular-based networks keep large buffers at base stations to smooth out the bursty data traffic, which has a negative impact on the user's Quality of Experience (QoE). With the boom of smart vehicles and phones, this has drawn growing attention. For this paper, we first conducted experiments to reveal the large delays, thus long flow completion time (FCT), caused by the large buffer in the cellular networks. Then, a receiver-side transmission control protocol (TCP) countermeasure named Delay-based Flow Control algorithm with Service Differentiation (DFCSD) was proposed to target interactive applications requiring high throughput and low delay in cellular networks by limiting the standing queue size and decreasing the amount of packets that are dropped in the eNodeB in Long Term Evolution (LTE). DFCSD stems from delay-based congestion control algorithms but works at the receiver side to avoid the performance degradation of the delay-based algorithms when competing with loss-based mechanisms. In addition, it is derived based on the TCP fluid model to maximize the network utility. Furthermore, DFCSD also takes service differentiation into consideration based on the size of competing flows to shorten their completion time, thus improving user QoE. Simulation results confirmed that DFCSD is compatible with existing TCP algorithms, significantly reduces the latency of TCP flows, and increases network throughput

Well-being and employment of young people in Ethiopia, India, Peru and Vietnam: Is work enough?

Motivation: Investing in youth employment is central to development agendas. However, policy directed towards increasing employment rates among young people needs to consider the well-being implications of the different kinds of jobs they are able to access. This would help countries to meet the Sustainable Development Goal of decent work for all, including young people, by 2030. Purpose: This article examines the association between the well-being of young people in Ethiopia, Peru, India, and Vietnam and their employment and the job attributes of the work they do. Methods and approach: The study uses five waves of the Young Lives longitudinal survey for a sample of children who are followed from the ages of eight to 22. Regression analysis estimates the relationship between well-being, employment, and job attributes, taking into account gender, wealth, current, and childhood health, and exposure to shocks over life-courses from the age of eight. Findings: The results show that in these four countries, employment does not have an unqualified positive effect on well-being. Not all jobs are “good jobs.” Job attributes matter, specifically, who employs the individual, their pay, the work environment, and the pride they take in their work. Well-being is predicted by current and childhood health and household wealth with ownership of consumer durables associated more strongly with well-being than housing quality or access to services. Greater exposure to shocks from the age of eight is found to have lasting effects on well-being into young adulthood. Policy implications: Policy aimed at improving young people’s opportunities for employment in the Global South also to consider the types of jobs they are able to access and how this impacts their well-being. Policy also needs to take into account pre-labour market conditions and circumstances

School closures and educational attainment in Ethiopia: Can extra classes help children to catch up?

School closures impact children's attainment adversely, but understanding the effects of closures on children's attainment in lower-income countries is still limited. Addressing this deficit, this study examines how past school closures have impacted children's educational attainment in Ethiopia. The study uses individual student-level data from the Young Lives School Survey and standardised test scores in mathematics and language recorded at the start and end of the school year to model children's attainment. Multiple regression with propensity score matching is used to analyse how attainment over the school year is impacted by school closures for a matched sub-sample of 4842 students. The effectiveness of additional classes to make up for lost learning is also evaluated. Past school closures have had a detrimental effect on attainment in mathematics, but not literacy. Extra classes, specifically those that families do not pay for, have helped children in the past to recuperate lost learning and could serve this function post-Covid-19. Inequalities in learning outcomes, measured by Gini coefficients in educational attainment, are widened by school closures. Applying these results to the extensive school closures under Covid-19 furthers our understanding of the likely effects on academic attainment and can inform policy to mitigate the impact