Miracle-dz/UniFAR-FTUs huggingface dataset:
Pathogenicity of Nosema sp. (Microsporidia) in the Diamondback Moth, Plutella xylostella (Lepidoptera: Plutellidae)

Biological control using pathogenic microsporidia could be an alternative to chemical control of the diamondback moth (DBM) Plutella xylostella (Lepidoptera: Plutellidae). The microsporidium Nosema bombycis (NB) is one of the numerous pathogens that can be used in the Integrated Pest Management (IPM) of DBM. However, its pathogenicity or effectiveness can be influenced by various factors, particularly temperature. This study was therefore conducted to investigate the effect of temperature on NB infection of DBM larvae. Second-instar larvae at different doses (spore concentration: 0, 1×102,1×103,1×104, and 1×105) at 15°, 20°, 25°, 30° and 35°C and a relative humidity(RH) of 65% and light dark cycle (L:D) of 12∶12. Larval mortality was recorded at 24 h intervals until the larvae had either died or pupated. The results showed that the spore concentration had a significant negative effect on larval survival at all temperatures, although this effect was more pronounced (92%) at 35°C compared with that at 20 and 30°C (≃50%) and 25°C (26%). Histological observations showed that Nosema preferentially infected the adipose tissue and epithelial cells of the midgut, resulting in marked vacuolization of the cytoplasm. These findings suggest that Nosema damaged the midgut epithelial cells. Our results suggest that Nosema had a direct adverse effect on DBM, and could be utilized as an important biopesticide alternative to chemical insecticides in IPM.
Angiotensin Receptor–Neprilysin Inhibition

The novel combination sacubitril/valsartan represents a new therapeutic approach in the management of heart failure. With the simultaneous blockage of the enzyme neprilysin (by sacubitril) and angiotensin II receptors (by valsartan), this combination reduces the degradation of natriuretic peptides and other counterregulatory peptide systems while avoiding the deleterious effect of angiotensin II receptors activation and thereby encompasses a beneficial impact of 2 important neurohormonal pathways activated in heart failure. As opposed to previously tested neprilysin inhibitors, sacubitril/valsartan represents a more effective method in reducing morbidity and mortality in heart failure, while preserving a safety profile comparable to well-established, standard, angiotensin-converting enzyme inhibitor’s therapy.
Molecular Spectra and Molecular Structure

THOSE who contributed to the recent Faraday Discussion on molecular spectra and molecular structure have now sent their written versions to the secretary for publication. Instead of the report we gave of Prof. Barker's explanation of the double Q branch of ammonia at 10.3 µand 10.7 µ (NATURE, Oct. 12, p. 587), we should like to substitute Prof. Barker's own written version:
First approximation to congenital malformation rates in embryos and hatchlings of sea turtles.

BACKGROUND Congenital malformations in sea turtles have been considered sporadical. Research carried out in the Mexican Pacific revealed high levels of congenital malformations in the olive ridley, but little or no information is available for other species. We present results from analyses of external congenital malformations in olive ridley, green, and hawskbill sea turtles from Mexican rookeries on the Pacific coast and Gulf of Mexico. METHODS We examined 150 green and hawksbill nests and 209 olive ridley nests during the 2010 and 2012 nesting seasons, respectively. Olive ridley eggs were transferred to a hatchery and incubated in styrofoam boxes. Nests from the other two species were left in situ. Number of eggs, live and dead hatchlings, and eggs with or without embryonic development were registered. Malformation frequency was evaluated with indices of prevalence and severity. RESULTS Mortality levels, prevalence and severity were higher in olive ridley than in hawksbill and green sea turtles. Sixty-three types of congenital malformations were observed in embryos, and dead or live hatchlings. Of these, 38 are new reports; 35 for wild sea turtles, three for vertebrates. Thirty-one types were found in hawksbill, 23 in green, and 59 in olive ridley. The head region showed a higher number of malformation types. Malformation levels in the olive ridley were higher than previously reported. CONCLUSION Olive ridleys seem more prone to the occurrence of congenital malformations than the other two species. Whether the observed malformation levels are normal or represent a health problem cannot be currently ascertained without long-term assessments.
Markov random field segmentation for industrial computed tomography with metal artefacts

X-ray Computed Tomography (XCT) has become an important tool for industrial measurement and quality control through its ability to measure internal structures and volumetric defects. Segmentation of constituent materials in the volume acquired through XCT is one of the most critical factors that influence its robustness and repeatability. Highly attenuating materials such as steel can introduce artefacts in CT images that adversely affect the segmentation process, and results in large errors during quantification. This paper presents a Markov Random Field (MRF) segmentation method as a suitable approach for industrial samples with metal artefacts. The advantages of employing the MRF segmentation method are shown in comparison with Otsu thresholding on CT data from two industrial objects.
Does Worksite Culture of Health (CoH) Matter to Employees? Empirical Evidence Using Job-Related Metrics

Objectives: This study examines the relationships between the workplace culture of health (CoH), job satisfaction, and turnover intention. We also examined the moderating effect of job classification. Methods: Structural equation modeling analysis was performed on data from employees of a Korean life insurance company (N = 880). Results: Workplace CoH directly influenced job satisfaction (&bgr; = 0.32; P < 0.001) and was indirectly associated with intention to leave. Job satisfaction was directly associated with intention to leave (&bgr; = −0.42; P < 0.001). The relationship between job satisfaction and intention to leave was stronger for managerial employees than for non-managerial employees. Conclusions: This study showed that a workplace CoH is related to job satisfaction and intention to leave. Supporting health at the workplace has implications beyond health that benefit both employees and the organization.
Incentive Regulation: Evidence From German Electricity Networks

We propose a difference-in-differences (DiD) approach to estimate the impact of incentives on cost reduction. We show theoretically, and estimate empirically, that German electricity distribution system operators (DSOs) pile up more costs in the year used to determine future prices when subject to a lower-powered regulation mechanism. The difference is particularly significant (about 10% of total cost) for firms in the upper quartile of the efficiency distribution, a pattern which is consistent with the pooling of types under the threat of ratcheting. In light of heterogeneous network reinforcement across DSOs due to local wind and solar power expansion, cost inflation will particularly hit already hard-struck DSOs’ customers.
Project ASPIRE: An Interactive, Multimedia Smoking Prevention and Cessation Curriculum for Culturally Diverse High School Students

A Smoking Prevention Interactive Experience (ASPIRE) is an innovative, computer-based smoking prevention and cessation intervention delivered to a culturally diverse population of high school students. Founded in the Transtheoretical Model of Change, five main and two “booster” sessions comprise the interactive intervention. Here we describe the intervention and the baseline characteristics from our study sample of 1,574 10th graders from 16 high schools in Houston, Texas. Environmental and behavioral smoking risk factors were assessed, and the two intervention groups were comparable with respect to most measured variables. The intervention program holds considerable promise in its ability to reduce smoking among teens.
A Radial-Based Mixed sampling method for imbalanced data classification

Mitigating the impact of imbalanced data on classifiers is a challenging task in machine learning. Oversampling, a well-known approach, modifies the data distribution and generates minority class samples to alleviate the influence of imbalanced data on classifiers. However, many existing oversampling methods often involve k-nearest neighbors (KNN) techniques, and changes in the KNN parameter values can lead to noticeable instability. The recently proposed Radial-Based Oversampling (RBO) addresses this issue, but it tends to introduce a significant amount of redundant samples and noise after sampling. In this study, we propose a Radial-Based Mixed Sampling method for imbalanced data classification. Firstly, we employ RBO to oversample a portion of the minority class samples. Then, we use the concept of potential to identify redundant samples and noise in the dataset. Finally, Radial-Based Undersampling (RBU) is employed as a data cleaning strategy to eliminate redundant samples and noise from the majority class samples. Extensive comparative experiments are conducted on 10 imbalanced datasets from KEEL, two different classifiers, and five sampling methods. The results indicate that our approach helps classifiers achieve higher F1 scores and G-means. This suggests a significant improvement in the classifier’s ability to identify minority class samples while considering majority class samples. Additionally, statistical analysis shows higher Friedman Ranking for our method.
Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement

Importance Systematic reviews of diagnostic test accuracy synthesize data from primary diagnostic studies that have evaluated the accuracy of 1 or more index tests against a reference standard, provide estimates of test performance, allow comparisons of the accuracy of different tests, and facilitate the identification of sources of variability in test accuracy. Objective To develop the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagnostic test accuracy guideline as a stand-alone extension of the PRISMA statement. Modifications to the PRISMA statement reflect the specific requirements for reporting of systematic reviews and meta-analyses of diagnostic test accuracy studies and the abstracts for these reviews. Design Established standards from the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network were followed for the development of the guideline. The original PRISMA statement was used as a framework on which to modify and add items. A group of 24 multidisciplinary experts used a systematic review of articles on existing reporting guidelines and methods, a 3-round Delphi process, a consensus meeting, pilot testing, and iterative refinement to develop the PRISMA diagnostic test accuracy guideline. The final version of the PRISMA diagnostic test accuracy guideline checklist was approved by the group. Findings The systematic review (produced 64 items) and the Delphi process (provided feedback on 7 proposed items; 1 item was later split into 2 items) identified 71 potentially relevant items for consideration. The Delphi process reduced these to 60 items that were discussed at the consensus meeting. Following the meeting, pilot testing and iterative feedback were used to generate the 27-item PRISMA diagnostic test accuracy checklist. To reflect specific or optimal contemporary systematic review methods for diagnostic test accuracy, 8 of the 27 original PRISMA items were left unchanged, 17 were modified, 2 were added, and 2 were omitted. Conclusions and Relevance The 27-item PRISMA diagnostic test accuracy checklist provides specific guidance for reporting of systematic reviews. The PRISMA diagnostic test accuracy guideline can facilitate the transparent reporting of reviews, and may assist in the evaluation of validity and applicability, enhance replicability of reviews, and make the results from systematic reviews of diagnostic test accuracy studies more useful.
Impact of net metering programs on optimal load management in US residential housing - a case study

1. ABSTRACT In the US, buildings represent around 40% of the primary energy consumption and 74% of the electrical energy consumption (U.S. DOE, 2012). Incentives to promote the installation of onsite renewable energy sources have emerged in different states, including net metering programs. The fast spread of such distributed power generation represents additional challenges for the management of the electricity grid hence the interest in smart control of building loads and demand response programs. This paper presents a study of a typical American house built in the 1990s in the Midwest and equipped with a single-speed air-to-air heat pump, an electric water heater and PV collectors. The study investigates the impact of different net metering tariffs on the optimal building electrical load management. The potential of load matching is characterized in terms of percentage of the electricity production consumed on-site and the proportion of the demand covered. Simulations are performed assuming perfect prediction of the electrical load profiles. Results show a potential increase of load matching greater than 7% through control optimization with a suitable net-metering tariff. The associated cost saving for the consumer is about 10% greater compared to no optimization. Depending on the PV panel area, pay-back time increase due to lower buy-back tariffs can be reduced by 3 to 55% through optimal load matching.
On the Completeness of FLH-Resolution

First-literal hyper-resolution (FLH) is a refinement of ordinary hyper-resolution in that positive clauses are only resolved upon their first literals. In this respect, positive literals are ordered in every clause, but negative literals are not. Due to the ordering of literals in this resolution method, standard techniques for demonstrating ground completeness have proven ineffective. In this paper we prove both the ground completeness and the general completeness of first-literal hyper-resolution for first-order logic (FOL) using a clause-ordering and modeling procedure. This technique also suggests a new proof procedure, ETOS-FLH-resolution, a refinement of FLH-resolution, which is more restrictive in that clauses are ordered in a tree with the consequent advantage that only one resolvent is generated at each resolution step. This proof also has an important implication in the completeness of a version of the interactive prover IMPLY.
A First-Principles-Based Potential for the Description of Alkaline Earth Metals

We present a set of Gupta potentials fitted against highest-level ab initio data for interactions of the alkaline earth metals: beryllium, magnesium, and calcium. Reference potential energy curves have been computed for both pure and mixed dimers with the coupled cluster method including corrections for basic set incompleteness and relativistic effects. To demonstrate their usability for the efficient description of high-dimensional complex energy landscapes, the obtained potentials have been used for the global optimization of 38- and 42-atom clusters. Both pure and mixed compositions (binary and ternary clusters) were investigated. Distinctive trends in the structure of the latter are discussed.
Forecasting electrical power consumption based on a hybrid PSO-XGBoost Model

Electrical Power consumption analysis and forecasting has become crucial for effective management and planning on academic campuses, as it helps optimize power generation and usage. Machine learning approaches have been widely used for this purpose as they provide strong capabilities for predictive data analysis, pattern identification, and making accurate forecasts of future electricity consumption. We introduce in this paper a methodology that utilizes a single machine learning model capable of predicting all the profiles of power consumption (e.g. students, staff, professors) in an academic campus. It is based on eXtreme Gradient Boosting (XGBoost) and we propose to optimize its hyper-parameters using the Particle Swarm Metaheuristic (PSO). Using the k-shape algorithm to cluster our electricity consumption data sets helps us achieve the multi-profile model ability. Our PSO-XGBoost model was trained and evaluated using real-time data extracted from an existing network of smart meters that we have implemented at our Academic Campus of INPT and documented in previous works.
Latern: Dynamic Continuous Hand Gesture Recognition Using FMCW Radar Sensor

Recently, hand gesture recognition systems have become increasingly interesting to researchers in the field of human–computer interfaces. Real-world systems for human dynamic hand gesture recognition is challenging as: 1) the system must be robust to various conditions; 2) there is a rich diversity in how people perform hand gestures, making hand gesture recognition difficult; and 3) the system must detect and recognize hand gestures continuously using unsegmented input streams in order to avoid noticeable lag between performing a gesture and its classification. In this paper, to address these challenges, we present Latern, a novel system for dynamic continuous hand gesture recognition based on a frequency-modulated continuous wave radar sensor. The radar system does not depend on lighting, noise, or atmospheric conditions. We employ a recurrent 3-D convolutional neural network to perform the classification of dynamic hand gestures. To enhance the processing performance, a connectionist temporal classification algorithm is used to train the network to predict class labels from inprogress gestures in unsegmented input streams. The experimental results show that Latern is able to achieve high recognition rates of 96%, which is higher than state-of-the-art hand gesture recognition systems. In addition, the conclusion in this paper can be used for a real-time hand gesture recognition system design.
A Finite-State Morphological Grammar of Hebrew

Abstract Morphological analysis is a crucial component of several natural language processing tasks, especially for languages with a highly productive morphology, where stipulating a full lexicon of surface forms is not feasible. This paper describes HAMSAH (HAifa Morphological System for Analyzing Hebrew), a morphological processor for Modern Hebrew, based on finite-state linguistically motivated rules and a broad coverage lexicon. The set of rules comprehensively covers the morphological, morpho-phonological and orthographic phenomena that are observable in contemporary Hebrew texts. Reliance on finite-state technology facilitates the construction of a highly efficient, completely bidirectional system for analysis and generation.
Inter-replicon Gene Flow Contributes to Transcriptional Integration in the Sinorhizobium meliloti Multipartite Genome

Integration of newly acquired genes into existing regulatory networks is necessary for successful horizontal gene transfer (HGT). Ten percent of bacterial species contain at least two DNA replicons over 300 kilobases in size, with the secondary replicons derived predominately through HGT. The Sinorhizobium meliloti genome is split between a 3.7 Mb chromosome, a 1.7 Mb chromid consisting largely of genes acquired through ancient HGT, and a 1.4 Mb megaplasmid consisting primarily of recently acquired genes. Here, RNA-sequencing is used to examine the transcriptional consequences of massive, synthetic genome reduction produced through the removal of the megaplasmid and/or the chromid. Removal of the pSymA megaplasmid influenced the transcription of only six genes. In contrast, removal of the chromid influenced expression of ∼8% of chromosomal genes and ∼4% of megaplasmid genes. This was mediated in part by the loss of the ETR DNA region whose presence on pSymB is due to a translocation from the chromosome. No obvious functional bias among the up-regulated genes was detected, although genes with putative homologs on the chromid were enriched. Down-regulated genes were enriched in motility and sensory transduction pathways. Four transcripts were examined further, and in each case the transcriptional change could be traced to loss of specific pSymB regions. In particularly, a chromosomal transporter was induced due to deletion of bdhA likely mediated through 3-hydroxybutyrate accumulation. These data provide new insights into the evolution of the multipartite bacterial genome, and more generally into the integration of horizontally acquired genes into the transcriptome.
Simulation-Based Testing of Distributed Systems ; CU-CS-1004-06

Developers of distributed systems routinely construct discrete-event simulations to help them understand and evaluate the behavior of inter-component protocols. Typically written using an imperative programming language, these simulations capture basic algorithmic functionality at the same time as they focus attention on properties critical to distribution, including topology, timing, bandwidth, and overall scalability. We ask the following question: Can simulations also be used to help in the testing of distributed-system implementations? Because simulations amount to specifications of intended behavior, the code of a simulation can be viewed as an operational, albeit non-traditional, formal model. We claim that this kind of model, when used within a specification-based testing regime, provides developers with the foundations of a powerful new method for selecting effective test suites. The primary tool used in our method is a fault-based analysis of the simulation code in which a set of mutants are generated using standard codemutation techniques. The analysis can be used to rate the effectiveness of a test suite, as well as the criterion used to form it. We substantiate our claim through experiments performed on the simulations and implementations of two different distributed systems.
Fabrication of castor‐oil/polycaprolactone based bio‐polyurethane foam reinforced with nanocellulose

Polyurethane (PU) foam retains many of the merits of PU such as low density, outstanding energy absorption, and high dimensional stability, which can satisfy various applications. PU foam based on biomaterials was investigated to replace traditional petroleum-based polyol. Polyols were synthesized from castor oil (CO) and polycaprolactone (PCL). In addition, the effects of the nanocellulose on the thermal and mechanical properties of CO-based PU foam were investigated. Nanocellulose at the content of 0.2 wt% was used as reinforcement for CO-based PU foam in this research. Investigation of thermal and mechanical properties found that the CO-based PU foam with the addition of the nanocellulose allowed the best properties. This result indicates that addition of the nanocellulose could be an effective way to improve the mechanical and thermal properties of PU foams. The foamed structure was examined using scanning electron microscopy to determine cell morphology. POLYM. COMPOS. , 2016. © 2016 Society of Plastics Engineers