Miracle-dz/UniFAR-FTUs huggingface dataset:
The state of clean transport policy: a 2014 synthesis of vehicle and fuel policy developments

This inaugural State of Clean Transport Policy report compiles advancements in national and international regulations to reduce energy use, mitigate climate change, and control air pollution from motor vehicles and fuels across eleven major vehicle markets from January 2013 through August 2014. These eleven vehicle markets - China, the United States (US), the European Union (EU), Japan, Brazil, India, Russia, Canada, South Korea, Australia, and Mexico - represented 85% of total vehicle sales in 2013. This report quantifies the benefits associated with environmental policies for light- and heavy-duty vehicles, marine vessels, aircraft, and fuels in terms of reduced greenhouse gas (GHG) emissions and local air pollution, fuel savings, and benefits to public health. Where opportunities are identified, the report also estimates the potential for additional benefits associated with the adoption of best-practice policies. The scope of this report excludes motorcycles, locomotives, and off-road vehicles. Future editions may expand to include other modes of transport, additional markets, or regulations for mobile refrigerants. Also excluded from this report are policies aimed at reducing transport activity and shifting people and goods to more environmentally-friendly modes, although such actions are also important to meet global environmental goals.
A ship for the taking: the wreck of the Brisbane as a case study in site salvage and material culture reuse

On the 10th of October 1881 the Brisbane, a large, modern and well equipped steamship carrying passengers and cargo struck Fish Reef, approximately 25 nautical miles from Port Darwin, and became permanently stranded. What followed over the next three months was an organised salvage programme in which the ship was salvaged of cargo, equipment and fittings. These goods were sold to Port Darwin locals through a series of auctions. The wreck provided a wide selection of second-hand goods to a small isolated community. Approximately one hundred years later locals return to this wreck to take objects they considered of value. This thesis is a case study in material culture salvage and reuse of material from the Brisbane. Local men purchased the wreck in 1881 and presided over an extensive salvage programme in which maritime technical equipment and a range of other equipment, furnishings and fittings were removed, sold and reused. Some items were not salvaged and were left on the wreck site, these being visible today. The decision of salvors to not reuse some machinery and equipment challenges broad assumptions that isolated pioneer settlements, with poor access to goods, without fail practiced full scale salvage and reuse out of necessity. This thesis examines what was taken, why it was selected and how it was used. Recent cases of salvage in which objects are valued as historic ornaments are analysed in detail to demonstrate that there is no consensus to either the historic value of this wreck or its objects. Analysing the kinds of qualities attributed to historic ornaments, identifying them for example as antiquities or curios, reflect different ways in which people engage with the past. A comparison of salvage in 1881 to that more recent shows change in how salvage and reuse have functioned as social mechanisms. This thesis emphasises that object transformations may not involve physical modification, and that object meaning is relevant to a specific time and place.
State of the Art Paper: Biomimetics: Adapting Performance and Function of Natural Materials for Biobased Composites

Natural materials may serve as an excellent template for the design of high-performance manufactured materials. Because natural materials are fabricated at standard temperature and pressure from benign chemicals, adapting or mimicking nature's design methods and structures offers the potential to enhance performance, lower energy requirements, decrease toxic chemical accumulation, and create materials with life cycles that better correspond with the environment. As the forest products industry has matured, adapting naturally occurring designs has meant potential innovation for commodity markets, decreasing manufacturing inputs (energy, carbon, or other materials), and enhancing product performance. This study reviews nature-inspired pathways for biocomposites to 1) enhance the specific mechanical properties, 2) assemble materials from aqueous systems, 3) create hybrid inorganic-biopolymer composites, and 4) develop functional hydrophobic coatings and photonic colored films. To achieve controlled architectures found in natural materials, innovative production technologies that allow for timed processes and self-assembly must be applied to biobased composite manufacturing.
Soldier Cognitive Processes: Supporting Teleoperated Ground Vehicle Operations

Abstract : Although small ground robotic vehicles provide great promise and benefit to units, there are challenges to overcome if the maximum benefit is to be gained from the introduction of these systems. The robots offer a host of capabilities. However, a person must know how to operate the system procedurally (e.g., use the hand controller buttons, know the menu options) and tactically (e.g., understand what the system can and cannot do). Learning how to operate and employ the ground robotic vehicle imposes a cognitive load on top of other military skills, perceptual decision-making skills, and communication skills that need to be utilized while operating the system. Therefore, trainers and leaders must understand what loads are placed on operators. The major issue is to understand how cognitive load impacts operators performance. Finally, training materials and approaches for operators, especially when the operators have diverse backgrounds and skills, must be designed and developed so operators can effectively and efficiently take advantage of the capabilities offered by the small ground robotic vehicles.
Performance optimized, small structurally integrated ion thruster system

A 5-cm structurally integrated ion thruster has been developed for attitude control and stationkeeping of synchronous satellites. As optimized with a conventional ion extraction system, the system demonstrates a thrust T = 0.47 mlb at a beam voltage of 1600 V, total mass efficiency of 76%, and electrical efficiency of 56%. Under the subject contract effort, no significant performance change was noted for operation with two dimensional electrostatic thrust-vectoring grids. Structural integrity with the vectoring grids was demonstrated for shock (+ or - 30 G), sinusoidal (9 G), and random (19.9 G rms) accelerations. System envelope is 31.2 cm long by 13.4 cm flange bolt circle, with a mass of 9.0 Kg, including 6.8 Kg mercury propellant.
Intelligence and High Intensity Drug Trafficking Areas (HIDTA's): A Critical Evaluation of the HIDTA Investigative Support Center (ISC)

Abstract : The purpose of this thesis is to evaluate critically the ongoing reform of the High Intensity Drug Trafficking Area (HIDTA) Investigative Support Center (ISC). Prior to 9/11, the national intelligence apparatus was littered with flaws, including lack of information sharing, interagency conflict, and autonomous operations. The HIDTA Intelligence Support Center in New Mexico was no exception. Post 9/11, many national agencies realized that in order to address successfully the increasing threat of terror, several changes needed to be made in the intelligence system at all levels. Similarly, the HIDTA Investigative Support Center has reacted to the post 9/11 environment by more strictly enforcing its framework for information-sharing and instituting a series of changes in its institutional processes. This process of reform has yielded positive results for the New Mexico HIDTA ISC. The ISC has now transformed into the centerpiece of information exchange and interagency cooperation among HIDTA members. The ISC is also acting as a conduit or Fusion Center for information sharing between agencies investigating crimes relating to drug trafficking, terrorism, and money laundering.
The Effect of Company Characteristics on Voluntary Disclosure with Corporate Governance as a Moderated Variables

In the business world, information is the main source of economic decision making. Companies will be encouraged to disclose information related to the company's performance and prospects either voluntarily or not. The availability of important information that is needed by the users of the information is usually regulated by a regulator in a country. In Indonesia, the obligation to submit minimum information in the annual report of companies listed on the Indonesia Stock Exchange is regulated in Bapepam Rule Number X.K. 6. In the Indonesian capital market, the level of compliance of companies related to mandatory disclosure is quite good, namely 88.89% (Diyanti 2010). Meanwhile, voluntary disclosure in Indonesia is still low, namely 33.71% (Yanuarto 2012). This low level of voluntary disclosure does not only occur in Indonesia but also in several other developing countries, as found by Barako (2007) in Kenya (11% -20%), Soliman (2013) in Egypt (31.92%) , AlShammari (2008) in Kuwait (15%), Bhasin et al (2012) in Khazastan (24.95%), Yuen et al (2009) in China (21.4%), and Hammami and Hossain (2009). ) in Qatar (36.84%).
Work Places: The Psychology of the Physical Environment in Offices and Factories

Series forward Preface Acknowledgements 1. Introduction Part I. The Past: 2. Historical view of offices and factories 3. Psychology of the work place Part II. The Individual Worker: 4. Psychological processes 5. Lighting and windows 6. Temperature and air 7. Noise 8. Music 9. Colour 10. Work stations and supporting facilities Part III. Interpersonal Relations: 11. Symbolic workspace: self-identity and status 12. Communication 13. Privacy 14. Small groups Part IV. Organisations: 15. Office and factories as components of organisations Part V. The Future: 16. The future of offices and factories 17. Conclusions References Indexes.
Modeling the spatial distribution of forest crown biomass and effects on fire behavior with FUEL3D and WFDS

Crown fire poses challenges to fire managers and ca n endanger fire fighters. Understanding of how fire interacts with tree crowns is essential to informed decisions about crown fire. Current operational crown fire predictions in the United St ates assume homogeneous crown fuels. While a new class of research fire models, which model fire behavior with computational fluid dynamics (CFD), can be used to model fire in heterogeneous c rown fuels, the potential impacts of variability in crown fuels have not yet been explored. In this study we introduce a new model, FUEL3D, which incorporates allometric theory and a simple 3 D plant architecture approach to model the distribution of fuel within individual tree crowns. We then test the effects of crown fuel heterogeneity on fire behavior with a CFD fire mode l, WFDS, by simulating fire under a homogeneous tree crown and a heterogeneous tree crown modeled with FUEL3D, with two different levels of surface fire intensity; model o utput are used to estimate the probability of tree mortality, linking fire behavior and fire effects a t the scale of an individual tree. Variability with in a tree crown altered the timing, magnitude and dyna mics of how fire burned through the crown; effects varied with surface fire intensity. In the lower fire intensity case, the heterogeneous tree crown barely ignited and would likely survive, whil e the homogeneous tree had nearly 80% fuel consumption and an order of magnitude difference in net radiative heat flux. In the higher intensity case, both cases burned readily. Differences for th e homogeneous tree between the two surface fire intensity cases were minimal in nature but were dra matic for the heterogeneous tree. These results suggest that heterogeneity within the crown causes more conditional, threshold-like interactions with fire; both crown fire initiation and propagati on may be more sensitive to crown fuel architecture than currently considered.
Effects of saturation and hysteresis on magnetisation dynamics: Analysis of different material models

Purpose – The purpose of this paper is to provide a comprehensive analysis of different material models when observing the magnetisation dynamics and power losses in non-oriented soft magnetic steel sheets (SMSSs). Design/methodology/approach – During the analysis four different magnetic material models were used for describing the static material characteristics, which characterised the materials’ magnetisation behaviour with increasing accuracies: linear material model, piecewise linear material model, non-linear H(B) characteristic and the static hysteresis material model proposed by Tellinen. The described material models were implemented within a parametric magneto-dynamic model (PMD) of SMSSs, where the dynamic responses as well as power loss calculations from the obtained models were analysed. Findings – The momentous influences of various levels of detail on the calculation of dynamic variables and power losses inside SMSS with non-uniform magnetic fields were elaborated, where various static mate.
QPoweredCompound2DeNovoDrugPropMax – a novel programmatic tool incorporating deep learning and in silico methods for automated in silico bio-activity discovery for any compound of interest

Abstract Network data is composed of nodes and edges. Successful application of machine learning/deep learning algorithms on network data to make node classification and link prediction have been shown in the area of social networks through which highly customized suggestions are offered to social network users. Similarly one can attempt the use of machine learning/deep learning algorithms on biological network data to generate predictions of scientific usefulness. In the presented work, compound-drug target interaction network data set from bindingDB has been used to train deep learning neural network and a multi class classification has been implemented to classify PubChem compound queried by the user into class labels of PBD IDs. This way target interaction prediction for PubChem compounds is carried out using deep learning. The user is required to input the PubChem Compound ID (CID) of the compound the user wishes to gain information about its predicted biological activity and the tool outputs the RCSB PDB IDs of the predicted drug target interaction for the input CID. Further the tool also optimizes the compound of interest of the user toward drug likeness properties through a deep learning based structure optimization protocol. The tool also incorporates a feature to perform automated In Silico modelling to find the interaction between the compounds and the predicted drug targets to uncover their protein-ligand interaction profiles. The program is hosted, supported and maintained at the following GitHub repository. https://github.com/bengeof/Compound2DeNovoDrugPropMax. Anticipating the use of quantum computing and quantum machine learning in drug discovery we use the Penny-lane interface to quantum hardware to turn classical Keras layers used in our machine/deep learning models into a quantum layer and introduce quantum layers into classical models to produce a quantum-classical machine/deep learning hybrid model of our tool and the code corresponding to the same is provided below. https://github.com/bengeof/QPoweredCompound2DeNovoDrugPropMax. HIGHLIGHTS Deep learning based network pharmacology approach to predict the bio-activity of compounds. Further optimization of the compound toward drug like properties using deep learning techniques. Automated in silico modeling and interaction profiling of deep learning predicted target protein-ligand interaction. Communicated by Ramaswamy H. Sarma
Viral Membrane Fusion Proteins and RNA Sorting Mechanisms for the Molecular Delivery by Exosomes

The advancement of precision medicine critically depends on the robustness and specificity of the carriers used for the targeted delivery of effector molecules in the human body. Numerous nanocarriers have been explored in vivo, to ensure the precise delivery of molecular cargos via tissue-specific targeting, including the endocrine part of the pancreas, thyroid, and adrenal glands. However, even after reaching the target organ, the cargo-carrying vehicle needs to enter the cell and then escape lysosomal destruction. Most artificial nanocarriers suffer from intrinsic limitations that prevent them from completing the specific delivery of the cargo. In this respect, extracellular vesicles (EVs) seem to be the natural tool for payload delivery due to their versatility and low toxicity. However, EV-mediated delivery is not selective and is usually short-ranged. By inserting the viral membrane fusion proteins into exosomes, it is possible to increase the efficiency of membrane recognition and also ease the process of membrane fusion. This review describes the molecular details of the viral-assisted interaction between the target cell and EVs. We also discuss the question of the usability of viral fusion proteins in developing extracellular vesicle-based nanocarriers with a higher efficacy of payload delivery. Finally, this review specifically highlights the role of Gag and RNA binding proteins in RNA sorting into EVs.
Relations Between Tourism Spending and Global Competitiveness – an Empirical Study in Developed OECD Countries

Global trends indicate a systematic increase in the importance of tourism. From an economic point of view, spending plays an essential role in the spectrum of tourism services indicators. Simultaneously, the competitiveness of economies is a key economic indicator; thus, research in this area is considered beneficial. This study's objective was to assess the significance of the structure of clients' spending on tourism in the context of the global competitiveness of OECD countries, with the primary focus on the effect of individual types of tourism spending on competitiveness. Several analytical procedures were used in the processing, such as descriptive analysis, relationship analysis, regression analysis, and cluster analysis. Secondary data were included in the analyses, and these data represented six variables determining tourism spending obtained from the World Travel & Tourism Council (WTTC) database: i - Business Tourism Spending (BTS), ii - Domestic Tourism Spending (DTS), iii - Internal T&T Consumption (ITTC), iv - Leisure Tourism Spending (LTS), v - Outbound Travel & Tourism Expenditure (OTTE), vi - Visitor Exports (Foreign spending) (VEFS); and one variable determining competitiveness: the Global Competitiveness Index (GCI), which was obtained from reports published by the World Economic Forum (WEF). These data were collected for all OECD countries from 2010 to 2018. The results of the regression analysis clearly confirmed the effect of tourism spending on competitiveness in OECD countries. The most significant effects were found in BTS and OTTE, and the least significant impact was identified in VEFS. The results provide valuable information for strategic and development plan makers and institutions responsible for improving the business environment in tourism. The study and its results also offer space for developing national and international benchmarking indicators in this area.
L-arginine and tetrahydrobiopterin modulate endothelin-1A receptor activity in isolated rat aorta

Endothelin-1 (ET-1), is a potent endogenous vasoconstrictor secreted by endothelial cells. It acts as the natural counterpart of the vasodilator effect of nitric oxide (NO). ET-1 exert it is the vasoconstrictor activity through two types of receptors, ET-1A and ET-1B receptors that are located on vascular smooth muscle cells (VSMCs). The present study was designed to evaluate the effect of L-arginine (LA), tetrahydrobiopterin (BH4), and their combination on ET-1A receptor activity in rat aortic rings. The study involved pre-incubation of rat aortic rings with LA, BH4, and their combination. Then, the vascular response to a cumulative dose of the ET-1A receptor antagonist (BQ-123) and in the second set of experiment cumulative doses of Acetylcholine (ACh) were applied to each group. BQ-123 potency increased after LA pre-incubation, but LA and BH4 in combination significantly potentiated BQ-123 potency and maximum response. In the second set of experiment, ACh potency does not change, while ACh efficacy markedly increased during pre-incubation of LA, BH4, and their combination. In conclusion, LA and BH4 may offer some pharmacological tools to modulate the ET-1A receptor activity and treat cardiovascular disease beyond pulmonary arterial hypertension.
Channel Estimation for OFDM System using Training Sequence Algorithms

Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation and multiplexing technique proposed for 3G, 4G LTE-A systems to achieve higher data rates with better spectral efficiency at low latency. Time varying nature of the wireless channel can cause frequency selectivity and multipath fading which affects performance of the system badly. Channel estimation techniques are proposed to tackle the issue and results in improved performance. In this paper, training based channel estimation techniques like Least Square and Minimum Mean Square Error are discussed. Both techniques are compared for Bit Error Rate (BER) performance and computational complexity in MATLAB.
Low peak current class E resonant full-wave low dv/dt rectifier driven by a voltage generator

Full-wave rectifiers allow a halving of the diode peak voltages (or currents), but these values may still be high at duty factor values far from 0.5. The first member of a new family of class E resonant full-wave rectifiers is proposed and analyzed, whose peak diode current is equal to the load current. Diode voltage slopes are ideally zero after switch-off only for duty factors larger than 0.5. The circuit contains two rectifier diodes but a single LC circuit. All major parasitic reactive elements are included in the rectifier topology. Basic parameters of the circuit are derived as functions of the diodes' duty factor, using time-domain analysis. Experimental waveforms and measurements agree with simulations and calculations.
Use of the Micro-Deval Test for Assessing the Durability of Virginia Aggregates

Aggregate is one of the most widely used construction material, and the key aspect of aggregate quality is durability. In this study, the Micro-Deval test, a new test developed in France and modified by Canadians, was studied to evaluate its suitability in assessing the durability of coarse and fine aggregates from Virginia sources. The Micro-Deval and several known aggregate tests were compared. The Micro-Deval test showed a very high potential in evaluating aggregate durability with higher precision and accuracy than the conventional tests such as the magnesium sulfate and Los Angeles abrasion tests. The Micro-Deval test was able to differentiate between good and poor performing aggregates at least 70 percent of the time and was able to identify the quality difference between similar aggregate types with varying degrees of weathering. Because of the study findings, the researchers recommend that the Micro-Deval test be used as a quality control tool for aggregate assessment to supplement the current measures of aggregate quality.