Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity Management in the New South Africa: An Acculturation Approach

Orientation: Multiculturalism seemed to have become the dominant strategy for dealing with pluralism in the South African public sphere. Research purpose: The authors addressed the relationship between conditions that are considered to be conducive to multiculturalism and the practices perceived to accomplish this, vis-à vis multiculturalism and well-being, as measured by ill-health and subjective work success. Motivation for the study: Although multiculturalism has been recommended as an effective way of dealing with diversity at societal and local levels, little is known about its effects in the workplace. Research design, approach and method: Following a quantitative approach, the authors utilised a cross-sectional design with a convenience sample of 241 Black employees and White employees from a mine in North-West Province for the research. Exploratory factor analyses and Cronbach alpha coefficients were used to test scale validity and reliability. Multivariate Analysis of Variance (MANOVA) and effect sizes was used to determine the effect of race on the experiences of miners, and multigroup path analysis (AMOS) was used to investigate whether or not identical relations between multiculturalism, work success, and ill-health could be found for Black employees and White employees. Main findings: Multiculturalism and mainstream tolerance coupled with ethnic integration demands at home and work were associated with success at work but not with ill-health. Black employees experienced the workplace slightly more positively. Practical/managerial implications: Multiculturalism and integration are related to subjective experiences of work success and, as such, should be supported in the workplace. Contribution/valueadd: Our findings suggest that multiculturalism is relatively well supported by both groups in the workplace. This positive finding should not be regarded as obvious because empirical research has suggested that the majority of members of the host culture do not always favour multiculturalism.
Pre-Launch Assessment of RADARSAT Constellation Mission Medium Resolution Modes for Sea Oil Slicks and Lookalike Discrimination

Abstract The RADARSAT Constellation Mission (RCM) is a Canadian Synthetic Aperture Radar (SAR) mission, providing C-band SAR data continuity of the RADARSAT-1 and RADARSAT-2 satellite missions. The RCM which was recently launched (June 2019) will provide compact polarimetry (CP) as a polarization option for all non-quad-polarization imaging modes. Maritime pollution monitoring is one of the RCM core applications. Thus, the purpose of this study is to provide an initial evaluation of the expected potential of the RCM mission for maritime pollution monitoring. Herein, we investigate simulated CP SAR data of three RCM Medium Resolution (MR) SAR modes for oil slick detection and discrimination from lookalike (LA) features. Results of our study indicated that the steeper radar incidence angle seems to be preferable for oil slick detection in all examined modes. The ScanSAR 50 m resolution (SC50M) mode showed the highest overall performance in terms of LA and Emulsion (EM) classification (95.4%). This was also valid for LA and Crude Oil (CO) classification (96.7%). The performance of the SC50M mode was slightly higher than that of the ScanSAR 30 m resolution (SC30M) mode.
Reproducible Partial-Load Experiments in Workload Colocation Analysis

Performance evaluation of computer systems is an important area of computer science research with a broad audience—understanding the performance of computer systems is of interest to datacenter operators, software architects, and researchers alike. Performance evaluation traditionally focuses on peak performance of a system at certain task, measured using real-world or synthetic workloads executing on dedicated hardware. However, recent advances in virtualization technology have turned dedicated hardware into a mere design option, and increasing amount of computation takes place in virtual machines deployed on public or private cloud platforms.
Ship Detection Using a Fully Convolutional Network with Compact Polarimetric SAR Images

Compact polarimetric synthetic aperture radar (CP SAR), as a new technique or observation system, has attracted much attention in recent years. Compared with quad-polarization SAR (QP SAR), CP SAR provides an observation with a wider swath, while, compared with linear dual-polarization SAR, retains more polarization information in observations. These characteristics make CP SAR a useful tool in marine environmental applications. Previous studies showed the potential of CP SAR images for ship detection. However, false alarms, caused by ocean clutter and the lack of detailed information about ships, largely hinder traditional methods from feature selection for ship discrimination. In this paper, a segmentation method designed specifically for ship detection from CP SAR images is proposed. The pixel-wise detection is based on a fully convolutional network (i.e., U-Net). In particular, three classes (ship, land, and sea) were considered in the classification scheme. To extract features, a series of down-samplings with several convolutions were employed. Then, to generate classifications, deep semantic and shallow high-resolution features were used in up-sampling. Experiments on several CP SAR images simulated from Gaofen-3 QP SAR images demonstrate the effectiveness of the proposed method. Compared with Faster RCNN (region-based convolutional neural network), which is considered a popular and effective deep learning network for object detection, the newly proposed method, with precision and recall greater than 90% and a F1 score of 0.912, performs better at ship detection. Additionally, findings verify the advantages of the CP configuration compared with single polarization and linear dual-polarization.
Compressive Sampling and Real-Time Data Transportation in MPAR Backend System

Massive data transportation has been an important bottleneck for the Multi-functional Phased Array Radar (MPAR), as the diversified waveforms require increasing sampling speeds for traditional quadrature sampling. In this work, we propose a method that “compresses” the quadrature (I/Q) data to reduce the data link bandwidth and transaction time between the receiver front-end and the processing unit of a phased array system. Keywords—quadrature sampling; data compression; phased array system
Mitigating and Tolerating Read Disturbance in STT-MRAM-Based Main Memory via Device and Architecture Innovations

As an important nonvolatile memory technology, spin transfer torque magnetoresistive RAM (STT-MRAM) is widely considered as a universal memory solution for future processors. Employing STT-MRAM as the main memory offers a wide variety of benefits, but also results in unique design challenges. In particular, read disturbance characterizes accidental data corruption in STT-MRAM after it is read, leading to the need of restoring data back to memory after each read operation. In this paper, we propose both device and architecture innovations to mitigate and tolerate read disturbance. First, we quantitatively demonstrate the relationship between read disturbance and key device parameters, conducting a number of read disturbance mitigation schemes. These device-level schemes turn out to be effective in reducing the read disturbance probability, but come with costs on other design metrics. Consequently, we further propose a restore-aware memory controller design at the architecture level to tolerate read disturbance. Since the extra restores incurred by read disturbance greatly change the timing scenarios that conventional memory controllers were optimized for, directly adopting restore-agnostic DRAM memory management techniques will lead to suboptimal designs for STT-MRAM. Therefore, we propose restore-aware policy selection (RAPS), a dynamic and hybrid row buffer management scheme that factors in the inevitable data restores in STT-MRAM-based main memory. RAPS monitors the row buffer hit rate at run time, dynamically switching between two static page-closure policies. By factoring in restores, RAPS accurately captures the optimal design points, achieving optimal policy selections at run time. Our experimental results show that RAPS significantly improves system performance and energy efficiency compared to conventional page-closure policies.
The distributional pattern of benthic macroinvertebrates in a spring-fed foothill tributary of the Ganga River, western Himalaya, India

Benthic macroinvertebrates play important ecosystem roles in the cycling and outflow of nutrients. The benthos transforms organic detritus from sedimentary storage into dissolved nutrients that can be mixed into overlying waters and used by rooted plants (macrophytes) and algae (phytoplankton) to enhance primary productivity. This study examined the distribution pattern of benthic macroinvertebrates in a lesser Himalayan foothill stream from the headwaters (2,200m) to mouth (375m). Five stations (S1 to S5) were established along the 43-km course of the stream. Samples were collected at bi-monthly intervals from January to December 2009. The total density of the benthic macroinvertebrate community increased with decreasing altitude and differed significantly among stations. Dominant orders were Diptera at S1 (Simulidae, 27%) & S5 (Chironomidae 24%), Trichoptera at S2 (Limnephilidae 16%) & S3 (Hydropsychidae 9.9%), and Ephemeroptera (Heptageniidae 9.2%) at S4. Principal component analysis revealed that the characteristic taxa were Simulidae at S1, Limnephildae at S2, Hydropsychiidae, Rhyacophilidae, Tipulidae, Perlodidae, Dryopidae & Notonectidae at S3, Heptageniidae at S4, and Chironomidae, Siphlonuridae, & Agrionidae at S5. Cluster analysis showed one large cluster comprising S1 and S2 as sub-groups with resemblance to S3-S4, and S5 as an outlier. The similarity between the stations S3-S4 was attributed to similar land-use pattern (agriculture) and stream order (II Order), while S1 and S2 were slightly similar due to partial similar forest type (oak forest at S1, pine-oak forest at S2) and stream order. At S5, however, the considerable change in forest type (mixed forest) land-use and stream order (III Order) caused S5 as an outlier in cluster. The variations in the abundant and characteristics taxon at different stations were attributed to change in substratum and land-use patterns.
Looking Beyond the Surface: Use of High Resolution X-Ray Computed Tomography on Archaeobotanical Remains

High Resolution X-Ray Computed Tomography (HRXCT) offers a powerful 3-dimensional, non-destructive and non-invasive diagnostic tool for imaging the external and internal structures of a range of specimens of interest including archaeobotanical remains. HRXCT offers new possibilities in terms of the research questions which may be asked of fragile and valuable archaeological and specifically archaeobotanical material. This technology, although currently somewhat limited in terms of time and access to beamtimes at National Synchrotrons, requires simple, non-destructive preparation of samples and produces exciting results. Based upon two rounds of successful work we believe that this new methodology has wider implications and utility for advancing the field of imaging, and investigating aspects of plant domestication such as internal anatomical changes.
Origin and Accumulation of Heavy Oils in the Qingdong Sag, Bohai Bay Basin, Eastern China

Numerous commercial oil reservoirs have been revealed in Qingdong Sag, a sub-sag of Jiyang Depression, Bohai Bay Basin (Wang Yongshi et al., 2017). Characteristics of crude oils in reservoirs of the fourth and third members of Paleogene Shahejie Formation (Es3 and Es4) in the Qingdong Sag are complex, with co-existence of conventional and heavy oil (Ma Lichi, 2014). Maturity of the major source rocks including dark mudstones of the Es3 and Es4 members of Shahejie Formation is mostly low in the study area except for the deep zone of the middlenorthern sag (Ge Haixia et al., 2016a; Ge Haixia et al., 2017). Heavy oils are important unconventional resources in the study area. However, the origin and accumulation processes of heavy oils in the study area remain unclear at present. It is of great significance to reveal the origin and accumulation processes of heavy oils in this area. In this paper, a set of source rock and crude oil samples were geochemically analyzed to study the hydrocarbon generation potential, the origin of immature oil, the biodegradation of crude oil, oil-source correlation and episodes of oil charging. Some indicators with highly resistant to biodegradation together with stable carbon isotopic compositions were used for oil-source correlation. And on this basis, the main factors controlling formation and distribution of heavy oils in the study area are discussed.
CLIMATE CHANGE AND DENGUE IN INDONESIA: A SYSTEMATIC REVIEW

Background: Climate change is a global issue because of its impact on environmental and human health. No exception for Indonesia, an archipelago state with a tropical climate. Climate change potentially influences the mosquitos borne disease, including dengue fever, which poses a vulnerability to the Indonesian populations. This article aims to review the association and the impact of climate change to dengue fever, particularly in Indonesia and to inform the policymaker on directing the adaptation option.Methods: Of thirteen peer review articles were included in this review sourced from google scholar database.Results: Climate change affects dengue incidence in Indonesia due to climate variability.Conclusions: It is essential to Strengthen the surveillance system and provide an early warning system (EWS) based on climate information.Keywords: Climate change, dengue, Indonesia
Digitalisation and energy: world experience and evidence of correlation from Kazakhstan

The rapid pace of development of the digital economy is an effect conditioned by technology and innovation that have been developing over several decades and becoming more common. The number of Internet users in Kazakhstan increased from less than 1% in the 1990s to 81% in 2018, which happened due to a sharp decline in the cost of access and a high increase in computing power. The technological revolution has become a source of stimulating economic growth with less energy consumption. Digitalisation is considered to be a factor contributing to energy efficiency in the economy. The relationship between digitalisation, energy consumption and economic growth is a theme which has gained momentum recently. This paper attempts to estimate the effects of technology and economic factors on the energy intensity in Kazakhstan. The paper employs econometric methods: the unit root test, cointegration methods and the Granger causality test. All data were obtained from the World Bank’s database for the period between 1994 and 2018 as well as the Statistics Committee of the Ministry of National Economy of the Republic of Kazakhstanand the Odyssee database by EU. The results demonstrate that Internet usage and trade openness impact energy intensity. The results demonstrate that Internet usage and trade openness has a negative effect on energy consumption in the long run. The liberalisation trade and economy reduces the consumption of energy obtained from fossil fuels and minimises environmental degradation. Digitalisation is supposed to stimulate the efficiency of the energy system by optimising consumption and metering, reducing losses, generating with lowest possible costs and emissions, etc. Economic growth has a positive and statistically significant impact on energy intensity. The article contains certain recommendations for policy makers: the government should attract more investment and provide consistent support for ICT to increase the energy efficiency and to decrease total energy consumption.
Pre-modelling as a tool for optimizing morphodynamical numerical simulations

ABSTRACT The present study proposes, systematizes and validates a new, robust hot-start approach to numerical hydro-morphodynamic modelling, aiming to improve the quality of the interpolated bathymetrical data used in the referred models for representing river channels. This approach works by criteriously removing the small scale systemic errors in a channel’s bathymetry which often obfuscate the behaviour of fluvial morphodynamics, thereby improving the accuracy of the interpolated bed level along the modelling grid and the intelligibility of morphodynamical simulations. The pre-modelling approach was demonstrated using data from a case study in Portugal. The improvements obtained in terms of the quality of the morphology were both qualitatively and quantitatively assessed. Pre-modelling was proven to produce, at least, small improvements regarding the overall bed level accuracy (∼5% reduction in mean error) and significant benefits to the overall intelligibility of the results (with up to 22% reduction in the spatial entropy of morphodynamics and up to 55% increase in the agreement between theoretical and simulated values for each different scenario).
Towards Self-Tracking Personal Pollution Exposure using Wearables

Recent epidemiological studies have shown that long-term exposure to air pollution is positively associated with mild cognitive impairment (MCI). Although interest in pollution monitoring is proliferating, self-tracking personal pollution exposure is little explored. In this thesis, I adopt a human-centered computing approach to explore the design space of personal pollution tracking wearables. This work makes three contributions to human-computer interaction: 1) design guidelines for rapid-prototyping low-cost, sub-optimal personal pollution tracking wearables and a physical prototype that measures pollutants shown to be associated with cognitive impairment in older adults: PM2.5 and ambient noise, 2) exploration of different calibration techniques to improve the accuracy of low-cost PM2.5 sensors, and 3) a characterization of how human interference, our day-to-day activities, significantly affect the operation of personal pollution tracking wearables. In sum, this thesis informs design guidelines about how to physically prototype personal pollution tracking wearables and where to wear them---beyond citizen-science efforts of data collection---rather toward monitoring personal long-term pollution exposures to mitigate the environmental risk factors for many illnesses such as early dementia.
DISCOL experiment revisited: Assessing the temporal scale of deep-sea mining impacts on sediment biogeochemistry

Abstract. Deep-sea mining for polymetallic nodules is expected to have severe environmental impacts because in addition to the nodules, benthic fauna as well as the upper reactive sediment layer is removed through the mining operation, and blanketed by resettling material from the suspended sediment plume. This study aims to provide a holistic assessment of the biogeochemical recovery after a disturbance event by applying prognostic simulations based on an updated diagenetic background model and validated with novel (micro)-biological data. It was found that the recovery strongly depends on the impact type; complete removal of the reactive surface sediment reduces seafloor nutrient fluxes over centuries, while geochemical processes after resuspension and mixing of the surface sediment are near pre-impact state one year after the disturbance. Furthermore, the geochemical impact in the DISCOL area would be mitigated to some degree by a clay-bound Fe(II)-reaction layer, impeding the downward diffusion of oxygen, thus stabilizing the redox zonation of the sediment during transient post-impact recovery. The interdisciplinary (geochemical, numerical and biological) approach highlights the closely linked nature of benthic ecosystem functions, e.g. through bioturbation, microbial biomass and nutrient fluxes, which is also of great importance for the system recovery.
Aerodynamic and structural analysis of a small-scale horizontal axis wind turbine using QBlade

In this paper the aerodynamic and structural analysis of a small-scale horizontal axis wind turbine using QBlade software will be presented. QBlade software will be used to validate the wind turbine design, according with the Blade Element Momentum theory. The influence of the tip and root losses on the power curve will be analysed. The pitch angle control curve will be obtained. The annual energy production will be analysed on the basis of Weibull parameters. The structural analysis in terms of modal and static structural will be presented for three different internal structures: solid blade, hollow blade without spar, and hollow blade with spar. It has been found that the natural frequencies obtained for lateral translations (flapwise and edgewise), chord rotation around the blade longitudinal axis and longitudinal translation are in a safety range from the harmonics of wind turbine rotational speed at the operating condition, thus avoiding the resonance.
Efficient Microorganisms Applied to the Soil and in Cover on the Quinoa Crop

The present study had as objective to know the effects of the natural fertilizer, from a biological compound of Efficient Microorganisms (EM-4), applied to the soil and in cover of quinoa, over its phytotechnics properties and its production. The experiment was conducted in a greenhouse, in a totally randomized block design, in a factorial scheme 4x2+1 with three replicates. The first factor constituted of four doses of EM (3, 6, 9 and 12%) applied to the soil before sowing, the second factor was the application or not of the compound via foliar. The additional treatment was considered a control treatment without any application of EM. It was evaluated plant height, inflorescence height, stem diameter, inflorescence diameter, root length, root volume, root dry mass and production. The results indicate that the use of Efficient Microorganisms (EMs) increases the production in 40% independent of the dose applied, when compared to the control. The foliar or soil application of EM-4 did not influence in the production components and in the production of quinoa.
The Potential of Open Geodata for Automated Large-Scale Land Use and Land Cover Classification

This study examines the potential of open geodata sets and multitemporal Landsat satellite data as the basis for the automated generation of land use and land cover (LU/LC) information at large scales. In total, six openly available pan-European geodata sets, i.e., CORINE, Natura 2000, Riparian Zones, Urban Atlas, OpenStreetMap, and LUCAS in combination with about 1500 Landsat-7/8 scenes were used to generate land use and land cover information for three large-scale focus regions in Europe using the TimeTools processing framework. This fully automated preprocessing chain integrates data acquisition, radiometric, atmospheric and topographic correction, spectral–temporal feature extraction, as well as supervised classification based on a random forest classifier. In addition to the evaluation of the six different geodata sets and their combinations for automated training data generation, aspects such as spatial sampling strategies, inter and intraclass homogeneity of training data, as well as the effects of additional features, such as topography and texture metrics are evaluated. In particular, the CORINE data set showed, with up to 70% overall accuracy, high potential as a source for deriving dominant LU/LC information with minimal manual effort. The intraclass homogeneity within the training data set was of central relevance for improving the quality of the results. The high potential of the proposed approach was corroborated through a comparison with two similar LU/LC data sets, i.e., GlobeLand30 and the Copernicus High Resolution Layers. While similar accuracy levels could be observed for the latter, for the former, accuracy was considerable lower by about 12–24%.