Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Verification of Digital Systems Using Meta-Heuristic Algorithms

Trends in technological developments, such as autonomous vehicles, home automation, connected cars, IoT, etc., are based on integrated systems or application-specific integrated circuits with high capacities, where these systems require even more complex devices. Thus, new techniques to design more secure systems in a short time in the market are needed. At this point, verification is one of the highest costs in the manufacturing stage and most expensive in the design process. To reduce the time and cost of the verification process, artificial intelligence techniques based on the optimization of the coverage of behavioral areas have been proposed. In this chapter, we will describe the main techniques used in the functional verification of digital systems of medium complexity, focusing especially on meta-heuristic algorithms such as particle swarm optimization, genetic algorithms, and so on. Several results are presented and compared, where the opportunity areas will be described.
How do dairy farmers wish their future farm?

Dairy farming systems are evolving. This study presents dairy producers’ perceptions of their ideal future farm (IFF) to ensure revenue and attempts to determine the reasons for this choice, the environmental aspects related to this choice, the proximity between the current farm and the IFF and the requirements for reaching this IFF. Just before the end of the European milk quota, a total of 245 dairy producers answered a survey about the characteristics of their IFF and other socio-environmental-economic information. A multiple correspondence analysis (MCA) was carried out using seven characteristics of IFF (intensive vs. extensive, specialised vs. diversified, strongly vs. weakly based on new technologies, managed by a group of managers vs. an independent farmer, employed vs. familial workforce, local vs. global market, standard vs. quality-differentiated production). Based on the main contributors to the second dimension of MCA, this axis was defined as an IFF gradient between the local-based extensive (LBE) producers (26%) and the global-based intensive (GBI) producers (46%). The differences of IFF gradient between modalities of qualitative variables were estimated using generalised linear models. Pearson correlations were calculated between the scores on the IFF gradient and quantitative variables. Finally, frequencies for IFF characteristic and the corresponding characteristic for the current situation were calculated to determine the percentages of “unhappy” producers. Some reasons for the choice of IFF by the producers have been highlighted in this study. Environmental initiatives were more valued by LBE than GBI producers. Low similarity was observed between the current farm situation of the respondents and their IFF choice. LBE and GBI producers differed significantly regarding domains of formation (technical and bureaucratic vs transformation and diversification respectively) and paths of formation (non-market vs. market respectively). Two kinds of farming systems were considered by dairy producers and some socioeconomic and environmental components differed between them.
Transferring Sclerotinia resistance genes from wild Helianthus species into cultivated sunflower

Eight Sclerotinia-resistant diploid accessions, one hexaploid, and five interspecific amphiploids have been successfully crossed with Sclerotinia-tolerant cultivated lines, backcrossed and selfed to produce progeny families for field evaluation. In 2009, replicated field screening of 163 and 316 progeny families for head and stalk rot resistance, respectively, indicated good-to-excellent resistance among the progeny families suggesting successful gene introgression. A protocol using genomic in situ hybridization (GISH) to distinguish between chromosomes of perennial Helianthus species and cultivated sunflower has been established providing a new tool for studying gene transfer. A molecular tracking study utilizing SSR markers indicated a higher frequency of gene introgression from diploid perennials than from hexaploid or interspecific amphiploids, suggesting an advantage in using diploid perennials.
The complete chloroplast genome of Vaccinium duclouxii, an endemic species in China

Abstract Vaccinium duclouxii is an endemic species in China, which is distributed in Sichuan and Yunnan province of China. The chloroplast (cp) genome of V. duclouxii is 168,953 bp in size containing 123 unique genes, including 8 rRNA genes, 38 tRNA genes, and 77 protein-coding genes (PCGs). Phylogenetic analysis exhibited that V. duclouxii and V. macrocarpon were most related to Arbutus unedo.
The Ciliary Lumen Accommodates Passive Diffusion and Vesicle Trafficking in Cytoplasmic-Ciliary Transport

Transport of membrane and cytosolic proteins into the primary cilium is essential for its role in cellular signaling. Using single molecule microscopy, we mapped the movement of membrane and soluble proteins at the base of the primary cilium. In addition to the well-known intraflagellar transport (IFT) route, we identified two new pathways within the lumen of the primary cilium - passive diffusional and vesicle transport routes - that are adopted by proteins for cytoplasmic-cilium transport in live cells. Independent of the IFT path, approximately half of IFT motors (KIF3A) and cargo (α-tubulin) take the passive diffusion route and more than half of membrane-embedded G protein coupled receptors (SSTR3 and HTR6) use RAB8A-regulated vesicles to transport into and inside cilia. Furthermore, ciliary lumen transport is the preferred route for membrane proteins in the early stages of ciliogenesis and inhibition of SSTR3 vesicle transport completely blocks ciliogenesis. Furthermore, clathrin-mediated, signal-dependent internalization of SSTR3 also occurs through the ciliary lumen. These transport routes were also observed in Chlamydomonas reinhardtii flagella, suggesting their conserved roles in trafficking of ciliary proteins.
Design and implementation of a communication network and operating system for an adaptive integrated hybrid AC/DC microgrid module

This paper proposes an adaptive integrated hybrid AC/DC microgrid module to accommodate a wide range of distributed renewable energy resources (DRERs), distributed energy storage devices (DESDs) and distributed demand resources (DDRs) into the existing distribution systems. This microgrid module is designed to be portable, scalable, easy to deploy, and simple to operate. The modeling of the proposed microgrid module, based on the IEC 61850 standard, is presented. A novel logical node is introduced, which describes functionalities of the bidirectional interlinking converter (BIC) interfacing AC sub-grid and DC sub-grid in a better way. To achieve the target of plug-and-play functionalities, specific microgrid module communication network (MMCN) and microgrid module operating systems (MMOS) are designed and implemented in the hardware prototype built in the laboratory. Experimental results obtained from the lab prototype clearly validate the effectiveness of the proposed design of the microgrid module, communication network and operating system.
Reliability-oriented intra-frequency dual connectivity for 5G systems: Configuration algorithms and performance evaluation

User association in wireless networks has historically been done on the basis of single connectivity, i.e. the user equipment (UE) being connected to a single serving access point (AP). Such a design was quite efficient for conventional homogeneous networks with mostly voice-centric applications. However, as networks become more heterogeneous and services become diverse with different performance requirements, connecting to a single AP has proven to be quite inefficient
Neonectria castaneicola and Neo. rugulosa in Japan

Differences between Neonectria castaneicola, which causes stem and perennial canker of trees, and Neo. rugulosa have not been clearly shown in previous studies. In this study these two species were compared in detail using 17 Japanese isolates consisting of 10 strains of Neo. castaneicola and seven of Neo. rugulosa. Fourspored asci were constantly found in Neo. castaneicola and this species produced larger ascospores and macroconidia than Neo. rugulosa which produced eight-spored asci. The mating system of Neo. castaneicola was homothallic while Neo. rugulosa was heterothallic. Characters in each species, such as the number of ascospores in an ascus and mating system, were constantly transferred to the 3rd generation. Molecular analysis revealed that the 10 isolates of Neo. castaneicola and seven of Neo. rugulosa were differentiated using rDNA sequence data from the nuclear rDNA ITS region. Moreover, Neo. castaneicola and Neo. rugulosa were separated into different clades. From these results, it was concluded that Neo. castaneicola should be maintained as an independent species, separate from Neo. rugulosa. The isolates of Neo. rugulosa used in this study were the first reported in Japan and found on Castanea crenata, Castanopsis sp. , Myrica rubra and Quercus acutissima.
A framework for testing different imputation methods for tabular datasets

Background and purpose Handling missing values is a prevalent challenge in the analysis of clinical data. The rise of data-driven models demands an efficient use of the available data. Methods to impute missing values are thus crucial. Here, we developed a publicly available framework to test different imputation methods and compared their impact in a typical stroke clinical dataset as a use case. Methods A clinical dataset based on the 1000Plus stroke study with 380 completed-entries patients was used. 13 common clinical parameters including numerical and categorical values were selected. Missing values in a missing-at-random (MAR) and missing-completely-at-random (MCAR) fashion from 0% to 60% were simulated and consequently imputed using the mean, hot-deck, multiple imputation by chained equations, expectation maximization method and listwise deletion. The performance was assessed by the root mean squared error, the absolute bias and the performance of a linear model for discharge mRS prediction. Results Listwise deletion was the worst performing method and started to be significantly worse than any imputation method from 2% (MAR) and 3% (MCAR) missing values on. The underlying missing value mechanism seemed to have a crucial influence on the identified best performing imputation method. Consequently no single imputation method outperformed all others. A significant performance drop of the linear model started from 11% (MAR+MCAR) and 18% (MCAR) missing values. Conclusions In the presented case study of a typical clinical stroke dataset we confirmed that listwise deletion should be avoided for dealing with missing values. Our findings indicate that the underlying missing value mechanism and other dataset characteristics strongly influence the best choice of imputation method. For future studies with similar data structure, we thus suggest to use the developed framework in this study to select the most suitable imputation method for a given dataset prior to analysis.
Anomaly detection in discussion forum posts using global vectors

Anomaly detection can be seen as an unsupervised learning task in which a predictive model created on historical data is used to detect outlying instances in new data. This work addresses possibly promising but relatively uncommon application of anomaly detection to text data. A Polish Internet discussion forum devoted to psychoactive substances received from home-grown plants, such as hashish or marijuana, serves as a text source that is both realistic and possibly interesting on its own, due to potential associations with drug-related crime. Forum posts are preprocessed by stopword removal, spelling correction, stemming, and frequency-based term filtering. The Global Vectors (GloVe) text representation, which is an example of the increasingly popular word embedding approach, is combined with two unsupervised anomaly detection algorithms, based on one-class SVM classification and based on dissimilarity to k-medoids clusters. The cluster dissimilarity approach combined with the GloVe representation outperforms one-class SVM with respect to detection quality and appears a more promising approach to anomaly detection in text data.
Comparison of Arm Selection Policies for the Multi-Armed Bandit Problem

Web content optimization involves deciding what content to put on a web page, its layout and design. All of which involve selecting few options among many. With the advent of personalization, many companies seek to make this decision even on a per-user basis in order to improve customer experience and satisfaction. Contextual multi-armed bandit provides several strategies to address this online decision-making problem at a lower experimental cost than traditional A/B testing. In this study, we compare three common Contextual Bandit strategies that exist in literature namely E-greedy, LinUCB and Thompson Sampling, and apply two of them, E-greedy and LinUCB, to three datasets. In doing so we offer further empirical evidence on the performance of these strategies and insights for practitioners on what strategy might work for them. Our results suggest that both approaches, E-Greedy and LinUCB are effective in improving click-through rate compared to the random approach. The more sophisticated approach has better results with large datasets, and a quite unstable performance when the number of datapoints is small. On the other hand, we find that the more sophisticated approach is more sensitive to parameter tuning and can have significantly worse outcome when parameters are incorrect. Our study also finds that LinUCB can have higher data requirements when performing evaluation offline. Collectively the varying performance of these approaches across dataset signal the need for better tools and procedures to help practitioners decide on the appropriate approach.
The first complete chloroplast genome sequence of Lanxangia tsaoko and phylogenetic analysis

Abstract Lanxangia tsaoko is a famous Chinese traditional medicine with long history. In this study, the complete chloroplast (cp) genome of L. tsaoko was characterized and assembled using a high-throughput sequencing method. The complete cp genome is 164,008 bp in length, including a large single copy (LSC) region of 89,134 bp and a small single copy (SSC) region of 15,372 bp separated by two inverted repeat (IR) regions of 29,751 bp. A total of 137 genes were identified, including 88 protein-coding genes (PCG), 38 transfer RNA genes, 8 ribosomal RNA genes, and 3 pseudogenes. The phylogenetic analysis revealed that L. tsaoko is located in Zingiberaceace, closely related to Amomum and Alpinia with a 100% bootstrap support.
Determining sex in pigeons (Columba livia)

In many birds, especially in monomorphic species and breeds, it is difficult to distinguish between sexes due to lack of phenotypic differences. Originally, sex identification was based on behavioural observations, structure of the pelvis and certain anatomical features. Direct methods, such as endoscopy, laparoscopy and laparotomy, have been widely criticized for being highly invasive, stressful and difficult, especially when the size of birds is considered. Karyotyping fails in some species (ostrich, emu) due to similarity of their sex chromosomes and can be used only in case of the species with heteromorphic female ZW sex chromosomes. With the advances of molecular diagnostics new methods of sex identification have been developed and these include hybridization and polymerase chain reaction (PCR). An effective method of sex identification in pigeons uses CHD1 gene, which is present both in Z and W chromosomes.
Prospects for genomic selection in forage plant species

Genomic selection (GS) is a powerful method for exploitation of DNA sequence polymorphisms in breeding improvement, through the prediction of breeding values based on all markers distributed genome-wide. Forage grasses and legumes provide important targets for GS implementation, as many key traits are difficult or expensive to assess, and are measured late in the breeding cycle. Generic attributes of forage breeding programmes are described, along with status of genomic resources for a representative species group (ryegrasses). Two schemes for implementing GS in ryegrass breeding are described. The first requires relatively little modification of current schemes, but could lead to significant reductions in operating cost. The second scheme would allow two rounds of selection for key agronomic traits within a time period previously required for a single round, potentially leading to doubling of genetic gain rate, but requires a purpose-designed reference population. In both schemes, the limited extent of linkage disequilibrium (LD), which is the major challenge for GS implementation in ryegrass breeding, is addressed. The strategies also incorporate recent advances in DNA sequencing technology to minimize costs.
The complete chloroplast genome sequence of plumed cockscomb (Celosia argentea, Amaranthaceae)

Abstract The complete chloroplast genome of Celosia argentea, an important horticultural and medicinal herb, was identified and sequenced in this study. The genome size is 153,474 bp, the GC content is 36.7%. A total of 123 genes were identified, including 84 protein-coding genes, 8 rRNA genes, and 33 tRNA genes. Twenty-nine plastome accessions from Caryophyllales were selected to assess the phylogenetic placement of genus and the result showed that C. argentea is most closely related to Amaranthus hypochondriacus.
Food and habitat provisions jointly determine competitive and facilitative interactions among distantly related herbivores

Interactions between distantly related herbivores exert powerful influences on ecosystems, but most studies to date have only considered unidirectional effects. Few have simultaneously examined the mutual effects that vertebrate herbivores and insect herbivores have on one another. We conducted a set of manipulative experiments to evaluate the potential competition and facilitation between two pairs of distantly related herbivore taxa: an insect caterpillar (Gynaephora alpherakii) and two large vertebrate herbivores, yak (Bos grunniens) and Tibetan sheep (Ovis aries tibetica). We found that these large herbivores consistently increased the density of caterpillars likely by improving the habitat for caterpillars. The caterpillars, in turn, decreased yak but increased Tibetan sheep foraging time and intake bites by differently changing available food resources of the two large herbivores. Diet preferences of herbivores modified the habitat and food resources, thereby causing a diet‐mediated competition between yak and caterpillars, and facilitation between sheep and caterpillars. The vertebrate herbivores non‐feeding upon Lamiophlomis rotata and Gentiana straminea, the caterpillars preferred habitat, increased densities of the two plant species, thus favouring the caterpillars. In turn, the caterpillar preference for Kobresia pygmaea significantly reduced food resources for yak, while promoting food resources (multiple forbs) for sheep. Synthesis. Our study indicates that two different mechanisms (the changes in habitat and food availability) induced by herbivore foraging jointly determine competitive and facilitative interactions between distantly related herbivore species. We also suggest that examining the bi‐directional effects between herbivores offers a better understanding of competition and facilitation in terrestrial animal communities.
Complete mitochondrial genome of Dacus trimacula (Diptera: Tephritidae) using next-generation sequencing from China

Abstract The complete mitochondrial genome (mitogenome) of the fruit fly species Dacus trimacula (Diptera: Tephritidae: Dacinae) are sequenced and annotated. The mitochondrial genome is 15,851 bp (GenBank No. MK940811) has an A + T content of 72.8% (A 39.2%; C 17.0%; G 10.2%, and T 33.6%), which is the classical structure for insect mitogenome. All PCGs started with ATN and stopped with TAN. The phylogenetic tree confirms that D. trimacula clustered with D. longicornis as the sister group to Zeugodacus. This study enriches the mitogenomes of the fruit flies.
A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection

ABSTRACT Learning a classifier from imbalanced data is a challenging problem in Machine learning. A dataset is said to be imbalanced when the number of instances belonging to one class is much less than the number of instances belonging to the other class. Classifiers that proves efficient on standard data fail when the data is imbalanced as they are over trained by the majority class instances. Since class imbalance is a common characteristic of real-world data, the need for better classifiers becomes essential. This paper proposes a novel instance-based classification algorithm called Weighted Pattern Matching based Classification (PMC+) for classifying imbalanced data. PMC+ classifies unlabelled instances by computing the absolute difference between the feature values of the instances in the dataset and the unlabelled instance. PMC+ employs a simple classification procedure with weights and shows reasonably good performance. To improve the performance of PMC+, Fireworks based Feature and Weight Selection algorithm based on the idea of PMC+ has been proposed. PMC+ is evaluated on 44 binary imbalanced datasets and 15 multiclass imbalanced datasets. Although PMC+ does not employ a resampling or cost-sensitive method, experiments show that PMC+ is effective for classification of imbalanced data. The results of the experiments were validated using various non-parametric statistical tests.
Inter-Species Differences in the Response of Sinus Node Cellular Pacemaking to Changes of Extracellular Calcium

Changes of serum and extracellular ion concentrations occur regularly in patients with chronic kidney disease (CKD). Recently, hypocalcemia, i.e. a decrease of the extra-cellular calcium concentration [Ca2+]o, has been suggested as potential pathomechanism contributing to the unexplained high rate of sudden cardiac death (SCD) in CKD patients. In particular, there is a hypothesis that hypocalcaemia could slow down natural pacemaking in the human sinus node to fatal degrees. Here, we address the question whether there are inter-species differences in the response of cellular sinus node pacemaking to changes of [Ca2+]o. Towards this end, we employ computational models of mouse, rabbit and human sinus node cells. The Fabbri et al. human model was updated to consider changes of intracellular ion concentrations. We identified crucial inter-species differences in the response of cellular pacemaking in the sinus node to changes of [Ca2+]o with little changes of cycle length in mouse and rabbit models (<83 ms) in contrast to a pronounced bradycardic effect in the human model (up to > 1000 ms). Our results suggest that experiments with human sinus node cells are required to investigate the potential mechanism of hypocalcaemia-induced bradycardic SCD in CKD patients and small animal models are not well suited.