Miracle-dz/UniFAR-FTUs huggingface dataset:
Current insights into fungal species diversity and perspective on naming the environmental DNA sequences of fungi

ABSTRACT The global bio-diversity of fungi has been extensively investigated and their species number has been estimated. Notably, the development of molecular phylogeny has revealed an unexpected fungal diversity and utilisation of culture-independent approaches including high-throughput amplicon sequencing has dramatically increased number of fungal operational taxonomic units. A number of novel taxa including new divisions, classes, orders and new families have been established in last decade. Many cryptic species were identified by molecular phylogeny. Based on recently generated data from culture-dependent and -independent survey on same samples, the fungal species on the earth were estimated to be 12 (11.7–13.2) million compared to 2.2–3.8 million species recently estimated by a variety of the estimation techniques. Moreover, it has been speculated that the current use of high-throughput sequencing techniques would reveal an even higher diversity than our current estimation. Recently, the formal classification of environmental sequences and permission of DNA sequence data as fungal names’ type were proposed but strongly objected by the mycologist community. Surveys on fungi in unusual niches have indicated that many previously regarded “unculturable fungi” could be cultured on certain substrates under specific conditions. Moreover, the high-throughput amplicon sequencing, shotgun metagenomics and a single-cell genomics could be a powerful means to detect novel taxa. Here, we propose to separate the fungal types into physical type based on specimen, genome DNA (gDNA) type based on complete genome sequence of culturable and uncluturable fungal specimen and digital type based on environmental DNA sequence data. The physical and gDNA type should have priority, while the digital type can be temporal supplementary before the physical type and gDNA type being available. The fungal name based on the “digital type” could be assigned as the “clade” name + species name. The “clade” name could be the name of genus, family or order, etc. which the sequence of digital type affiliates to. Facilitating future cultivation efforts should be encouraged. Also, with the advancement in knowledge of fungi inhabiting various environments mostly because of rapid development of new detection technologies, more information should be expected for fungal diversity on our planet.
The impact of segregated diversity on the code of the street: an analysis of violence-related norms in selected post-industrial neighborhoods in Germany

Youth violence remains a concern in Germany, particularly in specific “risky” neighborhoods that tend to be socially segregated and ethnically diverse. In this paper we critically compare the results of twenty-seven qualitative interviews conducted in three risky neighborhoods in the German Ruhr area with the code of the street. While this theoretical framework is frequently cited in explaining youth violence, it was based on research in an ethnically homogenous neighborhood in the United States and thus does not engage with questions of diversity. Our findings show that the core of the code of the street is also applicable in heterogeneous contexts, thus extending the generalizability of the theoretical framework. Manifestations of manhood, reputation, and symbolic power were found to be major elements of street culture, although characterized somewhat differently than in the original work.
A cross-layer design framework for robust IPTV services over IEEE 802.16 networks

This paper introduces a cross-layer design framework for robust and efficient video multicasting over IEEE 802.16 (also known as WiMAX) networks in metropolitan areas. In the framework, multiple description coding (MDC) on scalable video bitstreams at the source for achieving multiresolution robustness is jointly designed with superposition coding (SCM) on multicast signals at the channel to overcome multiuser channel diversity in wireless multicast. The coded multicast signals under the proposed framework can cope with multiuser channel diversity and mitigate the impact due to short-term channel fluctuations, which are the two most challenging issues in achieving robust and efficient video multicasting in metropolitan areas. We formulate the proposed framework and analyze its video quality performance in terms of the total receivable/ recoverable bitstreams by a receiver. A heuristic methodology is developed for system parameter selection and performance optimization that can be applied to practical scenarios of video multicasting for IPTV services in WiMAX. Simulation is conducted based on actual standard video sequences to verify the proposed methodology on parameter selection and performance optimization. Performance gains of the proposed cross-layer design framework in the presence of fading channel diversity are demonstrated.
An optimization model incorporating clash free mechanism for design of AUVs

This paper presents an optimization model that incorporates a clash free mechanism for design of Autonomous Underwater Vehicles/Gliders (AUVs/Gs). The present model allows the designer to pack the internal components satisfying the stability and buoyancy criteria and integration of Computer Aided Design (CAD) and Computational Fluid Dynamics (CFD, and this integration of CAD+CFD with the optimization computes a hydro-dynamically efficient hull form. The Genetic Algorithm (GA) is used in finding the optimum within given range of design parameters. Our optimization model is structured in two tiers: 1) hydrodynamic drag, and 2) LGB; and both are minimized. The hydrodynamic drag is evaluated using a CFD software (Shipflow*™) and the drag computation is integrated with CAD definition model implemented in Matlab**™. The clash free mechanism deals with packing and minimization of the distance (LGB) between Center of Gravity (COG) and Center of Buoyancy (COB). Finally, we present a design example of USS Dallas RC toy AUV for a particular velocity of 0.5 m/s. Our results show that the implementation of the present model results into a low drag hull form with compact and tight packing and higher stability.
Construction of an overproduction vector containing the novel srp (sterically repressed) promoter

We report the design, synthesis, and evaluation of a novel Escherichia coli promoter intended for use in overproduction of proteins that are deleterious to the host. In this sterically repressed promoter (srp), the lac operator site is positioned between the ‐10 and ‐35 elements, where it can interfere sterically with RNA polymerase and thereby prevent assembly of a poised transcriptional complex. An srp‐containing phagemid, pKEN1, and a tac‐containing phagemid, pHN1, which has been widely used in protein overproduction but is often unstable, are compared with respect to levels of uninduced and induced protein expression. The level of uninduced protein synthesis by the srp promoter in vivo is ∼ 50% of that observed with tac, whereas the leveIs of induced protein synthesis with the 2 vectors are approximately equal. A remarkable increase in stability of overproduction and growth was observed when the toxic Ada protein was overproduced in pKEN1, demonstrating the potential utility of this vector in overproducing toxic proteins.
Bulk acoustic wave coupled resonator filters synthesis methodology

This paper presents a synthesis methodology applied to bulk acoustic wave coupled resonator filters (BAW CRF). BAW-CRFs are able to realize wider bandwidth and higher rejection filter responses, but they present smoother roll-off coefficients compared to classical ladder topology. The proposed methodology enables to determine the filter structure dimensions able to synthesize Chebyshev responses. Finally, we address the design of an RF filter applied to the W-CDMA system employing the proposed methodology.
Deep Learning Guided Partitioned Shape Model for Anterior Visual Pathway Segmentation

Analysis of cranial nerve systems, such as the anterior visual pathway (AVP), from MRI sequences is challenging due to their thin long architecture, structural variations along the path, and low contrast with adjacent anatomic structures. Segmentation of a pathologic AVP (e.g., with low-grade gliomas) poses additional challenges. In this work, we propose a fully automated partitioned shape model segmentation mechanism for AVP steered by multiple MRI sequences and deep learning features. Employing deep learning feature representation, this framework presents a joint partitioned statistical shape model able to deal with healthy and pathological AVP. The deep learning assistance is particularly useful in the poor contrast regions, such as optic tracts and pathological areas. Our main contributions are: 1) a fast and robust shape localization method using conditional space deep learning, 2) a volumetric multiscale curvelet transform-based intensity normalization method for robust statistical model, and 3) optimally partitioned statistical shape and appearance models based on regional shape variations for greater local flexibility. Our method was evaluated on MRI sequences obtained from 165 pediatric subjects. A mean Dice similarity coefficient of 0.779 was obtained for the segmentation of the entire AVP (optic nerve only =0.791) using the leave-one-out validation. Results demonstrated that the proposed localized shape and sparse appearance-based learning approach significantly outperforms current state-of-the-art segmentation approaches and is as robust as the manual segmentation.
Ethnic Differences in Delays to Treatment for Substance Use Disorders: African Americans, Black Caribbeans and Non-Hispanic Whites

Abstract Prior research has shown that minority groups experience greater levels of disability associated with psychiatric and substance use conditions due to barriers to treatment. Treatment delays are an important part of the overall problem of service utilization and access to treatment, yet little work has been done to understand the factors associated with treatment delays among ethnic minorities. This study compares African Americans, Caribbean Blacks and non-Hispanic Whites regarding their probability of making treatment contacts over time, using a combined sample of African Americans and Caribbean Blacks from the National Survey of American Life (NSAL) and non-Hispanic Whites from the National Comorbidity Survey-Replication (NCS-R). Alcohol and other drug use disorders (abuse and dependence) were assessed using the World Mental Health Composite International Diagnostic Interview. Cumulative lifetime probability curves were used to examine race differences in treatment contact. Cox regression analysis was used to test the association between race and treatment groups while controlling for other potential confounding variables. Significant delays in making treatment contact were observed across all disorders. However, no evidence of delays was found for racial differences. In the multivariate analysis, race was not significantly associated with delays. However, comorbid anxiety disorders were found to be a consistent factor associated with a faster time to treatment.
Heat Transfer in an Enhanced Cable Insulation Scheme for the Superconducting Magnets of the LHC Luminosity Upgrade

The next generation of superconducting magnets for the interaction regions of particle colliders, as well as for fast cycled accelerators, will be confronted with large heat loads. In order to improve the evacuation of heat from the Nb-Ti coil towards He-II bath, a porous (enhanced) all-polyimide cable insulation scheme was proposed recently. The first results were promising, featuring a larger permeability to helium with respect to existing schemes under low compressive stress. In this paper we present an extended experimental study of heat transfer through the Enhanced Insulation into He-II bath, and comparison to the standard LHC insulation, at different levels of applied pressure. The thermal coupling between adjacent cables was investigated, as well as the impact of a localized heat deposition versus a distributed one. The results of this study show that, up to high pressure levels, the enhanced insulation scheme can provide a major improvement of heat transfer compared to the standard scheme used in the main LHC magnets.
Long‐Range Movement of Humpback Whales and Their Overlap with Anthropogenic Activity in the South Atlantic Ocean

Humpback whales (Megaptera novaeangliae) are managed by the International Whaling Commission as 7 primary populations that breed in the tropics and migrate to 6 feeding areas around the Antarctic. There is little information on individual movements within breeding areas or migratory connections to feeding grounds. We sought to better understand humpback whale habitat use and movements at breeding areas off West Africa, and during the annual migration to Antarctic feeding areas. We also assessed potential overlap between whale habitat and anthropogenic activities. We used Argos satellite‐monitored radio tags to collect data on 13 animals off Gabon, a primary humpback whale breeding area. We quantified habitat use for 3 cohorts of whales and used a state‐space model to determine transitions in the movement behavior of individuals. We developed a spatial metric of overlap between whale habitat and models of cumulative human activities, including oil platforms, toxicants, and shipping. We detected strong heterogeneity in movement behavior over time that is consistent with previous genetic evidence of multiple populations in the region. Breeding areas for humpback whales in the eastern Atlantic were extensive and extended north of Gabon late in the breeding season. We also observed, for the first time, direct migration between West Africa and sub‐Antarctic feeding areas. Potential overlap of whale habitat with human activities was the highest in exclusive economic zones close to shore, particularly in areas used by both individual whales and the hydrocarbon industry. Whales potentially overlapped with different activities during each stage of their migration, which makes it difficult to implement mitigation measures over their entire range. Our results and existing population‐level data may inform delimitation of populations and actions to mitigate potential threats to whales as part of local, regional, and international management of highly migratory marine species.
Mining Frequent Patterns from Uncertain Databases

: — In Many Real time application like sensors monitoring system, location based system and data integration are inexact in nature. It is difficult to extract frequent Item sets from these kind of application because of uncertainty. We study the problem of mining frequent itemsets from uncertain data under Possible Semantic Worlds (PSW). Uncertain database contain exponential large number of possible semantic worlds. We consider transactions whose items are associated with existential probabilities and give a formal definition of frequent patterns from uncertain data model. By observing that the mining process can be modelled as a Poisson binomial distribution, an algorithm was developed, which can efficiently and accurately discover frequent item sets in a large uncertain database. We are adopting mining algorithm which identifies Probabilistic Frequent Itemset (PFI) from evolving database. Traditional algorithms for mining frequent itemsets are inapplicable or computationally inefficient for uncertain database. Implementing incremental algorithm which can efficiently accurately discovered frequent item set in large uncertain database.
Antigenic Specificity of Serum Antibodies in Mice Fed Soy Protein

Background: Soybean protein is used in a number of food products but unfortunately is also a common cause of food allergy. Upon ingestion of soy protein, healthy mice like other animals and humans generate a soy-specific antibody response in the absence of signs of illness. Not much is known about the relationship between the immunogenic proteins involved in this nondeleterious antibody response and the pathological response associated with food allergy.The objective of the present study was to characterize the antigenic specificity of the soy protein-specific antibody response generated in healthy mice ingesting soy protein. Methods: Blood from mice fed a soy-containing diet was analyzed using ELISA and immunoblot for antibody reactivity towards various soy protein fractions and pure soy proteins/subunits. Mice bred on a soy-free diet were used as controls. Results: The detectable antigenic specificity of the serum antibodies of soy-consuming mice comprised glycinin and β-conglycinin. Immunoblots with soy protein extract demonstrated antibody reactivity towards both the basic and the acidic chains of glycinin and the β-conglycinin subunits with an individual response pattern among mice. Moreover, antibody reactivity was found towards the native quaternary structure of glycinin. Conclusions: Mice ingesting soy protein generate an antibody response with reactivity towards glycinin and β-conglycinin. Antibody reactivity found towards the native quaternary structure of glycinin indicates an oral immunogenicity of the highly processing-resistant oligomerized glycinin.
hcp Ising model in the cluster-variation approximation.

We present a study of the hexagonal-close-packed Ising model for binary alloys within the cluster-variation approximation. Ground states of order stabilized by interactions that span the next-nearest-neighbor (NNN) distance (octahedron and all of its subclusters) were determined with the cluster-configuration polyhedron method. We predict 32 physically realizable ground states with stoichiometries [ital A], [ital AB], [ital A][sub 2][ital B], [ital A][sub 3][ital B], [ital A][sub 5][ital B], and [ital A][sub 4][ital B3]. Of these structures, six are stabilized by NN pairs and eight by NNN pairs; the remaining 18 structures require multiplet interactions for their stability. The results in this study are consistent with previous pair-interaction studies. Information concerning ground states and their domains of stability was then used in conjunction with the cluster-variation method (CVM) to calculate the finite-temperature phase equilibria for prototypical binary alloys. We present ordering phase diagrams computed with the CVM that contain all relevant ground states for both isotropic and anisotropic NN pair interactions. The results of the ground-state and CVM calculations are compared with those for ordering on the face-centered-cubic lattice.
Automatic RF power adjustment for WirelessHART field devices

Industrial wireless networks are gradually being adopted in industry, especially due to the low installation costs and low maintenance provided by these systems. For the use in harsh environments, the communication system should provide reliable radio links and low power to allow battery powered devices. In this context, WirelessHART, ISA SP100.11a and WIA-PA protocols were developed to meet these requirements. The standards of these protocols define a minimum number of RF fixed power and selectable only by commissioning. Within this scenario, it is important to adapt RF power modulation, a procedure already used in several communication protocols to minimize the energy consumption of transceivers while maintaining link quality. In this paper, three ways to modulate RF power are analyzed within WirelessHART field devices. A specific approach that works in a decentralized way is developed and the results show it can save 50% of energy in certain cases. The proposal has the extra advantage to be compatible with the standard.
Modification of the KCF tracking method for implementation on embedded hardware platforms

This paper presents an improved kernelized correlation filters method for implementation on embedded hardware platforms. A software realization of the improved tracking method is developed and tested. The proposed method implemented on a personal computer platform can easily track any objects in real-time, and the same opportunity exists for the ARM platform (CPU Cortex-A8, frequency 1 GHz), but for small objects.
FISHER VECTOR FACES IN THE WILD 3 Facial landmark detection Aligned and cropped face Dense SIFT , GMM , and FV Discriminative dim

Several recent papers on automatic face verification have significantly raised the performance bar by developing novel, specialised representations that outperform standard features such as SIFT for this problem. This paper makes two contributions: first, and somewhat surprisingly, we show that Fisher vectors on densely sampled SIFT features, i.e. an off-the-shelf object recognition representation, are capable of achieving state-of-the-art face verification performance on the challenging “Labeled Faces in the Wild” benchmark; second, since Fisher vectors are very high dimensional, we show that a compact descriptor can be learnt from them using discriminative metric learning. This compact descriptor has a better recognition accuracy and is very well suited to large scale identification tasks.
Image super-resolution using conditional generative adversarial network

Recently, extensive studies on a generative adversarial network (GAN) have made great progress in single image super-resolution (SISR). However, there still exists a significant difference between the reconstructed high-frequency and the real high-frequency details. To address this issue, this study presents an SISR approach based on conditional GAN (SRCGAN). SRCGAN includes a generator network that generates super-resolution (SR) images and a discriminator network that is trained to distinguish the SR images from ground-truth high-resolution (HR) ones. Specifically, the discriminator network uses the ground-truth HR image as a conditional variable, which guides the network to distinguish the real images from the SR images, facilitating training a more stable generator model than GAN without this guidance. Furthermore, a residual-learning module is introduced into the generator network to solve the issue of detail information loss in SR images. Finally, the network is trained in an end-to-end manner by optimizing a perceptual loss function. Extensive evaluations on four benchmark datasets including Set5, Set14, BSD100, and Urban100 demonstrate the superiority of the proposed SRCGAN over state-of-the-art methods in terms of PSNR, SSIM, and visual effect.