Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Do Vocational High School Girls Drop Out? Unraveling the Correlation between Business Development in Rural Areas and Adolescents’ School Interest in the Blitar Regency, East Java

This paper explores the reasons for students to consider dropping out of school and choosing to work. It also assesses the benefits of marketing study programes with regards to the store clerk profession. This study employs qualitative design using phenomenology approach. The key subjects of this research were four vocational high school students in Blitar who had opted to leave school early. Data was extracted and explored using in-depth interviews, observation, and documentation. Triangulation of sources and methods was carried out to obtain accurate information, the analysis was carried out with the simultaneous stages of Approach, Excavation, Deepening, Matching, Interpretation and Presentation (6P). The results of this study demonstrate that the main reasons contributing to leaving school early are family background, environment, society, and the student’s experience during school. In addition, the vocational marketing study program gives students the requisite experience and skill sets to work as store clerks, further facilitating their decision to leave school early and start their professional careers. Keywords: vocational high school students drop out, marketing expertise competence, rural area business development
Financial Sustainability Evaluation and Forecasting Using the Markov Chain: The Case of the Wine Business

This paper proposes a framework for assessing the financial sustainability of a wine producing company. The probabilistic approach is used to model the expected changes in the financial situation of an enterprise based on the historical trends. The case of an enterprise in Ukraine is considered as an illustration. The Markov chain is adopted for the forecasting exercise. Using the Markov chain framework allows one to predict the probability of financial security change for several periods ahead. The forecast relies on the transition probabilities obtained by exploiting the historical data. The proposed framework is implemented by construction of the financial security level transition matrices for three scenarios (optimistic, baseline and pessimistic). The case study of a Ukrainian wine producing company is considered. The possibilities for applying the proposed method in establishing anti-crisis financial strategy are discussed. The research shows how forecasting the financial security level of a company can serve in anti-crisis financial potential buildup.
Green hay transfer for grassland restoration: species capture and establishment

Green hay transfer from species‐rich donor sites is now commonly used in Europe to restore species‐rich semi‐natural grassland, both on ex‐arable land and on former intensive grassland. However, species transfer rates are usually well below 100%, and due to lack of further colonization by additional target species after initial restoration, continued progress toward the target plant community is often very slow. We used data from a restoration experiment aiming to reestablish species‐rich grazed meadows of the MG5 grassland type according to the British National Vegetation Classification to investigate relationships between species abundance at a donor site, species capture by green hay and its seed content, and success of species establishment on experimental plots in formerly intensively managed species‐poor grassland undergoing restoration. Our results show that species with higher abundance at the donor site were more likely captured as seed in green hay, and were more likely to establish after hay application at the recipient site. Species with low abundance at the donor site that also possessed specific germination requirements that might prevent immediate establishment after green hay transfer were particularly unlikely to get established after transfer. These findings can provide guidance for additional measures aimed at ensuring establishment of a wider range of target species. Such measures could include targeted sowing of species in addition to green hay application, and management of restored grassland swards to extend or reopen an initial window of opportunity for the establishment of green hay species that might not be germinable immediately after hay transfer.
Extracting Fresnel zones from migrated dip-angle gathers using a convolutional neural network

Fresnel zones are helpful for obtaining a high signal-to-noise ratio (S/N)-migrated result. A migrated dip-angle gather provides a simple domain for estimating 2D Fresnel zones for 3D migration. We develop a deep-learning-based technology to automatically estimate Fresnel zones from migrated dip-angle gathers, thus avoiding the cumbersome task of manually checking and modifying the boundaries of the Fresnel zones. A pair of 1D Fresnel zones are incorporated to represent a 2D Fresnel zone in terms of the inline and crossline dip angles because it is difficult to directly extract 2D Fresnel zones from a 2D dip-angle gather. The proposed convolutional neural network (CNN) is established by modifying VGGNet. As picking boundaries of the Fresnel zones is a regression problem, we remove the last soft-max layer from the VGGNet. The last three convolution layers and a pooling layer are also removed because the feature maps are small enough. To improve the contrast and definition, we enhance the features of the reflected events in the dip-angle gather. Data normalisation is carried out to accelerate the training process using a simple-rescaling method before training the modified VGGNet. Field data examples demonstrate the effectiveness and efficiency of the proposed method.
A new species of leaf fish, Nandus banshlaii (Perciformes: Nandidae) from West Bengal, India

Nandus banshlaii, sp. nov. is described from the Banshlai River of West Bengal. This species is distinguished from all its congeners in having a golden brown body in live and a combination of characters like longest head and snout length (44.28% SL and 35.58% HL respectively) and from its two Indian congeners in containing largest eye diameter (22.22% HL), longest pre-dorsal length (47.16% SL), shortest pectoral fin length (14.60% SL) and smallest dorsal fin base length (45.53% SL). Like all three congeners of Ganga-Brahmaputra-Meghna river basin of Gangetic delta it possess a dark spot on caudal peduncle. To differentiate the present species from other two Indian congeners of Nandus, N. nandus and N. andrewi, PCA and heatmap is performed and a key of all three species is also provided.
Forage quality on family farms in Croatia: monitoring corn silage quality over the two winter feeding seasons of dairy cows

U okviru primijenjeno-istraživackog projekta: « Uspostava sustava analize krme NIR spektroskopijom» pracena je kvaliteta travne silaže, kukuruzne silaže i sijena na obiteljskim poljoprivrednim gospodarstvima (OPG) u RH tijekom sest mjeseci hranidbe u svakoj od dvije godine istraživanja (od studenog 2003. do svibnja 2004. i od studenog 2004. do svibnja 2005.). U istraživanje je bilo ukljuceno 18 OPG, vecih proizvođaca mlijeka iz 5 županija. Svrha ovog istraživanja bila je pratiti kvalitetu kukuruzne silaže tijekom druge godine istraživanja i usporediti kvalitetu kukuruzne silaže između prve i druge godine istraživanja. Uzorci kukuruzne silaže analizirani su jedanput mjesecno NIRS aparatom (Foss, Model 6500), a na temelju rezultata analize savjetnici HZPSS-a su davali preporuku hranidbe muznih krava za naredni mjesec. Utvrđivani su sljedeci parametri kvalitete: suha tvar (ST), korigirana ST (KST), organska tvar (OT), sirovi proteini (SP), neutralna detergent vlakna (NDF), metabolicka energija (ME), kiselost (pH), fermentirajuca metabolicka energija u ME (FME/ME), skrob i probavljivost organske tvari u suhoj tvari (D-vrijednost). Prosjecni rezultati analiza ispitivanih silaža pokazuju poželjan sadržaj KST (352.99 g kg-1), visok sadržaj skroba (339, 86 g kg-1ST) i NDF (422, 65 g kg-1ST). Silaža je u prosjeku bila stabilna (pH 3, 65), uobicajenog sadržaja FME/ME (79%) i vrlo dobre probavljivosti (D-vrijednost 71, 1%), ali vrlo niskog sadržaja proteina (58, 96 g kg-1ST). Statisticki znacajne razlike između pojedinih OPG dobivene su za sadržaj KST (P<0, 05), D-vrijednosti (P<0, 05), NDF (P<0.05), pH (P<0, 05), skroba (P<0, 05), ME (P<0, 05) i OT (P<0, 05). Usporedbom prosjecnih rezultata kvalitete uzoraka kukuruzne silaže u dvije godine istraživanja utvrđeno je, da su uzorci kukuruzne silaže druge godine istraživanja imali statisticki znacajno niži sadržaj KST, SP i FME/ME (P<0.01).
Architecture Optimization and Interpretability in Neural Networks for HRTEM Segmentation

Machine learning and deep learning are becoming key elements of Transmission Electron Microscopy (TEM) analysis. Several pipelines have been demonstrated both in the realm of high resolution STEM as well as TEM [3,4]. Most rely on a primary segmentation step with many using the U-Net architecture proposed by Ronneberger and coworkers [2]. However, a plethora of architectures have been proposed for segmentation of real images. There has been an effort in the biomedical community to understand the impact of network architecture on segmentation [5,6]. However, this area is still just beginning to be developed for segmentation of TEM for materials science [1]. Due to the fundamental nature of the segmentation problem in microscopy we chose to analyze network architectures for the segmentation task. We analyze both the classic U-Net architecture as well as the FCN8s network which is based on the standard image classification network VGG-16 [7,8]. Traditional image classification networks are known to have learned features very similar to traditional image processing filters such as filters that respond much like an edge detection filter [9,10]. The FCN8s architecture then builds on these base features to make segmentation maps. We are able to develop this architecture using the pretrained VGG16 from Keras which benefits from prior training on the ImageNet dataset which is much larger than any available dataset for HRTEM [8]. We compare these two in order to understand whether the presence of features focusing on edge detection, and other traditional real image features help in the very noisy HRTEM case and whether we can leverage pre-learned features to push past the performance of U-Nets. We then also analyze the use of convolutional dilation in order to learn the effects of changing the scale over which features can be learned from for the network. Beyond exploring which architecture yields best results, recent
Real time monitoring of peptidoglycan synthesis by membrane-reconstituted penicillin binding proteins

Peptidoglycan is an essential component of the bacterial cell envelope that surrounds the cytoplasmic membrane to protect the cell from osmotic lysis. Important antibiotics such as β-lactams and glycopeptides target peptidoglycan biosynthesis. Class A penicillin binding proteins are bifunctional membrane-bound peptidoglycan synthases that polymerize glycan chains and connect adjacent stem peptides by transpeptidation. How these enzymes work in their physiological membrane environment is poorly understood. Here we developed a novel FRET-based assay to follow in real time both reactions of class A PBPs reconstituted in liposomes or supported lipid bilayers and we demonstrate this assay with PBP1B homologues from Escherichia coli, Pseudomonas aeruginosa and Acinetobacter baumannii in the presence or absence of their cognate lipoprotein activator. Our assay allows unravelling the mechanisms of peptidoglycan synthesis in a lipid-bilayer environment and can be further developed to be used for high throughput screening for new antimicrobials.
Support Vector Regression for GPA Prediction

This study aims to predict student GPA. This research began by collecting data. The features used in predicting GPA are semester 1 and semester 1 IP grades. The process of GPA prediction uses SVM regression, Linear Regression, and Simple Linear Regression. Based on testing with normalized data, the smallest error is obtained by the SVM regression method with Kernel RBF which is equal to 0.1505. Whereas by using standardized data, the smallest error is obtained by using the SVM regression improve method with the Kernel RBF, which is 0.1487. Based on this research, in order to obtain prediction results that are closer to the actual values, it is better to standardize the data first and to predict the process using the SV Regression Improve method using the Kernel RBF.
SAVE: A secure cloud-based pipeline for CRISPR pooled screen deconvolution

We present a user-friendly, cloud-based, data analysis pipeline for the deconvolution of pooled screening data. This tool, termed SAVE for Screening Analysis Visual Explorer, serves a dual purpose of extracting, clustering and analyzing raw next generation sequencing files derived from pooled screening experiments while at the same time presenting them in a user-friendly way on a secure web-based platform. Moreover, SAVE serves as a useful web-based analysis pipeline for reanalysis of pooled CRISPR screening datasets. Taken together, the framework described in this study is expected to accelerate development of web-based bioinformatics tool for handling all studies which include next generation sequencing data. SAVE is available at http://save.nrihub. org.
Variability and Period Analysis for BL Lac AO 0235+164

Variability is one of the extreme observational properties of BL Lacertae objects. AO 0235+164 is a well-studied BL Lac throughout all electromagnetic wavebands. In the present work, we show its optical R-band photometric observations carried out during the period from 2006 November to 2012 December using the Ap6E CCD camera attached to the primary focus of the 70 cm meniscus telescope at Abastumani Observatory, Georgia. During our monitoring period, it showed a large variation of (14.19–19.07 mag) and a short timescale of . During the period of 2006 December to 2009 November, we made radio observations of the source using the 25 m radio telescope at Xinjiang Astronomical Observatory. By adopting a discrete correlation function to the optical and radio observations we found that the optical variation leads a radio variation of 23.2 ± 12.9 days.
Changing Mantle Sources and the Effects of Crustal Passage on the Steens Basalt, SE Oregon: Chemical and Isotopic Constraints

Continental flood basalts are more prone to compositional modification from passage through thicker and (or) more felsic crust in comparison to their oceanic counterparts. The Steens Basalt in southeast Oregon (~17 Ma) is among the oldest and most mafic members of the Columbia River Basalt Group and provides a record of the early stages of flood basalt volcanism. We evaluate the balance of mantle sources in time during the onset of Columbia River Basalt Group magmatism and assess the effect of crustal passage using stratigraphically controlled Sr, Nd, Pb, Hf, Os, and O isotopic compositions, as well as whole rock major and trace element data.
In Vitro Propagation of Ponytail Palm: Producing Multiple-shoot Plants

Fig. 2. One-year-old in vitro-propagated, multipleshoot ponytail palms. Ponytail palm (Beaucarnea recurvata Lem.) is indigenous to desert regions of Texas and Mexico (Everett, 1981). This slow-growing plant is resistant to dry conditions, low relative humidity, and shade, and has remarkable longevity indoors. It is imported into Europe from native regions in the form of whole stems or stem pieces that produce rather expensive plants. Sexual propagation results in a small plant with a swollen stem base and one shoot apex that can be marketed after 1 to 2 years. This paper describes a protocol for in vitro propagation of multiple-shoot, well-acclimatized plants as an alternative to seed propagation. In vitro culture was started with lto 2-mm shoot apexes from young seedlings germinated in peat. After excision, each apex was disinfested for 10 min in a bleach solution [ 1% NaOCl (w/v)], rinsed twice for 1 min in sterile distilled water, and aseptically cultured on a medium containing the following Murashige and Skoog (1962) inorganic salts (mg·liter): myo-inositol, 100; nicotinic acid, 1.0; thiamine·HCl, 0.5; pyridoxine·HCl, 0.5; and glycine, 4.0, which was solidified with 6 g MC 29 agar/liter (Lab M, Topley House, England). Before autoclaving at 120C for 20 min, growth regulators were added to the medium and the pH was adjusted to 5.8. Cultures were maintained at 22±1C with a 16-h photoperiod of 75 μmol·s ·m provided by cool-white fluorescent lamps. In the multiplication and rooting experiments, five or six glass vessels, 8 cm in diameter and containing 75 ml of medium, were planted for each concentration with 10 explants per vessel. Measurements on the effect of N -(phenylmethyl)-1H-purine-6-amine (BA) and 1-naphthaleneacetic acid (NAA) on producing multiple-shoot microcuttings per explant and roots per microcutting were subjected to regression analysis. Surviving and sufficiently developed (1 cm) explants were transferred after 2 months to a multiplication medium (MM) consisting of Quoirin et al. (1978) inorganic salts supplemented with (mg·liter) myo-inositol, 50; nicotinic acid, 0.5; thiamine·HCl, 0.25; pyridoxine·HCl, 0.25; glycine, 2.0; BA, 0.5; gibberellic acid (GA,), 0.1; sucrose, 20,000;
Confirmation of root-knot nematode resistant gene Rmi1 using SSR markers

Background: The Root Knot Nematode (RKN) is a serious economic threat to various cultivated crops worldwide. It is a devastating pest of soybean and responsible to cause severe yield loss in Pakistan. The cultivation of resistant soybean varieties against this pest is the sustainable strategy to manage the heavy loss and increase yield. There is an utmost need to identify RKN resistant varieties of soybean against cultivated in Pakistan. The presented study is an attempt to identify and confirm the presence of resistant gene Rmi1 in soybean. Method: Molecular studies have been done using Simple Sequence Repeat (SSR) marker system to identify resistant soybean varieties against Root Knot Nematode (RKN) using fifteen (15) indigenous cultivars and four (4) US cultivars. DNA was isolated, purified, quantified and then used to employ various SSR markers. The amplified product is observed using gel documentation system after electrophoresis. Results: Diagnostic SSR markers Satt-358 and Satt-492 have shown the presence of Rmi1 gene in all resistance carrying genotypes. Satt-358 amplified the fragment of 200 bp and Satt-492 generated 232 bp bands in all resistant genotypes. This study confirmed the Rmi gene locus (G248A-1) in all internationally confirmed resistant including six (6) native varieties. Conclusion: These investigations have identified six (6) resistant cultivars revealing the effective and informative sources that can be utilized in breeding programs for the selection of RKN resistance soybean genotypes in Pakistan.
Projects and programs of physical activity for old in the public Brazilian universities: a general view

The objective of this work was to describe a structure of projects/programs existing today in Brazilian public universities, to identify similarities and divergences and to point out indicators for changing new applications. Qualitative research of the descriptive exploratory type. Data were collected using an online instrument with 54 program coordinators, analyzed using the content analysis technique proposed by Bardin. Results: Found similarities regarding teaching strategies for elderly people according to what scientific literature prescribes. There was disagreement regarding the offer of activities in the different programs surveyed; there is no activity model to be followed. There was disagreement as to the type of physical activity offered in the programs. Not all regions have well-structured programs, there is a lack of resources, materials and personnel with experience in the area of physical activity for the elderly; built structures and places for carrying out activities are lacking. The offer of physical activities for the elderly in public universities is not yet a reality in all of them. Most programs increase through university extension and have been one of the maintainers of their legacy. We understand that there are indicators for the formulation of new proposals, such as: the experience of professionals in the field of Physical Education in offering and structuring the physical exercise offered; the need for teacher and continuing training; research and extension together in teaching; the importance of the evaluation as a subsidy for the continuity and prescription of the proposed exercises.
Egyptian Macroeconomic Status with Reference to the Shadow Economy during the Period 1991-2018

The Egyptian economy is one of the most diversified economies in the MENA region. During the past decades, various consecutive phases have been adopted targeting a comprehensive structural economic reform which resulted in a market-oriented economy, a liberalized stock market and a strong private sector. The shadow economy has a distorting effect on the accuracy of the country’s official records and statistics and affects the state’s fiscal and monetary policies. In this concern, the government should gain from the positive side of the shadow economy by merging it with the official one. Accordingly, this guarantees best results for all concerned parties.
A V-Band Miniaturized Bidirectional Switchless PALNA in SiGe:C BiCMOS Technology

This letter presents a <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>-band switchless bidirectional power amplifier-low noise amplifier (PALNA) in a SiGe:C 130-nm BiCMOS technology, featuring <inline-formula> <tex-math notation="LaTeX">$\text{f}_{t}/\text{f}_{\text {max}}$ </tex-math></inline-formula> of 250/340 GHz. This bidirectional PALNA architecture avoids the use of lossy transmit–receive switches by introducing a proper matching network that insures a good isolation when the amplifier is OFF and satisfies the input–output matching requirements when the amplifier is on. On-wafer measurements show that the designed PALNA has a peak small-signal gain of 16.5 and 17 dB in the Tx mode and Rx mode, respectively, with a reverse isolation better than 40 dB while maintaining wideband performance over the desired band from 57 to 66 GHz. In the Rx mode, the simulated noise figure (NF) is 6.5 dB over the required band. Furthermore, a 1-dB compression point (OP1dB) of 11 dBm in the Tx mode and an input 1-dB compression point (IP1dB) of −20 dBm in the Rx mode have been achieved. The switchless PALNA occupies only 0.18 mm<sup>2</sup> and consumes 130 and 36 mW in the Tx and Rx modes, respectively.
RTL3D: real-time LIDAR-based 3D object detection with sparse CNN

: LIDAR (light detection and ranging) based real-time 3D perception is crucial for applications such as autonomous driving. However, most of the convolutional neural network (CNN) based methods are time-consuming and computation-intensive. These drawbacks are mainly attributed to the highly variable density of LIDAR point cloud and the complexity of their pipelines. To find a balance between speed and accuracy for 3D object detection from LIDAR, authors propose RTL3D, a computationally efficient Real-time LIDAR-based 3D detector. In RTL3D, an effective voxel-wise feature representation is utilised to organise unstructured point cloud. By employing a sparse feature learning network (SFLN) on voxelised 3D data, RTL3D exploits the sparsity of point cloud and down-samples 3D data into 2D. Basing on the generated 2D feature map, an optimised dense detection network (DDN) is applied to regress the oriented bounding box without relying on any predefined anchor boxes. The authors also introduce an incremental data augmentation approach which greatly improves the performance of RTL3D. Empirical experiments on public KITTI benchmark demonstrate that RTL3D achieves a competitive performance with state-of-the-art works on 3D detection task. Owning to the simplicity of its single-stage and anchor-free design, RTL3D has a real-time inference speed of 40 FPS.