Miracle-dz/UniFAR-FTUs huggingface dataset:
The complete mitochondrial genome of the Colletes gigas (Hymenoptera: Colletidae: Colletinae)

Abstract The complete mitochondrial genome of the Colletes gigas (Hymenoptera: Colletidae) is determined to be 15,885 bp in length, containing 37 typical animal mitochondrial genes: 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes and a major non-coding AT-rich region. All PCGs initiate with typical ATN codons and end with the complete termination codon TAA, except for the cob gene, which harbors the stop codon of TAG. Twenty-four intergenic spacers (614 bp in total) and 7 overlapping regions (37 bp in total) are dispersed throughout the whole genome. The non-coding AT-rich region is 539 bp long and contains a tandem repeat region, which has also been reported in other insects. This is the first completely sequenced mitochondrial genome of the family Colletidae.
Multilevel image recognition using discriminative patches and kernel covariance descriptor

Computer-aided diagnosis of medical images has emerged as an important tool to objectively improve the performance, accuracy and consistency for clinical workflow. To computerize the medical image diagnostic recognition problem, there are three fundamental problems: where to look (i.e., where is the region of interest from the whole image/volume), image feature description/encoding, and similarity metrics for classification or matching. In this paper, we exploit the motivation, implementation and performance evaluation of task-driven iterative, discriminative image patch mining; covariance matrix based descriptor via intensity, gradient and spatial layout; and log-Euclidean distance kernel for support vector machine, to address these three aspects respectively. To cope with often visually ambiguous image patterns for the region of interest in medical diagnosis, discovery of multilabel selective discriminative patches is desired. Covariance of several image statistics summarizes their second order interactions within an image patch and is proved as an effective image descriptor, with low dimensionality compared with joint statistics and fast computation regardless of the patch size. We extensively evaluate two extended Gaussian kernels using affine-invariant Riemannian metric or log-Euclidean metric with support vector machines (SVM), on two medical image classification problems of degenerative disc disease (DDD) detection on cortical shell unwrapped CT maps and colitis detection on CT key images. The proposed approach is validated with promising quantitative results on these challenging tasks. Our experimental findings and discussion also unveil some interesting insights on the covariance feature composition with or without spatial layout for classification and retrieval, and different kernel constructions for SVM. This will also shed some light on future work using covariance feature and kernel classification for medical image analysis.
Influence of “traveling” youth and substance use behaviors in the social networks of homeless youth*

Abstract Traveling homeless youth (i.e., youth who migrate from city to city, after a short period of time) exhibit elevated levels of risky substance use behaviors compared to non-traveling youth. Using sociometric data, we examined the characteristics of homeless youth who are connected to at least one traveler and how at least one connection to travelers was associated with substance use of travelers and non-travelers. Data were collected from 386 homeless youth at two drop-in centers in Los Angeles, CA. Results indicated that, comparing to what would be expected by chance, youth who reported at least one connection to travelers were more likely to use substances, more travelers reported at least one tie to another traveler, and more substance-using travelers reported at least one tie to other substance-using travelers. Multivariate analyses revealed that binge drinking and marijuana use were associated with homeless youth reporting connections to at least one substance-using traveler. Injection drug use was associated with reporting at least one connection to an injection drug user, regardless of traveler status, once we controlled for demographic characteristics and traveler status. We suggest the need for substance-using traveler-specific services using brief one-on-one interventions to prevent further engagement in risky substance use.
Volterra polynomials in the intelligent control system of wind power plant operation

The paper is focused on the possibility of integrating situation control and simulation modeling based on the Volterra integro-power series when describing transient processes in a nonlinear dynamic object of input-output type. A reference object was represented by a model of horizontal-axis wind turbine. The research deals with nonlinear dynamics of a rotation speed of wind turbine components depending on the blade angle and wind speed. A two-level technology is applied to prevent emergency situations. It consists of a quantitative analysis and a qualitative analysis. The first level is implemented using the situation analysis tools based on semantic modeling. At the second level the simulation modeling is performed. An algorithm for construction of a set of current situations in the semantic model is based on the Volterra polynomial integral equations. The Newton-Kantorovich method was applied to develop an iterative method to approximately solve respective nonlinear equations. The paper demonstrates the specific features of numerically solving the studied equations with a fixed length of mantissa in machine representation of a floating-point number.
Maturation of Fibrinolytic Bacillopeptidase F Involves both Hetero- and Autocatalytic Processes

ABSTRACT Bacillopeptidase F (Bpr) is a fibrinolytic serine protease produced by Bacillus subtilis. Its precursor is composed of a signal peptide, an N-terminal propeptide, a catalytic domain, and a long C-terminal extension (CTE). Several active forms of Bpr have been previously reported, but little is known about the maturation of this enzyme. Here, a gene encoding a Bpr (BprL) was cloned from B. subtilis LZW and expressed in B. subtilis WB700, and three fibrinolytic mature forms with apparent molecular masses of 45, 75, and 85 kDa were identified in the culture supernatant. After treatment with urea, the 75-kDa mature form had the same molecular mass as the 85-kDa mature form, from which we infer that they adopt different conformations. Mutational analysis revealed that while the 85-kDa mature form is generated via heterocatalytic processing of a BprL proform by an unidentified protease of B. subtilis, the production of the 75- and 45-kDa mature forms involves both hetero- and autocatalytic events. From in vitro analysis of BprL and its sequential C-terminal truncation variants, it appears that partial removal of the CTE is required for the initiation of autoprocessing of the N-terminal propeptide, which is composed of a core domain (N*) and a 15-residue linker peptide, thereby yielding the 45-kDa mature form. These data suggest that the differential processing of BprL, either heterocatalytically or autocatalytically, leads to the formation of multiple mature forms with different molecular masses or conformations.
A fully integrated 13 GHz CMOS SOI stacked power amplifier for 5G wireless systems

This paper presents a fully integrated, four stack power amplifier for 5G wireless systems. The frequency of operation is tunable from 12 GHz to 14 GHz, with a maximum 3 dB bandwidth of 1 GHz and a maximum possible gain of 35 dB. The circuit is designed and fabricated using 45 nm CMOS SOI technology. Maximum RF output power, power-added efficiency (PAE) and output 1 dB compression point under maximum bandwidth configuration are 17.7 dBm, 23.2% and 12.3 dBm, respectively, achieved at 13.7 GHz.
Comparative characterization of SHED and DPSCs during extended cultivation in vitro

Dental pulp stem cells (DPSCs) and stem cells from human exfoliated deciduous teeth (SHED) are types of human dental tissue-derived mesenchymal stem cells (MSCs). These cells possess a capacity for self-renewal, multilineage differentiation potential and immunomodulatory functions. Previous studies have reported that DPSCs and SHED may be beneficial in regenerative treatments and immunotherapy. The substantial expansion of cells in vitro is a prerequisite to obtaining adequate cell numbers required for cell-based therapy. However, the regeneration and clinical potential of MSCs diminishes with long-term cell culture amplification. To assess the alterations in SHED and DPSCs characteristics that underlie cellular senescence and result from extended in vitro amplification, the biological properties of SHED and DPSCs at passages 4 (P4) and 20 (P20) were compared. The cells underwent senescence following serial expansion to P20, as determined by altered cell morphology, decreased proliferation and migration capacity, attenuated differentiation potential, elevated senescence-associated β-galactosidase (SA-β-gal)-positive rates and increased apoptosis. The phenotypic changes were also accompanied by a marked increase in the expression of p53, p21 and p16Ink4a. The present study also identified that senescent DPSCs exhibited an increased number of positive cells in SA-β-gal staining and demonstrated varying expressions of p53, p21 and p16Ink4a in comparison with SHED, indicating the involvement of diverse pathways in cellular senescence during long-term sequential in vitro culture and passage. Furthermore, at early and late passages, SHED exhibited a higher proliferation rate and osteogenic differentiation capability when compared with DPSCs. In addition, both cell types maintained their characteristic immunophenotype during long-term cultivation, while the expression levels of CD73 were higher in SHED at P20. The present study concluded that notable alterations were exhibited in SHED and DPSCs during the process of extensive expansion in vitro and the results may provide guidance for the selection of safe and effective expanded SHED and DPSCs for regenerative medicine and therapy.
Entropy-Based Symbolic Representation for Time Series Classification

In order to improve the performance of time-series classification, we introduce a new approach of time series classification. The first basic idea of the approach is to use entropy impurity measure to discretize and symbolize time series, which discretize the original time series into disjoint intervals using entropy impurity measure and then transform the time series into symbolic representations. The second idea of the approach is to combine symbolic representation of time series and k nearest neighbor to classify time series. The proposed approach is compared with a number of known pattern classifiers by benchmarking with the use of artificial and real-world data sets. The experimental results show it can reduce the error rates of time series classification, so it is highly competitive with previous approaches.
hiResilient response and performance of bitumen stabilized materials with foam incorporating reclaimed asphalt

The increased use of reclaimed asphalt (RA) in Bitumen Stabilised Materials (BSMs), shortcomings in the existing design guidelines and manuals and ongoing developments in the concepts and understanding of these materials require further research into the fundamental properties and behaviour of BSMs. The main objective of this study is to advance BSM technology by assessing the influence of the selected materials on durability behaviour, temperature distribution and long-term performance in all phases of application (i.e. mix design, construction, and in-service condition). This study begins with a comprehensive literature review of research dealing with the interactions between RA and mineral aggregates. A laboratory testing programme was set up to study the properties and behaviour of BSMs and to establish links with the compositional factors, i.e. the type of binder used, the percentage of RA in the mix and the addition of a small amount of cement as active filler. Tri-axial testing was carried out to determine shear parameters, resilient modulus and permanent deformation behaviour, while brushing testing was carried out to determine the possible durability performance of the BSMs. A considerable part of the efforts of this study were dedicated to characterise and model the temperature distribution in a pavement section, taking into account the mechanical properties and performance of the BSMs at different temperature layers. The study provides an insight into fundamental mechanical performance, material durability properties, and the thermal capacity and conductivity of the BSM-foam mixes with high percentage of RA. This will assist in improving the current procedure for selection, combining and formulation of the mix matrices for BSMs. In addition, the study provides guidelines that will enable practitioners to confidently understand the relationship between temperature gradient and mechanical behaviours of BSM-foam pavement section. The specific durability-related issues addressed in this study are substance for future research.
Anomalous‐Diffusion‐Assisted Brightness in White Cellulose Nanofibril Membranes

The understanding of the interaction between light and complex, random structures is the key for designing and tailoring the optical appearance and performance of many materials that surround us, ranging from everyday consumer products, such as those for personal care, paints, and paper, to light diffusers used in the LED‐lamps and solar cells. Here, it is demonstrated that the light transport in membranes of pure cellulose nanofibrils (CNFs) can be controlled to achieve bright whiteness in structures only a few micrometers thick. This is in contrast to other materials, such as paper, which require hundreds of micrometers to achieve a comparable appearance. The diffusion of light in the CNF membranes is shown to become anomalous by tuning the porosity and morphological features. Considering also their strong mechanical properties and biocompatibility, such white coatings are proposed as a new application for cellulose nanofibrils.
A neuromorphic approach to image processing and machine vision

Neuromorphic engineering is essentially the development of artificial systems, such as electronic analog circuits that employ information representations found in biological nervous systems. Despite being faster and more accurate than the human brain, computers lag behind in recognition capability. However, it is envisioned that the advancement in neuromorphics, pertaining to the fields of computer vision and image processing will provide a considerable improvement in the way computers can interpret and analyze information. In this paper, we explore the implementation of visual tasks such as image segmentation, visual attention and object recognition. Moreover, the concept of anisotropic diffusion has been examined followed by a novel approach employing memristors to execute image segmentation. Additionally, we have discussed the role of neuromorphic vision sensors in artificial visual systems and the protocol involved in order to enable asynchronous transmission of signals. Moreover, two widely accepted algorithms that are used to emulate the process of object recognition and visual attention have also been discussed. Throughout the span of this paper, we have emphasized on the employment of non-volatile memory devices such as memristors to realize artificial visual systems. Finally, we discuss about hardware accelerators and wish to represent a case in point for arguing that progress in computer vision may benefit directly from progress in non-volatile memory technology.
Cross-contextual use of integrated information systems

Large-scale organizations are increasingly promoting more collaborative and collective work practices across organizational boarders. A predominant way to achieve better collaboration in large- scale heterogeneous contexts is to establish an integrated and standardized technological infrastructure. Ethnographically inspired studies, on the other hand, have challenged such perspective and illustrated that generic technology does not fit in local contexts and needs to be worked-around. Similarly, this paper empirically exemplifies local workarounds and illustrates ongoing and persistently imperfect integration of a collaborative infrastructure in a global oil and gas company. More importantly, however, our analysis focuses on how integrated technology is used across contexts. We illustrate how local workarounds, as a result of tight technological integration, shape use patterns across contexts. Integrated systems establish interdependencies across contexts, thus, the use implies cross-contextual rather than local enactment. Since the trajectory of enactment is influenced by cross-contextual constrains, our study is addressing the existing overemphasis on studying/analysing the use of technology in isolated local contexts. Practically, our study suggests considering workarounds as an intrinsic part of every day work, which should be calculated as additional costs of making the generic technology to work in practice.
Toward network coding-based protocols for data broadcasting in wireless Ad Hoc networks

In this paper we consider practical dissemination algorithms exploiting network coding for data broadcasting in ad hoc wireless networks. For an efficient design, we analyze issues related to the use of network coding in realistic network scenarios. In detail, we quantify the impact of random access schemes, as used by IEEE 802.11, on the performance of network coding. In such scenarios, deadlock situations may occur where the delivery process stops and some of the nodes never gather the required packets. To tackle this problem, we propose a proactive mechanism (called proactive network coding) which adapts its transmission schedule according to the decoding status of neighboring nodes. This scheme can detect when nodes need additional packets in order to decode and acts accordingly. We finally investigate the behavior of network coding schemes in multi-rate environments, where we propose a distributed heuristic approach for the selection of data rates.
The Microstructure And Mechanical Properties Of The AlSi17Cu5 Alloy After Heat Treatment

Al-Si alloys are widely used in many branches of industry, especially in transport for the highly loaded parts of pistons and heads of the internal combustion engines. The work environment of combustion engines require that the castings need to have good mechanical, plastic and technological properties, which also allow manufacturing parts with complicated shapes and thin walls. Multicomponent hypereutectic Al-Si alloys with additions such as Cu, Ni, Mg [1-3], after precipitation strengthening meets this requirements. Intermetallic phases, mainly AlSiFe and AlSiCu, form during aluminum solution strengthening, this increases the mechanical properties [4-6], and thus increases the application range of hypereutectic AlSi-Me alloys. The shape and size of primary silicon crystals are also very important. Size can be reduced by: modification [7-9], mixing, and effects of electromagnetic fields [10]. This change in morphology of Si crystals also positively affects the machinability. Fine crystalline structure can also be obtained by the so-called thermal treatment of the alloy in the liquid state. It involves overheating of the liquid metal to about 250 ÷ 300oC above the liquidus temperature, holding for some time and quick cooling to pouring temperature just before pouring into the mold [11-15]. This technology results in dissolution of accidental inclusions which can become uncontrolled heterogeneous nucleation sites and also deliberate introduction of other icoculats. It is a viable alternative for the solid state heat treatment of castings.
Identification of KIF3A as a Novel Candidate Gene for Childhood Asthma Using RNA Expression and Population Allelic Frequencies Differences

Background Asthma is a chronic inflammatory disease with a strong genetic predisposition. A major challenge for candidate gene association studies in asthma is the selection of biologically relevant genes. Methodology/Principal Findings Using epithelial RNA expression arrays, HapMap allele frequency variation, and the literature, we identified six possible candidate susceptibility genes for childhood asthma including ADCY2, DNAH5, KIF3A, PDE4B, PLAU, SPRR2B. To evaluate these genes, we compared the genotypes of 194 predominantly tagging SNPs in 790 asthmatic, allergic and non-allergic children. We found that SNPs in all six genes were nominally associated with asthma (p<0.05) in our discovery cohort and in three independent cohorts at either the SNP or gene level (p<0.05). Further, we determined that our selection approach was superior to random selection of genes either differentially expressed in asthmatics compared to controls (p = 0.0049) or selected based on the literature alone (p = 0.0049), substantiating the validity of our gene selection approach. Importantly, we observed that 7 of 9 SNPs in the KIF3A gene more than doubled the odds of asthma (OR = 2.3, p<0.0001) and increased the odds of allergic disease (OR = 1.8, p<0.008). Our data indicate that KIF3A rs7737031 (T-allele) has an asthma population attributable risk of 18.5%. The association between KIF3A rs7737031 and asthma was validated in 3 independent populations, further substantiating the validity of our gene selection approach. Conclusions/Significance Our study demonstrates that KIF3A, a member of the kinesin superfamily of microtubule associated motors that are important in the transport of protein complexes within cilia, is a novel candidate gene for childhood asthma. Polymorphisms in KIF3A may in part be responsible for poor mucus and/or allergen clearance from the airways. Furthermore, our study provides a promising framework for the identification and evaluation of novel candidate susceptibility genes.