Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural network based approach for time to crash prediction to cope with software aging

Recent studies have shown that software is one of the main reasons for computer systems unavailability. A growing accumulation of software errors with time causes a phenomenon called software aging. This phenomenon can result in system performance degradation and eventually system hang/crash. To cope with software aging, software rejuvenation has been proposed. Software rejuvenation is a proactive technique which leads to removing the accumulated software errors by stopping the system, cleaning up its internal state, and resuming its normal operation. One of the main challenges of software rejuvenation is accurately predicting the time to crash due to aging factors such as memory leaks. In this paper, different machine learning techniques are compared to accurately predict the software time to crash under different aging scenarios. Finally, by comparing the accuracy of different techniques, it can be concluded that the multilayer perceptron neural network has the highest prediction accuracy among all techniques studied.
Characterization of sulfoxaflor resistance in the brown planthopper, Nilaparvata lugens (Stål).

BACKGROUND Sulfoxaflor is a new insecticide for controlling Nilaparvata lugens in the field. This study was conducted to investigate the risk of resistance development, the cross-resistance spectrum and the mechanisms of sulfoxaflor resistance in N. lugens. RESULTS A sulfoxaflor-resistant strain was obtained from a field population by successive selection with sulfoxaflor for 39 generations in the laboratory. Sulfoxaflor-resistant populations showed significant levels of cross-resistance to dinotefuran, nitenpyram, thiamethoxam, clothianidin, imidacloprid and cycloxaprid. However, they exhibited only minor or no cross-resistance to isoprocarb, etofenprox, chlorpyrifos, triflumezopyrim and buprofezin. Sulfoxaflor was synergized by the inhibitor piperonyl butoxide (PBO) in the sulfoxaflor-resistant strain (SFX-SEL) with 2.69-fold relative synergistic ratios compared with the unselected strain (UNSEL). Compared with UNSEL, the P450 enzyme activity of SFX-SEL was increased 3.50 times, and eight P450 genes were upregulated more than 2.0-fold in SFX-SEL. RNAi reduced the expression of CYP6ER1 (36.87-fold change) and significantly enhanced the susceptibility of SFX-SEL to sulfoxaflor. CONCLUSION Resistance development and cross-resistance risk of sulfoxaflor-resistance in N. lugens is evident. The enhanced detoxification of P450 enzymes caused by upregulation of several P450 genes is considered to be the metabolic resistance mechanism. These results suggest that CYP6ER1 might play an important role in sulfoxaflor resistance in N. lugens. © 2018 Society of Chemical Industry.
Lie bodies based 3D shape morphing and interpolation

Morphing and Interpolation algorithms aim to support the animator by automating animation in two scenarios. While morphing algorithms generate intermediate objects given two (or more) objects belonging to different classes, interpolation generates intermediate objects given two deformations of the same object. In this paper, we propose a framework for morphing and interpolation based on the Lie Bodies representation of triangular meshes. Without any physics based constraints on allowable deformations, the Lie group of transformations involved are able to handle both, morphing as well as interpolation. The Lie Bodies framework is known to fail in case of large deformations. In such cases, we propose to segment the mesh and use the Lie Bodies framework on individual components. Our segmentation scheme is based on detecting parts of meshes undergoing large deformations. The Lie bodies framework is thus able to handle large deformations, is able to produce any intermediate interpolation result directly, and is efficient due to the independent treatment of triangles in the mesh. We provide several interpolation and morphing results in support of our framework.
Mechanical loading mitigates osteoarthritis symptoms by regulating endoplasmic reticulum stress and autophagy

Osteoarthritis (OA) is a disease characterized by cartilage damage and abnormal remodeling of subchondral bone. Our previous study showed that in the early stage of OA, knee loading exerts protective effects by suppressing osteoclastogenesis through Wnt signaling, but little is known about loading effects at the late OA stage. Endoplasmic reticulum (ER) stress and autophagy are known to be involved in the late OA stage. We determined the effects of mechanical loading on ER stress and autophagy in OA mice. One hundred seventy‐four mice were used for a surgery‐induced OA model. In the first set of experiments, 60 mice were devoted to evaluation of the role of ER stress and autophagy in the development of OA. In the second set, 114 mice were used to assess the effect of knee loading on OA. Histologic, cellular, microcomputed tomography, and electron microscopic analyses were performed to evaluate morphologic changes, ER stress, and autophagy. Mechanical loading increased phosphorylation of eukaryotic translation initiation factor 2α(eIF2α) and regulated expressions of autophagy markers LC3II/I and p62. Osteoarihritic mice also exhibited an elevated ratio of calcified cartilage to total articular cartilage (CC/TAC), and synovial hyperplasia with increased lining cells was found. At the early disease stage, subchondral bone plate thinning and reduced subchondral bone volume fraction (B.Ar/T.Ar) were observed. At the late disease stages, subchondral bone plate thickened concomitant with increased B.Ar/T.Ar. Mice subjected to mechanical loading exhibited resilience to cartilage destruction and a correspondingly reduced Osteoarthritis Research Society International score at 4 and 8 wk, as well as a decrease in synovitis and CC/TAC. While chondrocyte numbers in the OA group was notably decreased, mechanical loading restored chondrogenic differentiation. These results demonstrate that mechanical loading can retard the pathologic progression of OA at its early and late stages. The observed effects of loading are associated with the regulations of ER stress and autophagy. —Zheng, W. , Li, X. , Liu, D. , Li, J., Yang, S. , Gao, Z. , Wang, Z. , Yokota, H. , Zhang, P. Mechanical loading mitigates osteoarthritis symptoms by regulating endoplasmic reticulum stress and autophagy. FASEB J. 33,4077–4088 (2019). www.fasebj. org
Building resilience in health visitor students for coping with adversity in practice

Health Visiting (the specialism of public health nursing focusing on families and children) has been under threat over the last decade, with a considerable reduction in staff establishment. This has contributed to discrepancies in practice between broad public health standards, against which health visitor education is validated, and the reality of practice that is dominated by safeguarding (child protection) work. Negative workplace experiences have coincided with this reduction in staff numbers, include growing workloads, diminishing resources, and significant organisational change. Encountering such adversity in practice can impact negatively on the functioning and wellbeing of a newly qualified health visitor.
Interactive viewing of large geometric databases using multiprocessor graphics workstations

In many visualization applications as well as computer graphics we need to consider large amounts of objects in order to render one image. In many cases rendering can be preceded by a culling phase which employs simple mechanisms to reject most of the objects. As a result, only a very small portion of the model has to actually go through the time consuming process of hidden object removal. We report on such a culling mechanism that is based on regular space subdivision into cells. These cells are classified into opaque and transparent and a cell-to-cell visibility algorithm determines, for a given cell, which other cells are potentially visible. Only the objects in the potentially visible set of cells are actually submitted to the hidden object removal algorithm. We report on the 2D implementation of the algorithm and its performance for walkthrough the interior of capillary blood vessels. We propose several improvements to our methods and suggest a simple way to extend it to 3D.
Hepatic Metabolic Profile Reveals the Adaptive Mechanisms of Ewes to Severe Undernutrition during Late Gestation

The mechanisms underlying the adaption of liver metabolism to the undernutrition in ewes during late gestation remain unclear. This research aimed to explore the adaptive mechanisms of liver metabolism by hepatic metabolome analysis in pregnant ewes to the negative energy balance induced by severe feed restriction. Twenty ewes carrying multiple fetuses and gestating for 115 days were fed normally or restricted to a 30% feed level (10 ewes in each group) for 15 days. All ewes were sacrificed and hepatic samples were collected and analyzed by liquid chromatography-mass spectrometry. Both the principal components analysis and partial least squares of discriminant analysis of hepatic metabolites showed the clear separation between ewes in the control and severely feed-restricted groups. The metabolic profile demonstrated that the proportions of differential metabolites between the two groups in fatty acids and lipids, organic acids, and amino acids and derivatives were 61.11%, 16.67%, and 11.11%, respectively. Enriched pathways of differential metabolites were mainly involved in fatty acids and amino acids metabolism and biosynthesis. Correlation networks of differential metabolites revealed that general metabolic pattern was changed apparently and mainly based on fatty acids and lipids in the livers of feed-restricted ewes. The accumulation and oxidation of long-chain fatty acids were intensified in the livers of feed-restricted ewes, while those of medium-chain fatty acids were the opposite. In general, severe feed restriction significantly affected the levels of hepatic metabolites and altered the overall metabolic pattern. Furthermore, fatty acids oxidation as well as the utilization of amino acids and organic acids were intensified to adapt to the negative energy balance during late gestation.
Novel PEGylated Liposomes Enhance Immunostimulating Activity of isRNA

The performance of cationic liposomes for delivery of therapeutic nucleic acids in vivo can be improved and specifically tailored to certain types of cargo and target cells by incorporation of PEG-containing lipoconjugates in the cationic liposome’s composition. Here, we report on the synthesis of novel PEG-containing lipoconjugates with molecular masses of PEG 800, 1500 and 2000 Da. PEG-containing lipoconjugates were used as one of the components in liposome preparation with the polycationic amphiphile 1,26-bis(cholest-5-en-3β-yloxycarbonylamino)-7,11,16,20-tetra-azahexacosan tetrahydrochloride (2X3) and the lipid-helper dioleoylphosphatidylethanolamine (DOPE). We demonstrate that increasing the length of the PEG chain reduces the transfection activity of liposomes in vitro, but improves the biodistribution, increases the circulation time in the bloodstream and enhances the interferon-inducing activity of immunostimulating RNA in vivo.
Potential limits to the benefits of admixture during biological invasion

Species introductions often bring together genetically divergent source populations, resulting in genetic admixture. This geographic reshuffling of diversity has the potential to generate favourable new genetic combinations, facilitating the establishment and invasive spread of introduced populations. Observational support for the superior performance of admixed introductions has been mixed, however, and the broad importance of admixture to invasion questioned. Under most underlying mechanisms, admixture's benefits should be expected to increase with greater divergence among and lower genetic diversity within source populations, though these effects have not been quantified in invaders. We experimentally crossed source populations differing in divergence in the invasive plant Centaurea solstitialis. Crosses resulted in many positive (heterotic) interactions, but fitness benefits declined and were ultimately negative at high source divergence, with patterns suggesting cytonuclear epistasis. We explored the literature to assess whether such negative epistatic interactions might be impeding admixture at high source population divergence. Admixed introductions reported for plants came from sources with a wide range of genetic variation, but were disproportionately absent where there was high genetic divergence among native populations. We conclude that while admixture is common in species introductions and often happens under conditions expected to be beneficial to invaders, these conditions may be constrained by predictable negative genetic interactions, potentially explaining conflicting evidence for admixture's benefits to invasion.
The Coq proof assistant : reference manual, version 6.1

Coq is a proof assistant based on a higher-order logic allowing powerful definitions of functions. Coq V6.1 is available by anonymous ftp at ftp.inria. fr:/INRIA/Projects/coq/V6.1 and ftp.ens-lyon.fr:/pub/LIP/COQ/V6.1
Prognosis of Venous Thromboembolic Complications after Hip Replacement on the Background of Modern Thromboprophylaxis

The objective of the study is to determine sufficient Thrombogenic Risk (TR) factors of post-operative Venous Thromboembolic Complications (VTEC) development on the background of modern thromboprophylaxis including non-pharmacological and pharmacological implications. Materials and methods The observation data of 351 patients who underwent primary total Hip Replacement (HR) are presented in the article. The interview of patients and the study of medical documentation were carried out. Some laboratory (as well as genetic) analysis methods were used to reveal the potential TR factors. Results Six TR factors out of 26 were determined to increase the possibility of VTEC occurrence significantly. They are type 2 diabetes mellitus (odd ratio OR 5.6; 95% confidence interval CI 1.8-17.0), female sex (OR 4.6; CI 1.5-13.6), low level of physical activity (OR 4.4; CI 1.7-11.1), age over 60 (OR 4.3; CI 1.8-10.6), increased level of D-dimers before operation (OR 3.5; CI 1.4-8.9) and varicose disease of the lower extremities (OR 3.4; CI 1.5-7.7). Conclusion Revealed TR factors allow for determining the group at high risk of VTEC after HR and developing approaches to the individual thromboprophylaxis among these patients.
Advanced Objective Metric for Image Quality Assessment

Image Quality Assessment (IQA) goal is to use computational models to measure the image quality consistently with subjective evaluations. In this paper, a peculiar feature-similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) perceives an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimension less measure of significance of a local structure, is used as the primary feature. Considering that PC is unaffected by contrast, while the contrast information does affect the HVS’ perception of image quality, the image gradient magnitude is employed as the secondary feature in FSIM. After obtaining the local quality map, we use PC again as a weighting function to derive single quality score. Extensive experiments performed on TID2008, a widely using bench mark IQA database demonstrated that FSIM can achieve much higher consistency with the subjective evaluations than state-ofthe art IQA metrics.
System for preventing loss of replay desire in games by guiding the user to voluntary leaving from and returning to the game sessions

We have conducted a research on the time-loss experience during game play. From the study, we propose system design for preventing loss of replay desire in games by guiding voluntary leave. Experiments have shown the effectiveness of the proposed system. In the first step of this study, we have conducted a preliminary experiment for finding whether increasing cognitive workload can guide voluntary leave. The results indicated that adjusting difficulty level by modifications to the appearances of the game objects makes a difference in the cognitive workload.
Automated Plant Count Using Unsupervised Classification on UAV Acquired Imagery

Precision farming is a farm management technique where in observing, measuring and responding is carried out using the latest technology. Its end output is to preserve the resources used in farming while optimizing on the returns. Previously satellites were used for this purpose and it had a lot of drawbacks of weather anomalies, low resolution and lack of real time data. This entire process can be done using an UAV system. In this study we focus on optimizing the time taken and maintain the accuracy of an industrial process of counting plants. Supervised classification is the most preferred method of classification as there is control over the classes and its well-established accuracy. But the main drawback is time taken in training the classifier. As there are more than hundreds of farms plots the same signature file cannot be used as there will be variation in the lighting conditions and shadows patterns. To solve this, we have used iso-cluster unsupervised classification and grouped the classes into plants and non-plant region. The accuracy stood at 95.4% compared to the accuracy of 97.8% obtained from supervised classification. This was within the 5% inaccuracy limit specified by the client. The major gain was the reduction of the time spent on the process. The supervised classification method took about 35 minutes whereas the unsupervised and grouping method took 10 minutes to complete the process for a 1.5 acres farm plot. This is a reduction of 70% of the time taken which is a very significant when plant counting has to be done for hundreds of plots.
Evaluating the Distribution of Students' Contributions in Theorizing: Idea Evenness in Knowledge Building Communities

Asymmetric collaboration in CSCL environments may lead to exclusion of some students and less idea diversity than needed for a productive, inclusive community. To uncover the degree of asymmetric collaboration, the social entropy index (the sum of relative participation proportions of each individual) was adopted in some studies, but only quantitative indicators (e.g., the number of characters) were considered in the measurement. In this study, we define participation evenness plus the dimension of the quality of students’ notes as “idea evenness”. Adopting the entropy and using the depth of understanding within students’ theorizing notes as the parameter, we analyzed the idea evenness of five Knowledge Building communities. We found that the idea evenness values are high in four of the communities and can reflect the different distributions of students’ depth of understanding in different communities. The results indicate that students participated in theorizing evenly in most knowledge building communities.
Machine Learning Based Localization in Large-Scale Wireless Sensor Networks

The rapid proliferation of wireless sensor networks over the past few years has posed some serious technical challenges to researchers. The primary function of a multi-hop wireless sensor network (WSN) is to collect and forward sensor data towards the destination node. However, for many applications, the knowledge of the location of sensor nodes is crucial for meaningful interpretation of the sensor data. Localization refers to the process of estimating the location of sensor nodes in a WSN. Self-localization is required in large wireless sensor networks where these nodes cannot be manually positioned. Traditional methods iteratively localize these nodes by using triangulation. However, the inherent instability in wireless signals introduces an error, however minute it might be, in the estimated position of the target node. This results in the embedded error propagating and magnifying rapidly. Machine learning based localizing algorithms for large wireless sensor networks do not function in an iterative manner. In this paper, we investigate the suitability of some of these algorithms while exploring different trade-offs. Specifically, we first formulate a novel way of defining multiple feature vectors for mapping the localizing problem onto different machine learning models. As opposed to treating the localization as a classification problem, as done in the most of the reported work, we treat it as a regression problem. We have studied the impact of varying network parameters, such as network size, anchor population, transmitted signal power, and wireless channel quality, on the localizing accuracy of these models. We have also studied the impact of deploying the anchor nodes in a grid rather than placing these nodes randomly in the deployment area. Our results have revealed interesting insights while using the multivariate regression model and support vector machine (SVM) regression model with radial basis function (RBF) kernel.
Unconventional Conceptions : Family Planning in Lesbian-Headed Families Created by Donor Insemination

This study aimed to systematically describe the decision-making phase of family formation in German lesbians planning to parent via donor insemination, to assess the issues pertinent to each mother role and those involved in donor type choice using a retrospective, structured questionnaire. Data was collected from 105 self-identified lesbian women, 55 of whom were birthmothers and 50 of whom were social mothers. The process of planning a lesbian-headed family created by donor insemination is, in many ways, unique to this family form. First of all, each woman has to successfully come-out and develop a positive self-identity as a lesbian and develop a committed lesbian relationship (in the case of planning a two-parent family). The decision-making phase of family building, which took 2 years on average, includes working through issues that are common to the decision of parenting shared by heterosexual couples as well as lesbian specific issues. The following lesbian specific aspects of family planning were identified in this study. Lesbian women must actively confront (internalized) societal taboos of lesbians and gays having children and develop strategies for handling homophobia. They must also develop a positive attitude towards a lesbian-headed family. In the absence of or outside of legally sanctioned relationships, women planning to parent in lesbian relationships consider the event of relationship dissolution or death of the birthmother for both the social mother and the child. The lesbian couple also decides what model of family they intend to build. In the absence of traditionally defined roles, the lesbian couple must negotiate and define the birth and social mother roles for their family. In the absence of terminology for the birth and social mothers, the lesbian couple must decide what they want the child to call them. Lesbian women must decide on the method by which they want to become parents. If a lesbian couple decides to become parents by conception, then they must negotiate which of the women will conceive (first). Another decision to be made regards that of donor type choice, i.e. how to get sperm and to what degree the male it stems from should be known to and involved in the life of the lesbian couple and child. Prospective lesbian parents must decide if, to what degree and in what way they intend to include men in their child’s lives. In contrast to heterosexual family planning, lesbian prospective parents are choosing a non-normative path and, correspondingly, are faced with the issues of resources, challenges and eliciting support for their family decisions. 104 of the 105 participants planned a two-parent family with their lesbian partner. The allocation of mother role between the two women occurred via the decision over which