Miracle-dz/UniFAR-FTUs huggingface dataset:
ON THE NATURE OF THE SMALL DARK GLOBULES IN THE ROSETTE NEBULA

The small dark globules seen against the nebulosity in the northwest quadrant of NGC 2237-2244 are shown on a 120-inch direct photograph to have an elongated, tear-drop form with the symmetry axes and sharper edges directed toward the central star cluster. This orientation is shared by the well-known elephant trunk structure, which in general lies farther from the center than these isolated dark spots. Examples of globules still connected with large dark masses by dust filaments are also present. It is suggested that these globules represent a late stage in the pinching-off and dissipation of elephant trunks as the central cavity of the H II region expands into the peripheral dust clouds, and that these globules are not protostars. It is estimated that the age of a typical small isolated globule in this region of NGC 2237-2244 is of the order of 10,000 years.
Diabetic Retinopathy Detection and Grading using Deep learning

— One of the complications of diabetes disease is diabetic retinopathy (DR). Diabetic patients may suffer from total loss of sight. That's if it is not detected and medicated early enough. The early detection of DR is very important during funds screening on a regular basis. Detection and grading of DR are difficult because most fundus images suffer from undersaturation and noise. This paper proposes a new enhancement process as a solution to the poor quality of fundus images. It also proposes two architectures for convolutional neural network (CNN) models. The first one is the binary classifier of DR images into normal and abnormal. The second CNN architecture to classify the severity grades of DR. In this study, we also utilized different pre-trained convolutional neural network models to show the impact on the performance of the use of transfer learning from pre-trained CNN models vs newly defined architectures. The pre-trained CNN models and the two new proposed CNN models are tested using Messidor 1, Messidor 2, and Kaggle EyePACS datasets. The proposed binary classifier model results in F1-scores of 0.9387, 0.9629, and 0.9430 on the Messidor-1, Messidor-2, and EyePACS datasets, respectively. The proposed second model classifies the five grades with an F1-score of 0.9133, 0.9226, and 0.9393 on the Messidor1, Messidor2, and Kaggle EyePACS datasets, respectively. The new proposed CNN model proved its reliability and efficiency in detecting DR and classifying severity grades of DR in fundus images. Preprocessing techniques enhanced the performance by 10.83% of accuracy and 0.13037 in AUC using the binary model
Progressive Shape Compression with Radial Basis Functions

A driven thread storage device for compensating instantaneous differences between thread feeding and withdrawal velocities in a textile machine includes a device for axially feeding thread at a feeding location, a device for axially withdrawing thread at a withdrawal location, a stationary storage drum, a driven thread guide in the form of a rotation-symmetrical disc conducting the thread to the storage drum and producing a thread balloon at the feeding location, the disc having an edge with at least one radially open thread guide slot formed therein, and a device disposed outside the thread balloon for supporting the disc.
ASSOCIATION MAPPING OF GERMINATION AND SOME EARLY SEEDLING STAGE TRAITS OF A TURKISH ORIGIN OAT COLLECTION

In recent years, oat plant especially for hay yield is on demand in Turkey. In this study, 167 oat landraces originated from Turkey were evaluated for germination and some early seedling stage traits and genotyped by 6K SNP Chip assay to detect candidate markers using association mapping analysis. Principal component analysis (PCA) were also performed to determine relationships among investigated traits. The variation in local oat genotypes for germination and other investigated traits was found significant at the 5% significance level, except for germination rate (GR). The values for germination rate was found between 52-76% and 52-100% for germination ratio, while 12.33 to 45 mm for coleoptile length and 8 to 21 mm for radicle length. On the other hand, plumula length varied between 2 to 28.45 mm and 1301.33 to 5494.40 for seed vigor index. In the research, PC1 and PC2 value was found 41.5% and 21.5%, respectively, explaining the 63% of the total variation. Germination rate and germination ratio (GP) were positively and significantly correlated with the other investigated traits. According to the results of the association mapping analysis a total number of 43 candidate markers were observed, 10 candidate markers for germination rate, five candidate markers for germination ratio (GP), five markers for radicle length (RL), eight markers for coleoptile length (CL), seven markers for plumula length (PL) and eight markers for seed vigor index (SVI). These candidate markers identified in this study for germination and early seedling stage traits could be used in future studies.
The combined foraging of a parasitoid and a predatory bug enhances mortality of Plutella xylostella larvae

Interactions between biocontrol agents of crop pests can lead to neutral, detrimental, or improved outcomes for pest control. We investigated the existence and the nature of the additive interactions between a parasitoid, Diadegma semiclausum (Hellén) (Hymenoptera: Ichneumonidae), and two hemipteran predators, Oechalia schellenbergii Guérin‐Méneville (Pentatomidae) and Nabis kinbergii Reuter (Nabidae), of the diamondback moth (DBM), Plutella xylostella (L.) (Lepidoptera: Plutellidae), under laboratory conditions. In the presence of the parasitoid, both O. schellenbergii and N. kinbergii increased predation by 56 and 66%, respectively. The escape response of the prey to avoid being parasitized (moving backwards and sometimes spinning down from the leaf on a silk thread, becoming less cryptic to the predators), may be at the basis of the enhanced predation by these predatory bugs; however, further studies are necessary to test this hypothesis. As the predators did not preferentially consume either parasitised or unparasitised larvae, coincidental intraguild predation should not affect this positive outcome in relation to DBM suppression. The findings highlight the potential utility of combining these natural enemies and may have important implications for the management of DBM in brassica crops in Australia and other multi‐species systems.
Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing

While Mobile CrowdSensing (MCS) has become a popular paradigm that recruits mobile users to carry out various sensing tasks collaboratively, the performance of MCS is frequently degraded due to the limited spatiotemporal coverage in data collection. A possible way here is to incorporate sparse MCS with data inference, where unsensed data could be completed through prediction. However, the spatiotemporal data inference is usually "fractured" with poor performance, because of following challenges: 1) the sparsity of the sensed data, 2) the unpredictability of a spatiotemporal fracture and 3) the complex spatiotemporal relations. To resolve such fracture data issues, we elaborate a data generative model for achieving spatiotemporal fracture data inference in sparse MCS. Specifically, an algorithm named Generative High-Fidelity Matrix Completion (GHFMC) is proposed through combining traditional Deep Matrix Factorization (DMF) and Generative Adversarial Networks (GAN) for generating spatiotemporal fracture data. Along this line, GHFMC learns to extract the features of spatiotemporal data and further efficiently complete and predict the unsensed data by using Binary Cross Entropy (BCE) loss. Finally, we conduct experiments on three popular datasets. The experimental results show that our approach performs higher than the state-of-the-art (SOTA) baselines in both data inference accuracy and fidelity.
Influence of Environmental Regulation on Corporate Green Supply Chain Management: The Regulating Effect of Environmental Dynamism

Environmental pollution, resource waste, and ecological imbalance have raised global concerns. Against this backdrop, green supply chain management (GSCM) becomes the focus of corporate sustainable development. Based on the institutional theory, thus study explores the influence of command-and-control environmental regulation (CCER) and market-based environmental regulation (MBER) over GSCM, as well as the regulating effect of environmental dynamism on the influence. A total of 191 valid responses were obtained through a questionnaire survey. The analysis of these responses shows that: CCER and MBER positive affect GSCM; environmental dynamism negatively regulates the correlations of CCER and MBER with GSCM. Based on these findings, theoretical guides and managerial implications were obtained for corporate GSCM.
Heatmap Assisted Accuracy Score Evaluation Method for Machine-Centric Explainable Deep Neural Networks

There have existed many studies about the explainable artificial intelligence (XAI) that explains the logic behind the complex deep neural network called a black box. At the same time, researchers have tried to evaluate the explainability performance of various XAIs. However, most previous evaluation methods are human-centric, that is, subjective, where they rely on how much the results of explanation are similar to what people’s decision is based on rather than what features actually affect the decision in the model. Their XAI selections are also dependent of datasets. Furthermore, they are focusing only on the output variation of a target class. On the other hand, this paper proposes a robust heatmap assisted accuracy score (HAAS) scheme over datasets that helps selecting machine-centric explanation algorithms to show what actually leads to the decision of a given classification network. The proposed method modifies the input image with the heatmap scores obtained by a given explanation algorithm and then puts the resultant heatmap assisted (HA) images into the network to estimate the accuracy change. The resultant metric (HAAS) is computed as a ratio of accuracies of the given network over HA and original images. The proposed evaluation scheme is verified in the image classification models of LeNet-5 for MNIST and VGG-16 for CIFAR-10, STL-10, and ILSVRC2012 over totally 11 XAI algorithms of saliency map, deconvolution, and 9 layer-wise relevance propagation (LRP) configurations. Consequently, for LRP1 and LRP3, MINST showed largest HAAS values of 1.0088 and 1.0079, CIFAR-10 achieved 1.1160 and 1.1254, STL-10 had 1.0906 and 1.0918, and ILSVRC2012 got 1.3207 and 1.3469. While LRP1 consists of ϵ-rules for input, convolutional, and fully-connected layers, LRP3 adopts a bounded-rule for an input layer and the same ϵ-rules for other layers as LRP1. The consistency of evaluation results of HAAS and AOPC has been compared by means of Kullback-Leibler divergence, ensuring that HAAS is the more robust evaluation method than AOPC independently of datasets since HAAS has much lower average divergence of 0.0251 than AOPC of 0.3048. In addition, the validity of the proposed HAAS scheme is further investigated through the inverted HA test that employs inverted HA images made up with inverted heatmap scores and estimates the accuracy degradation caused by applying them to the network. The XAI algorithms with largest HAAS results experience biggest accuracy degradation in the inverted HA test.
Performance Analysis for the Most Convenient Wind Turbine Selection in Wind Energy Facility

As governments seek renewable and more sustainable energy resources, wind energy has emerged as one of the most rapidly developing renewable power resources. The relevance of wind energy turbines has grown as more nations turn to renewable energy. A significant criterion that conduces to wind energy’s efficient production is the proper wind turbine’s utilize. Due to the fact that a lot of wind turbine manufacturers have built a global presence, it is critical for project administrators to do informed selections about which wind energy turbines to establish in every specific design. Therefore the problem of wind energy turbine choice is critical for nations experiencing global warming and climate change. This study proposes a new hybrid MCDM model including CCSD and MULTIMOOSRAL methods. In this study, 11 100kW wind turbines (T) are evaluated based on 14 criteria. According to the results of the proposed model, T7 coded wind turbine alternative was determined as the best one. The results of the proposed method were compared with other MCDM methods and it was confirmed that the proposed method reached accurate results. In addition, it was determined that the changes in the criteria weights changed the ranking of the alternatives.
Wideband Bidirectional Same Sense Endfire Circularly Polarized Antenna

In this paper, a wideband bidirectional endfire circularly polarized (CP) antenna is proposed by combining two endfire CP antennas with a single coaxial probe feed. The wideband characteristics are achieved with the help of a two-layered substrate separated by an air gap, and the excitation of CP waves in the endfire directions is yielded by the wideband magnetic dipoles and tapered electric dipoles. The proposed CP antenna has shown wide 10-dB impedance bandwidth (IBW) and 3-dB axial ratio bandwidth (ARBW) of 20.76% (5.05 - 6.22 GHz) and 16.10% (5.14 - 6.04 GHz), respectively. Besides showing an overall size of 0. 733λL × 0. 863λL× 0. 058λL (λL is the wavelength corresponding to the lowest operating frequency) with wide operational bandwidth, the proposed CP antenna has also demonstrated a desirable peak gain of 4.45 dBic.
Augmentation of 3D Holographic Image Graticule With Conventional Microscopy

In this paper, we report an implementation of a computer-generated holographic projection technique to display a holographic scene like a measuring graticule around the magnified sample image in a reflected bright-field microscopy. The implemented system acts as a gauging tool for lateral and longitudinal measurements of a sample that is being observed under a microscope through the assistance of a holographic measuring graticule. Numerical and experimental verifications have been performed, demonstrating the successful augmentation of a holographic projection system as a measuring tool with a conventional bright-field microscopic system.
Surfaces of mean curvature one in hyperbolic space

An endless belt trained between a driving roller and a guiding roller, such e.g. as a wide rubber belt having a flight thereof bearing against and serving to transport photoprinting sheets over a perforated wall of a tank holding a gaseous developing medium, is maintained in alignment by mounting the belt guiding roller, through rigid members rigidly connected with its bearing supports, on oppositely inclined guide tracks, such as ball tracks each holding one or two bearing balls, which are rigidly supported by structures at the opposite ends of the guiding roller. The guide tracks support parts of the roller mounting members for sliding movement in limited paths so inclined that their linear projections intersect at a point located away from the axis of the guiding roller on or near to a line connecting the mid-points of the axes of the two rollers. The mounting members present flanges at opposite sides of the belt path, each engageable by an edge of the belt for corrective displacement of the guiding roller if the belt travels too far sidewise. Rigid arms provided as the structures supporting the guide tracks can be swung about the axis of the driving roller for movement of the belt and guiding roller assembly away from working position, and can be adjusted in length to provide the required belt tension.
Cognitive and balance performance of older adult women during COVID-19 pandemic quarantine: an ex post facto study

Introduction Isolation and self-quarantine can expose individuals, particularly older people, to cognitive and physical decline. Due to a reduction in their musculoskeletal and neural flexibility, older adults are more likely to be affected by quarantine limitations. This study aimed to investigate the effect of self-quarantine on cognitive and balance performance of older women during the COVID-19 outbreak. Material and methods In a convenience sampling method, a total of 75 older adult women were recruited in this ex post facto study. The mini-mental state exam, single leg stance test, and timed up and go test were used to assess cognitive functions, static, and dynamic balance, respectively. Fall risk was measured by the Johns Hopkins assessment tool. Evaluations were performed before and after 7 months of quarantine due to the COVID-19 outbreak (November 2019 – June 2020), in which volunteers were at the lowest level of physical and social interaction. Results No significant difference was observed in the mean static balance performance of the older adult women between the baseline and quarantine phases [p = 0.095, t (df) = –1.69]. The dynamic balance performance [p < 0.001, t (df) = 5.6] and cognitive status (p < 0.001, t = –7.4) decreased and the fall rate increased [p < 0.001, t (df) = 7.35] after 7 months of quarantine. Conclusions It seems that self-quarantine can cause a decline in cognitive functions and dynamic balance performance of older women. It implies that the decrease in social interactions and physical activities caused by the limitations of self-quarantine put individuals at greater risk of cognitive impairment and increase their falling rate by impairing dynamic balance.
Hierarchal Rendering of Trees from Precomputed Multi-Layer Z-Buffers

Chen and Williams[2]show how precomputedz-bufferhnagesfromdifferentfixedviewing positionscanbe reprojectedtoproducean imagefora new viewpoint.Here imagesareprecom-putedfortwigsand branchesatvariouslevelsinthehierarchicalstructureof a tree,and adap-tivelycombined,dependingon thepositionof thenew viewpoint.The precomputedimages containmultiplez levelstoavoidmissingpixelsinthereconstruction,subpixelmasks foranti-aliasing, and colors and normalsfor shadingafterreprojection.
The Better I Can Be: In Defence of Human Enhancement for a New Genetic Equality

The main objection to genetic enhancement is that it will create a “genetic apartheid,” deepening existing inequalities. This paper offers considerations that can weaken the inequality argument against genetic enhancement. First, I question the dichotomy of treatment versus enhancement since the differences between the two are unclear. Second, I argue that human enhancement is part of human nature and that there is no sound reason to accept it in other domains while rejecting it in genetics. The paper also demonstrates that inequality is present in every dimension of society, that “God-given” genetics is profoundly unequal, Résumé Abstract La principale objection à l’amélioration génétique est qu’elle créera un “apartheid génétique”, aggravant les inégalités existantes. Cet article met en lumière des considérations qui peuvent affaiblir l’argument de l’inégalité contre l’amélioration génétique. Tout d’abord, je remets en question la dichotomie entre traitement et amélioration, car les différences entre les deux ne sont pas claires. Deuxièmement, je démontre que l’amélioration humaine fait partie de la nature humaine et qu’il n’y a aucune raison valable de l’accepter dans d’autres domaines tout en la rejetant en génétique. L’article démontre également que l’inégalité est présente dans toutes les dimensions de la société, que la génétique “divine” est profondément inégale et que l’amélioration génétique peut fonctionner comme un mécanisme permettant d’atteindre une nouvelle égalité génétique. Toutefois, l’article souligne que l’égalité génétique n’est pas, en soi, une valeur à laquelle aspirer si elle nous conduit à une communauté uniforme d’êtres humains réduits. L’égalité génétique n’a de valeur que si elle améliore l’humanité en général. paper against differences between the two are unclear. Second, I argue that human enhancement is part of human nature and that there is no sound reason to accept it in other domains while rejecting it in genetics. The paper also demonstrates that inequality is present in every dimension of society, that “God-given” genetics is profoundly unequal, and that genetic enhancement can operate as a mechanism by which a new genetic equality can be achieved. However, the paper underlines that genetic equality is not, per se, a value to which we ought to aspire if it leads us to a uniform community of downsized human beings. Genetic equality is only valuable if it enhances humankind in general.
Genome-Wide Association Study of Egg-Laying Traits and Egg Quality in LingKun Chickens

Egg production is the most important trait of laying hens. To identify molecular markers and candidate genes associated with egg production and quality, such as body weight at first oviposition (BWF), the number of eggs produced in 500 days (EN500), egg weight (EW), egg shell thickness (EST), egg shell strength (ESS), and Haugh unit (HU), a genome-wide analysis was performed in 266 LingKun Chickens. The results showed that thirty-seven single nucleotide polymorphisms (SNPs) were associated with all traits (p < 9.47 × 10−8, Bonferroni correction). These SNPs were located in close proximity to or within the sequence of the thirteen candidate genes, such as Galanin And GMAP Prepropeptide (GAL), Centromere Protein (CENPF), Glypican 2 (GPC2), Phosphatidylethanolamine N-Methyltransferase (PEMT), Transcription Factor AP-2 Delta (TFAP2D), and Carboxypeptidase Q (CPQ) gene related to egg-laying and Solute Carrier Family 5 Member 7 (SLC5A7), Neurocalcin Delta (NCALD), Proteasome 20S Subunit Beta 2 (PSMB2), Slit Guidance Ligand 3 (SLIT3), and Tubulin Tyrosine Ligase Like 7 (TTLL7) genes related to egg quality. Interestingly, one of the genes involved in bone formation (SLIT3) was identified as a candidate gene for ESS. Our candidate genes and SNPs associated with egg-laying traits were significant for molecular breeding of egg-laying traits and egg quality in LingKun chickens.
Polymorphism of the Signal Transducer and Activator of Transcription 5A (STAT5A) gene in Egyptian water buffaloes using the SSCP technique

Buffalo is the main source of white milk and contributes 45% of the annual milk production in Egypt. The STAT5A protein has an important role in the signal transduction process within uterine epithelial cells and mammary glands affecting milk yield, fertilization, and embryonic survival rates in cattle. The studies conducted for the improvement of the genetic potentiality of productive and reproductive traits of Egyptian buffalo are still scanty. Data on polymorphisms of the buffaloes STAT5A gene is limited. Hence, the present study aimed to identify novel polymorphisms in the STAT5A gene and to validate its genotypic frequencies in Egyptian buffalo. A 929 bp including part of intron 7 to part of intron 9 and the intervening exons of the STAT5A gene was amplified and genotyped by the SSCP method. Three different conformation patterns in the investigated 60 buffaloes were observed. Pattern B showed the highest observed frequency of 51.7%, while patterns A and C occurred at frequencies of 45% and 3.3% respectively. A Chi-square test showed that the Egyptian water buffalo population was in Hardy-Weinberg equilibrium. STAT5A gene might be utilized as a potential molecular marker for effective animal selection and breeding programs.