Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of community knowledge and perception on environmental issues in Jimma Zone, Southwest Ethiopia

Environmental knowledge and perceptions of community govern the sustainable use and management of environmental resources. Developing countries such as Ethiopia has been facing serious environmental problems. In spite of the existing problems, little is known about public understanding and perception of environmental issues. Thus, the overall objective of this research was to assess community perception and knowledge of environmental issues. Interview was conducted using structured questionnaire. The collected data was coded, cleaned and analyzed using descriptive and inferential statistics. The result indicates, most of the community members believed that they have better knowledge of environmental issues but the evidence obtained from measured knowledge shows the reverse. The principal source of environmental information (local media broadcasting) had positive correlation with perceived knowledge, and negatively correlated with assessed knowledge and perception index of environmental issues. Correctly answered questions used in the evaluation of environmental knowledge were weekly associated (r < .2) with perceived knowledge and perception, which indicates the respondents lacks same concept on environmental issues. Perceived knowledge was negatively and significantly (P <.001) determined by age and educational levels of respondents. But, measured knowledge was negatively and significantly (P <.05) affects by age, childhood area, education and occupation when positively and significantly (P = .001) influenced by origin of residence. The perception of community was positively and significantly (P =.001) determined by respondent's age, childhood area, education and information source but negatively and significantly (P < .05) influenced by origin of residence and ethnic group. Generally, self-reported knowledge is not reliable source of information for environmental management decisions. So, stakeholders should strongly works on environmental awareness campaigns, engage students in outdoor activities, and training to improve factors negatively determined community's factual knowledge and perception of environment.
Assessing the Reality Gap of Robotic Simulations with Educational Purposes

The use of simulation and visualization tools to validate mechanical designs and programming for robots has become increasingly important. Being used in many scenarios, simulators have collaborated for research in machine learning, deep learning and training of professionals. Nowadays, with the Covid-19 pandemic and social distancing, simulators have great potential as a tool to help in the teaching of robotics. However, research indicates that the user may encounter differences between what happens in the simulator and in real life, this effect is called reality gap. This article aims to investigate the effects of this gap in an educational robotics simulator, named Virtual Robotics Toolkit (VRT), as well as its impacts on the testing of algorithms and to propose strategies to reduce the impact of this effect. Three batch tests were carried out on two different robots, both in the simulation and in the real world. By capturing data from sensors such as tachometer, infrared, gyroscope and a light sensor, it was possible to compare the performance in the two scenarios and their differences. Finally, the entire test field and models were made available along with videos of some tests.
Artificial reforestation produces less diverse soil nitrogen‐cycling genes than natural restoration

Author(s): Wang, Y; Zheng, H; Chen, F; Yang, Y; Zeng, J; D. Van Nostrand, J; Zhou, J; Ouyang, Z | Abstract: © 2019 The Authors. Reforestation is effective in restoring ecosystem functions and enhancing ecosystem services of degraded land. The three most commonly employed reforestation methods of natural reforestation, artificial reforestation with native Masson pine, and introduced slash pine plantations were equally successful in biomass yield in southern China. However, it is not known whether soil ecosystem functions, such as nitrogen (N) cycling, are also successfully restored. Here, we employed a functional microarray to illustrate soil N-cycling. The composition of N-cycling genes in soils varied significantly with reforestation method and varied with constructive species identity and plant diversity. Artificial reforestation had less superior organization of N-cycling genes than natural reforestation, as indicated by the less diverse and less stable pathways to perform the biogeochemical N-cycling processes. Besides, artificial reforestation had lower functional potential (abundance of ammonification, denitrification, assimilatory, and dissimilatory nitrate reduction to ammonium genes) in soils than natural method. Evaluations of the abundance and interactions of N-cycling genes in soils showed that plantations, especially artificial reforestation with slash pine plantations, possessed a smaller range of ecosystem functions that provide a less diverse array of N-related substrates and nutrients to microbial communities compared with natural restoration. This might lead to a lower independence of N-cycling, which indicated a higher risk of N release in plantations. The unfavorable N-cycling conditions in plantations were corroborated by the lower contents of available N, ammonium N, and nitrate N. These findings demonstrate that reforestation methods could have broad regional and possibly global implications for N-cycling.
Effect of storage and cooking time on the antioxidant properties of two commonly used ghanaian vegetables

Green leafy vegetables are good sources of antioxidants. This study was designed to evaluate the effect of storage and cooking time on the antioxidant properties of two commonly used Ghanaian vegetables: Corchorus olitorius and Solanum macrocarpon locally known as "adeimey" and "gboma" respectively. The storage conditions were: Left to stand overnight at room temperature, refrigerated for one day and refrigerated for one week, and cooked for ten and thirty minutes at 100oC. The reducing power and the total carotenoid content were determined by measuring absorbance using a Shimadzu UV-120-02 spectrophotometer at 700nm and 450 nm respectively. The free radical scavenging activity was determined by the 1, 1-diphenyl-2-picryl- hydrazil (DPPH) method. The antioxidant activity (AOA) ranged from 91.59 to 38.42%. The total carotenoid content (TCC) varied from 5.10 to 27.30 mg/100 g. The reducing power ranged from 9.52 to 50.59%. The results show that Solanum macrocarpon and Corchorus olitorius are good sources of antioxidants with the later exhibiting higher antioxidant properties than the former. However the AOA, TCC and reducing power decreased drastically when the vegetables were refrigerated for one day and one week and cooked for thirty minutes at 100oC. Similarly the AOA, TCC and reducing power decreased slightly when the stored vegetables were cooked for ten minutes. These findings suggest modification in the storage and cooking practices of these green leafy vegetables to ensure retention of antioxidants for the best nutritional value and health benefit. The results also indicate that in areas where refrigeration is not possible, vegetables can be left overnight at room temperature to preserve the antioxidants in them.
Multiclass state‐dependent service systems with returns

In this paper, we consider a service system facing several classes of customers in which the arrival rate and service time depend on the workload in the system, while the chance of return is a function of the service time. We first model the problem as a multiclass multiserver queueing network and investigate its stability by examining the conditions under which the Markov chain representing the network is positive recurrent. We then examine the impact of the relationship among the workload, service time, arrival rate, and the chance of return on the dynamics of the system using a fluid approach. We first characterize all equilibria of the system and show that the system may shift between several equilibrium states. We establish that all equilibria can be easily determined and demonstrate conditions under which an equilibrium is stable. We then prove that, surprisingly, the stability of an equilibrium and the congestion in the system may depend on the amount of time a customer spends outside of the system before returning for rework. However, we show that if the relationship between the workload and service time in a system facing a single class of customers is nondecreasing, the long‐run behavior of the system is not affected by how long it takes until a customer returns.
Female variation in allocation of steroid hormones, antioxidants and fatty acids: a multilevel analysis in a wild passerine bird

The environment where an embryo develops can be influenced by components of maternal origin, which can shape offspring phenotypes and therefore maternal fitness. In birds that produce more than one egg per clutch, females differ in the concentration of components they allocate into the yolk along the laying sequence. However, identification of processes that shape female yolk allocation and thus offspring phenotype still remains a major challenge within evolutionary ecology. A way to increase our understanding is by acknowledging that allocation patterns can differ depending on the level of analysis, such as the population versus the among-female (within-population) level. We employed mixed models to analyze at both levels the variation in allocation along the laying sequence of four steroid hormones, three antioxidants, and four groups of fatty acids present in the egg yolks of wild great tits (Parus major). We also quantified repeatabilities for each component to study female consistency. At a population level, the concentrations/proportions of five yolk components varied along the laying sequence, implying that the developmental environment is different for offspring developing in first versus last eggs. Females varied substantially in the mean allocation of components and in their plasticity along the laying sequence. For most components, these two parameters were negatively correlated. Females were also remarkably repeatable in their allocation. Overall, our data emphasize the need to account for female variation in yolk allocation along the laying sequence at multiple levels, as variation at a population level is underpinned by different individual patterns. Our findings also highlight the importance of considering both levels of analysis in future studies investigating the causes and fitness consequences of yolk compounds. Finally, our results on female repeatability confirm that analyzing one egg per nest is a suitable way to address the consequences of yolk resource deposition for the offspring.
Extinctions of interactions: quantifying a dung beetle–mammal network

Loss of large-bodied mammals across the globe through hunting, habitat degradation, and fragmentation is one of the most signi ﬁ cant anthropogenic impacts on the environment. Cascading effects of these extinctions through ecosystems have been little studied, although correlative studies have revealed co-extinctions in closely linked groups, with implications for ecosystem structure and function. Despite play-ing important roles in seed dispersal and hence seedling recruitment, mammals have been largely neglected in network studies. Similarly, the role of secondary seed dispersers, such as ants and dung beetles, has been largely unexplored. Most dung beetles rely on mammal feces for feeding and breeding and provide a suite of important ecosystem functions and services. While dung beetle community responses to environmental change have been widely investigated, studies quantifying the network of associations between dung beetle and mammal species are lacking. By developing the ﬁ rst quantitative mammal – dung beetle networks, we address several important knowledge gaps contributing to the understanding of how interactions in networks involving mammals and secondary insect seed dispersers are structured. We use the resulting quantitative interaction networks to model mammal species extinction scenarios to further explore the consequences for dung beetle populations, and the extent to which networks change the strength of interactions through resource switching. Dung beetle feeding and breeding networks did not differ signi ﬁ cantly in structure and showed high nestedness and low levels of trophic specialization. Simulations suggested that mammal extinction scenarios based on mammal body mass and mammal dung volume will impact dung beetle populations to a greater extent than random scenarios of mammal loss. Thus, despite their generalist feeding preferences, realistic mammal extinction scenarios have the potential to negatively impact the dung beetle community, which may have consequences for ecosystem functioning.
The normal distribution fitting method for frequency distribution characteristics of peak arrival time of earthquake

The physical meaning of phase difference controls the occurrence time of peak values of triangular series, which can be abbreviated as peak arrival time. This article describes a method for deducing the correspondence between the energy distribution characteristics in the time domain and the peak arrival time. The variation laws of acceleration time–history curve of natural seismic wave can be transformed into its energy distribution characteristics in time domain. Based on the needs of seismic engineering, this article proposes a conversion formula to describe the relationship between the peak arrival time and the energy distribution characteristics in the time domain. To ensure that the variation laws of acceleration time–history curve of artificial seismic waves are more consistent with those of natural seismic waves, a normal-fitting annealing algorithm is proposed based on the normal-fitting method. The proposed method not only considers the frequency distribution characteristics of the peak arrival time comprehensively but also optimizes the fitting parameters according to the actual situation. The results of all the experimental cases verify the rationality and reliability of the proposed method.
Study of the Efficacy of Two Extraction Techniques from Crithmum maritimum and Salicornia europaea

The aim of this work was to study the characteristics of the extracts from two halophytes, sea fennel (Crithmum maritimum L.) and marsh samphire (Salicornia europaea L.) that naturally grow on the Mediterranean coast, by using ultrasound-assisted extraction (UAE) and supercritical fluid extraction (SFE). Best conditions for UAE were found at temperature 50°C, 20 min extraction time, 1:30 ratio solid:solvent and 40% (v/v) ethanol concentration. For SFE best conditions were at 50°C and 300 bar pressures with 40% (v/v) ethanol concentration. Total extract yield, total phenolic content, total flavonoid content and antioxidant capacity of the extracts were measured. For both species the best results were obtained with UAE technique. Between the two halophytes, the C. maritimum extract was the richest one in antioxidant compounds (total phenol = 23.44 mg GAEs gdw-1); under the best conditions the S. europea extract allowed recording only 9.31 mg GAEs gdw-1 of total phenol.
Benchmarker: an unbiased, association-data-driven strategy to evaluate gene prioritization algorithms

Genome-wide association studies (GWAS) are valuable for understanding human biology, but associated loci typically contain multiple associated variants and genes. Thus, algorithms that prioritize likely causal genes and variants for a given phenotype can provide biological interpretations of association data. However, a critical, currently missing capability is to objectively compare performance of such algorithms. Typical comparisons rely on “gold standard” genes harboring causal coding variants, but such gold standards may be biased and incomplete. To address this issue, we developed Benchmarker, an unbiased, data-driven benchmarking method that compares performance of prioritization strategies to each other (and to random chance) by leave-one-chromosome-out crossvalidation with stratified linkage disequilibrium (LD) score regression. We first applied Benchmarker to twenty well-powered GWAS and compared gene prioritization based on strategies employing three different data sources, including annotated gene sets and gene expression. No individual strategy clearly outperformed the others, but genes prioritized by multiple strategies had higher per-SNP heritability than those prioritized by one strategy only. We also compared two gene prioritization methods, DEPICT and MAGMA; genes prioritized by both methods strongly outperformed genes prioritized by only one. Our results suggest that combining data sources and algorithms should pinpoint higher quality genes for follow-up. Benchmarker provides an unbiased approach to evaluate any method that provides genome-wide prioritization of gene sets, genes, or variants, and can determine the best such method for any particular GWAS. Our method addresses an important unmet need for rigorous tool assessment and can assist in mapping genetic associations to causal function.
Credit Risk, Islamic Contracts and Ownership Status: Evidence From Malaysian Islamic Banks

The paper attempts to model the key drivers of credit risk for Islamic banks in Malaysia. This paper is motivated to introduce Islamic financing types (IFT) and banks ownership status (STATUS) as additional factors in investigating the key drivers. This study also investigates the level of credit risk between the crisis and non-crisis period. This study employs a panel data analysis method using generalized least squares (GLS) regression for random effect model . The dependent variable is credit risk which assumed to be a function of bank-specific variables and other potential variables that are ownership status, Islamic financing types and financial crisis. The sample of this study comprised of 160 observations for 15 full-fledged Islamic banks in Malaysia, covering the period of 2000 to 2016. The finding suggests that financing expansion, financing and capital buffer are amongst important drivers that significantly influence the level of credit risk of Malaysian Islamic banks. The estimation results of this study also suggest that any Islamic bank that offers equity-based financing (EBF) has significantly higher credit risk.
Characterization of hop-and-sink daphniid locomotion

This study characterizes the hop-and-sink locomotion of Daphnia magna, a zooplankton species widely studied in a variety of biological fields. Time-resolved tomographic particle image velocimetry (tomo-PIV) is used to obtain 3D kinematics and flow field data with high spatial and temporal resolution. The kinematics data show that the daphniid’s velocity quickly increases during the power stroke, reaching maximum accelerations of 1000 body lengths/s2, then decelerates during the recovery stroke to a steady sinking speed. The hop-and-sink locomotion produces a viscous vortex ring located under each second antennae. These flow structures develop during the power stroke, strengthen during the recovery stroke, and then decay slowly during the sinking phase. The time records of vortex circulation are self-similar when properly normalized. The flow fields were successfully modeled using an impulsive stresslet, showing good agreement between the decay of circulation and a conceptual model of the impulse. While no relationships were found between kinematics or flow field parameters and body size, the total energy dissipated by the daphniid hop-and-sink motion was found to scale exponentially with the vortex strength.
Radiative Characteristics at 89 and 36 GHz for Satellite-Based Cloud Water Estimation Over Land

Satellite-based passive microwave (PMW) remote sensing is an essential technique to clarify long-term and large-scale distribution patterns of cloud water content (CWC). However, most CWC estimation methods are not implemented over land because of high heterogeneity of land radiation, and the detailed characteristics of microwave (MW) radiative transfer between land and atmosphere including clouds have not been elucidated. This study aims to elucidate these characteristics and reveal the accuracy of land emissivity representation necessary for adequate CWC estimation over land using satellite-based PMW under various CWC conditions. First, important parameters related to MW radiative transfer between land and atmosphere at CWC-relevant frequencies in the presence of clouds are determined theoretically. Next, the relationship between errors in these parameters and the brightness temperatures used for CWC estimation is clarified through considerations based on radiative transfer equations. Then, ground-based PMW observations and numerical simulation are used to reveal the actual values of these important parameters and the size of errors. Finally, the results show that for any cloud liquid water path (LWP) value greater than 1.6 kg/m2 at 89 GHz and 5 kg/m2 at 36 GHz, we can reasonably neglect the heterogeneity of emissivity and radiation from the land surface for CWC estimation. However, when LWP values are below the threshold, the error in the representation of land emissivity should be kept below 0.015 for both 89- and 36-GHz data, and volumetric soil moisture content should have an error lower than 5%–6% for both frequencies.
Balancing Data Utility versus Information Loss in Data-Privacy Protection using k-Anonymity

Data privacy has been an important area of research in recent years. Dataset often consists of sensitive data fields, exposure of which may jeopardize interests of individuals associated with the data. In order to resolve this issue, privacy techniques can be used to hinder the identification of a person through anonymization of the sensitive data in the dataset to protect sensitive information, while the anonymized dataset can be used by the third parties for analysis purposes without obstruction. In this research, we investigated a privacy technique, k-anonymity for different values of $\pmb{k}$ on different number $\pmb{c}$ of columns of the dataset. Next, the information loss due to k-anonymity is computed. The anonymized files go through the classification process by some machine-learning algorithms i.e., Naive Bayes, J48 and neural network in order to check a balance between data anonymity and data utility. Based on the classification accuracy, the optimal values of $\pmb{k}$ and $\pmb{c}$ are obtained, and thus, the optimal $\pmb{k}$ and $\pmb{c}$ can be used for k-anonymity algorithm to anonymize optimal number of columns of the dataset.