An Analysis Scheme for 3D Visualization of Positron Emitting Radioisotopes Using Positron Emission Mammography System

Proton range monitoring and verification is important to enhance the effectiveness of treatment by ensuring that the correct dose is delivered to the correct location. Upon proton irradiation, different positron emitting radioisotopes are produced by the inelastic nuclear interactions of protons with the target elements. Recently, it was reported that the 16O(p,2p2n)13N reaction has a relatively low threshold energy, and it could be potentially used for proton range verification. In the present work, we have proposed an analysis scheme (i.e., algorithm) for the extraction and three-dimensional visualization of positron emitting radioisotopes. The proposed step-by-step analysis scheme was tested using our own experimentally obtained dynamic data from a positron emission mammography (PEM) system (our developed PEMGRAPH system). The experimental irradiation was performed using an azimuthally varying field (AVF) cyclotron with a 80 MeV monoenergetic pencil-like beam. The 3D visualization showed promising results for proton-induced radioisotope distribution. The proposed scheme and developed tools would be useful for the extraction and 3D visualization of positron emitting radioisotopes and in turn for proton range monitoring and verification.

A case study of the impact of INSAT derived humidity profiles on precipitation forecast by limited area model

The impact of humidity profiles estimated from INSAT digital IR cloud imagery data on initial moisture analysis in the IMD's operational limited area forecast system has been investigated. Method for assimilation of humidity profiles data as pseudo observations in the analysis scheme has been developed and implemented in the regional analysis scheme. Verification of humidity analysis with this data has shown substantial improvements in the moisture analysis over the data sparse region of tropics. Impact of the improved humidity analysis on model predicted rainfall is examined. The experiments show improved rainfall prediction.

Pointer-Based Divergence Analysis for OpenCL 2.0 Programs

A modern GPU is designed with many large thread groups to achieve a high throughput and performance. Within these groups, the threads are grouped into fixed-size SIMD batches in which the same instruction is applied to vectors of data in a lockstep. This GPU architecture is suitable for applications with a high degree of data parallelism, but its performance degrades seriously when divergence occurs. Many optimizations for divergence have been proposed, and they vary with the divergence information about variables and branches. A previous analysis scheme viewed pointers and return values from functions as divergence directly, and only focused on OpenCL 1.x. In this article, we present a novel scheme that reports the divergence information for pointer-intensive OpenCL programs. The approach is based on extended static single assignment (SSA) and adds some special functions and annotations from memory SSA and gated SSA. The proposed scheme first constructs extended SSA, which is then used to build a divergence relation graph that includes all of the possible points-to relationships of the pointers and initialized divergence states. The divergence state of the pointers can be determined by propagating the divergence state of the divergence relation graph. The scheme is further extended for interprocedural cases by considering function-related statements. The proposed scheme was implemented in an LLVM compiler and can be applied to OpenCL programs. We analyzed 10 programs with 24 kernels, with a total analyzed program size of 1,306 instructions in an LLVM intermediate representation, with 885 variables, 108 branches, and 313 pointer-related statements. The total number of divergent pointers detected was 146 for the proposed scheme, 200 for the scheme in which the pointer was always divergent, and 155 for the current LLVM default scheme; the total numbers of divergent variables detected were 458, 519, and 482, respectively, with 31, 34, and 32 divergent branches. These experimental results indicate that the proposed scheme is more precise than both a scheme in which a pointer is always divergent and the current LLVM default scheme.

A computational approach for shallow water forced Korteweg–De Vries equation on critical flow over a hole with three fractional operators

The Korteweg–De Vries (KdV) equation has always provided a venue to study and generalizes diverse physical phenomena. The pivotal aim of the study is to analyze the behaviors of forced KdV equation describing the free surface critical flow over a hole by finding the solution with the help of q-homotopy analysis transform technique (q-HATT). he projected method is elegant amalgamations of q-homotopy analysis scheme and Laplace transform. Three fractional operators are hired in the present study to show their essence in generalizing the models associated with power-law distribution, kernel singular, non-local and non-singular. The fixed-point theorem employed to present the existence and uniqueness for the hired arbitrary-order model and convergence for the solution is derived with Banach space. The projected scheme springs the series solution rapidly towards convergence and it can guarantee the convergence associated with the homotopy parameter. Moreover, for diverse fractional order the physical nature have been captured in plots. The achieved consequences illuminates, the hired solution procedure is reliable and highly methodical in investigating the behaviours of the nonlinear models of both integer and fractional order.

The Importance of the Integrative Relationship Between Cause and Effect Analysis and The Sustainable Balanced Scorecard in Solving Problems of Economic Units

The aim of the research is to highlight the complementarity between cause-and-effect analysis and the Sustainable Balanced Tag Card. The problem with the research is that economic units are poorly aware of the theoretical and philosophical foundations of cause-and-effect analysis and their importance in costing and solving administrative problems and inadequate attention to financial and non-financial measures. In order to achieve the objective of research and test its hypotheses, the Wasit Textile and Weaving Plant of the State Company for the Textile and Leather Industries, located in the centre of the Wasit prefecture, has been selected as a centre for research. Its performance has been evaluated and a model has been presented to solve the problems it faces through a cause-and-effect analysis scheme with a sustainable balanced tag card (SBSC) that details all environmental and social aspects, both quantitative and financial. A set of conclusions has been reached, the most important of which is that the cause-and-effect relationship is not just a correlation, but a reasonable relationship between the level of the activity and its costs, because it gives analysts and managers confidence in the relationships repeatedly estimated in other sets of data, The identification of cost guides gives managers a vision of several methods they use to reduce costs and the quantity of routers, and the sustainable balanced labeling card uses both financial and non-financial performance measures to bridge the gap arising from the use of financial measures only, as well as to measure and improve performance , The economic unit wishing to take advantage of the characteristics of the adopted economic unit strategies that are relevant to each dimension of the sustainable balance tag and its drawbacks should be careful not to reduce the costs of products or services on an ongoing basis, and focus not only on reducing costs, but also on providing distinct products and services that meet

SECURE MEDICAL IMAGE ENCRYPTION FOR REMOTE VIRTUAL DOCTOR SYSTEM BASED ON H-IOT APPLICATIONS OVER 5G NETWORK: A COMPARISON STUDY

Recent years have seen a new amalgamation between Remote virtual doctor systems and healthcare IoT applications which plays a crucial role in enhancing patient’s healthcare life. The Remote VDS connected with smart Healthcare devices through the wireless network to be accessible anytime and anywhere is anticipated to treat rapidly valuable and confidential data such as personal medical images. Therefore, quick medical image encryption is an essential task in healthcare topic. Some medical image encryption research like the Scan methodology proposed for Remote VDS suffers from a long computational time. Then, the patient will confront difficulty on treatment availability in real-time and especially for critical situations. To overcome this problem, in this work, three medical image encryption methods are compared, (1) A Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications, (2) A new chaotic map with dynamic analysis and encryption application on the Internet of Health Things, and (3) Robust medical image encryption based on DNA chaos method. The comparison results have proven that the new chaotic map with a dynamic analysis scheme has high-security analysis and performances with low computational time compared to other methods. That makes it a good candidate for the H-IOT-RVDS environment connecting over 5G technology like a cellular network to enable connectivity between nodes.

Performing the Pandemics

Stemming from one creative experience that emerged in London during the lockdown period of early 2020, called the “Emergency Festival”, this article is a result of observations based on practice, centred around the festival that a group of multicultural, interdisciplinary movement-based researchers and dancers created, curated, and participated in. It explores the possibility of making a radical alterity out of a hitherto previously established ideas of territory, time, and community, using performative writing as practice-based analysis scheme. Employing the concept of “communitas” by Victor Turner (1969) to approach the phenomenon of dance through distance, the article examines the importance of the emergence of collaboration as a way forward, epistemologically looking at dance as a method of creating and sustaining communities that are longing for a sense of home in times of change. The writing is divided into three parts, focussing on the aspects of space, time, and community, all the while embedded in the nature of movement and its effect on the practitioners, and onlookers, concluding with contemplation on the place of dance in varied mediums and the way forward to study it in a period of global disruption.

De Novo Determination of Molecular Orientation at Interfaces through Multimode Polarization-Dependent Sum-Frequency Generation Spectroscopy

Many essential processes occur at soft interfaces, from chemical reactions on aqueous aerosols in the atmosphere to biochemical recognition and binding at the surface of cell membranes. The spatial arrangement of molecules specifically at these interfaces is crucial for many of such processes. The accurate determination of the interfacial molecular orientation has been challenging due to the low number of molecules at interfaces and the ambiguity of their orientational distribution. Here, we combine phase- and polarization-resolved sum-frequency generation spectroscopy to obtain the molecular orientation at the interface. We extend an exponentially decaying orientational distribution to multiple dimensions, which, in conjunction with multiple SFG data sets obtained from the different vibrational modes, allows us to determine molecular orientation. We apply this new approach to formic acid molecules at the air-water interface. The inferred orientation of formic acid agrees very well with ab initio molecular dynamics data. The phase-resolved SFG multimode analysis scheme using the multi-dimensional orientational distribution thus provides a universal approach for obtaining the interfacial molecular orientation.

Monitoring the effects of therapeutic interventions in depression through self-assessments

The treatment of major psychiatric disorders is an arduous and thorny path for the patients concerned, characterized by polypharmacy, massive adverse side effects, modest prospects of success, and constantly declining response rates. The more important is the early detection of psychiatric disorders prior to the development of clinically relevant symptoms, so that people can benefit from early interventions. A well-proven approach to monitoring mental health relies on voice analysis. This method has been successfully used with psychiatric patients to ‘objectively’ document the progress of improvement or the onset of relapse. The studies with psychiatric patients over 2-4 weeks demonstrated that daily voice assessments have a notable therapeutic effect in themselves. Therefore, daily voice assessments appear to be a lowthreshold form of therapeutic means that may be realized through self-assessments. To evaluate performance and reliability of this approach, we have carried out a longitudinal study on 82 university students in 3 different countries with daily assessments over 2 weeks. The sample included 41 males (mean age 24.2±3.83 years) and 41 females (mean age 21.6±2.05 years). Unlike other research in the field, this study was not concerned with the classification of individuals in terms of diagnostic categories. The focus lay on the monitoring aspect and the extent to which the effects of therapeutic interventions or of behavioural changes are visible in the results of self-assessment voice analyses. The test persons showed an over-proportionally good adherence to the daily voice analysis scheme. The accumulated data were of generally high quality: sufficiently high signal levels, a very limited number of movement artifacts, and little to no interfering background noise. The method was sufficiently sensitive to detect: i) habituation effects when test persons became used to the daily procedure; and ii) short-term fluctuations that exceeded prespecified thresholds and reached significance. Results are directly interpretable and provide information about what is going well, what is going less well, and where there is a need for action. The proposed self-assessment approach was found to be well-suited to serve as a health-monitoring tool for subjects with an elevated vulnerability to psychiatric disorders or to stress-induced mental health problems. Daily voice assessments are in fact a low-threshold form of therapeutic means that can be realized through selfassessments, that requires only little effort, can be carried out in the test person’s own home, and has the potential to strengthen resilience and to induce positive behavioural changes.