Workflows for Construction of Spatio-Temporal Probabilistic Maps for Volcanic Hazard Assessment

Probabilistic hazard assessments for studying overland pyroclastic flows or atmospheric ash clouds under short timelines of an evolving crisis, require using the best science available unhampered by complicated and slow manual workflows. Although deterministic mathematical models are available, in most cases, parameters and initial conditions for the equations are usually only known within a prescribed range of uncertainty. For the construction of probabilistic hazard assessments, accurate outputs and propagation of the inherent input uncertainty to quantities of interest are needed to estimate necessary probabilities based on numerous runs of the underlying deterministic model. Characterizing the uncertainty in system states due to parametric and input uncertainty, simultaneously, requires using ensemble based methods to explore the full parameter and input spaces. Complex tasks, such as running thousands of instances of a deterministic model with parameter and input uncertainty require a High Performance Computing infrastructure and skilled personnel that may not be readily available to the policy makers responsible for making informed risk mitigation decisions. For efficiency, programming tasks required for executing ensemble simulations need to run in parallel, leading to twin computational challenges of managing large amounts of data and performing CPU intensive processing. The resulting flow of work requires complex sequences of tasks, interactions, and exchanges of data, hence the automatic management of these workflows are essential. Here we discuss a computer infrastructure, methodology and tools which enable scientists and other members of the volcanology research community to develop workflows for construction of probabilistic hazard maps using remotely accessed computing through a web portal.

Developing the Social, Political, Economic, and Criminological Awareness of Cybersecurity Experts

The global shortage in skilled labor for cybersecurity and the risk it presents to international business can only be solved by a significant increase in the number of skilled personnel. However, as the nature of risks proliferate and bifurcate the training of such, personnel must incorporate a broader understanding of contemporary and future risks. That is, while technical training is highly important, it is contended that future cybersecurity experts need to be aware of social, political, economic, and criminological issues. Towards this end, this chapter considers a number of exemplary issues that are considered worthy of inclusion in the development of future cybersecurity workers. Accordingly, an overview is given of the issues of the “dark side of the net” that cause problems for global cybersecurity and international business risk. The issues are discussed so that from these a skill set can be articulated which will attend to (and mitigate against) potential threats.

Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches

To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of fly-ash concrete using a comparative study of machine learning techniques, namely random forest regression (RFR) and gene expression programming (GEP). A widespread database comprising 216 experimental records was constructed from available research. The database includes depth of wear as a response parameter and nine different explanatory variables, i.e., cement content, fly ash, water content, fine and coarse aggregate, plasticizer, air-entraining agent, age of concrete, and time of testing. The performance of the models was judged via statistical metrics. The GEP model gives better performance with R2 and ρ equals 0.9667 and 0.0501 respectively and meet with the external validation criterion suggested in the previous literature. The k-fold cross-validation also verifies the accurateness of the model by evaluating R2, RSE, MAE, and RMSE. The sensitivity analysis of GEP equation indicated that the time of testing is the influential parameter. The results of this research can help the designers, practitioners, and researchers to quickly estimate the depth of wear of fly-ash concrete thus shortening its ecological susceptibilities that push to sustainable and faster construction from the viewpoint of environmentally friendly waste management.

Promising Applications of Nanotechnology in Cancer Diagnostics and Therapeutics

: Cancer is characterized by the accumulation of genetic mutations in cells by different types of mutagens such as physical, chemical, and biological. Consequently, normal cell cycles get interrupted. Conventional techniques used for diagnosis include. Various conventional techniques used for cancer diagnosis include immunological assays, histopathogical tests, polymerase chain reaction, computed tomography, magnetic resonance, radiation therapy, and many more. These techniques are expensive, time consuming, tedious, adverse effects to healthy cells and requirement of skilled personnel for their operation. Therefore nanomaterials based biosensors have been used for the sensitive, selective, economic and quick detection of cancer biomarkers. Electrochemical biosensors have shown profound impact in efficient diagnosis of cancers that facilitate the effective treatment of patient in acute stage. Nanomaterials including inorganic, organic and polymeric nanomaterials have been used in the treatment of different types of cancers. Nanoapproaches have offered several merits including site-specific, require traces amount of therapeutic molecules, limited toxicity, avoid drug resistance, more efficient, sensitive and reliable than conventional chemotherapeutics and radiation therapies. Therefore, future research should be focussed on development of highly inventive nanotools for the diagnosis and therapeutics of cancers.

Examination and Redesign of Inclusive Special Education Service Delivery in a Rural School

In this article, we describe the self-directed change made by a rural elementary school in response to a data-based examination of its service-delivery model that revealed its lowest performing students were spending most of their time with the school’s least qualified staff. This mixed-method case study describes (a) why and how the school shifted personnel deployment and utilization, (b) factors that facilitated the shifts in service delivery, and (c) perceived effects of the changes. Findings demonstrate how implementing data-based decision-making through strong collaborative leadership led to recognizing, exploring, and modifying the school’s overreliance on paraprofessionals by increasing the availability of more highly skilled personnel to facilitate more inclusive instruction and collaboration. Participants also described challenges and perceived negative aspects related to change. We conclude with implications for practice, including how this study could inform similar change efforts in small rural schools, and suggestions for future research.

Smart and Agile Turnaround Management

Oil&Gas facilities operators are looking for safe and efficient Turnaround cycles with minimum downtime. However planning such project, ensuring availability of materials, of equipment and of skilled personnel, as well as orchestrating the hundreds of processes and stakeholders involved in the execution to keep it on schedule and on budget is a huge and complex challenge. How to handle and take into account what is planned and what is unplanned? A Turnaround project can be managed with similar approach than an EPC (Engineering Procurement Construction) project. It should leverage collaborative best practices developed to handle capital projects. Those practices allow to plan more productively, to execute with agility while taking into account unplanned changes "on the fly" without affecting on-going activities. A digital collaborative platform enables integrated knowledge as well as real-time visibility into every aspect of the Turnaround. It provides seamless collaboration for productive planning and intelligent execution. This is a strategy, which eliminates unproductive tasks and brings stakeholders together in a dynamic, collaborative management system. With better orchestration, plant owners and operators can reduce their planning and preparation workload by around 30% with also positive impact on all subcontractors. With a better seamless execution, plant owners and operators can get things done right the first time and recover to unplanned events. They can reduce the risk to be out of schedule and keep on track with more margin. They can even reduce the execution time by up to 5% in some situation. Finally, it enforces the reuse of insights that are gathered along Turnarounds to improve safety and extend by 20% the cycle in future Turnaround. A 3D collaborative platform provides an easy to use single source of truth to manage and monitor a Turnaround. Using such 3D environment, one can quickly identify the location of an issue where potential bottlenecks occur, and get access to any relevant vendor's specification, inspection or maintenance history report. Such 3D platform can also help to easily track with color-coding the leak test results of the many joints and their potential disturbances after Turnaround inspection.

An analysis of the Causes of Building Defects in Residential Properties in Diobu area of port Harcourt, River State, Nigeria.

Currently, derelict buildings with little or no amenities have remained a challenge to the physical fabric of properties in Diobu in Port Harcourt. These derelictions are observed to be affecting the economic and physical functionality of these buildings. Therefore, the paper aims to investigate the causes of the dereliction in the buildings in Diobu area in Port Harcourt Rivers State of Nigeria. A survey research design was adopted where 153 questionnaires was administered to the resident of the study area and another 56 questionnaires to property managers in Port Harcourt. Out of the 209 (Nr) questionnaires administered, a total of 197 was retrieved representing a response rate of 94%. Data gathered were analyzed using Relative Important Index, mean and percentages and presented in tabular and pictorial formats. The paper’s finding revealed and confirmed that wall cracks, wall/floor dampness, roof leakages, faulty plumbing fittings, poor ventilation and peeling/faded wall paints are some of the defects in the properties in Diobu. A further investigation revealed that poor building designs, old age, poor maintenance culture, adverse climatic condition, misuse, overcrowding and insect attack are among the causes of these defects on the buildings. This research work is original and has not been previously published anywhere; its reflection is that effective maintenance culture, good occupancy ratio, use of skilled personnel and quality building materials should be encouraged by residents, property managers and landlords in order to check the menace of building defects in the study area. Keywords: Residential Buildings, Defects, causes, Analysis, Diobu.

Management practices and their relation to success of Polish SMEs: The empirical verification

Purpose The aim of the paper is to identify management practices that are characteristic for SMEs that achieve market success measured by their business performance in last their years of their operation analyze the relationships between management practices applied in small and medium-sized enterprises and their success measured by their business performance drawing on the data from 2710 SMEs operating on the Polish market. Approach/Methodology/Design A cluster analysis was used to distinguish homogenous SME groups in view of their management practices. We examined differences between groups in terms of their business performance. The HINoV algorithm allowed six variables to be selected out of 32 management practices chosen initially for testing, with these variables providing the basis for grouping. Modal values and medians were calculated for 17 business performance measures in the three clusters produced. The subsequent analysis of those findings was focused on capturing significant differences. Findings In the group of 2710 Polish SMEs, it was possible to verify that there existed an association between management practices in the field of modern HRM, computer systems supporting management and the company’s economic performance, as measured by an increase in net revenue and number of customers over the last three years. In clusters where the above mentioned practices were appreciated, modal and median values of the increase reported in net revenue and number of customers were significantly higher. Practical implications The research has shown that at a time marked by a shortage of highly skilled personnel one should pay particular attention to building an integrated and committed team of workers and to employee empowerment. The research has also shown that SME managers monitor only a fraction of basic business performance measures, which may prove to be a major risk to SMEs. Originality/Value Previous studies have been largely conducted in a fragmentary manner, i.e. they were concerned with the relationships between the application of some practices (strategic management, BPR, entrepreneurial orientation, monitoring, etc.) and selected business effectiveness measures. In this paper, the research covered SME management practices from a variety of areas which were then compared with the entrepreneurs’ assessment as to whether the company’s economic condition changed over the last three years. It is also the first attempt in post-socialist economies to identify those SME management practices that are related to better economic results.

Harnessing CRISPR-Cas to Combat COVID-19: From Diagnostics to Therapeutics

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global threat with an ever-increasing death toll even after a year on. Hence, the rapid identification of infected individuals with diagnostic tests continues to be crucial in the on-going effort to combat the spread of COVID-19. Viral nucleic acid detection via real-time reverse transcription polymerase chain reaction (rRT-PCR) or sequencing is regarded as the gold standard for COVID-19 diagnosis, but these technically intricate molecular tests are limited to centralized laboratories due to the highly specialized instrument and skilled personnel requirements. Based on the current development in the field of diagnostics, the programmable clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) system appears to be a promising technology that can be further explored to create rapid, cost-effective, sensitive, and specific diagnostic tools for both laboratory and point-of-care (POC) testing. Other than diagnostics, the potential application of the CRISPR–Cas system as an antiviral agent has also been gaining attention. In this review, we highlight the recent advances in CRISPR–Cas-based nucleic acid detection strategies and the application of CRISPR–Cas as a potential antiviral agent in the context of COVID-19.