Miracle-dz/UniFAR-FTUs huggingface dataset:
Discerning morpho-anatomical, physiological and molecular multiformity in cultivated and wild genotypes of lentil with reconciliation to salinity stress

One hundred and sixty two genotypes of different Lens species were screened for salinity tolerance in hydroponics at 40, 80 and 120 mM sodium chloride (NaCl) for 30 d. The germination, seedling growth, biomass accumulation, seedling survivability, salinity scores, root and shoot anatomy, sodium ion (Na+), chloride ion (Cl-) and potassium ion (K+) concentrations, proline and antioxidant activities were measured to evaluate the performance of all the genotypes. The results were compared in respect of physiological (Na+, K+ and Cl-) and seed yield components obtained from field trials for salinity stress conducted during two years. Expression of salt tolerance in hydroponics was found to be reliable indicator for similarity in salt tolerance between genotypes and was evident in saline soil based comparisons. Impressive genotypic variation for salinity tolerance was observed among the genotypes screened under hydroponic and saline field conditions. Plant concentrations of Na+ and Cl- at 120 mM NaCl were found significantly correlated with germination, root and shoot length, fresh and dry weight of roots and shoots, seedling survivability, salinity scores and K+ under controlled conditions and ranked the genotypes along with their seed yield in the field. Root and shoot anatomy of tolerant line (PDL-1) and wild accession (ILWL-137) showed restricted uptake of Na+ and Cl- due to thick layer of their epidermis and endodermis as compared to sensitive cultigen (L-4076). All the genotypes were scanned using SSR markers for genetic diversity, which generated high polymorphism. On the basis of cluster analysis and population structure the contrasting genotypes were grouped into different classes. These markers may further be tested to explore their potential in marker-assisted selection.
Intra- and Inter-Fractional Variation Prediction of Lung Tumors Using Fuzzy Deep Learning

Tumor movements should be accurately predicted to improve delivery accuracy and reduce unnecessary radiation exposure to healthy tissue during radiotherapy. The tumor movements pertaining to respiration are divided into intra-fractional variation occurring in a single treatment session and inter-fractional variation arising between different sessions. Most studies of patients' respiration movements deal with intra-fractional variation. Previous studies on inter-fractional variation are hardly mathematized and cannot predict movements well due to inconstant variation. Moreover, the computation time of the prediction should be reduced. To overcome these limitations, we propose a new predictor for intra- and inter-fractional data variation, called intra- and inter-fraction fuzzy deep learning (IIFDL), where FDL, equipped with breathing clustering, predicts the movement accurately and decreases the computation time. Through the experimental results, we validated that the IIFDL improved root-mean-square error (RMSE) by 29.98% and prediction overshoot by 70.93%, compared with existing methods. The results also showed that the IIFDL enhanced the average RMSE and overshoot by 59.73% and 83.27%, respectively. In addition, the average computation time of IIFDL was 1.54 ms for both intra- and inter-fractional variation, which was much smaller than the existing methods. Therefore, the proposed IIFDL might achieve real-time estimation as well as better tracking techniques in radiotherapy.
Contained Entity of an Educational Innovation: The Realities of Micropolitics

This study was about a single case of educational innovation and excellence in educational technology in a secondary school in Ontario. The researcher explored the question of how the innovation resulted from an individual effort and attainment remained a “contained entity” after its decade-long existence. From the lenses of multiple realities, the researcher critically interpreted how micropolitics including gender and power dynamics and teacher resistance could create complexities for the institutionalization of the innovation. The district was urged to consider the lack of time and professional development issues raised by teachers. Further research was required to address the conspicuous absence of gender gap in this study.
The Power of Sparsity in Convolutional Neural Networks

Deep convolutional networks are well-known for their high computational and memory demands. Given limited resources, how does one design a network that balances its size, training time, and prediction accuracy? A surprisingly effective approach to trade accuracy for size and speed is to simply reduce the number of channels in each convolutional layer by a fixed fraction and retrain the network. In many cases this leads to significantly smaller networks with only minimal changes to accuracy. In this paper, we take a step further by empirically examining a strategy for deactivating connections between filters in convolutional layers in a way that allows us to harvest savings both in run-time and memory for many network architectures. More specifically, we generalize 2D convolution to use a channel-wise sparse connection structure and show that this leads to significantly better results than the baseline approach for large networks including VGG and Inception V3.
Differential Privacy for Bayesian Inference through Posterior Sampling

Differential privacy formalises privacy-preserving mechanisms that provide access to a database. Can Bayesian inference be used directly to provide private access to data? The answer is yes: under certain conditions on the prior, sampling from the posterior distribution can lead to a desired level of privacy and utility. For a uniform treatment, we define differential privacy over arbitrary data set metrics, outcome spaces and distribution families. This allows us to also deal with non-i.i. d or non-tabular data sets. We then prove bounds on the sensitivity of the posterior to the data, which delivers a measure of robustness. We also show how to use posterior sampling to provide differentially private responses to queries, within a decision-theoretic framework. Finally, we provide bounds on the utility of answers to queries and on the ability of an adversary to distinguish between data sets. The latter are complemented by a novel use of Le Cam's method to obtain lower bounds on distinguishability. Our results hold for arbitrary metrics, including those for the common definition of differential privacy. For specific choices of the metric, we give a number of examples satisfying our assumptions.
Transmembrane Protein Alignment and Fold Recognition Based on Predicted Topology

Background Although Transmembrane Proteins (TMPs) are highly important in various biological processes and pharmaceutical developments, general prediction of TMP structures is still far from satisfactory. Because TMPs have significantly different physicochemical properties from soluble proteins, current protein structure prediction tools for soluble proteins may not work well for TMPs. With the increasing number of experimental TMP structures available, template-based methods have the potential to become broadly applicable for TMP structure prediction. However, the current fold recognition methods for TMPs are not as well developed as they are for soluble proteins. Methodology We developed a novel TMP Fold Recognition method, TMFR, to recognize TMP folds based on sequence-to-structure pairwise alignment. The method utilizes topology-based features in alignment together with sequence profile and solvent accessibility. It also incorporates a gap penalty that depends on predicted topology structure segments. Given the difference between α-helical transmembrane protein (αTMP) and β-strands transmembrane protein (βTMP), parameters of scoring functions are trained respectively for these two protein categories using 58 αTMPs and 17 βTMPs in a non-redundant training dataset. Results We compared our method with HHalign, a leading alignment tool using a non-redundant testing dataset including 72 αTMPs and 30 βTMPs. Our method achieved 10% and 9% better accuracies than HHalign in αTMPs and βTMPs, respectively. The raw score generated by TMFR is negatively correlated with the structure similarity between the target and the template, which indicates its effectiveness for fold recognition. The result demonstrates TMFR provides an effective TMP-specific fold recognition and alignment method.
Does submucosal diathermy to the inferior turbinates reduce nasal resistance to airflow in the long term?

Abstract The operation of submucosal diathermy is commonly performed for the relief of nasal obstruction due to mucosal swelling. In this study the effect of the procedure on nasal resistance to airflow is assessed by rhinomanometry. The results show that although the operation is effective in the short term (two months), there is no significant difference between the nasal resistances prior to surgery and at 15 months after surgery.
Development of a Novel Molecular Sensor for Imaging Estrogen Receptor-Coactivator Protein-Protein Interactions

Anti-estrogens, in particular tissue selective anti-estrogens, have been the bedrock of adjuvant therapy for patients with estrogen receptor alpha (ERα) positive breast cancer. Though current therapies have greatly enhanced patient prognosis, there continues to be an impetus for the development of improved anti-estrogens. ERα is a nuclear receptor transcription factor which activates gene expression through the recruitment of transcriptional coactivator proteins. The SRC family of coactivators, which includes AIB1, has been shown to be of particular importance for ERα mediated transcription. ERα-AIB1 interactions are indicative of gene expression and are inhibited by anti-estrogen treatment. We have exploited the interaction between ERα and AIB1 as a novel method for imaging ERα activity using a split luciferase molecular sensor. By producing a range of ERα ligand binding domain (ER-LBD) and AIB1 nuclear receptor interacting domain (AIB-RID) N- and C-terminal firefly luciferase fragment fusion proteins, constructs which exhibited more than a 10-fold increase in luciferase activity with E2 stimulation were identified. The specificity of the E2-stimulated luciferase activity to ERα-AIB1 interaction was validated through Y537S and L539/540A ER-LBD fusion protein mutants. The primed nature of the split luciferase assay allowed changes in ERα activity, with respect to the protein-protein interactions preceding transcription, to be assessed soon after drug treatment. The novel assay split luciferase detailed in this report enabled modulation of ERα activity to be sensitively imaged in vitro and in living subjects and potentially holds much promise for imaging the efficacy of novel ERα specific therapies.
Proliferation and differentiation of human tenocytes in response to platelet rich plasma: An in vitro and in vivo study

Platelet rich plasma (PRP) is the autologous plasma fraction with a platelet‐rich cellular component which is enriched with a number of growth factors. Due to its availability and low cost, PRP has become an increasingly popular clinical tool as an alternative source of growth factors for various applications, for example, tendon regeneration but with limited success in clinical trials. The main objective of the current study was to determine whether activated PRP [i.e., platelet rich plasma‐clot release (PRCR)] could be used to induce the proliferation and collagen synthesis in human tenocyte in vitro. The advantage of using PRCR is that the platelet‐derived bioactive factors are more concentrated and could initiate a more rapid and accelerated healing response than PRP. Our results demonstrated that 10% PRCR treatment accelerated the extent of cell proliferation and collagen production by human tenocytes in vitro. The expression of specific tenocyte markers were similar to conventional fetal bovine serum (FBS)‐treated tenocytes implanted in mice within 14 days of implantation in diffusion chambers. Moreover, relatively more collagen fibrils were evident in PRCR‐treated tenocytes in vivo as compared to 10% FBS‐treated cells. Overall, our feasibility study has indicated that PRCR can induce human tenocyte proliferation and collagen synthesis which could be implemented for future tendon regeneration in reconstructive surgeries. © 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:982–990, 2012
Integrity-driven Power and Signal Network

Conventional physical design flow separates the design of power network and signal network. Such a separated approach results in slow design convergence for wire-limited deep sub-micron designs. In this paper, we present a novel design methodology that simultaneously considers global signal routing and power network design under integrity constraints. The key part to this approach is a simple yet accurate power net estimation formula that decides the minimum number of power nets needed to satisfy both power and signal integrity constraints prior to detailed layout. The proposed design methodology is a one-pass solution to the co-design of power and signal networks in the sense that no iteration between them is required in order to meet design closure. Experiment results using large industrial benchmarks show that compared to the state-of-the-art alternative design approach, the proposed method can reduce the power network area by 19.4% on average under the same signal and power integrity constraints with better routing quality, but use less runtime.
Analytical Temporal Specification Issues for Industrial Control Systems

Control system architectures are expanding significantly in terms of functionality, complexity and scalability. Real-time programming methodologies have evolved in the last decade with increasing complexity of control system and scalability of equipment in the industrial automation domain. The paper proffers an analytical survey of tools and methodologies that can enhance the control action simulation and software design. The paper includes a diagnostic view for application of Real Time-Languages like Giotto and RT-Java for time critical tasks within the control system. Secondly, the paper uses the statistical approach to model the network induced delays to manifest their impact on control system operation. The aim of the paper is to analyze, model and validate the timing aspects within a control loop and physical plant operation
An Efficient Content-Based Event Matching Algorithm Based on Double-Deck Tree Decomposition

A novel algorithm for event matching of publish /subscribe systems is presented. To use the filtering abilities of attribute names and values synthetically, a double-deck tree structure is proposed. For the first deck, the proposed algorithm builds a tree structure by using the attribute names. All subscriptions are partitioned into the nodes of the first deck tree according to the attribute contained in their constraints. For the second deck, the other tree structure is constructed for each leaf node of the first deck tree based on the attribute values. The subscriptions stored in each node of the first deck tree are also classified in order to be stored in the nodes of the second deck tree. When an event is being processed, the number of the possible matched subscriptions can be cut down by using the attribute values as the criterion. Experimental results show that the algorithm can shorten the matching time and improve efficiency of the event matching.
In vivo protein complex topologies: Sights through a cross‐linking lens

Proteins are a remarkable class of molecules that exhibit wide diversity of shapes or topological features that underpin protein interactions and give rise to biological function. In addition to quantitation of abundance levels of proteins in biological systems under a variety of conditions, the field of proteome research has as a primary mission the assignment of function for proteins and if possible, illumination of factors that enable function. For many years, chemical cross‐linking methods have been used to provide structural data on single purified proteins and purified protein complexes. However, these methods also offer the alluring possibility to extend capabilities to complex biological samples such as cell lysates or intact living cells where proteins may exhibit native topological features that do not exist in purified form. Recent efforts are beginning to provide glimpses of protein complexes and topologies in cells that suggest continued development will yield novel capabilities to view functional topological features of many proteins and complexes as they exist in cells, tissues, or other complex samples. This review will describe rationale, challenges, and a few success stories along the path of development of cross‐linking technologies for measurement of in vivo protein interaction topologies.
Understanding Scotland: The Sociology of a Nation

1. The Making of Modern Scotland 2. What is Scotland? 3. Understanding Scotland's Development 4. Getting on in Scotland 5. Power and Politics in a Cold Country 6. Scottish Culture: Images and Icons 7. Roots and Routes: Seeking Scottish Identity 8. The Sociology of a Nation.
Guidelines for ToBI labelling

0 Preface 2 0.1 What are the “Guidelines for ToBI Labelling”? 2 0.1. 1 Notice of copyright and restrictions on use . 2 0.1. 2 Acknowledgements . 2 0.2 Getting and using the digitized utterances and f0 tracks . 3 0.2. 1 Getting the digitized utterances and f0 tracks . 3 0.2. 2 Using the digitized utterances and f0 tracks . 6 0.2. 3 A less interactive electronic version that can be used on a Mac . 7 0.3 Getting and using the audio recording and paper f0 records . 7 0.4 Future editions and a disclaimer . 8
Protease-Sensitive Synthetic Prions

Prions arise when the cellular prion protein (PrPC) undergoes a self-propagating conformational change; the resulting infectious conformer is designated PrPSc. Frequently, PrPSc is protease-resistant but protease-sensitive (s) prions have been isolated in humans and other animals. We report here that protease-sensitive, synthetic prions were generated in vitro during polymerization of recombinant (rec) PrP into amyloid fibers. In 22 independent experiments, recPrP amyloid preparations, but not recPrP monomers or oligomers, transmitted disease to transgenic mice (n = 164), denoted Tg9949 mice, that overexpress N-terminally truncated PrP. Tg9949 control mice (n = 174) did not spontaneously generate prions although they were prone to late-onset spontaneous neurological dysfunction. When synthetic prion isolates from infected Tg9949 mice were serially transmitted in the same line of mice, they exhibited sPrPSc and caused neurodegeneration. Interestingly, these protease-sensitive prions did not shorten the life span of Tg9949 mice despite causing extensive neurodegeneration. We inoculated three synthetic prion isolates into Tg4053 mice that overexpress full-length PrP; Tg4053 mice are not prone to developing spontaneous neurological dysfunction. The synthetic prion isolates caused disease in 600–750 days in Tg4053 mice, which exhibited sPrPSc. These novel synthetic prions demonstrate that conformational changes in wild-type PrP can produce mouse prions composed exclusively of sPrPSc.
FireCite: Lightweight real-time reference string extraction from webpages

We present FireCite, a Mozilla Firefox browser extension that helps scholars assess and manage scholarly references on the web by automatically detecting and parsing such reference strings in real-time. FireCite has two main components: 1) a reference string recognizer that has a high recall of 96%, and 2) a reference string parser that can process HTML web pages with an overall F1 of 878 and plaintext reference strings with an overall F1 of 97. In our preliminary evaluation, we presented our FireCite prototype to four academics in separate unstructured interviews. Their positive feedback gives evidence to the desirability of FireCite's citation management capabilities.
Heterogeneous and Elastic Computation Framework for Mobile Cloud Computing

The number and variety of applications for mobile devices continue to grow. However, the resources on mobile devices including computation and storage do not keep pace with the growth. How to incorporate the computation capacity on cloud servers into mobile computing has been desired and challenge issues to resolve. In this work, we design an elastic computation framework to take advantage the heterogeneous computation capacity on cloud servers, which consist of CPUs and GPGPUs, to meet the computation demands of ever growing mobile applications. The computation framework extends OpenCL framework to link remote processors with local mobile applications. The framework is flexible in the sense that the computation can be stopped at any time and gains results, which is called imprecise computation in real-time computing literature. The framework has been evaluated against OpenCL benchmark and physical computation engine for gaming. The results show that the framework supports OpenCL benchmark, RODINIA, without modifying the codes with few exceptions. The elastic computation framework allows the cloud servers to support more mobile clients without sacrificing their QoS requirements. The experiment results also show that IO intensive applications do not perform well when the network capacity is insufficient or unreliable.
Fingerprint Classification by Directional Image Partitioning

In this work, we introduce a new approach to automatic fingerprint classification. The directional image is partitioned into "homogeneous" connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification. A set of dynamic masks, together with an optimization criterion, are used to guide the partitioning. The adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point, which can be conceived as a continuous classification. Different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification. Experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature: As to fingerprint retrieval based on continuous classification, our method gives the best performance and exhibits a very high robustness.
A low profile PIFA antenna with a via-less square-ring artificial magnetic conductor at 5.8GHz

A new low profile antenna comprised of a PIFA and an Artificial Magnetic Conductor (AMC) are presented. The PIFA antenna is placed at the edge of the AMC structure for bandwidth improvement. Use of a square-ring elementary element AMC without via is shown to maintain the PIFAs radiation efficiency with a low profile. The chosen AMC exhibits the required zero phase reflection coefficient for normally incident waves. Results suggest that additional directivity can be achieved for the combined PIFA/AMC system.
A Note on Preconditioning by Low-Stretch Spanning Trees

Boman and Hendrickson observed that one can solve linear systems in Laplacian matrices in time $\bigO{m^{3/2 + o (1)} \ln (1/\epsilon)}$ by preconditioning with the Laplacian of a low-stretch spanning tree. By examining the distribution of eigenvalues of the preconditioned linear system, we prove that the preconditioned conjugate gradient will actually solve the linear system in time $\softO{m^{4/3} \ln (1/\epsilon)}$.