Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Initiation Timing of Drought Stress on Carbohydrate Content and Vegetative Growth in Japanese Apricot (Prunus mume Sieb. et Zucc.) ‘Nanko’

The effects of initiation timing of drought stress on the carbohydrate content and growth of Japanese apricot (Prunus mume Sieb. et Zucc.) ‘Nanko’ tree were investigated. Three-year-old trees were subjected to drought stress for three months in May (‘Spring’) and August (‘Summer’), respectively. Irrigation was started immediately after drought stress treatment had finished. The starch concentration in the roots of stressed trees increased in both ‘Spring’ and ‘Summer’ two months after starting drought stress treatment and rapidly decreased just after starting irrigation in ‘Spring’; however, it still temporarily increased in ‘Summer’. These different results were attributed to seasonal changes in the carbohydrate demand. The dry matter weight of each tree organ in February of the following year was suppressed by drought stress, particularly in ‘Spring’. This result indicates that, if a tree suffers drought stress in spring, vegetative growth is suppressed more seriously than in summer and tree growth, declined by suffering from severe and long-term drought stress, will hardly recover even the tree is re-irrigated. The total starch in all organs of the drought-stressed trees in February of the following year was significantly less than that in well-irrigated trees. These results indicate that severe drought stress for three months inhibits not only current tree growth but also the accumulation of carbohydrates that is necessary for the following year’s growth. Hence, irrigation to avoid a fatal growth decline due to severe drought stress is needed during the current growth stage, especially in the early growth stage in spring.
Factors influencing ambulation in myelomeningocele: a cross‐sectional study

A consecutive series of 53 children with myelomeningocele (mean age 7.6, range 3.2 to 11.4 years) was assessed in order to see if the children with motor paresis of the lower limbs achieved the expected level of ambulation, and if not, to identify possible causative factors. Methods used were clinical examination of orthopaedic and neurological status, information from medical reports, and documentation of orthoses use. Functional skills were documented and energy expenditure was examined. Thirty‐one of 53 children had reached the expected ambulation considered possible according to their motor paresis, whereas 22 of the 53 performed worse than expected. Balance disturbances, occurrence of spasticity in knee and hip joints, and number of shunt revisions made differed significantly between the groups that achieved and did not achieve expected ambulation. Functional skills of mobility differed significantly between two muscle‐function levels in children who had walking ability. Energy expenditure was higher in the non‐achieving group than in the group who achieved expected ambulation in each of the muscle‐function levels. Results show that children with similar muscle paresis exhibit different ambulatory function. This indicates the importance of a close analysis of other factors which may cause ambulation to deteriorate in order to predict future ambulation in children with myelomeningocele.
ADHD: increased dopamine receptor availability linked to attention deficit and low neonatal cerebral blood flow

Attention‐deficit‐hyperactivity disorder (ADHD), while largely thought to be a genetic disorder, has environmental factors that appear to contribute significantly to the aetiopathogenesis of the disorder. One such factor is pretern birth with vulnerable cerebrovascular homeostasis. We hypothesised that cerebral ischaemia at birth could contribute to persistent deficient dopaminergic neurotransmission, which is thought to be the pathophysiological basis of the disorder. We examined dopamine D2/3 receptor binding with positron emission tomography (PET) using [11C] raclopride as a tracer, and continuous reaction times (RT) with a computerized test of variables (TOVA) in six adolescents (12–14 years of age, one female) who had been examined with cerebral blood flow (CBF) measurements at preterm birth and had a subsequent history of attention deficit. We found that high dopamine receptor availability (‘empty receptors’) was linked with increased RT and RT variability, supporting the concept of a dopaminergic role in symptomatology. High dopamine receptor availability was predicted by low neonatal CBF, supporting the hypothesis of cerebral ischaemia as a contributing factor in infants susceptible to ADHD.
THE USE OF TRAPS IN SAMPLING MOSQUITO POPULATIONS

Mosquito populations in southern England were sampled by animal baited, carbon dioxide and light traps. Cylindrical traps baited with rabbits caught both zoophilous and ornithophilous species, but very few individuals were caught when they were baited with chickens. Direct bait catches, however, showed that ornithophilous species were not attracted to rabbits outside traps. Many more species were caught in Trinidad traps baited with dry ice than in cylindrical traps. A New Jersey light trap caught unfed females and males of a few species, many common species were not attracted to light.
Evolving Community College Shared Governance To Better Serve the Public Interest.

Intended to stimulate improvemeats in shared governance in the California Community Colleges, this report outlines the evolution and current structures of shared governance at the local and system levels and provides recommendations for change to better serve the public interest. Following a preface, chapter 1 describes the evolution of shared governance at the local level from 1907 to 1994, highlighting the movement from the broad governance originally allowed local districts to the current bilateral and legalistic governance model granting power to the State Legislature. Chapter 2 provides an analysis of shared governance at the local level, indicating that it has resulted in improvements in the nature and quality of educational decision-making but has also led to counterproductive competition for power and resources among institutions. Chapter 3 summarizes the evolution of shared governance at the systemwide level, examining the creation and transformations of the role of the Board of Governors and Chancellor's Office. Chapter 4 aLlalyzes the effectiveness of shared governance systemwide, highlighting strengt.hs of the current structure, related to fact that institutional participation in policy-making is more formalized, broad-based, open and effective, and weaknesses related to the competition among institutions. Finally, chapter 5 provides recommendations for improving shared governance related to instituting a code of ethics, implementing multi-institutional councils, and giving districts the authority to create additional revenue. The proposed code of ethics is appended. (TGI) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ***********************************************************************
The Potential of Refugee Seed Systems to Promote Contemporary Adaptation in Traditional Crops: A Case Study of African Maize in New England

There are many mechanisms by which landraces evolve in a contemporary agricultural setting; however, the influence of forced human migration on landrace redistribution and evolution has received little attention in comparison to the stochastic effects of drift, mutation, and gene flow in the centers of origin. Although the seed systems of forcedly-displaced people remain poorly understood, evidence suggests that refugees often continue to grow traditional crops after resettlement. From a genetics perspective, the crops that are transported to highly disparate environments provide an interesting opportunity to study adaptation. This research addresses how forced human migration has impacted contemporary landrace evolution in a specific case study of African maize being grown by new American farmers in Vermont and New Hampshire. We utilize a whole genome sequencing approach and methods in population genetics to investigate the origin, genetic diversity, and potential adaptation in these crops. Our findings suggest that maize grown by new American farmers in the study does in fact originate from Africa and that each farmer is growing a genetically distinct crop, although we are unable to link origin of the crop to immigration history of the farmer. We also found that genetic diversity is remarkably high across all samples, even compared to landrace panels assembled from the U.S. National Plant Germplasm System. Lastly, we found numerous signatures of positive selection across all farmer samples, and through Gene Ontology analysis, we identified two significant biological processes enriched by positive selection, (1) cinnamoyl-CoA reductase biosynthesis and (2) glutathione synthase activity, that may indicate recent adaptation and be correlated to increased cold tolerance. Overall, through this case study we show a specific example of how forced human migration has affected landrace redistribution, subsequent evolution, and potential adaptation to a disparate environment. We believe these findings hold interesting implications towards agrobiodiversity conservation and suggest the potential of refugee seed systems to promote contemporary adaptation in traditional crops.
University Fully automatic 3D segmentation of the thoracolumbar spinal cord and the vertebral canal from T2-weighted MRI using K-means clustering algorithm

To develop a reliable protocol for automatic segmentation of Thoracolumbar spinal cord using MRI based on K- means clustering algorithm in 3D images. : 42 T2 structural volumes acquired from the spinal cord of 20 uninjured volunteers on a 3T MR scanner. We proposed an 43 automatic method for spinal cord segmentation based on the K-means clustering algorithm in 3D images and compare 44 our results with two available segmentation methods (PropSeg, DeepSeg) implemented in the Spinal Cord Toolbox. 45 Dice and Hausdorff were used to compare the results of our method (K-Seg) with the manual segmentation, PropSeg, and DeepSeg. The accuracy of our automatic segmentation was or SCT methods, in terms 3D Dice were and Hausdorff Distance contrary other methods T2-weighted
Exact 
N
-point-function mapping between pairs of experiments with Markovian open quantum systems

We formulate an exact spacetime mapping between the $\mathcal{N}$-point correlation functions of two different experiments with open quantum gases. Our formalism extends a quantum-field mapping result for closed systems [Phys. Rev. A \textbf{94}, 043628 (2016)] to the general case of open quantum systems with Markovian property. For this, we consider an open many-body system consisting of a $D$-dimensional quantum gas of bosons or fermions that interacts with a bath under Born-Markov approximation and evolves according to a Lindblad master equation in a regime of loss or gain. Invoking the independence of expectation values on pictures of quantum mechanics and using the quantum fields that describe the gas dynamics, we derive the Heisenberg evolution of any arbitrary $\mathcal{N}$-point function of the system in the regime when the Lindblad generators feature a loss or a gain. Our quantum field mapping for closed quantum systems is rewritten in the Schrodinger picture and then extended to open quantum systems by relating onto each other two different evolutions of the $\mathcal{N}$-point functions of the open quantum system. As a concrete example of the mapping, we consider the mean-field dynamics of a simple dissipative quantum system that consists of a one-dimensional Bose-Einstein condensate being locally bombarded by a dissipating beam of electrons in both cases when the beam amplitude or the waist is steady and modulated.
Uniﬁed long-term 3D simultaneous localization and mapping for service robots

– We address in this paper the problem of loop closure detection for laser-based simultaneous localization and mapping (SLAM) of very large areas. Consistent with the state of the art, the map is encoded as a graph of poses, and to cope with very large mapping capabilities, loop closures are asserted by comparing the features extracted from a query laser scan against a previously acquired corpus of scan features using a bag-of-words (BoW) scheme. Two contributions are here presented. First, to beneﬁt from the graph topology, feature frequency scores in the BoW are computed not only for each individual scan but also from neighboring scans in the SLAM graph. This has the eﬀect of enforcing neighbor relational information during document matching. Secondly, a weak geometric check that takes into account feature ordering and occlusions is introduced that substantially improves loop closure detection performance. The two contributions are evaluated both separately and jointly on four common SLAM datasets, and are shown to improve the state-of-the-art performance both in terms of precision and recall in most of the cases. Moreover, our current implementation is designed to work at nearly frame rate, allowing loop closure query resolution at nearly 22 Hz for the best case scenario and 2 Hz for the worst case scenario.
Impact of uncertainty on a HELIAS 5- B stellarator fusion power plant

With a lack of plasma disruptions and current-driven instabilities, stellarators are potentially an attractive option for a fusion power plant. Previous system studies have been performed to optimise a HELIAS (HELIcal-axis Advanced Stellarator) 5-B power plant using process, however these have been based around a single design point. In reality there is a lot of uncertainty extrapolating from present day devices and understanding. In this paper we study how this will affect the design by identifying eight uncertainty distributions on the input. We then perform parameter studies and Monte-Carlo based analysis to look at the impact on fusion power and divertor heat load. We find that the two uncertainties that have the largest impact on the fusion power are the helium primary coolant mechanical pumping power and the energy multiplication in the blanket and shield. Eighty-three per cent of our solutions are within a tolerable divertor heat load, however this is additionally influenced by the tungsten impurity levels. In order to stay below the density cutoff limit for Electron Cyclotron Resonance Heating, the confinement time needs to be enhanced relative to the ISS04 scaling relation to produce acceptable performance. By identifying the highest impact design parameters, we are able to highlight the areas that need to be prioritised for additional study.
Identifying Investment Opportunities: A Business Model Performance Approach

In order to achieve the maximum productivity in a competitive business arena, organizations have to improve their performance in spite of potential limitations caused by the firm and industry’s characteristics. Such progress will be possible only by choosing a proper business model, which can help managers in making appropriate decisions through systematic analysis of the company's status. The successful model creates more value for customers and finally, brings more profit to the company. Despite the importance of the mentioned issue and frequent utilization of the concept of a business model in academic and administrative environments, this concept has been rarely studied in Iran. Based on the statements of one hundred top Iranian companies, the present study examines successful business models from shareholder's perspective. The results show that business models like manufacturers and distributors are the most common seen models in Iran. The results also show that compare to industry classifications, business models are better predictors of financial performance. In addition we find that some business models perform better than others. In particular a business model based on intangible assets in general, and manufacturers and distributors and Financial Landlord, in atomic view, have the greatest impact on the company's performance and hence achieving an appropriate competitive position.
Optimization of double-plane surface electrode ion trap lattices

Ion traps have proven to be promising systems for quantum computation and simulation. Periodic lattices of trapped ions have been shown to be one interesting setting for quantum simulation. Small arrays of trapped ions have already been realized experimentally in Penning traps as well as in Paul traps, and proof-ofprinciple quantum simulation could be successfully performed. We will focus on Paul traps, that are more open to miniaturization then Penning traps. While trapping a small array of ions in a single trap is now a well investigated problem, the number of ions that could be stored as a 2D array in a single Paul trap has shown intrinsic limitations. To circumvent these limitations, it has been proposed to trap larger arrays of ions by placing each ion in a separate trap. This is a relatively new concept and several settings realizing this have been implemented. One of them is realized through a (single plane-) surface electrode trap (SET), and is currently being implemented and built. Our aim was to analyze how adding a second surface electrode plane above the other would affect the properties of the trap. A well known drawback of surface electrode traps is the limit on the ratio of electrode-ionover ion-ion distance. This is of great importance because it is of interest to increase the ion-ion coupling, and thus to minimize the ion-ion distance, while also increasing the ion-surface distance to minimize the effects of Johnson Noise and anomalous heating. Our aim was thus to analyze if this ratio could be improved. We show that while improving the depth of each single trap by roughly 100%, for a given Electrode rf-voltage, the ratio of height over distance could be improved by nearly 50%.
Machine Learning Techniques for the Classification of Product Descriptions from Darknet Marketplaces

Over the past decade, the darknet has created unprecedented opportunities for traﬃcking in illicit goods, such as weapons and drugs, and it has provided new ways to oﬀer crime as a service. Natural language processing techniques can be applied to ﬁnd the types of goods that are traded in these markets. In this paper we present the results of evaluating state-of-the-art machine learning methods for the classiﬁcation of darknet market oﬀers. Several embeddings, such as GloVe embeddings [20], Fasttext [15], Tensor Flow Universal Sentence Encoder [7], Flair’s contextual string embedding [2] and term-frequency inverse-document-frequency (TF-IDF), as well as our domain-speciﬁc darknet embedding have been evaluated with a series of machine learning models, such as Random Forest, SVM, Naïve Bayes and Multilayer Perceptron. To ﬁnd the best combination of feature set and machine learning model for this task, the performance was evaluated on a publicly available collection covering 13 darknet markets with more than 10 million product oﬀers [6]. After extracting unique advertisements from the corpus, the classiﬁer was trained on a subset with those advertisements that contain strings related to weapons. The purpose was to determine how well the classiﬁer can distinguish between diﬀerent types of advertisements which seem all to be related to weapons according to the keywords they contain. The best performance for this classiﬁcation task was achieved using the
Domain-independent Punctuation and Segmentation Insertion

Punctuation and segmentation is crucial in spoken language translation, as it has a strong impact to translation performance. However, the impact of rare or unknown words in the performance of punctuation and segmentation insertion has not been thoroughly studied. In this work, we simulate various degrees of domain-match in testing scenario and investigate their impact to the punctuation insertion task. We explore three rare word generalizing schemes using part-of-speech (POS) tokens. Experiments show that generalizing rare and unknown words greatly improves the punctuation insertion performance, reaching up to 8.8 points of improvement in F-score when applied to the out-of-domain test scenario. We show that this improvement in punctuation quality has a positive impact on a following machine translation (MT) performance, improving it by 2 BLEU points.
Optimized operation of dielectric laser accelerators: Multibunch

We present a self-consistent analysis to determine the optimal charge, gradient, and efficiency for laser driven accelerators operating with a train of microbunches. Specifically, we account for the beam loading reduction on the material occurring at the dielectric-vacuum interface. In the case of a train of microbunches, such beam loading effect could be detrimental due to energy spread, however this may be compensated by a tapered laser pulse. We ultimately propose an optimization procedure with an analytical solution for group velocity which equals to half the speed of light. This optimization results in a maximum efficiency 20% lower than the single bunch case, and a total accelerated charge of 10 electrons in the train. The approach holds promise for improving operations of dielectric laser accelerators and may have an impact on emerging laser accelerators driven by high-power optical lasers.