Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytoplankton communities and environmental variables as indicators of ecosystem productivity in a shallow tropical lake

Abstract The water quality and ecosystem productivity of a tropical lake in Ethiopia (Lake Arkiet) was evaluated using phytoplankton and environmental factors. This was to ascertaining the lake’s potential for various applications. Phytoplankton communities and some selected environmental variables were collected from two predefined sampling sites (open water and littoral) using a seasonal campaign between March to May (dry season) and June to August (wet season) in 2022. The analysis of the physicochemical characteristics of this study showed that the lake’s water was well-oxygenated (6.8–16.7 mg/L), warm (25.8–29.8 °C), turbid (154–317 NTU), had poor water transparency (4.3–16.1 cm), and was alkaline (pH = 7.29–11.31). The concentrations of inorganic nutrients (phosphate and nitrate) were notably high, ranging from 2.12–5.26 and 2.19–10.64 mg/L, respectively. A total of 34 phytoplankton taxa from four divisions were identified in Lake Arekit. Bacillariophyceae (18 taxa) and Chlorophyceae (10 taxa) were the major groups of phytoplankton which together represented the largest (82%) phytoplankton taxa. The total biovolume of phytoplankton in the lake was to be 384.15 mm3/L. Cyanobacteria contributed the largest (41%) phytoplankton biovolume followed by Bacillariophyta (32%). The highest biovolume (about 75%) was constituted in the Microcystis aeruginosa, Cylindrospermopsis raphidiopsis, Anabaena spiroides, Pediastrum duplex, Aulacoseira granulate, Navicula schroeteri, and Nitzschia palea. The distribution of environmental factors and phytoplankton communities showed greater seasonality. High phytoplankton biovolume was observed in the dry season at both sampling sites concurrently with high water transparency and low water temperature. Findings from this study revealed that Lake Arkeit was a moderately polluted but productive lacustrine ecosystem that can still support aquatic life, fish production, irrigation, and aquaculture. The primary source of the pollution is the entry of inorganic and organic wastes from a brewery and other water bottling industries nearby and around the lake, as well as possible excessive nutrient levels due to the lake’s geological background. It is advised that commercial factories stop producing or releasing waste in open spaces that are heavily washed and enter the lake via flooding and tributary rivers and streams. Additionally, the local government should work with the nearby communities to set up a buffer zone where people are prohibited from engaging in agricultural activities to protect and reduce pollution, which will help to preserve the lake’s water and ecosystem.
Phytochemical properties and in-vitro cytotoxicity, genotoxicity and mutagenicity assessment of ethanolic and aqueous extracts of Argyrolobium roseum (Camb.)

ABSTRACT The current study aimed to investigate the phenolic and flavonoid contents, cytotoxicity, genotoxicity, and mutagenicity of ethanolic and aqueous extracts of A. roseum (Camb.). The MTT assay was used to determine cytotoxicity, Comet assay was used to determine genotoxicity and mutagenicity of extracts was assessed through Ames test. The results showed that total phenolic contents were higher in aqueous extract (538.26 mg GAE/100 g); however, total flavonoid contents were significantly higher in ethanolic extract (6553.29 mg Eq. of Quercetin/100 g). The cells survival percentage was significantly (P <.05) decreased as concentrations of ethanolic extract increased. However, no significant toxicity was observed in groups treated with 0.031–0.25 mg/ml of ethanolic extract of A. roseum compared to negative control (P > .05). IC50 of ethanolic and aqueous extract of A. roseum was 5.54 mg/ml and 11.39 mg/ml, respectively. The results indicated that all concentration groups of ethanolic and aqueous extract of A. roseum significantly (P < .05) lowered DNA damage than positive control group. The lowest DNA damage was observed at 0.031 and 0.062 mg/ml in both aqueous and ethanolic extracts. Moreover, at higher concentrations of 4, 8, and 16 mg/ml of both ethanolic and aqueous extract observed 100% DNA damage cells (comet cells). Moreover, Ames mutagenicity showed that no significant (P > .05) changes were observed in revertant colonies of both bacterial strains (T 98; T 100) at 0.25, 0.5, and 1 mg/ml concentrations of both aqueous and ethanolic extract of A. roseum as MI index was less than 2. The research concluded that A. roseum extracts exhibited no cytotoxicity, genotoxicity, and mutagenicity at lower concentrations (≤2 mg/ml).
Possibilities of Plant Preparations Use for Collagen Structure and Metabolism Disturbances Correction: Modern State of Problem

The review summarizes information on possibilities of plant preparations use for collagen structure and metabolism disturbances correction. Biologically active compounds of plant origin can both stimulate and inhibit the biosynthesis of various types collagens, accelerate or slower down their catabolism, regulate the activity of enzymes involved in the collagen's metabolism. Most of the studied compounds realize their effects simultaneously by several mechanisms. Among them, the most common are the direct influence of the substance on the processes of collagen genes expression and indirect influence via TGF-beta1- pathway. In addition, a fairly common are effects on collagen synthesis by changing organism's pools of free amino acids (as the starting compounds for this protein synthesis) and by regulation of hydroxylases (performing collagen post-translational modifications and crosslinking). Besides TGF-beta1 others cytokines can also be involved in the processes of collagen metabolism regulation by compounds of plant origin. In particular, this is characteristic of triterpenes and phytoestrogens. Such a variety of methods for collagens metabolism regulation creates a wide range of possibilities for developing new preparations based on extracts or pure plant compounds able to correct connective tissue collagen structure and metabolic disorders with minimal adverse effects. Fundamentally different possibilities for the influence of plant organisms on collagens are opened with the use of genetically modified plants. Recombinant collagens allow to obtain proteins with new programmed features, making it possible to synthesize proteins with predetermined properties for medical use.
THE IMPORTANCE OF DEEP GENOTYPING IN CROP BREEDING

One of the greatest challenges facing humanity is the development of sustainable strategies to ensure food availability in response to population growth and climate change. One approach that can contribute to increase food security is to close yield gaps and enhancing genetic gain; to such end, what is known as “molecular breeding” plays a fundamental role. Since a crop breeding program is mainly based on the quality of the germplasm, its detailed genetic characterization is mandatory to ensure the efficient use of genetic resources and accelerating development of superior varieties. Deep genotyping is an essential tool for a comprehensive characterization of the germplasm of interest and, fortunately, the technology is now accessible at a reasonable cost. What must be ensured is the correct interpretation of the genotypic information and on that basis develop efficient practical molecular crop breeding strategies that respond to the real needs of the breeding program. Key words: breeding population, genetic resources, marker assisted selection, Single Nucleotide Polymorphism (SNP)
Turbulence Modelling of Suspended Sediment in the Surf Zone

A computational model is developed for the prediction of the wave period averaged turbulence structure under a breaking wave. The principal forcing function for the model is the generation of turbulent production at the surface boundary, this energy production being calculated from the rate of wave energy dissipation according to bore theory. The computed depth dependent eddy viscosity coefficient allows the calculation of the turbulent mass flux and consequently the distribution of suspended sediment concentration under breaking waves.
The AMBRE Project: [Y/Mg] stellar dating calibration with Gaia

Chemical abundance dating methods open new paths for temporal evolution studies of the Milky Way stellar populations. In this paper, we use a high spectral resolution database of turn-off stars in the solar neighbourhood to study the age dependence of the [Y/Mg] chemical abundance ratio. Our analysis reveals a clear correlation between [Y/Mg] and age for thin disc stars of different metallicities, in synergy with previous studies of solar-type stars. In addition, no metallicity dependence with stellar age is detected, allowing us to use the [Y/Mg] ratio as a reliable age proxy. Finally, the [Y/Mg]–age relation presents a discontinuity between thin and thick disc stars around 9–10 Gyr. For thick disc stars, the correlation has a different zero point and probably a steeper trend with age, reflecting the different chemical evolution histories of the two disc components.
Efficient Data Mining Algorithms for Screening Potential Proteins of Drug Target

The past few decades have witnessed the boom in pharmacology as well as the dilemma of drug development. Playing a crucial role in drug design, the screening of potential human proteins of drug targets from open access database with well-measured physical and chemical properties is a task of challenge but significance. In this paper, the screening of potential drug target proteins (DTPs) from a fine collected dataset containing 5376 unlabeled proteins and 517 known DTPs was researched. Our objective is to screen potential DTPs from the 5376 proteins. Here we proposed two strategies assisting the construction of dataset of reliable nondrug target proteins (NDTPs) and then bagging of decision trees method was employed in the final prediction. Such two-stage algorithms have shown their effectiveness and superior performance on the testing set. Both of the algorithms maintained higher recall ratios of DTPs, respectively, 93.5% and 97.4%. In one turn of experiments, strategy1-based bagging of decision trees algorithm screened about 558 possible DTPs while 1782 potential DTPs were predicted in the second algorithm. Besides, two strategy-based algorithms showed the consensus of the predictions in the results, with approximately 442 potential DTPs in common. These selected DTPs provide reliable choices for further verification based on biomedical experiments.
The control of near-wall turbulence through surface texturing

Certain surfaces that exhibit small textured features can interact with near-wall turbulence and reduce drag, which is of great interest to industries in the aerospace, naval, transport and energy sectors. This paper reviews and discusses the dynamic mechanisms at play in that interaction. General principles of application across different technologies are discussed, and the parameters of interest and relevance are identified. It is argued that the main effect of these surfaces can be expressed as an offset between the positions of the virtual, equivalent smooth walls perceived by different parts of the flow, namely by the mean velocity profile and by the background turbulence, which remains otherwise smooth-like. Individual technologies are also reviewed, including superhydrophobic surfaces, riblets and permeable substrates, with particular emphasis on physical mechanisms that are specific to each technology. We discuss the capillary waves that form in superhydrophobic surfaces and the spanwise-elongated rollers that form over riblets and permeable surfaces.
Could morningstar sustainability rating be an indicator for downside protection?

This study investigates whether the Morningstar Sustainability Rating indicates the downside protection for the 2018 Global stock market downturn and 2020 Stock market crash by using daily time-series analysis and investigate whether fund characteristics have an effect on performance of each Morningstar Sustainability Rating by using a panel data analysis at a quarterly frequency for the active equity mutual fund in the US market. This paper finds the neutral performance in every group of ratings in any market period according to the neutral alpha or abnormal return and the fund characteristics influence the fund performance pattern which can observe that the better rating’s fund tend to have the better performance which can indicate that the better Morningstar Sustainability Rating provides the less downside risk in the crisis period.
The Impact of Female Education and Employment on Service Sector Value Added Growth: Evidence From Panel Data

The world economy has experienced a considerable shift in structure from the late 1980s, with the service sector contributing approximately 62 percent to the overall economic output and 50 percent of the total employment share from 1991 to 2010. Given the importance of the service sector, we study the inter-relationship between female education attainment, female employment in the service sector, and the per capita value-added growth of the service sector. Our analysis uses data from 146 countries from 1991 – 2015. Using fixed effects panel estimations, we conclude that globally, an increase in female education significantly primary education attainment increases the growth of the service sector. In contrast, an increase in female employment in the service industry relative to male employment leads to decreased service sector growth. We suggest that the negative effects of female employment on growth are based primarily on discriminatory factors women face in the workplace. Our results are robust across all specifications and hold after correcting for possible endogeneity.
Spectral collocation method for the time-fractional diffusion-wave equation and convergence analysis

In this talk, we consider the numerical solution of the time-fractional diffusion-wave equation. Essentially, the time fractional diffusion-wave equation differs from the standard diffusion-wave equation in the time derivative term. We propose a spectral collocation method in both temporal and spatial discretizations with a spectral expansion of Jacobi interpolation polynomial for this equation. The convergence of the method is rigorously established. Numerical tests are carried out to confirm the theoretical results.
Credit risk assessment with Bayesian model averaging

ABSTRACT Many credit risk models are based on the selection of a single logistic regression model, on which to base parameter estimation. When many competing models are available, and without enough guidance from economical theory, model averaging represents an appealing alternative to the selection of single models. Despite model averaging approaches have been present in statistics for many years, only recently they are starting to receive attention in economics and finance applications. This contribution shows how Bayesian model averaging can be applied to credit risk estimation, a research area that has received a great deal of attention recently, especially in the light of the global financial crisis of the last few years and the correlated attempts to regulate international finance. The paper considers the use of logistic regression models under the Bayesian Model Averaging paradigm. We argue that Bayesian model averaging is not only more correct from a theoretical viewpoint, but also slightly superior, in terms of predictive performance, with respect to single selected models.
Identification of Epicoccum poaceicola causing eggplant leaf spot and its cross-infection potential to other solanaceous vegetable crops

Abstract This study characterised and identified the causative agent of irregular necrotic leaf spots in eggplant. The culture characteristics and morphology of three fungal isolates indicate that they are from the Didymellaceae group. Using a polyphasic approach—combined morphological, cultural, pathogenicity, and molecular characterisation (concatenated sequences of three gene loci: ITS, TUB2, LSU), the fungal isolates MBELIQ03A and MBELIQ03D were identified as Epicoccum poaceicola. Isolate MBELIQ02 was identified as Epicoccum sp. due to a lack of clear grouping with a single Epicoccum species. In repeated trials, the three Epicoccum isolates were pathogenic to eggplant leaves in detached leaf assays. Similar fungi were consistently re-isolated from the inoculated leaves and thus, establishing Koch’s postulates. Inoculation of the three isolates on solanaceous leaves and fruits (tomato, eggplant, and pepper) revealed their varied pathogenicity. This is the first confirmed scientific report of Epicoccum poaceicola causing eggplant leaf spots. This is also the first record of this fungal species in the Philippines. Inoculum from leaf infection could serve as inoculum for fruit infection and other solanaceous vegetable crops grown nearby a field planted with eggplant.
Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

Most prior multimodal transport networks have been organized as relational databases with multilayer structures to support transport management and routing; however, database expandability and update efficiency in new networks and timetables are low due to the strict database schemas. This study aimed to develop multimodal transport networks using a graph database that can accommodate efficient updates and extensions, high relation‐based query performance, and flexible integration in multimodal routing. As a case study, a database was constructed for London transport networks, and routing tests were performed under various conditions. The constructed multimodal graph database showed stable performance in processing iterative queries, and efficient multi‐stop routing was particularly enhanced. By applying the proposed framework, databases for multimodal routing can be readily constructed for other regions, while enabling responses to diversified routings, such as personalized routing through integration with various unstructured information, due to the flexible schema of the graph database.
Eksplorasi Potensi Pasir Besi di Pesisir Barat Kecamatan Nusawungu Kabupaten Cilacap Berdasarkan Data Resistivitas Batuan Bawah Permukaan

Eksplorasi geofisika untuk mengestimasi potensi pasir besi di pesisir barat Kecamatan Nusawungu Kabupaten Cilacap telah dilakukan pada bulan Mei – Juli 2017 menggunakan metode geolistrik resistivitas. Pengukuran data resistivitas dilakukan di 6 titik lokasi yang diperkirakan prospek mengandung bijih besi berdasarkan peta anomali magnetik lokal daerah penelitian yang membentang pada posisi geografis 109,3143° – 109,3445°BT dan 7,6908° – 7,7091°LS. Survei geolistrik resistivitas bertujuan untuk memperkirakan kedalaman dan ketebalan endapan pasir besi serta potensinya. Berdasarkan hasil pemodelan dan interpretasi data resistivitas diperoleh endapan pasir besi yang berselingan dengan lanau dan lempung dari formasi alluvium di seluruh titik lokasi. Endapan pasir besi ini memiliki nilai resistivitas 12,24 – 46,96 Ωm dan kedalaman berkisar 2,39 – 27,81 meter. Berdasarkan hasil eksplorasi menggunakan metode geolistrik resistivitas, potensi pasir besi di kawasan pesisir barat Kecamatan Nusawungu Kabupaten Cilacap diperkirakan cukup besar
Group Link Gear Locus Modeling Based on Motion Relativity

In order to solve the comprehensive analysis problem of the mechanism link locus and motion, this paper bring forward the parameter calculation of locus based on motion relativity and differential geometry theory. The problem of point-group calculation is thus solved, and the comprehensive analysis of motion and position is realized. Moreover, the method is simplified and the calculation accuracy is also improved. In the paper, a moving frame of axes is set up by using the lever axes to describe the complex structure of linkage. Motion relativity theory is adopted to study the overall motion rule of the structure. By using the calculation result of the linkage axes, the calculation model is set up to analyze its motion, which simplifies the point-group motion calculation. The point-groups form the same component have the same angle velocity, angle acceleration velocity, base point, and calculation model, which makes the calculation procedure modularized and the program shortened. Owning to complete digital analysis, the characteristic parameter calculations of locus are very accurate, the data-base is easy to establish, the transfer and analysis of data become convenient. This also makes it easy to establish the shape chart of the linkage locus and to analyze their resemblance. It’s a useful method to analyze the locus and motion of the link gear comprehensively.
A level-set-based topology optimisation of carpet cloaking devices with the boundary element method

We investigate a topology optimisation based on the level set method for a design problem of carpet cloaking devices. In topology optimisation of carpet cloaking devices, we need to calculate the electromagnetic response in a semi-infinite domain. We use the boundary element method (BEM) for the electromagnetic analysis since the BEM is more suitable to topology optimisation in wave field than the finite element method; the infinite domain can be evaluated exactly and mesh generation is required only on a boundary with the BEM. Along with the detailed formulation of the BEM-based topology optimisation, we present some numerical examples of design for carpet cloaks. We have confirmed that the designed carpet cloaking devices effectively work for the cases where permittivity, wavelength and angle of incidence are fixed. In addition, we have confirmed that cloaking devices for perturbed permittivity and wavelength can be obtained by redefining the objective function with the KS function.
Impact of Air Mass Conditions and Aerosol Properties on Ice Nucleating Particle Concentrations at the High Altitude Research Station Jungfraujoch

Ice nucleation is the source of primary ice crystals in mixed-phase clouds. Only a small fraction of aerosols called ice nucleating particles (INPs) catalyze ice formation, with their nature and origin remaining unclear. In this study, we investigate potential predictor parameters of meteorological conditions and aerosol properties for INP concentrations at mixed-phase cloud condition at 242 K. Measurements were conducted at the High Altitude Research Station Jungfraujoch (Switzerland, 3580 m a.s.l.), which is located predominantly in the free troposphere (FT) but can occasionally receive injections from the boundary layer (BLI). Measurements are taken during a long-term study of eight field campaigns, allowing for the first time an interannual (2014–2017) and seasonal (spring, summer, and winter) distinction of high-time-resolution INP measurements. We investigate ranked correlation coefficients between INP concentrations and meteorological parameters and aerosol properties. While a commonly used parameterization lacks in predicting the observed INP concentrations, the best INP predictor is the total available surface area of the aerosol particles, with no obvious seasonal trend in the relationship. Nevertheless, the predicting capability is less pronounced in the FT, which might be caused by ageing effects. Furthermore, there is some evidence of anthropogenic influence on INP concentrations during BLI. Our study contributes to an improved understanding of ice nucleation in the free troposphere, however, it also underlines that a knowledge gap of ice nucleation in such an environment exists.