Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Seasonal Distribution and Threats to Avian Fauna of Lahore Safari Zoo

Sr # Order Family Common name Scientific name IUCN status Occurrence 1 Ciconiformes Ardeidae Black-crowned night heron Nycticorax nycticorax LC SB 2 Indian pond heron Ardeola grayii LC R 3 Cattle egret Bubulcus ibis LC R 4 Anseriformes Anatidae Mallard Anas platyrhynchos LC WM 5 Falconiformes Accipitridae Black kite Milvus migrans LC R 6 Shikra Accipiter badius LC R 7 Long-legged buzzard Buteo rufinus LC WM 8 Galliformes Phasianidae Grey francolin/partridge Francolinus pondicerianus LC R 9 Gruiformes Rallidae White breasted waterhen Amaurornis phoenicurus LC R 10 Common moorhen Gallinula chloropus LC R 11 Charadiiformes Scolopacidae Temminck's stint Calidris temminckii LC WM 12 Common sandpiper Actitis hypoleucos LC WM 13 Charadriidae Red-wattled lapwing Vanellu indicus LC R 14 Rostratulidae Greater painted snipe Rostratula benghalensis LC R 15 Columbiformes Columbidae Rock dove (pigeon) Columba livia LC R 16 Yellow fronted green pigeon Treron phoenicoptera LC WM 17 Eurasian collard –dove Streptopelia decaocto LC R 18 Red collard dove Streptopelia tranquebarica LC SB 19 Laughing dove Streptopelia senegalensis LC R 20 Pied coucko Reinwardtoena browni NT SB 21 Psittaciformes Psittacidae Alexandrine parakeet Psittacula eupatria NT R 22 Rose-ringed parakeet Psittacula krameri LC R 23 Strigiformes Strigidae Spotted owlet Athene brama LC R 24 Coraciiformes Upupidae Common hoopoe Upupa epops LC R 25 Alcedinidae Pied kingfisher Ceryle rudis LC R 26 White-throated kingfisher Halcyon gularis LC R Pakistan J. Zool. , vol. 50(2), pp 533-538, 2018. DOI: http://dx.doi. org/10.17582/journal.pjz/2018.50. 2.533. 538
Numerical Simulation‐Based Clarification of a Fluid‐Flow System in a Seafloor Hydrothermal Vent Area in the Middle Okinawa Trough

Despite many studies on seafloor hydrothermal systems conducted to date, the generation mechanism of seafloor massive sulfide (SMS) deposits is not yet fully understood. To elucidate this mechanism, this study clarifies the three‐dimensional regional temperature distribution and fluid flow of a seafloor hydrothermal system of the Iheya North Knoll, middle Okinawa Trough. Lateral flow and boiling of hydrothermal fluids below a caprock were the main features found by the simulation. A caprock formation generated by anhydrite precipitation and hydrothermal alteration is the most plausible cause of these features, because caprocks can increase the temperature and induce boiling of fluids by preventing seawater inflow. Such a formation also gradually makes the top of the conduit less permeable; thus, lateral flow occurs. Consequently, vapor‐rich hydrothermal fluids poor in metals are discharged from vents as white smokers, whereas liquid‐dominated hydrothermal fluids rich in metals flow laterally below the caprocks, forming subseafloor SMS deposits.
Incidencia de contaminantes microbianos en la micropropagación de la caña de azúcar

The incidence of microbial contaminants in Establishment, Multiplication and Rooting stages of the sugarcane micropropagation was determined by visual observation of the culture vessels. The type of microorganism was confirmed in observations to the optic microscope. The percentage of contamination for microbial group was determined in 731 apexes in the Establishment stage, in each multiplication subculture (up to the seventh) in a total of 5 225 in vitro plants and 6 650 in the Rooting stage. In three stages the presence of microbial contaminants was verified (filamentous fungi, bacteria and yeasts) with prevalence of the bacteria (13.7-31.6%). In the Multiplication stage the percentages of bacterial contamination were increased with the number of subcultures. The results indicated the high incidence of microbial contaminants in sugarcane micropropagation and the necessity of paying attention to the control of the bacterial contamination. Key words: bacteria, filamentous fungi, in vitro plants, yeast
Analysis and modification of a common energy harvesting system using magnetic shape memory alloys

In this paper, a common energy harvester is investigated which uses a specimen of magnetic shape memory alloy (MSMA). The aim of this study is to improve system performance and to evaluate the magneto-mechanical loading on the MSMA material. Since demagnetization effect is not included in the employed original MSMA model, a method to incorporate this effect is proposed which has a good performance for the specific magneto-mechanical loading of this problem. In order to decrease the need for bias magnetic field and increase system efficiency, a new return mechanism for the MSMA specimen is proposed. The results indicate that the maximum harvested power from the improved system is obtained at 0.55 T bias field, with 30% increase in power. Then, input mechanical loading in the system is studied. Firstly, applied strain rate caused by mechanical loading is studied, and a nonlinear relation between the induced RMS voltage and strain rate is observed. Next, 2D applied mechanical loading is investigated, and it is shown that by increasing the phase difference between mechanical loads in two directions, the induced voltage decreases. Moreover, applying dynamic effect to the model shows that for thin MSMA specimens, this effect is minor, but by increasing the thickness and loading frequency, the effect becomes tangible.
Synthesis of Normal Heart Sounds Using Generative Adversarial Networks and Empirical Wavelet Transform

Currently, there are many works in the literature focused on the analysis of heart sounds, specifically on the development of intelligent systems for the classification of normal and abnormal heart sounds. However, the available heart sound databases are not yet large enough to train generalized machine learning models. Therefore, there is interest in the development of algorithms capable of generating heart sounds that could augment current databases. In this article, we propose a model based on generative adversary networks (GANs) to generate normal synthetic heart sounds. Additionally, a denoising algorithm is implemented using the empirical wavelet transform (EWT), allowing a decrease in the number of epochs and the computational cost that the GAN model requires. A distortion metric (mel–cepstral distortion) was used to objectively assess the quality of synthetic heart sounds. The proposed method was favorably compared with a mathematical model that is based on the morphology of the phonocardiography (PCG) signal published as the state of the art. Additionally, different heart sound classification models proposed as state-of-the-art were also used to test the performance of such models when the GAN-generated synthetic signals were used as test dataset. In this experiment, good accuracy results were obtained with most of the implemented models, suggesting that the GAN-generated sounds correctly capture the characteristics of natural heart sounds.
Dyeing mechanism and photodegradation kinetics of gardenia yellow natural colorant

In this study, gardenia yellow solution is used to dye 100% cotton fabric. The dyeing rate curve and adsorption isotherms were recorded to explore the thermodynamic model and to calculate the corresponding parameters. A definite concentration of gardenia yellow solution was placed under the xenon arc lamp for irradiation to test its photodegradability. Absorbance of the solution was measured at different degradation times and the corresponding varying curve of the absorbance was drawn to explore the photodegradation reaction order of the natural colorant and consistent parameters were calculated. The experimental results proved that the dyeing of cotton fabric with gardenia yellow colorant followed the pseudo second order kinetic model whereas adsorption isotherm followed the Langmuir model and the photodegradation process followed the second order kinetic model. Values of different parameters were calculated: reaction rate constant k = 2.26 × 10–3 (mg · L−1)1−m h−1, the correlation coefficient R2 = 0.994, and half decay time t1/2 = 5.82 h.
Learning with large, complex data and visualizations: youth data wrangling in modeling family migration

ABSTRACT We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using screen-capture and video recordings, field notes, and artifacts, we analyzed youth’s step-by-step decision-making and interaction with data interfaces in data wrangling, which we define as the practices for selecting, interpreting, and integrating datasets in order to build meaningful data displays and tell a story with the data. We identify patterns in youth’s data wrangling trajectories and propose a conceptual model for describing the stages (Find, Relate, Challenge, Build) of youth learning to construct models and tell stories about family migration. In addition, we highlight student struggles and opportunities for learning to be explored in future learning environment designs with large, complex datasets and data interfaces.
Comparative study of the subcellular localisation and the N-glycosylation patterns of a recombinant glycoprotein expressed in Oryza sativa, Nicotina tabacum and Medicago truncatula

Nowadays, plants have become a promising alternative over the traditional expression systems for the production of biologically active complex recombinant proteins. So far, research has been focussed on increasing accumulation levels of recombinant proteins expressed in many plant models. On the other hand, the cell compartment where recombinant proteins are deposited often refers to protein quality in term of protein folding and posttranslational modification (e.g. N-glycosylation). Recombinant proteins directed to the secretory pathway in plants require a leader peptide for translocation into the endoplasmic reticulum. In the absence of further targeting information such proteins are generally secreted, via the default pathway, to the apoplast. This has been well-documented in protoplasts and leaf cells, but the trafficking of recombinant proteins in storage tissues such as endosperm or cotyledons has only received little attention. In addition, it has been suggested that the high specificity of seed tissue for starch, minerals and proteins storage might interfere with protein secretion. We used Aspergillus niger phytase as a model glycoprotein to compare the intracellular fate and the N-glycosylation profile of a recombinant protein in different plant tissues (seeds and leaves) in rice, tobacco and Medicago truncatula. After determination of N-glycosylation patterns and microscopy analyses, we reported that the recombinant protein was preferably retained in protein storage organelles within rice and tobacco endosperm cells, while it was efficiently secreted in leaf and cotyledon tissues as expected for protein following the default secretory pathway. Interestingly, in rice and M. tuncatula leaves, a significant part of A. niger phytase was misrouted to the vacuole. Besides, we revealed an important heterogeneity in the N-glycosylation patterns of A. niger phytase when produced in different plants and tissues. In addition, only A. niger phytase extracted from M. truncatula leaves harboured Lewis-bearing N-glycans known to be potentially highly immunogenic. Together, these results showed that localisation and N-glycosylation of a recombinant protein is tissue dependent, with obvious implications for the production of pharmaceutical proteins by molecular farming.
Effects of Sprint And Plyometric Training on Speed, Jumping And Anaerobic Strenght of Hearing Impaired Male Sportsmen

The study aims to determine the effect of a 8 week sprint and pliometric training out regularly on speed, jump and anaerobic power parameters among hearing impaired male athletes at the age of 18-21. The measurement and tests of the study was carried out in 2018 and the article was written in 2019 in Samsun. 45 male volunteers with hearing impairment participated in this study. 15 of whom are sprint training (experimental) group aged 19.6±1,18; 15 of whom are pliometrik training (experimental) group aged 19.33±1,12 and 15 of whom are control group aged 19.87±1,19. The experiment groups was made to take sprint and pliometric training practices for 8 weeks, the content of which had been determined before hand while the participants attended their trainings in their local teams. Two assessments were carried out in specified parameters for three groups at the beginning and end of the study. In statistical analysis, the significance level was taken as α=0,05. One way analysis of variance was used to determine the differences between the groups. When the differences were found, Tukey test was used. Paired sample t-test for within group analysis. There are not any statistically difference in parameters of age, weight and training age of the participants (p>0.05). There is statistically significant difference in height parameter (p<0.05). 8 weeks of training, at the end of the results of participants data, there are significant differences among body weight, verticalle and horizontal jumping, 20 meters and 30 meters sprint (p<0,01); anaerobic power, sprint group (p<0.05), pliometric group (p<0,01) positive increase. There is significant difference found in anaerobic strenght in control group (p<0,05). In conclusion, the results of the present study showed that both sprint and plyometric training for 8 weeks improve the sprint, jump and anaerobic power performance.
Leveraging spatial textures, through machine learning, to identify aerosol and distinct cloud types from multispectral observations

Abstract. Current cloud and aerosol identification methods for multi-spectral radiometers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS), employ multi-channel spectral tests on individual pixels (i.e. field of views). The use of the spatial information in cloud and aerosol algorithms has been primarily statistical parameters such as non-uniformity tests of surrounding pixels with cloud classification provided by the multi-spectral microphysical retrievals such as phase and cloud top height. With these methodologies there is uncertainty in identifying optically thick aerosols, since aerosols and clouds have similar spectral properties in coarse spectral-resolution measurements. Furthermore, identifying clouds regimes (e.g. stratiform, cumuliform) from just spectral measurements is difficult, since low-altitude cloud regimes have similar spectral properties. Recent advances in computer vision using deep neural networks provide a new opportunity to better leverage the coherent spatial information in multi-spectral imagery. Using a combination of machine learning techniques combined with a new methodology to create the necessary training data we demonstrate improvements in the discrimination between cloud and severe aerosols and an expanded capability to classify cloud types. The training labeled dataset was created from an adapted NASA Worldview platform that provides an efficient user interface to assemble a human labeled database of cloud and aerosol types. The Convolutional Neural Network (CNN) labeling accuracy of aerosols and cloud types was quantified using independent Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and MODIS cloud and aerosol products. By harnessing CNNs with a unique labeled dataset, we demonstrate the improvement of the identification of aerosol and distinct cloud types from MODIS and VIIRS images compared to a per-pixel spectral and standard deviation thresholding method. The paper concludes with case studies that compare the CNN methodology results with the MODIS cloud and aerosol products.
Teaching Genetic Linkage and Recombination through Mapping with Molecular Markers

Most introductory genetics courses cover genetic linkage, a core concept in the CourseSource genetics learning outcome framework. Although it is a classical genetics topic, genetic linkage remains an important concept to understand in order to grasp modern genetics research approaches including Single Nucleotide Polymorphism (SNP) mapping, Genome Wide Association Studies (GWAS), and gene discovery. Typically, genetic linkage is taught in a very traditional way within our introductory genetics classes. Invariably, we see students struggling with the same aspects of linkage: how to distinguish between parental and recombinant combinations of alleles and how to relate phenotype proportions to meiotic processes and outcomes. We designed a lesson that provides a practical and experimental context to target these common student difficulties in learning about linkage and recombination. This student-centered interactive lesson and associated postclass problem set teaches genetic linkage through mapping a gene by determining co-segregation of a phenotype with microsatellite sequences revealed by gel electrophoresis banding patterns. This lesson includes very interactive class sessions and a follow-up problem set and post-test that allows students to develop a deeper understanding of genetic linkage, and provides instructors with insights about student thinking. When we implemented this lesson, we observed a dramatic increase in student understanding of genetic linkage and how to use molecular markers to map the location of genes.
Effect of nerve mobilization with intermittent cervical segment traction on pain, range of motion, endurance, and disability of cervical radiculopathy

Objective: This study aimed to evaluate the effects of the Kaltenborn-Evjenth concept of nerve mobilization combined with intermittent cervical segment traction (ICST) on pain, Neck Disability Index (NDI) scores, range of motion (ROM) and endurance in persons with cervical radiculopathy (CR). pretest-posttest design. Methods: Thirty subjects participated in this study and were randomly assigned to two groups. The ICST group (n=15) was performed simultaneously with nerve mobilization and cervical traction for the segment with cervical pain at the same time. The intermittent cervical total traction (ICTT) group (n=15) performed nerve mobilization and cervical traction for the whole cervical area at the same time. In this study, outcome measures such as the Visual Analog Scale (VAS), NDI, ROM, endurance (cranio-cervical flexion test), and passive intervertebral motion performed before and 4 weeks after the experiment were compared to investigate the effects of each intervention. Results: In both groups, there were significant differences in the VAS, NDI scores, and endurance, and there were significant differences between the two groups except for endurance ( p <0.05). In the ICST group, significant differences were found in all ROM, and in the ICTT group, significant differences were found in only extension, and there were significant differences between the two groups ( p <0.05). Conclusions: The ICST group showed more improvement than the ICTT group in pain, NDI scores and ROM. Moreover, our findings show that the ICST could be used as a new strategy for manual therapy in persons with CR.
Quantitative Analysis of the Sub-Cloud Evaporation of Atmospheric Precipitation and Its Controlling Factors Calculated By D-Excess in an Inland River Basin of China

Atmospheric precipitation is an important part of the water circle in an inland basin. Based on the analytical results of 149 precipitation samples and corresponding surface meteorological data collected at four sampling sites (Lenglong, Ningchang, Huajian and Xiying) at different elevations in the Xiying river basin on the north slope of Qilian Mountains from May to September 2017, the sub-cloud evaporation in precipitation and its controlling factors are analyzed by the Stewart model. The results show that sub-cloud evaporation led to d-excess value in precipitation decrease and d-excess variation from cloud-base to near surface (Δd) increase with decreasing altitude. The remaining evaporation fraction of raindrop (f) decreases with decreasing altitude. The difference of underlying surface led to a difference change of f and Δd in the Xiying sampling site. For every 1% increase in raindrop evaporation, d-excess value in precipitation decreased by about 0.99‰. In an environment of high relative humidity and low temperature, the slope of the linear relationship between f and Δd is less than 0.99. In contrast, in the environment of low relative humidity and high temperature, the slope is higher than 0.99. In this study, set constant raindrop diameter may affect the calculation accuracy. The Stewart model could have different parameter requirements in different study areas. This research is helpful to understand water cycle and land–atmosphere interactions in Qilian Mountains.
Investigation of the Molecular Response in Blood and Skin of Belugas in Response to Stressors

Abstract : The overall goal of this project is to characterize the beluga immune response at the molecular level utilizing archived and fresh blood and skin samples collected in association with different stressors. In the long term, selected biomarkers found to be informative will be utilized in skin, potentially eliminating the need for blood sampling from wild populations.
Dendritic needle network modeling of the Columnar-to-Equiaxed transition. Part I: two dimensional formulation and comparison with theory

Abstract The columnar-to-equiaxed transition is a technologically important phenomenon that controls the grain structure in the casting of alloys. Analytical and coarse-grained models, used to investigate this transition, rely on several assumptions concerning dendrite growth kinetics and grain structures. In the first part of this two part paper, we test these assumptions using a two-dimensional (2D) dendritic needle network model that describes both the transient growth dynamics of primary, secondary and higher order branches of the dendritic network within each grain and the solutal interactions between grains that can grow with arbitrary shapes. Our results provide novel insights into the columnar-to-equiaxed transition, distinguishing between abrupt and progressive transitions with different grain structures. Furthermore, they highlight the limitations of commonly used assumptions in analytical and coarse-grained numerical models of this transition. These results are extended to 3D in part II of the paper.