Miracle-dz/UniFAR-FTUs huggingface dataset:
Accumulated Expression Level of Cytosolic Glutamine Synthetase 1 Gene (OsGS1;1 or OsGS1;2) Alter Plant Development and the Carbon-Nitrogen Metabolic Status in Rice

Maintaining an appropriate balance of carbon to nitrogen metabolism is essential for rice growth and yield. Glutamine synthetase is a key enzyme for ammonium assimilation. In this study, we systematically analyzed the growth phenotype, carbon-nitrogen metabolic status and gene expression profiles in GS1;1-, GS1;2-overexpressing rice and wildtype plants. Our results revealed that the GS1;1-, GS1;2-overexpressing plants exhibited a poor plant growth phenotype and yield and decreased carbon/nitrogen ratio in the stem caused by the accumulation of nitrogen in the stem. In addition, the leaf SPAD value and photosynthetic parameters, soluble proteins and carbohydrates varied greatly in the GS1;1-, GS1;2-overexpressing plants. Furthermore, metabolite profile and gene expression analysis demonstrated significant changes in individual sugars, organic acids and free amino acids, and gene expression patterns in GS1;1-, GS1;2-overexpressing plants, which also indicated the distinct roles that these two GS1 genes played in rice nitrogen metabolism, particularly when sufficient nitrogen was applied in the environment. Thus, the unbalanced carbon-nitrogen metabolic status and poor ability of nitrogen transportation from stem to leaf in GS1;1-, GS1;2-overexpressing plants may explain the poor growth and yield.
Feature Selection for Optimized High-dimensional Biomedical Data using the Improved Shuffed Frog Leaping Algorithm.

High dimensional biomedical datasets contain thousands of features which can be used in molecular diagnosis of disease, however, such datasets contain many irrelevant or weak correlation features which influence the predictive accuracy of diagnosis. Without a feature selection algorithm, it is difficult for the existing classification techniques to accurately identify patterns in the features. The purpose of feature selection is to not only identify a feature subset from an original set of features [without reducing the predictive accuracy of classification algorithm] but also reduce the computation overhead in data mining. In this paper, we present our improved shuffled frog leaping algorithm which introduces a chaos memory weight factor, an absolute balance group strategy and an adaptive transfer factor. Our proposed approach explores the space of possible subsets to obtain the set of features that maximizes the predictive accuracy and minimizes irrelevant features in high-dimensional biomedical data. To evaluate the effectiveness of our proposed method we have employed the K-nearest neighbor method with a comparative analysis in which we compare our proposed approach with genetic algorithms, particle swarm optimization, and the shuffled frog leaping algorithm. Experimental results show that our improved algorithm achieves improvements in the identification of relevant subsets and in classification accuracy.
Genetic structure and reproductive strategy of the ant Cardiocondyla elegans: strictly monogynous nests invaded by unrelated sexuals

Cardiocondyla elegans is a Mediterranean ant that nests on river banks. It rears only wingless (ergatoid) males that live peacefully in the same nest as opposed to other species of the same genus, which have both peaceful, winged and mutually aggressive ‘ergatoid’ males. Using microsatellite analysis, we investigated the genetic structure of 21 colonies from three different locations as well as the parentage of sexuals of two colonies of C. elegans. We show that C. elegans is strictly monogynous, and that its nests can contain foreign sexuals. The presence of alien sexuals inside ant nests is described for the first time and probably counteracts inbreeding resulting from matings between siblings. In the laboratory, aggression tests showed that workers only allow alien males to enter their nests, while all winged female sexuals attempting to enter were attacked. Nevertheless, the presence of alien female sexuals in nests in the field seems to result from active carrying behaviour by workers during the reproductive period.
CS 364 A : Algorithmic Game Theory Lecture # 13 : Potential Games ; A Hierarchy of Equilibria ∗

Last lecture we proved that every pure Nash equilibrium of an atomic selfish routing game with affine cost functions (of the form ce(x) = aex + be with ae, be ≥ 0) has cost at most 5 2 times that of an optimal outcome, and that this bound is tight in the worst case. There can be multiple pure Nash equilibria in such a game, and this bound of 5 2 applies to all of them. But how do we know that there is at least one? After all, there are plenty of games like Rock-Paper-Scissors that possess no pure Nash equilibrium. How do we know that our price of anarchy (POA) guarantee is not vacuous? This lecture introduces basic definitions of and questions about several equilibrium concepts. When do they exist? When is computing one computationally tractable? Why should we prefer one equilibrium concept over another?
Assess the Quality Of Life of Nurses Working In Shift Duties In Public Sector Hospital

Working in shifts is a prerequisite for nurses to help patients, jeopardizing their own physical and mental health as well as having an influence on their social and family life, consequently leading to a lack of attentiveness and subpar job performance, putting the patients' lives in peril. This study aims to assess the nurses’ quality of life working in shift duties. 255 nurses participated in a cross-sectional analytical study of a public sector hospital. Participants were selected through consecutive non-probability sampling techniques. Data was collected using demographic characteristics and the WHO SF36 questionnaire and analyzed through SPSS version 21.0. The mean age was 31.6 ±7.3 years with the majority of 67.8% female nurses. The mean experience was 8.7 ± 6.4 years, duty hours 39 ± 11.7 hours, and 31% were working night shifts. Comparing the shift duties with all seven health parameters of quality of life, and general health, social activities energy and emotions were found statistically significant P<0.05. Compared with experience, only general health was found to have a statistically significant association at P<0.005 whereas no other parameter was found to have any association. Age and marital status showed a statistically significant association moreover, education also had an association with 3 health parameters. However, the experience was found to have a statistically significant association with mental health (P<0.007). The current study concluded that the health and quality of life of nurses are negatively impacted by the stress of their shift work. It may also cast a shadow over the delivery of care, which may be one of the variables influencing patients' outcomes.
Metal-catalyzed epoxidations of alkenes with hydrogen peroxide.

3. Soluble Metal Oxides 2459 3.1. Polyoxometalates 2459 3.2. Peroxotungstates 2459 3.3. Peroxomolybdates 2460 3.4. Methyltrioxorhenium 2461 3.5. Other Metal Oxides 2461 4. Metal Oxides Generated in Situ 2461 4.1. Selenium and Arsenic Compounds 2461 4.2. Simple Metal Salts 2462 5. Coordination Complexes 2463 5.1. Manganese Porphyrins 2463 5.2. Iron Porphyrins 2464 5.3. Manganese Salen Complexes 2466 5.4. 1,4,7-Triazacyclononane (TACN) Complexes 2466 5.5. Iron and Manganese Pyridyl-Amine Complexes 2468
Research on Robot Grasping Strategy Based on Deep Learning and K-Means Algorithm

In order to effectively improve the robot grasping accuracy and sorting efficiency of the valve body on the butterfly valve automated assembly line, a butterfly valve body grasping strategy based on machine vision and YOLOv3 deep learning algorithm is proposed. Based on the YOLOv3 algorithm, the visual inspection model of the valve body is generated. According to the depth image information and distance between the camera and the valve body is obtained by using the K-Means++ clustering algorithm, then the pose of robot grasping the valve body are estimated. Finally by using the hand-eye calibration method, it obtains the mapping matrix between the valve body coordinate system and the camera coordinate system. Experiments are carried out rapid self-identification detection, positioning and grasping for the butterfly valve body being arbitrarily placed, they prove that the strategies effectively avoided the influence of uncertain factors such as the position and posture of the butterfly valve body in the actual working environment, and the grasping accuracy is high. It provides a reference for the efficient and automated sorting of components in automated production lines.
Economics of forest and forest carbon projects. Translating lessons learned into national REDD+ implementation

REDD+ implementation DTU Orbit (16/12/2018) Economics of forest and forest carbon projects. Translating lessons learned into national REDD+ implementation The financial implications of implementing a new forest management paradigm have not been well understood and have often been underestimated. Resource needs for e.g., stakeholder consultation, capacity building and addressing the political economy are seldom fully accounted for in the resource needs estimates put forward in connection to REDD+. This report investigates the economics of implementing forest and REDD+ projects through eight case studies from Africa, Latin America and Asia, analyzing real forest and REDD+ investments. The report is part of efforts to share financial experiences and lessons learned with policymakers, project developers and stakeholders, with the objective to inform forest project and strategy development. It presents experiences and advice on the risks, costs and revenues of forest projects, thereby informing not only the development of future REDD+ initiatives but also the testing of advanced market commitments as a finance option for sustainable forest management. The findings in the report underline the fact that only through sound and transparent financial information will forest projects and national forest initiatives become interesting for private financial institutions and comparable with other investment opportunities. It is therefore important to include robust analysis of the operations business case and its financial attractiveness to commercial investors, early in the design process. As for the economics of forest and forest carbon projects, it appears that REDD+ payments alone, especially at current prices, will not deliver the revenues that cover all expenses of transparent and long-term mitigation of forest carbon emissions. Instead the findings underline the importance of building up forest operations which effectively manages risk and delivers several revenue streams. These findings are aligned with the advocacy efforts of UNEP and the UN-REDD Programme on multiple benefits and the combination of various funding and revenue streams. Only through this wider approach can our management and utilization of forest resources be ensured to deliver long-term benefits to national development, local livelihoods and climate change adaptation and mitigation efforts. A transformation towards a low carbon green economy is also likely to present new market opportunities. While building on the traditional forest revenue streams (trade in timber and non-timber forest products) the emerging trade opportunities should also be included in the business model. As the demand for traditional forest goods is increasing and a green economy creates demands for new services, goods and solutions, it is foreseeable that with the right enabling conditions from the public sector, much more private sector investment will be directed towards forests in order to capitalize on a green economy.
Exploring visual feedback of change conflict in a distributed 3D environment

Teams that are geographically distributed often share information both in real-time and asynchronously. When such sharing is through groupware, change conflicts can arise when people pursue parallel and competing actions on the same information. This leads to problems in how the systems and its users maintain a consistent view of shared information across distance and time. We explore change awareness of conflicts in a three-dimensional distributed shared space. Our user study compares the use of visual feedback to an optimistic concurrency control strategy for both synchronous and asynchronous distributed groupware. Our feedback provides a means for synchronous users to recognize and resolve real-time changes, and for asynchronous users to view and resolve changes when switching from an offline to online mode of work. Results of our study suggest that the visual feedback serves as a useful feedthrough mechanism in the synchronous case, but that asynchronous users may be overwhelmed by the quantity of changes if they come online after many changes have been made.
A Case of Immunoglobulin G4-Related Disease Presenting as a Pleural Mass

Immunoglobulin G4 (IgG4)-related disease is a newly recognized condition characterized by fibroinflammatory lesions with dense lymphoplasmacytic infiltration, storiform-type fibrosis and obliterative phlebitis. The pathogenesis is not fully understood but multiple immune-mediated mechanisms are believed to contribute. This rare disease can involve various organs and pleural involvement is even rarer. We report a case of IgG4-related disease involving pleura. A 66-year-old man presented with cough and sputum production for a week. Chest radiography revealed consolidation and a pleural mass at right hemithorax. Treatment with antibiotics resolved the consolidation and respiratory symptoms disappeared, but the pleural mass was unchanged. Video-assisted thoracoscopic surgery was performed. Histopathology revealed dense lymphoplasmacytic infiltration and storiform fibrosis with numerous IgG4-bearing plasma cells. The serum IgG4 level was also elevated. Further examination ruled out the involvement of any other organ. The patient was discharged without further treatment and there is no evidence of recurrence to date.
Wavelet-Based Multiresolution Matching for Content-Based Image Retrieval

In this paper, a content-based image retrieval method based on the wavelet transform is proposed. In the image database establishing phase, each image is first transformed from the standard RGB color space to the YUV space; then Y component of the image is further transformed to the wavelet domain. After the kth level wavelet decomposition, a series of low-pass subimages with different resolution level are obtained. In the image retrieving phase, the system compares these subimages of the query image and those of the images in the database and find out good matches. Through the combination of the features with different resolution level, we can not only obtain the better precision rate but also the good reduction rate. We have performed experiments on a thousand images database and the results support our approach.
Vitamin D-rich marine Inuit diet and markers of inflammation – a population-based survey in Greenland

Abstract The traditional Inuit diet in Greenland consists mainly of fish and marine mammals, rich in vitamin D. Vitamin D has anti-inflammatory capacity but markers of inflammation have been found to be high in Inuit living on a marine diet. Yet, the effect of vitamin D on inflammation in Inuit remains unsettled. This led us to investigate the association between vitamin D and markers of inflammation in a population with a high intake of a marine diet. We studied 535 Inuit and non-Inuit living in West and East Greenland. Information concerning dietary habits was obtained by interview-based FFQ. Blood samples were drawn for analysis of 25-hydroxyvitamin D, high-sensitivity C-reactive protein (hsCRP) and chitinase-3-like protein 1(YKL-40). Participants were divided into three groups based on degree of intake of the traditional Inuit diet. The diet groups (Inuit diet/mixed diet/imported foods) were associated with vitamin D levels in serum (74·2, 69·8 and 52·9 nm; P < 0·001), hsCRP (1·6, 1·4 and 1·3 mg/l; P = 0·002) and YKL-40 (130, 95 and 61 ng/ml; P < 0·001), respectively. YKL-40 level decreased with rising vitamin D level in Inuit (Inuit diet P = 0·002; mixed diet P = 0·011). YKL-40 was lower in groups with higher vitamin D levels after adjusting for other factors known to influence inflammation (P < 0·001). This was not seen for hsCRP. In conclusion, vitamin D and markers of inflammation vary in parallel with the intake of the marine Inuit diet. Vitamin D levels were inversely associated with YKL-40 levels, but no association with hsCRP was found. The hypothesised anti-inflammatory effect of vitamin D was not supported. Other factors in the marine diet may be speculated to influence inflammation.
A Weakly Supervised Approach to Train Temporal Relation Classifiers and Acquire Regular Event Pairs Simultaneously

Capabilities of detecting temporal and causal relations between two events can benefit many applications. Most of existing temporal relation classifiers were trained in a supervised manner. Instead, we explore the observation that regular event pairs show a consistent temporal relation despite of their various contexts and these rich contexts can be used to train a contextual temporal relation classifier, which can further recognize new temporal relation contexts and identify new regular event pairs. We focus on detecting after and before temporal relations and design a weakly supervised learning approach that extracts thousands of regular event pairs and learns a contextual temporal relation classifier simultaneously. Evaluation shows that the acquired regular event pairs are of high quality and contain rich commonsense knowledge and domain specific knowledge. In addition, the weakly supervised trained temporal relation classifier achieves comparable performance with the state-of-the-art supervised systems.
Design of Aging-Robust Clonable PUF Using an Insulator-Based ReRAM for Organic Circuits

We enhance the robustness of organic thin-film transistor (OTFT)-based physically unclonable functions (PUFs) against unstable output responses that originate from OTFT characteristic degradation. The proposed PUF incorporates a new resistive random access memory (ReRAM) constructed from metal-oxide thin films, enabling both ReRAM and OTFT components to be simultaneously fabricated using common materials and processes. The device combinations facilitate the efficient design of clonable PUF (CPUF) circuits with equivalent response outputs. Evaluations using measurements and simulations validate the successful operation of the CPUF.
EFSM-based model-driven approach to concolic testing of system-level design

State-of-the-art approaches for testing of system-level design of embedded systems generally work at source-code level, thus they require an implementation of the system to be tested. For this reason, they cannot be applied in the context of model-driven design, where code is available only at end of the design process. Moreover, traditional approaches based on combined concrete and symbolic execution (concolic) suffer two main drawbacks: they are limited in width and depth of the search and not corner-cases oriented. To address such limitations, this paper presents a concolic testing approach for model-driven design of embedded systems. It explores a model of the system, i.e., the extended finite state machine (EFSM), and it relies on weight-oriented analysis of the EFSM paths to achieve high controllability of EFSM transitions, by interleaving longrange concrete approach with symbolic multi-level backjumping strategy. The experimental evaluation on several case studies demonstrates the competitiveness of the proposed approach, which achieves higher transition and instruction coverage than other approaches in significantly reduced time.
Investigating Layer-2 Scalability Solutions for Blockchain Applications

Scalability is one of the trilemma of blockchain technology that hinders its adoption for large-scale decentralized applications (dApps). Researchers have proposed several layer-1 and layer-2 solutions to address the issue. This paper focuses on layer-2 solutions or protocols operating on top of the primary blockchain to enhance scalability. Previous works surveying these solutions mainly focused on a particular layer-2 solution, like rollup, or a specific application, such as smart manufacturing. However, in this paper, we present a comprehensive analysis of layer-2 scalability solutions, such as state channels, side-chain, and rollup, from the perspectives of various functional requirements of block chain applications. More precisely, the goal is to evaluate the applicability of the layer-2 scalability solutions in terms of the application patterns that depict the transactional dependencies, interoperability, decentralization, and security. To further illustrate these features, the paper evaluates the applicability of the layer-2 solutions on the case studies of major blockchain applications, including supply chain management and healthcare. Our analysis suggests that in terms of throughput, application pattern is the most crucial aspect in selecting the scaling solutions, in conjecture with other features as per the application demand.
Undoing CRDT Operations Automatically

In a distributed replicated data system, Conflict-free Replicated Data Types (CRDTs) keep data replicas consistent on different nodes, while providing intuitive programming abstractions for accessing and modifying the replicas. Due to user errors, program bugs, or hardware malfunctions, a CRDT can be updated incorrectly, so the effect of the executed CRDT update operations needs to be undone. However, because CRDT libraries rarely include the undo capability, adding it requires modifying source code by hand, a task that is hard to accomplish in a modular and reusable fashion. As a result, programmers end up adding this advanced functionality in an ad-hoc fashion, with the resulting code being hard to understand, maintain, and reuse. To address this problem, this paper presents AUTO-UNDO, an automatic approach that generates and actuates undo functionality for existing CRDT libraries, based on simple configurations and without modifying the library code by hand. The configurations specify which CRDT operations undo each other and the conditions that trigger the execution of undo procedures. Based on the configuration, AUTO-UNDO generates and actuates a sequence of update operations that undo the specified updates on a given replica. We have implemented and evaluated AUTO-UNDO in JavaScript, a popular CRDT language, demonstrating our approach’s effectiveness, flexibility, and efficiency. Our experiences show that AUTO-UNDO effectively provides the undo capability for CRDT-based applications, thus streamlining the complexity of adding features to distributed programming frameworks.
Pororobot : Child Tutoring Robot for English Education

The recent success of machine learning has lead to advancements in robot intelligence and human-robot interaction. It is reported that robots can well understand visual scene information and describe the scenes in language using computer vision and natural language processing methods. Image Question-Answering (QA) systems can be used for human-robot interaction. However, to achieve human-level artificial intelligence based on lifelong learning, a model must deal with real-world environments including dynamic, uncertain, and asynchronous properties based on lifelong learning. In this paper, we propose a prototype system for a video QA robot "Pororobot". The system uses the state-of-the-art machine learning system using dual memory model for implementing robot intelligence. In our scenario, a robot and a child plays a video QA game. Here we demonstrate preliminary results of our system. Keywords—videoQA; tutoring robot; human-robot interaction; robot intelligence; machine learning;