Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of grapevine bunch exposure to sunlight on berry surface temperature and Lobesia botrana (Lepidoptera: Tortricidae) egg laying, hatching and larval settlement

Bunch‐zone leaf removal reduced infestation by Lobesia botrana, although the mechanism responsible for this effect is unknown. Based on the mortality of eggs and newly‐hatched larvae exposed to high temperatures (≥37 °C) in the laboratory, the present study aimed to assess the influence of (i) bunch‐zone leaf removal and grapevine‐row orientation on berry surface temperature and (ii) bunch exposure to sunlight on egg and larval mortality. Berry temperatures were measured using a noncontact infrared thermometer in two vineyards and showed that, in direct sunlight, the temperatures of berry surfaces were 9 °C or more above air temperature, and the highest mean temperatures occurred on southwest‐side bunches followed by west‐ and south‐side bunches. The results of four two‐choice field assays, carried out confining fertile females in cages with two bunches, one exposed and one non‐exposed to sunlight, showed that: (i) the females did not avoid laying eggs on sun‐exposed bunches and (ii) the lowest percentages of both egg‐hatching and larval settlement occurred on sun‐exposed bunches. The hypothesis that the high temperatures reached by sun‐exposed berries cause egg and especially larval mortality is confirmed. Bunch‐zone leaf removal combined with optimized grapevine‐row orientations can improve L. botrana control.
Leaf Area Estimate of Erythroxylum simonis Plowman by Linear Dimensions

This research aimed to determine an equation to estimate the leaf area of Erythroxylum simonis using the length and width of leaf blades. Two hundred leaf blades of this species were collected in Mata do Pau-Ferro, a State Park located in Areia, PB, Brazil. Regression analyses were used to determine the estimation equations. The linear, linear without intercept, quadratic, cubic, power and exponential statistical models were used. The criteria used for model selection were based on an examination of the coefficient of determination, the Akaike information criterion and standard error of the estimate. All the equations presented can be used to estimate the leaf area of E. simonis. From a practical point of view, the linear regression equation without intercept involving the product between length and width is recommended, using the equation Y=0.6426*LW, which corresponds to 64.26% of the product between length and width, with a coefficient of determination of 0.9936.
Identification and characterization of Pseudomonas fluorescensstrains effective against Xanthomonasoryzaepv. oryzae causing bacterial blight of rice in Punjab, India

For the control of bacterial blight of rice caused by Xanthomonasoryzaepv. oryzae, sixty four Pseudomonas fluorescens strains were recovered from rice and wheat rhizosphere. These strains were identified on the basis of internal transcribed spacer (ITS) region. It was observed that the strains showing fluorescence in the selective media showed the amplification of the targeted P. fluorescens specific ITS region. The strains were also characterized for the production of the antibiotic 2, 4-diacetylphloroglucinol (DAPG) using phlDlocus. The characteristic 750bp region was amplified in all the DAPG producing strains. These strains were evaluated against X. oryzae in vitro by dual culture method. The P. fluorescens strains found effective in vitro were further tested in field for their antagonistic potentiality and disease suppression ability. P. fluorescens strain number Pf-4-R showed maximum inhibition i.e. of 5.5 mm against the test pathogen X. oryzaepv. oryzae. Talc based powder formulation of the effective strain Pf-4-R used for field evaluation, showed that pre-inoculation foliar sprays were effective in controlling bacterial blight of rice with disease suppression efficiency ranging from 29.6 to 65.6 percent in different treatments.
The relationship between mobile learning and self-regulated learning: A systematic review

A systematic review of 38 primary research peer-reviewed articles, drawn from six databases and spanning from January 2007 to January 2019, was conducted to determine the principle information that they collectively offered on the relationship between mobile learning (m-learning) and self-regulated learning (SRL). In answering the research questions posed, a synthesis of the following 12 key elements was undertaken: (1) research aims, (2) research methodologies, (3) outcomes, (4) education discipline areas, (5) educational levels, (6) educational contexts, (7) geographic location, (8) time frame, (9) type of device, (10) m-learning and SRL definitions, (11) theoretical models, and (12) m-learning, self-regulation (SR), and SRL variable measurement instruments. The frequency of studies on the relationship between m-learning and SRL increased in more recent years, as did the types of devices used in these studies. More than three quarters of the studies concluded that m-learning enhanced SRL, SRL enhanced m-learning, or m-learning and SRL enhanced other learning factors (e.g., health, curriculum development). Moreover, the relationship between m-learning and SRL was dynamic and complex. A primary recommendation was to intentionally integrate m-learning and SRL into formal curricula guided by informed, technologically adept educators who provided appropriate, ever-decreasing support and scaffolding as learners became more self-determined. Implications for practice or policy: M-learning research and practice should be founded upon relevant theory and validated definitions of m-learning that consider ever-advancing technologies and related pedagogies that include participatory activities. M-learning designers should ensure that mobile technologies are used intentionally and selectively, guided by clearly defined learning objectives, and integrated into the curriculum by technologically adept educators who provide appropriate, ever-decreasing support and scaffolding as learners become more self-determined. When designing m-learning, educators should consider digital safety and privacy issues.
A Survey of Ontologies for Simultaneous Localization and Mapping in Mobile Robots

Autonomous robots are playing important roles in academic, technological, and scientific activities. Thus, their behavior is getting more complex, particularly, in tasks related to mapping an environment and localizing themselves. These tasks comprise the Simultaneous Localization and Mapping (SLAM) problem. Representation of knowledge related to the SLAM problem with a standard, flexible, and well-defined model, provides the base to develop efficient and interoperable solutions. As many existing works demonstrate, Semantic Web seems to be a clear approach, since they have formulated ontologies, as the base data model to represent such knowledge. In this article, we survey the most popular and recent SLAM ontologies with our aim being threefold: (i) propose a classification of SLAM ontologies according to the main knowledge needed to model the SLAM problem; (ii) identify existing ontologies for classifying, comparing, and contrasting them, in order to conceptualize SLAM domain for mobile robots; and (iii) pin-down lessons to learn from existing solutions in order to design better solutions and identify new research directions and further improvements. We compare the identified SLAM ontologies according to the proposed classification and, finally, we explore new data fields to enrich existing ontologies and highlight new possibilities in terms of performance and efficiency for SLAM solutions.
Optimizing biodiversity informatics to improve information flow, data quality, and utility for science and society

Vast amounts of Primary Biodiversity Data exist online (~109 records, each documenting an individual species at a point in space and time). These data hold immense but unrealized promise for science and society, including use in biogeographic research addressing issues such as zoonotic diseases, invasive species, threatened species and habitats, and climate change. Ongoing and envisioned changes in biodiversity informatics involving data providers, aggregators, and users should catalyze improvements to allow efficient use of such data for diverse analyses. We discuss relevant issues from the perspective of modeling species distributions, currently the most common use of Primary Biodiversity Data. Key cross-cutting principles for progress include harnessing feedback from users and increasing incentives for improving data quality. Critical challenges include: (1) establishing individual and collective stable unique identifiers across all of biodiversity science, (2) highlighting issues regarding data quality and representativeness, and (3) improving feedback mechanisms. Such changes should lead to ever-better data and increased utility and impact, including greater data integration with various research areas within and beyond biogeography (e.g., population demography, biotic interactions, physiology, and genetics). Building on existing pilot functionalities, biodiversity informatics could see transformative changes over the coming decade via a combination of community consensus building, coordinated efforts to justify and secure funding, and technical innovations.
Material Requirements Planning Under Demand Uncertainty Using Stochastic Optimization

Material Requirements Planning (MRP), a core component of enterprise resource planning (ERP) systems, is widely used by manufacturers to determine the production lot sizes of components. These lot sizes are typically computed based on deterministic and dynamic demand assumptions, while safety stocks, which hedge against demand uncertainty, are determined independently based on different assumptions. As the lot sizes and safety stocks are not determined simultaneously, sub‐optimal decisions are often used in practice. The critical impact of inventories and service levels in manufacturing motivates the study of stochastic optimization methods for MRP. In this study, we investigate stochastic optimization methods for MRP systems under demand uncertainty. A two‐stage and a multi‐stage model are proposed to deal with the static‐static and static‐dynamic decision frameworks, respectively. We first derive structural properties of the two‐stage and multi‐stage models to provide insights on the differences between the plans created with these two models. As multi‐stage stochastic programs are not convenient in real‐world applications, several practical enhancements are proposed. First, to address scalability issues, we employ heuristics in combination with advanced sampling methods. Second, to allow real‐time static‐dynamic decisions, we derive a policy from the solution of the multi‐stage model. Third, to deal with the dynamic‐dynamic decision framework, we employ a rolling horizon implementation. The effectiveness and performance of stochastic optimization for MRP are validated by numerical experiments, which demonstrate that the stochastic optimization approaches have the potential to generate significant cost savings compared to traditional methods for production planning and safety stocks determination.
Visual tracking based on transfer learning of deep salience information

In this paper, we propose a new visual tracking method in light of salience information and deep learning. Salience detection is used to exploit features with salient information of the image. Complicated representations of image features can be gained by the function of every layer in convolution neural network (CNN). The characteristic of biology vision in attention-based salience is similar to the neuroscience features of convolution neural network. This motivates us to improve the representation ability of CNN with functions of salience detection. We adopt the fully-convolution networks (FCNs) to perform salience detection. We take parts of the network structure to perform salience extraction, which promotes the classification ability of the model. The network we propose shows great performance in tracking with the salient information. Compared with other excellent algorithms, our algorithm can track the target better in the open tracking datasets. We realize the 0.5592 accuracy on visual object tracking 2015 (VOT15） dataset. For unmanned aerial vehicle 123 (UAV123) dataset, the precision and success rate of our tracker is 0.710 and 0.429.
Inter-simple sequence repeat (ISSR) analysis to molecular characteristic determination of Heliotropium digynum in Saudi Arabia

Manuscript History: Heliotropium digynum, is a member of Boraginaceae family. The growth of the plant, as well as its size, length of inflorescence and speed of development depends on the amount of rain in their habitat. In this study, we aim to the applicability of inter-simple sequence repeat (ISSR) with polymorphism in Heliotropium digynum in different region of Saudi Arabia. Fifteen primers were used for ISSR-PCR optimization through ISSR analysis while, only five primers (UBC810, UBC811, UBC818, UBC834and UBC849) gave the best amplification results which produced a total of 43 polymorphic bands. The number of polymorphic loci was 20 and the percentage of polymorphism was 90.47%. The similarity result indicates the presence of high level genetic diversity between populations and a dendrogram constructed by UPGMA method.
A lifeworld theory-led action research process for humanizing services: improving “what matters” to older people to enhance humanly sensitive care

ABSTRACT Purpose: Using a theory-led action research process test applicability of humanizing care theory to better understand what matters to people and assess how the process can improve human dimensions of health care services. Consideration of the value of this process to guide enhancements in humanly sensitive care and investigate transferable benefits of the participatory strategy for improving human dimensions of health care services. Methods: Action research with service users, practitioners and academics, with participatory processes led through the application of theory via a novel Humanizing Care Framework in two diverse clinical settings. Results: Participants engaged in a theory-led participatory process, understood and valued the framework seeing how it relates to own experiences. Comparative analysis of settings identified transferable processes with potential to enhance human dimensions of care more generally. We offer transferable strategy with contextualized practical details of humanizing processes and outcomes that can contribute to portable pathways to enhance dignity in care through application of humanizing care theory in practice. Conclusion: The theoretical framework is a feasible and effective guide to enhance human dimensions of care. Our rigorous participative process facilitates sharing of patient and staff experience, sensitizing practitioners’ understandings and helping develop new ways of providing theoretically robust person-centred care based on lifeworld approaches.
The endangered São Tomé Grosbeak Neospiza concolor is the world's largest canary

The Sao Tome Grosbeak Neospiza concolor, endemic to the island of Sao Tome (Gulf of Guinea), is one of the least known birds in the world. Formerly considered to be an aberrant weaver (Ploceidae), it is currently placed in a monotypic genus within the true finches (Fringillidae). Phylogenetic inference based on mitochondrial and nuclear sequences confidently identifies N. concolor as an Old World finch (Fringillidae: Carduelinae) within the Crithagra seedeater/canary clade. The Sao Tome Grosbeak is therefore the world's largest canary, 50% heavier than the next largest species, and it co-occurs with a population of its sister species, the Principe Seedeater Crithagra rufobrunnea.
A novel geomatics method for assessing the Haughton impact structure

Terrestrial impact structures are typically modified by erosion, burial, and tectonic deformation. Their systematic morphologies are typically reconstructed through a combination of geological and topographic mapping, satellite imagery, and geophysical surveys. This study applies a novel geomatics approach to assessment of the morphology of the extensively studied Haughton impact structure (HIS), Devon Island, Nunavut, in order to test its potential to improve the accuracy and quality of future impact structure reconstruction. This new methodology integrates HIS lithological data, in the form of digitized geologic mapping, with a digital elevation model, within diametrically opposed, wedge‐shaped couplets, and plots these data as pseudo cross sections that capitalize on the radial symmetry of the impact structure. The pseudo cross sections provide an accurate reconstruction of the near‐surface stratigraphic sequences and terraces in the faulted annulus of the modified crater rim. The resultant pseudo cross sections support current interpretations regarding the 10–12 km diameter of the transient cavity, and successfully reproduce the visible outer ring and intermediate uplifted zone within the central basin. Observed positions of vertical offsets suggest that the extent of impact deformation extends beyond the current estimates of the apparent crater rim to radial distances of between 14 and 15 km. Finally, the new geomatics approach provides an improved determination of the spatial, stratigraphic, and temporal relationships among the Haughton Formation lake sediments, allochthonous crater‐fill impactites, and uplifted target rocks, and indicates that there was a not‐insignificant time gap between the formation of the impact structure and the deposition of the sediments.
The effect of physicochemical conditions and nutrient sources on maximizing the growth and lipid productivity of green microalgae

Biodiesel is a renewable fuel produced mostly from edible and non‐edible vegetables, by transesterification of neutral lipids (triacylglycerols). However, vegetable oil‐based biodiesel production competes with food crops for arable land, increasing food prices and leading to biodiversity loss. The production of biodiesel from oleaginous microorganisms – particularly microalgae – has attracted attention due to the higher lipid productivity of these organisms, when compared with vegetables. Several environmental factors – including light, temperature, pH and the presence of nutrients (particularly nitrogen, phosphorus and iron) – influence directly the ability of microalgae to produce and store triacylglycerols and other lipids, and also modulate microalgal growth. Although some environmental factors affect several species in a similar manner, differential responses between species are frequent, highlighting the importance of identifying optimal cultivation conditions for each species, to balance growth and lipid productivity for biodiesel production. Here, we reviewed the particular influence of the physicochemical and nutritional factors on the growth and lipid productivity of different green oleaginous microalgae species.
Reliable data storage in heterogeneous wireless sensor networks by jointly optimizing routing and storage node deployment

In the era of big data, sensor networks have been pervasively deployed, producing a large amount of data for various applications. However, because sensor networks are usually placed in hostile environments, managing the huge volume of data is a very challenging issue. In this study, we mainly focus on the data storage reliability problem in heterogeneous wireless sensor networks where robust storage nodes are deployed in sensor networks and data redundancy is utilized through coding techniques. To minimize data delivery and data storage costs, we design an algorithm to jointly optimize data routing and storage node deployment. The problem can be formulated as a binary nonlinear combinatorial optimization problem, and dueto its NP-hardness, designing approximation algorithms is highly nontrivial. By leveraging the Markov approximation framework, we elaborately design an efficient algorithm driven by a continuous-time Markov chain to schedule the deployment of the storage node and corresponding routing strategy. We also perform extensive simulations to verify the efficacy of our algorithm.
CEBPA Germline Mutation Screening in Cytogenetically Normal Acute Myeloid Leukemia with Somatically Acquired CEBPA Mutations.

Background: Mutations in the myeloid transcription factor CEBPA (CCAAT enhancer binding protein-alpha) have been implicated in 10–15% of cytogenetically normal (CN) acute myeloid leukemia (AML) patients (pts). At the molecular level, two types of heterozygous CEPBA mutations have been identified. First, nonsense mutations affecting the N-terminal region, preventing the expression of the full-length protein, and second, in-frame mutations located in the basic-region-leucine zipper domain, resulting in a decreased CEBPA DNA-binding or dimerization activity. Clinically, CN-AML with mutant CEBPA is associated with a favorable prognosis. Recently, two independent families were reported in whom several family members affected by AML carried heterozygous germline CEBPA mutations. All germline mutations were located in the N-terminus. In addition, somatically acquired C-terminal mutations were detected in one out of three and two out of four family members, respectively. These findings led to the hypothesis that CEBPA germline mutations predispose to AML and that additional somatically acquired mutations may contribute to the development of the disease. Aim: To screen CN-AML pts with somatically acquired CEBPA mutations for germline CEBPA mutations as predisposing events for the development of AML. Methods: Pts were entered in the AML HD98-A or AMLSG 07-04 multicenter treatment trials of the German-Austrian AML Study Group. Buccal mucosa was obtained using commercial FTA filter cards after informed consent; CEBPA mutation screening was performed as recently described. Results: Buccal DNA from 18 pts exhibiting CEBPA mutations in their leukemic cells (biallelic N-terminal and C-terminal, n=12; heterozygous C-terminal, n=5; heterozygous N-terminal, n=1) was available for analysis. In 16 pts, no CEBPA germline mutations could be detected. In one pt, the heterozygous C-terminal in-frame mutation (1609G>A) that was identified in the diagnostic sample was also present in the germline DNA. In a second pt with an N-terminal deletion and a C-terminal insertion mutation in the diagnostic sample, the N-terminal mutation was also identified in the germline material. Interestingly, the daughter of this pt also developed AML at the age of three years, exhibiting the identical N-terminal germline mutation, while the t C-terminal mutation was acquired and different to that of her mother. None of the remaining family members who could be analyzed had CEBPA germline mutations or a history of leukemia. Conclusion: The detection of CEBPA germline mutations in another pedigree with familial AML further sustains the hypothesis that CEBPA germline mutations might be the predisposing event in the development of AML in these families. Since other AML-associated gene mutations are rarely detected in CEBPA mutated cases, somatic mutations in the second allele represent a possible ‘second hit’ in this molecularly defined AML subtype.