Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of seed addition and cutting regime on the success of grassland restoration on former arable land

Abstract Questions: Can seed addition enhance the success of establishing species-rich grassland on former arable land? Are sowing date and cutting regime important in determining success? Location: Aberdeen and Elgin, northeast Scotland, United Kingdom. Methods: A field experiment was conducted at two sites to assess the effect of seed addition, sowing date and cutting regime on the vegetation developing on former arable land, the aim being to compare the success of different treatments at producing a species-rich grassland. Results: Sowing a seed mix resulted in the establishment of vegetation very distinct from the species-poor vegetation dominated by perennial grasses which otherwise developed, though establishment success of the sown grassland species was highly variable between sites. Where establishment of the sown species was poor, sowing date had no significant effect on species composition, whereas the cutting regime was very important. Cutting the vegetation significantly increased both the number and abundance of sown species compared with the uncut control. Conversely, where establishment had been good, the cutting regime in the first year had little effect on species composition. Cutting the vegetation at least twice a year appeared to be the most effective management over the length of the experiment. Conclusions: Sowing a seed mixture significantly reduced the abundance and number of naturally colonising species, effectively controlling problem weed species such as Senecio jacobaea and Cirsium vulgare, highlighting the agronomic value of sowing seed mixtures on fallow farmland. The sowing of a seed mix on former arable land has demonstrated that it is feasible to create vegetation similar in character to that of species-rich grasslands. Nomenclature: Clapham et al. (1987).
EFFECTIVE BRANCH AND DU COVERAGE TESTING THROUGH TESTCASE PRIORITIZATION USING GENETIC ALGORITHM

Software testing is all about ensuring an error free execution of the system or module being developed. The testing procedure initially consists of a large number of test cases that are needed to be reduced so that the execution time needed for testing could be minimized. After the reduction has been done, a few test cases are left. Here an important factor becomes the order of the execution of the obtained number of test cases. This ordering is called as test case prioritization. Prioritization of test cases is a process in which test cases are executed in an ordered fashion so as to increase the fault detection rate. There are many types of prioritization techniques used for statement coverage that have been used in past. In this paper, the testcase prioritization technique used for branch coverage and DU pair coverage to improve the effectiveness of testing process. The proposed methodology uses genetic process for prioritizing the test cases to detect the fault as earlier as possible to improve the effectiveness of branch and DU pair testing.
First record of Myotis alcathoe von Helversen & Heller, 2001 (Chiroptera: Vespertilionidae) in Macedonia

Only recently separated from the Myotis mystacinus species complex, the Alcathoe whiskered bat (Myotis alcathoe) is one of the rarest tree-dwelling bats in Europe. In fact, despite the increased number of records across the continent, it is generally still poorly known. Here we present its discovery in Macedonia. A molecularly confirmed Myotis alcathoe was mist netted in the lower part of Štučka River Valley, near the Štuka village in SE Macedonia. The species is new for the bat fauna of Macedonia. This discovery brings the total number of bat species known to occur in the country to 29. In addition, the study reports the third record of the rare Western Barbastelle bat, Barbastella barbastellus (Schreber, 1774) from Macedonia. Nikola Micevski, Javier Juste, Branko Micevski
Considerations regarding the implementation of the ESPL programming language

— This paper’s scope is to describe the back-end implementation of the ESPL compiler, precisely the platform for the cod’s simulation – a virtual machine – and the virtual code generator for this platform. ESPL is an object oriented programming language that is used for embedded systems and consequently the virtual machine is implemented in a manner that allows the simulation and testing of specific features of embedded systems. The virtual code generation is strongly dependent on the configuration of the virtual machine. Its starting point is the intermediate code produced by the front-end of the compiler, and, as final point, a file with machine code that will be load and executed by the virtual machine. The implementation is based on the OOP principles and every module can be replaced and upgraded if the interface rules are followed. The interaction with the user is realized trough the ESPL GUI. New windows and options were added to the previous GUI to support the features offered by virtual machine and the virtual code-generation.
A Fraud Detection System for Health Insurance in Nigeria

*Corresponding author: Address: University of Agriculture, Makurdi, Nigeria. Email: lordesty2k7@ymail.com Tel: +2348064067803, +2347056808523 © 2019 HELINA and JHIA. This is an Open Access article published online by JHIA and distributed under the terms of the Creative Commons Attribution Non-Commercial License. J Health Inform Afr. 2019;6(2):64-73. DOI: 10.12856/JHIA-2019-v6-i2-256 A Fraud Detection System for Health Insurance in Nigeria
Cuckoo Hashing: An efficient technique for data de-duplication in cloud storage

: Cloud computing has provided a different perspective to users for storing and accessing their data by bringing a new era of a digital revolution. In the cloud, users might store the same data which results in more memory consumption. In order to solve this problem, one needs to restrict the duplicate entries of data in the cloud system. For this purpose, the cuckoo hashing algorithm is preferred because of its fast execution and retrieval time. It is also one of the best algorithms for avoiding collision of keys. The proposed system handles the data de-duplication process and thus saves bandwidth.
Activation Function: Key to Cloning from Human Learning to Deep Learning

7 Maneuvering a steady on-road obstacle at high speed involves taking multiple decisions in 8 split seconds. An inaccurate decision may result in crash. One of the key decision that needs 9 to be taken is can the on-road steady obstacle be surpassed. The model learns to clone the 10 drivers behavior of maneuvering a non-surpass-able obstacle and pass through a surpass-able 11 obstacle. No data with labels of ? surpass-able? and ? non-surpass-able? was provided during 12 training. We have development an array of test cases to verify the robustness of CNN models 13 used in autonomous driving. Experimenting between activation functions and dropouts the 14 model achieves an accuracy of 87.33
Protein turnover, physiological energetics and heterozygosity in the blue mussel, Mytilus edulis: the basis of variable age-specific growth

Genotype-dependent changes in whole-body protein turnover are shown to be of significance to metabolic efficiency, energetic maintenance requirements and associated rates of dietary absorption in Mytilus edulis. Faster growth rates were, on average, evident in more heterozygous mussels. Such variation did not stem from different efficiencies of nitrogen conversion, which remained high and independent of either genotype or age. Rather, faster growth derived from decreased energy requirements for maintenance. This decrease was associated with greater efficiencies of protein synthesis [(net protein balance/gross protein synthesis) x 100] and lower intensities of nitrogen metabolism. Energy ‘saved’ by virtue of higher metabolic efficiency was used to effect increases of both ingestion and absorption efficiency. Alternatively, reduced synthetic efficiencies among more homozygous mussels necessitated elevated protein synthesis per unit deposition, high efficiencies of nitrogen conversion being sustained by a greater proportional recycling of breakdown products. Energetic costs were thus enhanced, with a consequent reduction in growth. Efficiencies of protein synthesis declined with age, whereas maintenance requirements grew. These findings are discussed in relation to individual fitness, and proposed as a mechanism by which genotype may mediate intraspecific variations of growth among animals generally.
12.1 A COMPARISON BETWEEN THE 4D-VAR AND THE ENSEMBLE FILTER TECHNIQUES FOR RADAR DATA ASSIMILATION

A complete atmospheric state estimate is required for numerical weather prediction (NWP). A prior state estimate (background) is usually available and can be improved by using newly obtained observations of the atmosphere. The four dimensional variational data assimilation (4D-Var) and the ensemble Kalman filter techniques are two family of methods for combining the background and the observations in an analysis suitable for NWP. The ability of 4D-Var has been proven in some NWP centers. For radar data assimilation, the 4D-Var was also used successfully (Sun and Crook, 1997). Recently, ensemble Kalman filter techniques have been developed and tested on simple models (for examples, see Whitaker and Hamill, 2002). The application of ensemble Kalman filtering with more realistic atmospheric models is yet to be fully explored. In this paper, the ensemble Kalman filter is applied to the assimilation of radar data in a cloud-resolving model and compared with the results of 4D-Var.
A stepwise procedure for isolation of murine bone marrow and generation of dendritic cells

Bone marrow derived Dendritic cells (BMDCs) are routinely employed in cell based assays to evaluate immunomodulatory and anti-inflammatory activities. Hence, simplified, stepwise, defined and standardized methods are required for isolation of bone marrow cells from mice, propagating them in presence of growth factors and obtaining high and reproducible yields of BMDCs. Here, we describe a detailed, stepwise protocol with pictorial representation to isolate bone marrow from mouse femur and development of dendritic cells. Mouse bone marrow cells are cultured in presence of granulocyte-macrophage colony stimulating factor (GM-CSF) for 6 days to generate BMDCs.
Explosiveness in foreign remittance inflow to Pakistan

‐ Foreign remittance inflow to Pakistan is mounting erratically upward from almost a decade and half at a pace never seen historically. We examine the explosiveness in remittance inflow to Pakistan from July 1972 to July 2016 and from various source (host) countries. We use a rolling-window based augmented Dickey–Fuller unit root test and find that periods of abrupt remittance inflow match with the important historical events occurring in the country and internationally. Overall, we put forward conceptually the new notion of temporary explosiveness in the
Transparent failure diagnostics for railway switches using Bayesian networks Transparente Fehlerdiagnose bei Weichenstörungen mittels Bayes’scher Netze

D ie Anwendung moderner Verfahren der künstlichen Intelligenz (KI) zu Diagnosezwecken erfordert insbesondere bei sicherheitskritischen Anlagen eine sorgfältige Betrachtung der Verlässlichkeit der Ergebnisse. Bayes’sche Netze als etablierte KI-Methode weisen in dieser Hinsicht aufgrund ihrer Transparenz und eines hohen Maßes an Nachvollziehbarkeit der mit ihrer Hilfe algorithmisch realisierten, diagnostischen Schlussfolgerungen einige sehr positive Merkmale auf. Der vorliegende Beitrag diskutiert und demonstriert das theoretische und praktische Potenzial Bayes’scher Netze für die Fehlerdiagnose bei Weichenstörungen anhand konkreter numerischer Beispiele.
CLASSIFICATION OF WILD BIRD BY BEHAVIOR WITH FASTER R-CNN FOR COMPLICATED ENVIRONMENT LIKE ORCHARD

Wild birds cause significant damages to agricultural crops in orchards every year. The previous wild bird detection algorithms have limitations that cannot be accurately detected because of the biological characteristics of wild birds. In this paper, we propose a vision-based real-time wild bird detection algorithm that operates in a complicated environment like orchard using Faster R-CNN of deep learning. That is the Wild Bird Behavior Classification (WBBC) algorithm, classifies wild birds according to their behavior, which intended to improve the detection accuracy in a complicated environment. We verified the benefit of Behavior Classification model and the performance of the WBBC algorithm through experiments. In our experiments, the Behavior Classification shows 3.6 percent growth than unused. The WBBC algorithm has detected by 95.7 percent of average accuracy in a variety of environments.
A HYBRID WORD EMBEDDING MODEL BASED ON ADMIXTURE OF POISSON-GAMMA LATENT DIRICHLET ALLOCATION MODEL AND DISTRIBUTED WORD-DOCUMENT-TOPIC REPRESENTATION

This paper proposes a hybrid Poisson-Gamma Latent Dirichlet Allocation (PGLDA) model designed for modelling word dependencies to accommodate the semantic representation of words. The new model simultaneously overcomes the shortcomings of complexity by using LDA as the baseline model as well as adequately capturing the words contextual correlation. The Poisson document length distribution was replaced with the admixture of Poisson-Gamma for words correlation modelling when there is a hub word that connects words and topics. Furthermore, the distributed representation of documents (Doc2Vec) and topics (Topic2Vec) vectors are then averaged to form new vectors of words representation to be combined with topics with largest likelihood from PGLDA. Model estimation was achieved by combining the Laplacian approximation of log-likelihood for PGLDA and Feed-Forward Neural Network (FFN) approaches of Doc2Vec and Topic2Vec. The proposed hybrid method was evaluated for precision, recall, and F 1 score based on 20 Newsgroups and AG’s News datasets. Comparative analysis of F 1 score showed that the proposed hybrid model outperformed other methods.
A NOVEL METHOD FOR EVALUATION OF NOSQL DATABASES: A CASE STUDY OF CASSANDRA AND REDIS

In today's complex world, due to the increasing use of web-based programs, smart phones and social networks, production rate is increasing constantly as well as volume of data . Also, companies try to provide their services with more features in order to stay ahead of their competitors. That increases the production of information by the users too. In this case, it seems that moving from rational databases to non-relational databases in a necessity. With regard to the various of use cases and their requirements, also the primary features of NoSQL databases, choosing the most appropriate NoSQL database can be big concern of developers. The right selection of NoSQL databases will avoid to wasting time, money, and energy. On this paper, we propose a general and structured method to help developers, customers, and managers to evaluate NoSQL databases in the right way and facilitate the process of decision making to select one of them.
The establishment of fucoid zonation on algal‐dominated rocky shores: hypotheses derived from a simulation model

A model was developed for the growth of intertidal algae with photosynthesis simulated both in air and in a tidal water column. Morphological data on dry mass per unit area and length-area relationships were used to separate the growth of different fucoid species. The relative growth rate of fronds at any height on the shore depended on a trade-off between net photosynthetic performance and tolerance to desiccation. 2. The simulated zonation patterns and growth rates were consistent with those observed previously for Fucus spp. and Pelvetia canaliculata. 3. The simulated growth of Ascophyllum nodosum was always slower than for the other species. This species did not form its characteristic distribution zones in simulations without including further processes in the model. However, Ascophyllum collected from the field could be separated into upper and lower shore morphologies which formed separate zones when they were simulated in competition with each other. 4. Several hypotheses were proposed concerning the relative locations and sharpness of interspecies boundaries on the shore. Zonation patterns were relatively insensitive to changes in most model parameters except the desiccation rate.
The in vitro human fracture hematoma model - a tool for preclinical drug testing.

The aim of the study was to establish an in vitro fracture hematoma (FH) model, which mimics the in vivo situation of the human fracture gap in order to assess drug efficacy and effectiveness for the treatment of fracture healing disorders. Therefore, human peripheral blood and mesenchymal stromal cells (MSCs) were coagulated to produce in vitro FH models, incubated in osteogenic medium under normoxia/hypoxia, and analyzed for cell composition, gene expression and cytokine/chemokine secretion. To evaluate the model, we studied the impact of dexamethasone (impairing fracture healing) and deferoxamine (promoting fracture healing). Under hypoxic conditions, MSCs represented the predominant cell population, while the frequencies of leukocytes decreased. Marker gene expression of osteogenesis, angiogenesis, inflammation, migration and hypoxic adaptation increased significantly over time and compared to normoxia while cytokine/chemokine secretion remained unchanged. Finally, dexamethasone favored the frequency of immune cells compared to MSCs, suppressed osteogenic and pro-angiogenic gene expression and enhanced the secretion of inflammatory cytokines. Conversely, deferoxamine favored the frequency of MSCs over that of immune cells and enhanced the expression of the osteogenic marker RUNX2 and markers of the hypoxic adaptation. In summary, we demonstrate that hypoxia is an important factor for in vitro modeling the initial phase of fracture healing, that both fracture-healing disrupting and promoting substances can influence the in vitro model comparable to the in vivo situation. Therefore, we conclude that our model is able to mimic in part the human FH and to reduce the number of animal experiments in early preclinical studies.
APPLYING INTELLIGENT MOTION AND LOCATION MONITORING SYSTEM FOR THE ELDERLY

One of three adults 65 years or older falls every year. As medical science advances, people can live with better health and alone up to a very advanced age. Therefore, to let elderly people live in their own homes leading their normal life and at the same time taking care of them requires new kinds of systems. In this paper, we propose a multi-sensor monitoring system for the fall detection in home environments. The proposed system extracts motion and location data from the webcam, and heart rate from the heart rate sensor.The extracted parameters are the face and body speeds, center of mass, aspect ratio and heart rate. These parameters will be fed to a neural network classifier in order to classify the fall event in two classes: fall and not fall. Reliable recognition rate of experimental results underlines satisfactory performance of our system.
Characterization of two sibling species of the genus Stylonychia (Ciliata, Hypotricha): S. mytilus Ehrenberg, 1838 and S. lemnae n.sp. I: Morphology and reproductive behavior

All Stylonychia mytilus-like ciliates which were collected and sent to us during the last 20 years belonged either to S. mytilus or to a new species, S. lemnae, which is described here. The only morphological differences are the shape and the size. Stylonychia mytilus that have been starved for one day average 300 μm in length, and S. lemnae starved for a day are 230 μm long. The occurrence of mating types is described.
Scotland's Rural College Hepatic expression patterns in psychosocially high-stressed pigs suggest mechanisms following allostatic principles Oster,

47 Psychosocial challenges are known to introduce cellular and humoral adaptations in various 48 tissues and organs, including parts of the sympatho-adrenal-medullary system and 49 hypothalamic–pituitary–adrenal axis as well as other peripheral tissue being responsive to 50 cortisol and catecholamines. The liver is of particular interest given its vital roles in 51 maintaining homeostasis and health as well as regulating nutrient utilization and overall 52 metabolism. We aimed to evaluate whether and how response to psychosocial stress is 53 reflected by physiological molecular pathways in liver tissue. A pig mixing experiment was 54 conducted to induce psychosocial stress culminating in skin lesions which reflect the 55 involvement in aggressive behavior and fighting. At 27 weeks of age, animals prone to 56 psychosocially lowand high-stress were assigned to mixing groups. Skin lesions were 57 counted before mixing and after slaughter on the carcass. Individual liver samples (n=12) 58 were taken. The isolated RNA was hybridized on Affymetrix GeneChip porcine Genome 59 Arrays. Relative changes of mRNA abundances were estimated via variance analyses. 60 Molecular routes related to tRNA charging, urea cycle, acute phase response, galactose 61 utilization, and steroid receptor signaling were found to be increased in psychosocially high62 stressed animals, whereas catecholamine degradation and cholesterol biosynthesis were 63 found to be decreased. In particular, psychosocially high-stressed animals show decreased 64 expression of catechol-O-methyltransferase (COMT) which has been linked to molecular 65 mechanisms regulating aggressiveness and stress response. The expression patterns of 66 high-stressed animals revealed metabolic alterations of key genes related to energy67 mobilizing processes at the expense of energy consuming processes. Thus, the coping 68 following psychosocial challenges involves transcriptional alterations in liver tissue which 69 may be summarized with reference to the concept of allostasis, a strategy which is critical for 70 survival. 71 72
Randomized Fast Subspace Descent Methods

Randomized Fast Subspace Descent (RFASD) Methods are developed and analyzed for smooth and non-constraint convex optimization problems. The efficiency of the method relies on a space decomposition which is stable in $A$-norm, and meanwhile, the condition number $\kappa_A$ measured in $A$-norm is small. At each iteration, the subspace is chosen randomly either uniformly or by a probability proportional to the local Lipschitz constants. Then in each chosen subspace, a preconditioned gradient descent method is applied. RFASD converges sublinearly for convex functions and linearly for strongly convex functions. Comparing with the randomized block coordinate descent methods, the convergence of RFASD is faster provided $\kappa_A$ is small and the subspace decomposition is $A$-stable. This improvement is supported by considering a multilevel space decomposition for Nesterov's `worst' problem.