Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Elevated CO 2 Combined with Two Nitrogen Levels on Photosynthesis , Growth and Leaf Structure in CAM Orchid Phalaenopsis

In C3 plants, elevated CO2 will increase plant growth and physiological performance through its effect on photosynthesis, but nitrogen (N) usability is a key factor to limit the growth of plants and augment the response to the long-term elevated CO2. To detect whether higher N availability holds back the photosynthetic down-regulation in CAM plant, the effects of photosynthetic physiology, leaf structure and growth of Phalaenopsis in the greenhouses under the combined conditions of two CO2 concentrations (400 and 800 μmol·mol) and two N levels (6 and 12 mmol·L) was studied. The results showed that elevated CO2 increased net CO2 uptake rate of facilitated the accumulation of starch and soluble sugar in Phalaenopsis leaves, but no marked differences were discovered between two N levels. Meanwhile, long-term elevated CO2 reduced the contents of N and soluble proteins, but N application had beneficial effect on the contents of soluble proteins and N in Phalaenopsis leaves under high CO2 concentration conditions. The elevated CO2 combined with N levels markedly increased the activities of photosynthetic enzyme. And elevated CO2 significantly improved the thickness of Phalaenopsis leaves, LE (low N level and elevated CO2 concentration) and HE (high N level and elevated CO2 concentration) increased by 6% and 8% compared with LA (low N level and atmospheric CO2 concentration) and HA (high N level and atmospheric CO2 concentration), respectively; the number of starch grains each chloroplast profile was augmented ~60% by elevated CO2, so the chloroplast profile area was added by 19% in LE and 11% in HE, compared with LA and HA. The elevated CO2 significantly accelerated the biomass accumulation in Phalaenopsis, and the high N level further promoted this increase. Thus, increasing supply of N and CO2 simultaneously was not very important in commercial production of CAM orchid Phalaenopsis during shortterm elevated CO2 exposure, but it is still necessary to properly increase the supply of N during short-term elevated CO2 exposure. © 2019 Friends Science Publishers
Author ' s personal copy A robust EM clustering algorithm for Gaussian mixture models

Clustering is a useful tool for finding structure in a data set. The mixture likelihood approach to clustering is a popular clustering method, in which the EM algorithm is the most used method. However, the EM algorithm for Gaussian mixture models is quite sensitive to initial values and the number of its components needs to be given a priori. To resolve these drawbacks of the EM, we develop a robust EM clustering algorithm for Gaussian mixture models, first creating a new way to solve these initialization problems. We then construct a schema to automatically obtain an optimal number of clusters. Therefore, the proposed robust EM algorithm is robust to initialization and also different cluster volumes with automatically obtaining an optimal number of clusters. Some experimental examples are used to compare our robust EM algorithm with existing clustering methods. The results demonstrate the superiority and usefulness of our proposed method. & 2012 Elsevier Ltd. All rights reserved.
Comparison of seroprevalence of transfusion transmissible infections between voluntary and replacement donors at a tertiary care center

Introduction: Transfusion transmissible infections (TTI) are a major threat for the recipients of blood and blood products. Voluntary blood donations (VBD) are considered safe to Replacement blood donations (RBD). Our main of the study is to find out the seroprevalence of TTIs in our area and also to find out whether there is a significant difference in seroprevalence of TTIs between VBD and RBD. Materials and Methods: It is a retrospective, cross sectional study carried out in the regional blood bank of a tertiary care centre. Records of total 33341 blood donations carried out in a period of 6 years (January 2012 to December 2017) were studied for calculating the seroprevalence of HIV, HBsAg, HCV and Syphilis. Comparison of seroprevalence between VBD and RBD was done. Results: Predominant donor population was male (91.86%). 91.63% donations were VBD and 8.37% donations were RBD. Most common type of TTI was HBsAg (85.9%) followed by HIV (6.72%), HCV (4.98%) and Syphilis (2.38%) respectively. The difference in seroprevalence of TTIs between VBD and RBD was statistically significant (p value <0.05). Conclusion: There is seen statistically significant difference in seroprevalence of TTIs between VBD and RBD suggesting RBD are at more risk for transmitting TTIs than VBD. Hence we recommend regular, non-remunerated, voluntary blood donations for assuring better safety and quality of blood and blood products.
SELECTIVE MODULATION OF MUCOSAL IMMUNE RESPONSES BY CYTOKINES ENCODED IN VACCINE VECTORS

We have developed vector systems encoding vaccine antigens and cytokines and have used these constructs to selectively modulate mucosal antibody and cell-mediated immune (CMI) responses. Information gained from studies in cytokine-deficient mice pointed to the importance of Th2-type factors, particularly IL-4 and IL-6, for the development of mucosal antibody responses, whilst type 1 factors, such as IL-12, would be expected to promote CMI. In this article, we describe the use of three distinct vectors, each constructed to encode cytokine genes along with the gene encoding a model vaccine antigen, the haemagglutinin (HA) of influenza virus, for the delivery of these proteins in vivo for mucosal immunomodulation. The vectors included DNA vaccines and poxviral vectors, including vaccinia virus (VV) and fowlpoxvirus (FPV). Each of these systems elicited measurable mucosal antibody responses when delivered locally and these were, in all cases, significantly enhanced by the co-expression of IL-6. In contrast, the mucosal delivery of IL-12 by DNA vaccine had little influence on mucosal antibody responses but stimulated good CMI responses. Indeed, mucosal CMI was not detected unless IL-12 was co-expressed with the vaccine antigen. The combined use of DNA and FPV vectors encoding the same vaccine antigen in a consecutive immunisation strategy gave rise to mucosal antibody responses of greatly enhanced magnitude and duration, even when the DNA priming dose was given by a systemic route. In addition, mucosal delivery of DNA vaccine primed not only for strong local responses but also for specific antibody production at distant mucosal tissues. Finally, the co-expression of IL-6 significantly further enhanced responses stimulated by consecutive immunisation. Thus, vector-driven cytokine delivery represents a powerful approach for the selective modulation of the mucosal immune system.
Trade Blocks, Common Markets, Currency Unions and FDI Stocks: The Impacts of NAFTA and the EU

This paper examines the factors affecting bilateral Foreign Direct Investment (FDI) stocks from 14 high income countries to 31 OECD countries over the period 1995-2015. We specifically emphasise the effect of regional trade agreements such as the European Union (EU) and the North American Free Trade Area (NAFTA) along with membership of the Currency Union. Our empirical analysis applies the generalised method of moments (GMM) estimator to a gravity model of bilateral FDI stocks. The findings imply that EU membership is a significant determinant of FDI even when we condition on the variables that follow from the application of the gravity model. We look at the effects of the North American Free Trade Area on within block FDI and find no similar effect. Our results suggest that European Integration has a large effect on FDI stocks, raising intra Single Market FDI noticeably. We note that the UK’s departure from the Single Market may reduce the stock of intra EU FDI by up to 30 per cent in the long run. In addition, the findings point that the UK has no labour market or competitive environment advantage above the rest of the EU in attracting FDI.
List-length and list-strength effects in recognition memory

The study of interference effects is important to constrain models of memory. List-length manipulations test how adding new information to memory affects memory for the other stored information (list-length effect; LLE). List-strength manipulations test how strengthening some information in memory affects memory for the other non-strengthened information (list-strength effect; LSE). Whereas LLE and LSE are generally found in recall tasks, their empirical status in recognition tasks is less well established. In this thesis, we investigated some boundary conditions for both list-length and list-strength effects. The results provided evidence for the following claims: i) LLE and LSE are real effects in recognition (the effects were obtained after controlling for several confounds); ii) LLE and LSE are modulated by the relative contribution of recall-like processes operating at test (more recollection at test yielded larger effects); iii) LLE and LSE can be modulated by the number of study-test blocks in an experimental session (fewer study-test blocks resulted in larger effects); iv) LLE and LSE can be modulated by the time interval between study and test (shorter intervals produced larger effects) and iv) LLE and LSE may not be strongly modulated by the magnitude of length and strength manipulations (stronger manipulations did not result in larger effects). Taken together, the results support memory models that attribute forgetting in recognition to competition between memory traces during either encoding or retrieval. The results provide little support for models that attribute forgetting solely to interference between the contexts in which a memory was originally stored.
A framework for real-time discrete event control

The TTM/RTTL (timed transition model with real-time temporal logic) framework is presented for modeling, specifying, and analyzing real-time discrete-event systems. TTMs are used to represent the process of the plant and its controller. RTTL is the assertion language for specifying plant behavior and verifying that a controller satisfies the specification. The framework adapts features from the program verification literature which are useful for posing problems of interest to the control engineer, such as modular synthesis and design. Examples are used to illustrate the ideas presented. The authors' published analytical results are summarized and referenced. >
EmoTEA: Teaching Children with Autism Spectrum Disorder to Identify and Express Emotions

In this paper we present a novel software application developed as a serious game to teach children with Autism Spectrum Disorder (ASD) to identify and express emotions. The system incorporates cutting-edge technology to support innovative interaction mechanisms based on Tangible User Interfaces (TUI) and emotion recognition based on facial expressions. This way, children interact with the system in a natural way just by grasping objects with their hands and using their faces. The system has been assessed in the premises of an association with children with ASD. The outcomes of the evaluation are very positive showing the validity of the proposal.
Planar graphs of bounded degree have bounded queue number

A queue layout of a graph consists of a linear order of its vertices and a partition of its edges into queues, so that no two independent edges of the same queue are nested. The queue number of a graph is the minimum number of queues required by any of its queue layouts. A long-standing conjecture by Heath, Leighton and Rosenberg states that the queue number of planar graphs is bounded.This conjecture has been partially settled in the positive for several sub- families of planar graphs (most of which have bounded treewidth). In this paper, we make a further important step towards settling this conjecture. We prove that planar graphs of bounded degree (which may have unbounded treewidth) have bounded queue number. A notable implication of this result is that every planar graph of bounded degree admits a three-dimensional straight-line grid drawing in linear volume. Further implications are that every planar graph of bounded degree has bounded track number, and that every k-planar graph (i.e., every graph that can be drawn in the plane with at most k crossings per edge) of bounded degree as bounded queue number.
OmniGlobe: An Interactive I/O System For Symmetric 360-Degree Video Communication

Video communication systems have been suffered from the narrow field of view. To solve this limitation, one study proposed symmetric 360° video communication system by combining an omnidirectional camera and a hemispherical display. However, the system still had several issues, e.g., the invisibility of hemisphere which was at the opposite side from a user caused the inconvenience of observing the remote environment. To solve these issues, we introduce OmniGlobe, a novel symmetric full 360° video communication system which incorporates an omnidirectional camera, a full spherical display, and several visual or interactive techniques. Based on an experiment, we could indicate that our system is effective in reducing the inconvenience of observing the remote environment and increased the remote space awareness and user's gaze awareness to support remote collaboration. We also discuss the takeaways, limitations and application areas in our system which help improve the system.
Chronoscope: Designing Temporally Diverse Interactions with Personal Digital Photo Collections

With the massive proliferation of digital photos, new approaches are needed to enable people to engage with their vast photo archives over time. We describe the Research through Design process of Chronoscope, a domestic technology that leverages temporal metadata embedded in digital photos as a resource to encourage more temporally diverse, rich, and open-ended experiences when re-visiting one's personal digital photo archive. We unpack and reflect on design choices that made use of digital photo metadata to support new ways of interacting with personal photo archives through and across time. We conclude with opportunities for future HCI research and practice.
Tangible Interactions with Acoustically Levitated Voxels

Acoustic Levitation can trap small objects in mid-air without physical contact, this can be exploited to create displays made of levitating voxels. Sound diffracts around objects, thus we can insert the hand inside the levitator and touch the levitated particles. In this demo, we show some possible tangible interactions with acoustically levitated particles by passing acoustically-transparent meshes through the particles, using wearable levitators to move particles or employing direct manipulation by pinching close to the particles and dragging them. All the presented devices are available as Instructables, we will encourage visitors to build their own levitators and experiment further with acoustic levitation.
Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together

Subgraph matching (or subgraph isomorphism) is one of the fundamental problems in graph analysis. Extensive research has been done to develop practical solutions for subgraph matching. The state-of-the-art algorithms such as \textsfCFL-Match and \textsfTurbo\textsubscriptiso convert a query graph into a spanning tree for obtaining candidates for each query vertex and obtaining a good matching order with the spanning tree. However, by using the spanning tree instead of the original query graph, it could lead to lower pruning power and a sub-optimal matching order. Another limitation is that they perform redundant computation in search without utilizing the knowledge learned from past computation. In this paper, we introduce three novel concepts to address these inherent limitations: 1) dynamic programming between a directed acyclic graph (DAG) and a graph, 2) adaptive matching order with DAG ordering, and 3) pruning by failing sets, which together lead to a much faster algorithm \textsfDAF for subgraph matching. Extensive experiments with real datasets show that \textsfDAF outperforms the fastest existing solution by up to orders of magnitude in terms of recursive calls as well as in terms of the elapsed time.
Active Sparse Mobile Crowd Sensing Based on Matrix Completion

A major factor that prevents the large scale deployment of Mobile Crowd Sensing (MCS) is its sensing and communication cost. Given the spatio-temporal correlation among the environment monitoring data, matrix completion (MC) can be exploited to only monitor a small part of locations and time, and infer the remaining data. Rather than only taking random measurements following the basic MC theory, to further reduce the cost of MCS while ensuring the quality of missing data inference, we propose an Active Sparse MCS (AS-MCS) scheme which includes a bipartite-graph-based sensing scheduling scheme to actively determine the sampling positions in each upcoming time slot, and a bipartite-graph-based matrix completion algorithm to robustly and accurately recover the un-sampled data in the presence of sensing and communications errors. We also incorporate the sensing cost into the bipartite-graph to facilitate low cost sample selection and consider the incentives for MCS. We have conducted extensive performance studies using the data sets from the monitoring of PM 2.5 air condition and road traffic speed, respectively. Our results demonstrate that our AS-MCS scheme can recover the missing data at very high accuracy with the sampling ratio only around $11%$, while the peer matrix completion algorithms with similar recovery performance requires up to 4-9 times the number of samples of ours for both the data sets.
Mechanisms of harmony and the ordering of word order: consistencies and inconsistencies in language change and acquisition

The thesis is based on the learning of word-orders in a cross-lingUistic and historic perspective. In linguistics, a certain hannony is expected in word order. X-bars of a language are supposed to be right-branched or left-branched. So, a language, which is right-branched has its head usually first, and a language, which is left-branched has its head usually last. In the generative framework, linguists argue that when a child encounters a structure where the head is to the right, she will assume that the whole language is constructed this way. Cognitive scientists like Christiansen argue that inconsistencies, that means a mixture of right- and left- branching are more difficult to learn because of recursive embeddings, and thus inconsistencies should simply die out or never come into existence in the first place. Greenberg established language universals after having considered forty languages. These universals would show consistencies in an X-bar branching, but Greenberg also cited exceptions and spoke of statistical universals. We are interested in these inconsistencies. If they are really more difficult to learn, why do they evolve in the first place and why are they often quite consistent in language evolution, i.e. they do not die out. Historical linguistics often argue that languages tend to develop from one consistent language via a transitional one and then develop again towards a consistent language. Inconsistent structures exist in most languages although there is a statistical trend towards consistencies. So, how do languages change and what makes persons learn at one stage a language differently and what are the mechanisms involved in learning that we can see as an end-result in language change. We will examine some of these phenomena, when we discussA? Â· language change in Romance, the introduction of postpositions in Gennan, and the role of the infinite verb in Gennan and in Old English. Experimental work has been done for the frontability of Gennan particles, which is closely linked to the introduction of postpositions. We did an experiment in English language for the role of the infinite verb in verb-final languages such as Gennan and replicated this experiment in French because of its richer verb morphology because this gives us a greater distinction between finite and infinite verbs. An SRN-simulation on the role of the infinite verb supports the experiments.
SVQ: Streaming Video Queries

Recent advances in video processing utilizing deep learning primitives achieved breakthroughs in fundamental problems in video analysis such as frame classification and object detection enabling an array of new applications. In this demo we present \em SVQ a system capable of executing declarative queries on streaming video. The system utilizes a set of approximate filters to speed up queries that involve objects of specific type (e.g., cars, trucks, etc.) on video frames with associated spatial relationships among them (e.g., car left of truck). The resulting filters are able to assess quickly if the query predicates are true to proceed with further analysis of the frame or otherwise not consider the frame further avoiding costly object detection and localization operations. The filters utilize extensible deep neural architectures and are easy to deploy and utilize. We demonstrate that the application of our filtering techniques in the context of SVQ enable declarative queries on video streams increasing dramatically the frame processing rate and speed up query processing by at least two orders of magnitude depending on the query.
PneumAct: Pneumatic Kinesthetic Actuation of Body Joints in Virtual Reality Environments

Virtual Reality Environments (VRE) create an immersive user experience through visual, aural, and haptic sensations. However, the latter is often limited to vibrotactile sensations that are not able to actively provide kinesthetic motion actuation. Further, such sensations do not cover natural representations of physical forces, for example, when lifting a weight. We present PneumAct, a jacket to enable pneumatically actuated kinesthetic movements of arm joints in VRE. It integrates two types of actuators inflated through compressed air: a Contraction Actuator and an Extension Actuator. We evaluate our PneumAct jacket through two user studies with a total of 32 participants: First, we perform a technical evaluation measuring the contraction and extension angles of different inflation patterns and inflation durations. Second, we evaluate PneumAct in three VRE scenarios comparing our system to traditional controller-based vibrotactile and a baseline without haptic feedback.
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models

In the era of big data, computing exact answers to analytical queries becomes prohibitively expensive. This greatly increases the value of approaches that can compute efficiently approximate, but highly-accurate, answers to analytical queries. Alas, the state of the art still suffers from many shortcomings: Errors are still high unless large memory investments are made. Many important analytics tasks are not supported. Query response times are too long and thus approaches rely on parallel execution of queries atop large big data analytics clusters, in-situ or in the cloud, whose acquisition/use costs dearly. Hence, the following questions are crucial: Can we develop AQP engines that reduce response times by orders of magnitude, ensure high accuracy, and support most aggregate functions? With smaller memory footprints and small overheads to build the state upon which they are based? With this paper, we show that the answers to all questions above can be positive. The paper presents DBEst, a system based on Machine Learning models (regression models and probability density estimators). It will discuss its limitations, promises, and how it can complement existing systems. It will substantiate its advantages using queries and data from the TPC-DS benchmark and real-life datasets, compared against state of the art AQP engines.