Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization

A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a particular health effect of a predefined magnitude, the critical effect size (CES). The exposure level that results in exactly that CES in a particular person is that person's individual critical effect dose (ICED). Individuals in a population typically show variation, both in their individual exposure (IEXP) and in their ICED. Both the variation in IEXP and the variation in ICED are quantified in the form of probability distributions. Assuming independence between both distributions, they are combined (by Monte Carlo) into a distribution of the individual margin of exposure (IMoE). The proportion of the IMoE distribution below unity is the probability of critical exposure (PoCE) in the particular (sub)population. Uncertainties involved in the overall risk assessment (i.e., both regarding exposure and effect assessment) are quantified using Monte Carlo and bootstrap methods. This results in an uncertainty distribution for any statistic of interest, such as the probability of critical exposure (PoCE). The method is illustrated based on data for the case of dietary exposure to the organophosphate acephate. We present plots that concisely summarize the probabilistic results, retaining the distinction between variability and uncertainty. We show how the relative contributions from the various sources of uncertainty involved may be quantified.
Balancing control for grid-scale battery energy storage system

Lithium (Li)-ion cells are becoming increasingly attractive for use in grid-scale battery energy storage systems (BESSs). A key problem with BESSs is the potential for poor utilisation of mismatched cells and reliability issues resulting from the use of large series strings of cells. This paper investigates the close integration of a full-bridge modular multi-level converter and a large number of lithium-ion cells interfacing with an AC electrical grid. The cells are organised in a hierarchical structure consisting of modules, sub-banks, banks and phases. The control strategy includes five levels of balancing: balancing of cells within a module, balancing of modules within a sub-bank, sub-banks within banks, banks within phases and balancing between phases. The system is validated in simulation for a 380 kWh BESS using 2835 lithium-ion cells. Charge balancing is demonstrated for mismatched cells by varying the parameters such as ampere-hour capacity, internal resistance and initial state of charge. A ‘peak sharing’ concept is implemented so that alternative modules assume a portion of the load when certain modules are not capable of meeting the demand. This work is intended to address the challenges of eventual scaling towards a 100 MWh + BESS, which may be composed of 100 000 individual cells.
Enhancement low-voltage ride through capability of permanent magnet synchronous generator-based wind turbines using interval type-2 fuzzy control

Increased penetration level of the wind power generation has brought new issues and challenges of power quality. One of these issues is low-voltage ride through (LVRT). This study proposes an LVRT scheme for the permanent magnet synchronous generator (PMSG) variable speed wind turbine at grid faults. The machine side converter controller is used to control the dc-link voltage using interval type-2 fuzzy logic control taking into account the non-linear relationship between the generator speed and the dc-link voltage. Under grid faults, there is a power mismatch between the generated active power and the active power delivered to the grid. This excess power is stored in the generator inertia to keep the dc-link voltage constant. To validate the proposed control strategy, simulation results for 1.5 MW PMSG-based wind energy conversion system are carried out by MATLAB-Simulink under symmetrical and asymmetrical faults.
Will RANS Survive LES? A View of Perspectives

The paper provides a view of some developments and a perspective on the future role of the Reynolds-averaged Navier-Stokes (RANS) approach in the computation of turbulent flows and heat transfer in competition with Large-eddy simulations (LES). It is argued that RANS will further play an important role, especially in industrial and environmental computations, and that the future increase in the computing power will be used more to utilize advanced RANS models to shorten the design and marketing cycle rather than to yield the way to LES. We also discuss some current and future developments in RANS aimed at improving their performance and range of applicability, as well as their potential in hybrid approaches in combination with the LES strategy. Limitations in LES at high Reynolds (Re) and Rayleigh (Ra) number flows and heat transfer are revisited and some hybrid RANS/LES routes are discussed. The potential of very large eddy simulations (VLES) of flows dominated by (pseudo)-deterministic eddy structures, based on transient RANS (T-RANS) and similar approaches is discussed and illustrated in an example of “ultra-hard” (very high Ra) thermal convection.Copyright © 2004 by ASME
AUTOMATION BY LABORATORY ROBOTICS IN PHARMACEUTICAL RESEARCH INDUSTRY: A LATEST VENTURE IN INNOVATIVE IDEA

Robots in laboratory, life science and pharmaceutical applications perform tasks at rates beyond human capability. These robots function in potentially hazardous settings in proximity to biological dangers, the threat of radioactive contamination and toxic chemotherapy compounds. Robotics is called upon to assemble and package a variety of medical devices and implants as well as preparing prescriptions for mail-order pharmacies or hospitals. Robots are doing assay analysis and automating the movement of test tubes in research laboratories. Because of the high number of samples that need analysis and the amount of data collection required, the process and costs are easily validated with robotics. In pharmaceutical applications, hospitals use robots to mix potentially hazardous cancer drugs and those associated with radiation. The Laboratory Robotics Interest Group (LRIG) is an international non-profit organization dedicated to the study and discussion of laboratory automation. LRIG activates the uses of laboratory automation in high-throughput screening, drug discovery, combinatorial chemistry, chemical synthesis, compound purification, compound distribution, data management, pharmaceutical dosage form sample preparation, dissolution testing, bio analytical technology, chemical analysis, solid phase extraction, validation and product formulation.
Performance of a Heat Pipe Solar Collector

This paper presents a comparative study between theoretical predictions and experimental results of a flat-plate solar collector with heat pipes. The theoretical model for the heat pipe solar collector is based upon the method by Duffie and Beckman (1980), modified to use heat pipes for energy transport. The methanol filled heat pipes are self-contained devices whose evaporators are inserted under pressure in the flat plate of the solar collector and the heat exchange is carried out at their condensers. The evaporators contain a wick of one mesh layer to ensure a better distribution of the working fluid. The condensers are wickless and inclined 15 deg more than the inclination of the evaporators to facilitate the return of the condensate to the evaporators. The time constant of the heat pipe solar collector was calculated and found to be about 23 minutes. Also presented in this paper are comparative experimental results of the proposed solar collector and a conventional commercial solar collector. The two collectors were tested simultaneously. The instantaneous efficiencies of the heat pipe solar collector are lower than the conventional collector in the morning and higher when the heat pipes reach their operating temperatures.
Insects and their Laboulbeniales (Ascomycota, Fungi) of Lake Eustis and Emeralda Marsh Conservation Area: A case study on urbanization and diversity

Abstract A rapid biodiversity assessment of insects and associated Laboulbeniales fungi was conducted over the course of five nights in August, 2018, at two central Florida lakes: Lake Eustis and the nearby protected and restored National Natural Landmark, Emeralda Marsh Conservation Area (EMCA), which encompasses a portion of Lake Griffin. Lake Eustis was surveyed for Laboulbeniales in 1897 by mycologist Dr. Roland Thaxter but has not since been investigated. Because Lake Eustis has been urbanized, with the lake perimeter almost entirely altered by human development, the site offers a look into Laboulbeniales diversity across a 121‐year timeline, before and after human development. By surveying Lake Eustis and EMCA, a modern case study comparison of Laboulbeniales and insect diversity between a developed and a protected and restored system is made. A total of 4022 insects were collected during the rapid assessment. Overall, insect abundance was greater at EMCA, with 3001 insects collected, than 1021 insects collected from Eustis. Although family‐level insect richness was comparable between sites, with 55 families present at EMCA and 56 at Eustis, 529 out of 3001 (17.6%) of the insects collected at EMCA were hosts to parasitic Laboulbeniales fungi, whereas only 2 out of 1021 (0.19%) collected from Eustis were infected. A total of 16 species of Laboulbeniales found at EMCA compared with only one at Eustis. The current number of Laboulbeniales species documented at Eustis was incredibly depauperate compared with the 26 species and two varieties recorded by Thaxter in 1897. These findings suggest the possibility of utilizing Laboulbeniales as indicators of ecosystem health, and future research should investigate this question further. A figure displaying host–parasite records and a species list of Laboulbeniales are presented. Finally, updated occurrence records for species of Ceratomyces and Hydrophilomyces are provided.
Study of Burst Alarming and Data Sampling Frequency in Water Distribution Networks

AbstractIn recent research, the residual of the Kalman filter applied to flow measurements in water distribution systems has been found to strongly correlate with bursts. A positive residual represents an unexpected extra flow, which is likely caused by an event such as a burst in the downstream network. However, there is a certain level of uncertainty in the flow measurements, leading to a noisy and fluctuating residual during normal and abnormal network operations. This work investigates how changes to a residual threshold affect the success rates of burst alarming during burst and nonburst periods, respectively, and presents a statistical method to automatically select a suitable residual threshold to tolerate uncertainty in flow measurements. In addition, this work also investigates how the number of burst alarms is influenced by using different flow measurement sampling frequencies and different averaging window sizes in the data sets. Engineered tests with three simulated burst events were conducted.
A V‐band band‐pass filter design using advanced integrated passive devices technology

This article presents a design approach of a band‐pass filter which is fabricated on an integrated passive device process and is capable of operating over the unlicensed 60‐GHz band (57–64 GHz). The band‐pass filter proposed in this article evolves from a typical one comprising two identical, mirrored open‐loop half‐wavelength microstrip line resonators. The experimental results demonstrate an insertion loss of less than 2.4 dB, a return loss of better than 10 dB over the 60‐GHz band, and a 3‐dB bandwidth of 24 GHz (∼42%). The simulation and measurement results are well matched up to 110 GHz. This filter is suited for system‐in‐a‐package V‐band front‐end systems. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:199–202, 2016
Probabilistic lane detection and lane tracking for autonomous vehicles using a cascade particle filter

This paper proposes a robust lane detection algorithm with a cascade particle filter that incorporates a model decomposition approach. Despite the sophisticated tracking mechanism of a particle filter, the conventional particle-filter-based lane detection system suffers from an estimation accuracy problem and a high computational load. In order to improve the robustness and the computation time for lane detection systems, the proposed cascade particle filter decomposes a lane model into two submodels: a straight model and a curve model. By dividing the lane model, not only can the computation time be decreased, but also the accuracy of the lane state estimation system can be increased. The proposed lane detection algorithm and the cascade particle filter were evaluated on various roads and environmental conditions with the autonomous vehicle A1, which was the winner of the 2010 and 2012 Autonomous Vehicle Competition in the Republic of Korea organized by the Hyundai motor group. The proposed algorithm proved to be sufficiently robust and fast to be applied to autonomous vehicles as well as to intelligent vehicles for improving the vehicle safety.
Towards energy efficient content delivery networks

A content delivery network (CDN) typically consists of geographically-distributed data centers (DCs), which are deployed within proximity to end-users who request Internet content. Content copies are stored at the DCs and are delivered to end-users in a localized manner to improve service availability and end-to-end latency. On one hand, CDNs have improved QoS experienced by end-users. On the other hand, the rapid increase in Internet traffic volume has caused the global DC industry's energy usage to skyrocket. Therefore, our focus in this thesis is to realize energy awareness in CDN management while assuring end-to-end QoS. First, we surveyed the literature on energy-aware DC and CDN management schemes. We highlighted the significance of dynamically provisioning server and network resources in DCs in order to reduce DC energy usage. We also recognized that in order to achieve optimal CDN energy saving, energy optimization should be performed both within each DC and among multiple DCs in a CDN. Second, we proposed a theoretical framework that minimizes server power consumption in cross-domain CDNs. The term "server" refers to any co-locating entity that can handle user requests, e.g., server clusters or DCs. Our strategy was to put a subset of servers to sleep mode during off-peak hours to save energy. In order to avoid deteriorated QoS caused by less live server resources, we enforced constraints on utilization of servers and network links respectively to avoid them from being overloaded. Third, we designed an energy-aware CDN management system. The strategy was not only to put a subset of servers within each DC to sleep, but also to put entire DCs to sleep during off-peak hours through load unbalancing among DCs. We showed how the proposed system can be integrated within a typical modern CDN architecture. We also developed a heuristic algorithm that allows CDN operators to quickly make decisions on server and DC sleeping, as well as energy-aware request resolution. QoS was assured through constraints on server response time and end-to-end delay. Fourth, we built an optimization model that minimizes the overall energy consumption of CDN DCs, including their servers and cooling systems. We derived a lower bound to its optimal objective. Through comparing with the lower bound, we showed that our earlier developed heuristic algorithm's energy-saving gain was guaranteed to be near-optimal. We also quantitatively studied the trade-off between CDN energy saving and QoS performance in terms of end-to-end delay and server response time.
Institutions and Economic Performance: A Critical Evaluation of the Nigeria Economy

: The objective of this study is to critically evaluate the impact of institutions on the economic performance of Nigeria. To achieve this, annual time series data were employed from 1999 to 2020. Six institutional quality indicators of Political Stability Index, corruption perception index, Voice and Accountability, Rule of Law, Regulatory Quality, and Ease of Doing Business indicator, were employed as the independent variables while the dependent variable, economic performance was proxied by Gross Domestic Product (GDP) Per Capita. The result indicates that all the indicators of institutional quality have positive impact on economic performance in Nigeria in the period under review. Political Stability Index, Corruption Perception Index, Regulatory Quality and Ease of doing business have significant impact on economic performance while Voice and Accountability as well as Rule of Law had insignificant positive effect. The study concludes that there is the need for strong institutions in Nigeria as it engenders higher economic performance, thus noting that institution is the oil that lubricates the engine of economic growth and development in an economy.
Redesigning learning spaces through students and academics contributions: the role of participatory design

Participatory design is a trend for designing products and services which suggests that end-users become active participants in the design of what they consume. This concept originated in the Scandinavian countries, matches with new trends in learning and teaching in which learners construct their knowledge by dialogue, discussion and negotiation, hence through participation and engagement. Simultaneously, it also implies that institutions embrace plurality and diversity of perceptions by joining different stakeholders in designing aspects of the learning and teaching process. In this paper we present a research experience in its preliminary stage wherein using a Participatory Design approach we will re-design technology-enabled learning spaces by combining the perceptions of students and teaching staff in individual and group design sessions. We aim to build the foundations for discussing learning spaces as a dynamic and co-designed concept that can bridge the gap between staff and student perceptions of learning spaces.
Evaluation of Permeability of Superpav® Asphalt Mixtures

The presence of water in a pavement system is detrimental to its life. Permeable asphalt concrete pavement structures are vulnerable to stripping, which causes premature damage under heavy traffic. To assess the permeability of asphalt mixtures, a research study was conducted at the Louisiana Transportation Research Center (LTRC). Laboratory permeability tests were performed on field cores taken from 17 Superpave® projects in Louisiana. An LTRC-modified version of Karol-Warner's falling-head permeameter was used to conduct the permeability test. A sensitivity analysis was performed to relate the permeability test results to mixture volumetric properties such as air void content, compaction effort, mixture gradation, and lift thickness. A statistical regression model was developed to predict the permeability of Superpave mixtures from the mixture volumetric properties. The model successfully predicted the coefficient of permeability of asphalt mixtures from a separate data set that was not included in the model development.
ELECTROSTATIC SIMULATIONS FOR TWO-DIMENSIONAL SEMICONDUCTOR-SUPERCONDUCTOR HYBRID DEVICES

In this thesis we study the electrostatics of recently investigated two dimensional semiconductorsuperconductor hybrid devices, that host Majorana Zero Modes (MZMs) [Fornieri et al., 2019],[Nichele et al., 2017]. We conduct electrostatic simulations using COMSOL multiphysics, and solve a three dimensional Thomas-Fermi model using the finite element method. In our work, we have successfully recreated experimental data from three recently investigated devices, by reproducing qualitative features of experimental conductance gate-gate maps. The devices are based on InAs/InGaAs quantum wells realized in planar heterostructures, in contact with a superconducting layer [Shabani et al., 2016]. We have verified experimental intuition regarding the geometry of the devices, and how this affects tunneling spectroscopy in the devices. We focus on the electrostatic potential generated by quantum point contacts (QPC’s), formed by two negatively biased split gates, placed at the edge between a superconducting and a non-superconducting region. We show that when the QPCs are in proximity of another grounded gate at 0V, it is possible to define a sharp tunnel barrier that can be used to perform effective tunneling spectroscopy.
Contextualizing entrepreneurial identity amongst Syrian refugees in Jordan: the emergence of a destabilized habitus?

This paper aims to contextualise the entrepreneurial identity of Syrian refugees living outside refugee camps in Jordan. The research adopts a social lens to consider the situation Syrians find themselves in by drawing on the work of Bourdieu. A qualitative design is applied to explore the different experiences and perceptions that pervade refugee stories and the work of refugee aid agencies. By contextualising entrepreneurial identity in the Jordanian context, the paper reveals how a destabilized refugee habitus based on an embodied disposition of survivability is emerging. The paper makes an empirical and conceptual contribution by highlighting how the entrepreneurial activities of Syrian refugees are driven by their experiences of the harsh social conditions they find themselves in.
Chronic pharmacological antagonism of murine GM-CSF-R-alpha does not replicate the Pulmonary Alveolar Proteinosis phenotype but does alter lung surfactant turnover.

Granulocyte macrophage colony stimulating factor (GM-CSF) is a key participant in, and a clinical target for, the treatment of inflammatory diseases including rheumatoid arthritis (RA). Therapeutic inhibition of GM-CSF signalling using monoclonal antibodies to the α-subunit of the GM-CSF receptor (GMCSFRα) has shown clear benefit in patients with RA, giant cell arteritis (GCA) and some efficacy in severe SARS-CoV-2 infection. However, GM-CSF autoantibodies are associated with the development of pulmonary alveolar proteinosis (PAP), a rare lung disease characterised by alveolar macrophage (AM) dysfunction and the accumulation of surfactant lipids. We assessed how the anti-GMCSFRα approach might impact surfactant turnover in the airway. Female C57Bl/6J mice received a mouse-GMCSFRα blocking antibody (CAM-3003) twice per week for up to 24 weeks. A parallel, comparator cohort of the mouse PAP model, GMCSFRβ knock-out (KO), was maintained up to 16 weeks. We assessed lung tissue histopathology alongside lung phosphatidylcholine (PC) metabolism using stable isotope lipidomics. GMCSFRβ KO mice reproduced the histopathological and biochemical features of PAP, accumulating surfactant PC in both broncho-alveolar lavage fluid (BALF) and lavaged lung tissue. The incorporation pattern of methyl-D9-choline showed impaired catabolism and not enhanced synthesis. In contrast, chronic supra-pharmacological CAM-3003 exposure (100mg/kg) over 24 weeks did not elicit a histopathological PAP phenotype despite some changes in lung PC catabolism. Lack of significant impairment of AM catabolic function supports clinical observations that therapeutic antibodies to this pathway have not been associated with PAP in clinical trials.
Design of Quadrature Mirror Hilbert Transformers with Perfect Reconstruction

Applying a /2 π frequency shift to the original quadrature mirror filter bank (QMFB), ( ) ( ) 0 0 z H z H z P - = . The related QMHT is obtained by substituting -jz z → into ( ) z P. This work establishes the relationship between QMFB and QMHT for systems with perfect reconstruction. For a given QMFB, filter specifications and the design procedure for the QMHT are investigated.