Miracle-dz/UniFAR-FTUs huggingface dataset:
Streptomycetaceae and Promicromonosporaceae: Two Actinomycetes Families from Moroccan Oat Soils Enhancing Solubilization of Natural Phosphate

Soil actinomycetes explorations appear to be an efficient alternative as biofertilizers to optimize the use of phosphorus (P) resources and enhance plant growth. This research aimed to explore the distribution of actinomycetes isolated from four different rhizospheric Moroccan oat soils and to investigate their potential for P solubilization. The distribution of actinomycetes was significantly more abundant in Settat (9.68%), Tangier (7.38%), and Beni Mellal (6.87%) than in the Merchouch-Rabat (4.90%) region. A total of 235 actinomycete strains were isolated from all sites and tested for their ability to grow on a synthetic minimum medium (SMM) containing insoluble natural rock phosphate (RP) or synthetic tricalcium phosphate (TCP) as the unique P source. One hundred forty-three isolates (60.8%) had the ability to grow in the SMM with RP whereas only twenty-five isolates (17%) had the most active growth using the SMM with TCP. Eight isolates with the most active growth in solid SMM were selected for their P solubilization abilities in liquid SMM cultures. The highest amount of P solubilized was 163.8 µg/mL for RP and 110.27 µg/mL for TCP after 5 days of culture. The biosolubilization process of AM2, the most efficient RP and TCP solubilizing strain, probably implied the highest excretion of siderophore substances. Eight of these strains were shown to belong to the Streptomyces genus and one to the Promicromonospora genus. These findings bolster the phosphate biosolubilization abilities of actinomycetes and may participate in increasing agricultural yields in an eco-efficient and environmentally friendly manner.
Assessment of WorldView-2 images for aboveground seagrass carbon stock mapping in patchy and continuous seagrass meadows

ABSTRACT Spatially explicit information on aboveground seagrass carbon stock (AGCseagrass) is required to understand the role of seagrass as a nature-based solution to mitigating and adapting to climate change. Remote sensing provides the most effective and efficient means to map AGCseagrass. This research aimed to assess the accuracy of multispectral images to map AGC in seagrass meadows with different characteristics. Kemujan Island in Indonesia was selected to represent patchy beds with relatively low seagrass percent cover and low water clarity, whereas Labuan Bajo of Indonesia served an example of continuous beds with a relatively high percent cover and water clarity. WorldView-2 is a high-spatial-resolution multispectral image with six visible bands, by which water can be penetrated. Several image processing techniques, including sunglint and water column correction, principal component analysis, and co-occurrence texture analysis, were applied to the atmospherically corrected WorldView-2 images. These datasets were used as inputs in the AGC empirical model using seven regression algorithms, namely, single-band linear regression, band-ratio linear regression, stepwise regression, random forest regression, support vector regression, extreme gradient boosting, and multivariate adaptive regression spline. Seagrass field data collected using photo quadrat technique were used to train the regression model and assess the accuracy of the resulting AGCseagrass maps. The results indicated that WorldView-2 can be used to map AGC in different seagrass meadows with a consistent accuracy. The most accurate AGCseagrass map for Kemujan Island had a root mean square error (RMSE) of 4.11 g C m−2 for the aboveground stock in the range of 0–28.70 g C m−2, and for Labuan Bajo, the RMSE of the map was 9.73 g C m−2, with aboveground stock range of 0.31–64.38 g C m−2. Model cross-validation revealed that the mapping model can be site-specific or robust depending on the characteristics of the field-derived AGCseagrass data used to train the regression algorithm. For example, the model developed for Labuan Bajo seagrasses, which had a higher AGC variance, can be successfully applied to Kemujan Island with its lower AGC variance, but not vice versa. This finding is a key factor in the future development of a robust AGCseagrass mapping model that is applicable to various seagrass meadows as a stepping stone to accelerating the filling of gaps in the global seagrass dataset.
Detection of Pits in Olive Using Hyperspectral Imaging Data

The unknowing presence of pits in olives is an undesirable and even dangerous experience that affects overall quality of products contain olives or serving dishes in salad bars, airline meals, and cocktail lounges. Therefore, detection for removal of pits and pit fragments are very important for maintaining a high quality of products/services. The contributions of the paper are a) new hyperspectral data captured in a specific range of the wavelengths that are suitable for detecting olives with pits inside; b) developing a classification method, that is the CNN classifier that yields a high accuracy of pit detection. We have collected spectral responses of Manzanilla (black and green) and Gemlik (black) olives in the 400 nm- 900 nm spectrum. Olives have been classified using 1D convolutional neural networks (1D-CNN) with 99.5% and 97.69% of classification accuracies of pitted and whole olives for training and test sets, respectively. Further boosting of the accuracy up to 98.27% on the test dataset has been attained by CNN with a dropout layer. As expected, the CNN attained a better performance than those of the Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Random Forest (RF), and Logistic Regression (LA) classifiers.
Effect of the Grell‐Freitas Deep Convection Scheme in Quasi‐Uniform and Variable‐Resolution Aquaplanet CAM Simulations

The Grell‐Freitas deep convection scheme (GF) has been implemented in the Community Atmosphere Model (CAM) with the nonhydrostatic Model for Prediction Across Scales dynamical core. Aquaplanet simulations have been performed with a global quasi‐uniform resolution mesh with ∼120 km grid spacing and a variable resolution mesh employing a circular refined region with ∼30 km grid spacing centering at the equator and ∼120 km elsewhere. GF produces overall patterns of the general circulations comparable to those of other aquaplanet experiments, including those produced using the default Zhang‐McFarlane convection scheme (ZM) in CAM Version 5.4. GF alleviates the overestimated occurrence of weak intensity precipitation characteristic of ZM due to GF's different closure methods and deep‐convection trigger conditions. Compared to ZM, the GF characteristics of the equatorial Kelvin waves are closer to observations. GF also better simulates precipitation at variable resolution, with no unrealistic wave distortion by the refinement. Overall, GF shows less sensitivity of convective precipitation and heating/moistening tendencies to changes in horizontal resolution compared to ZM. However, vertically overlapped total cloud fraction simulated with GF in the tropics is more sensitive to the resolution than ZM due to the larger resolution‐sensitivity of high‐level cloud fraction in the tropics.
Drosophila melanogaster as a dynamic in vivo model organism reveals the hidden effects of interactions between microplastic/nanoplastic and heavy metals

Plastic waste in different environments has been constantly transforming into microplastic/nanoplastic (MNPLs). As they may coexist with other contaminants, they may behave as vectors that transport various toxic trace elements, including metals. Because the impact of exposure to such matter on health still remains elusive, the abundant presence of MNPLs has lately become a pressing environmental issue. Researchers have been utilizing Drosophila melanogaster as a dynamic in vivo model in genetic research for some time. The fly has also recently gained wider recognition in toxicology and nanogenotoxicity studies. The use of nanoparticles in numerous medical and consumer products raises serious concern, since many in vitro studies have shown their toxic potential. However, there is rather limited in vivo research into nanomaterial genotoxicity using mice or other mammalians owing to high costs and ethical concerns. In this context, Drosophila, thanks to its genetic tractability, short life span, with its entire life cycle lasting about 10 days, and distinct developmental stages, renders this organism an excellent model in testing toxic effects mediated by MNPLs. This review therefore aims to encourage research entities to employ Drosophila as a model in their nanogenotoxicity experiments focusing on impact of MNPLs at the molecular level.
Seismic Data Quality Analysis Based on Image Recognition Using Convolutional Neural Network

Seismometer monitoring and evaluation activities at the Indonesia Tsunami Early Warning System (InaTEWS) station can be carried out through a seismometer sensor calibration system with the use of the software of Seismic Data Quality Analysis. The software output is in the form of a spectrum image that represents the conditions of the seismometer following the spectrum results. The identification of the seismometer condition can be made by pattern recognition in the spectrum image. This study employed a neural network, specifically the Convolutional Neural Network (CNN), to analyse the pattern condition. The test results show that the performance of the system will be excellent if 1024 hidden layers are used. In addition, the epoch test shows that the system works well when given a maximum epoch value of 50. The test of image size gives the result that the system performance will result in good using input with a size of 30x20 pixels. The final results of the classification of spectrum images using CNN will exhibit the identification of seismometer. For the validation, the confusion matrix test shows that the corresponding findings are 80%, while the conflicting results are 20%.
Think-aloud analysis of commonly used screening instruments for Internet use disorders: The CIUS, the IGDT-10, and the BSMAS

Abstract Background Despite the constant publication of new screening instruments for Internet use disorders (IUD), little is known about their content validity. This study aimed to identify potential mismatches between the items' intention and young adults' interpretation of these items when answering three screening instruments that are commonly used in research and clinical settings: The Compulsive Internet Use Scale (CIUS), the 10 Item-Internet Gaming Disorder Test (IGDT-10), and the Bergen Social Media Addiction Scale (BSMAS). Methods In total, 30 vocational students (50% female, age = 21.3; SD = 2.1) took part in individual think-aloud interviews. All participants were asked to report their thoughts while completing the CIUS. In addition, participants who reported online games (OG) as their main Internet activity (n = 11) answered the IGDT-10. Participants who reported social networks (SN) as their main Internet activity (n = 18) answered the BSMAS. One participant used OG and SN equally and completed both screening instruments. All interviews were audio-recorded, transcribed, and content-analysed. Results Overall, four potential sources for errors were identified: (1) High scorings were often not congruent with the underlying diagnostic criteria. In particular, such discrepancies were found in items aimed to assess dysfunctional emotional regulation strategies and cognitive involvement. (2) Some participants were uncertain which time frame or Internet activity should be considered in their answers. (3) Long and complex items led to the building of mean values or the choice of the middle answer category. (4) Some wordings were perceived to be outdated and difficult to understand. Discussion These findings might help to provide recommendations on how to improve screening instruments for IUD. Most important, items should more clearly distinguish between Internet use as a “normal” leisure activity and Internet use that leads to functional impairments in daily life.
α-Glucosidase, α-Amylase and Antioxidant Evaluations of Isolated Bioactives from Wild Strawberry

Diabetes mellitus is a metabolic disorder and is a global challenge to the current medicinal chemists and pharmacologists. This research has been designed to isolate and evaluate antidiabetic bioactives from Fragaria indica. The crude extracts, semi-purified and pure bioactives have been used in all in vitro assays. The in vitro α-glucosidase, α-amylase and DPPH free radical activities have been performed on all plant samples. The initial activities showed that ethyl acetate (Fi.EtAc) was the potent fraction in all the assays. This fraction was initially semi-purified to obtain Fi.EtAc 1–3. Among the semi-purified fractions, Fi.EtAc 2 was dominant, exhibiting potent IC50 values in all the in vitro assays. Based on the potency and availability of materials, Fi.EtAc 2 was subjected to further purification to obtain compounds 1 (2,4-dichloro-6-hydroxy-3,5-dimethoxytoluene) and 2 (2-methyl-6-(4-methylphenyl)-2-hepten-4-one). The two isolated compounds were characterized by mass and NMR analyses. The compounds 1 and 2 showed excellent inhibitions against α-glucosidase (21.45 for 1 and 15.03 for 2 μg/mL), α-amylase (17.65 and 16.56 μg/mL) and DPPH free radicals (7.62 and 14.30 μg/mL). Our study provides baseline research for the antidiabetic bioactives exploration from Fragaria indica. The bioactive compounds can be evaluated in animals-based antidiabetic activity in future.
The influence of mean arterial blood pressure during cardiopulmonary bypass on post-operation acute kidney injury in hypertensive patients

Introduction: Over a period of time, kidney blood vessels will be damaged in those patients suffering from hypertension. Objectives: This study aimed to investigate the effect of mean arterial pressure during cardiopulmonary bypass (CBP). Patients and Methods: The present observational prospective study was conducted on 90 high risk patients, having records of hypertension and being candidates for open heart surgery. Patients divided into three groups based on their mean arterial pressure (MAP), lower than 60 mmHg (first group), between 60 to 70 mm Hg (second group) and higher than 70 mm Hg (third group) respectively during cardiopulmonary bypass. Clinical outcomes being studied included cardiac surgery-associated acute kidney injury (CSA-AKI) (RIFLE class), serum creatinine levels, glomerular filtration rate (GFR) and urinary output up to 24 hours after the surgery. Results: Data related to 90 case-patients have been analyzed. There was no difference between the groups in terms of demographic information. Prevalence of AKI in preliminary course after cardiac surgery was different among the groups. AKI occurred in six patients (15%) of the first group, five patients (12.5%) of the second group and two patients (5%) of the third group (P = 0.03). There have been no differences in terms of serum creatinine levels, GFR and urinary output during 24 hours after cardiac surgery, among the groups. However, delta creatinine level and delta GFR were significant in those groups with MAP of lower than 60 mm Hg and also between 60-70 mm Hg. Conclusion: This study showed that MAP level during CBP directly affects occurrence of AKI in patients after open heart surgery. High risk patients such as those suffering from hypertension have to be constantly monitored during CBP regarding their MAP. We concluded that MAP drops to lower than 70 mm Hg has to be prevented in hypertensive patients.
Compact Co-polarized Decoupled Microstrip Patch Array Antenna Based on TM02/TM03 Modes Cancellation

In this communication, two compact co-polarized decoupled microstrip patch array antennas based on TM02/TM03 modes cancellation are proposed. It is only necessary to introduce shorting pins and etch slots on the patch antenna to precisely adjust the frequency and impedance of TM02 and TM03 modes to make them consistent, which can significantly reduce the strong coupling between the tightly spaced patch antennas. In addition, the L-shaped open-stub coupling feeding is used to eliminate the parasitic inductance caused by the shorting pins to achieve better impedance matching. Finally, the proposed two/eight-port microstrip patch array antennas are fabricated and measured. The simulation and measurement results show that the coupling of adjacent ports is decreased lower than -30 dB within the impedance matching bandwidth (3.42 - 3.58 GHz), while the edge-to-edge spacing is only 0.023 λ0 between the antenna elements. With the advantages of simple design, significant decoupling effect, and good radiation performance, the proposed decoupling scheme has broad application prospects in 5G array antennas.
Thermo‐mechanical experiments on reinforced concrete beams: Assessing thermal, mechanical, and mixed impacts on fiber optic measurements

Strain and temperature measurements on reinforced concrete structures with Rayleigh‐based fiber optic sensors (FOS) promise dense data networks of crucial structural parameters. In this context, the measurement of temperature and mechanical strain is invariably intertwined, precipitating in a frequency shift recorded via FOS. Consecutive experiments were carried out on reinforced concrete beams under mechanical, thermal, and thermo‐mechanical loading. Basic analysis of fiber optics equations indicates the sensitivities toward both influences. These are quantified and juxtaposed in experiments, first separately and subsequently combined. As concerns temperature measurement, the slightest tensile forces exerted onto the FOS may engender distortions of several degrees Celsius. Conversely, strain measurements are affected by temperature changes to a lesser degree. Nevertheless, the level of strain to be sensed and the severity of corrupting temperature shifts must be carefully weighted. The article raises awareness for the coupling of temperature and strain and enables the practitioner to identify and assess perturbations.
Diosmetin Targeted at Peroxisome Proliferator-Activated Receptor Gamma Alleviates Advanced Glycation End Products Induced Neuronal Injury

The present study aimed to evaluate the role of diosmetin in alleviating advanced glycation end products (AGEs)-induced Alzheimer’s disease (AD)-like pathology and to clarify the action mechanisms. Before stimulation with AGEs (200 μg/mL), SH-SY5Y cells were treated with diosmetin (10 μmol/L), increasing cell viability. The induction of AGEs on the reactive oxygen species overproduction and downregulation of antioxidant enzyme activities, including superoxide dismutase, glutathione peroxidase, and catalase, were ameliorated by diosmetin. Amyloid precursor protein upregulation, accompanied by increased production of amyloid-β, caused by AGEs, was reversed by diosmetin. In the presence of diosmetin, not only β-site amyloid precursor protein cleaving enzyme1 expression was lowered, but the protein levels of insulin-degrading enzyme and neprilysin were elevated. Diosmetin protects SH-SY5Y cells from endoplasmic reticulum (ER) stress response to AGEs by suppressing ER stress-induced glucose regulated protein 78, thereby downregulating protein kinase R-like endoplasmic reticulum kinase, eukaryotic initiation factor 2 α, activating transcription factor 4, and C/EBP homologous protein. Diosmetin-pretreated cells had a lower degree of apoptotic DNA fragmentation; this effect may be associated with B-cell lymphoma (Bcl) 2 protein upregulation, Bcl-2-associated X protein downregulation, and decreased activities of caspase-12/-9/-3. The reversion of diosmetin on the AGEs-induced harmful effects was similar to that produced by pioglitazone. The peroxisome proliferator-activated receptor (PPAR)γ antagonist T0070907 (5 μmol/L) abolished the beneficial effects of diosmetin on AGEs-treated SH-SY5Y cells, indicating the involvement of PPARγ. We conclude that diosmetin protects neuroblastoma cells against AGEs-induced ER injury via multiple mechanisms and may be a potential option for AD.
Adsorbents Used for the Adsorptive Removal of Highly Hazardous Arsenic from Aqueous Solution: A Review

Millions of people worldwide are adversely affected by Arsenic continuing exposure, so providing arsenic-free consumption of water is an immense task for the researchers. The chemistry, content of arsenic-contaminated water as well as adsorption play a big role in arsenic elimination. The mechanism of adsorption technology's elimination of As (V) from the water was simply presented as the elements that govern various adsorption paths. The effects of a variety of adsorbents on As (V) elimination from aquatic were explored in the present research, which classified the materials used as adsorbents based on physical, chemical, and biological processes. When choosing an adsorbent, adsorption capability is an important factor to consider. As a result, developing As (V) elimination from aquatic adsorption strategies includes developing environmentally acceptable materials with effectual adsorption abilities, refining the preparation and alteration procedures of recent adsorbents, and boosting renewal effectiveness. After choosing a particular adsorbent for As (V) elimination from water, regional features of arsenic-polluted water, applied viability of the adsorption process, besides suitable environments of respectively material must be extensively reviewed and analyzed. The current study gives an outline of the adsorption technique to remove arsenic from wastewater, as well as the adsorption capacity of various adsorbents.
AUTOMATIC EXTRACTION OF FACADES AND WINDOWS FROM MLS POINT CLOUDS USING VOXELSPACE AND VISIBILITY ANALYSIS

Abstract. This contribution presents a method for extracting a 3D model of facades and windows from a point cloud. The point cloud is segmented based on a voxel octree, in which the facades are sought as planes. These can be used to filter out potential window points within the building, which are then analysed on their visibility by checking the occupancy grid of the voxel space. Here, methods of digital image processing are used for analysing both point clusters behind the facade and holes in the estimated facade planes as window candidates. Facades and windows are both simplified as rectangles. The test data set was gathered in a Mobile Laser Scanning campaign. While the segmentation fails in some cases, the extraction of facades and windows shows good results: 25 facades with 702 detected windows yield a detection rate of 86% with a false alarm rate of 13%. The reconstructed sizes of the windows differ from reference measurements in the range of centimetres to a few decimetres. These refined geometries can be used to enrich existing building models or for vehicle navigation without GNSS.
Detection of body position changes on the surface ECG

Changes in body position are sometimes mistaken for myocardial ischemia during ECG monitoring in the coronary care unit. Two different methods for detecting body position changes based on spatial and scalar approaches are investigated. These methods have been tested in two databases containing controlled body position changes, and ischemic episodes, respectively. The results show that reliable detection is possible in more than 90% of the cases.