A Compact and Discriminative Feature Based on Auditory Summary Statistics for Acoustic Scene Classification

One of the biggest challenges of acoustic scene classification (ASC) is to find proper features to better represent and characterize environmental sounds. Environmental sounds generally involve more sound sources while exhibiting less structure in temporal spectral representations. However, the background of an acoustic scene exhibits temporal homogeneity in acoustic properties, suggesting it could be characterized by distribution statistics rather than temporal details. In this work, we investigated using auditory summary statistics as the feature for ASC tasks. The inspiration comes from a recent neuroscience study, which shows the human auditory system tends to perceive sound textures through time-averaged statistics. Based on these statistics, we further proposed to use linear discriminant analysis to eliminate redundancies among these statistics while keeping the discriminative information, providing an extreme com-pact representation for acoustic scenes. Experimental results show the outstanding performance of the proposed feature over the conventional handcrafted features.Comment: Accepted as a conference paper of Interspeech 201

Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events

In this paper, we propose a new strategy for acoustic scene classification (ASC) , namely recognizing acoustic scenes through identifying distinct sound events. This differs from existing strategies, which focus on characterizing global acoustical distributions of audio or the temporal evolution of short-term audio features, without analysis down to the level of sound events. To identify distinct sound events for each scene, we formulate ASC in a multi-instance learning (MIL) framework, where each audio recording is mapped into a bag-of-instances representation. Here, instances can be seen as high-level representations for sound events inside a scene. We also propose a MIL neural networks model, which implicitly identifies distinct instances (i.e., sound events). Furthermore, we propose two specially designed modules that model the multi-temporal scale and multi-modal natures of the sound events respectively. The experiments were conducted on the official development set of the DCASE2018 Task1 Subtask B, and our best-performing model improves over the official baseline by 9.4% (68.3% vs 58.9%) in terms of classification accuracy. This study indicates that recognizing acoustic scenes by identifying distinct sound events is effective and paves the way for future studies that combine this strategy with previous ones.Comment: code URL typo, code is available at https://github.com/hackerekcah/distinct-events-asc.gi

A microencapsulation approach to design microbial seed coatings to boost wheat seed germination and seedling growth under salt stress

IntroductionSalt stress in seed germination and early seedling growth is the greatest cause of crop loss in saline-alkali soils. Microbial seed coating is an effective way to promote plant growth and salt resistance, but these coatings suffer from poor seed adhesion and low survival rates under typical storage conditions.MethodsIn this study, the marine bacterium Pontibacter actiniarum DSM 19842 from kelp was isolated and microencapsulated with calcium alginate using the emulsion and internal gelation method.ResultsCompared to unencapsulated seeds, the spherical microcapsules demonstrated a bacterial encapsulation rate of 65.4% and survival rate increased by 22.4% at 25°C for 60 days. Under salt stress conditions, the seed germination percentage of microcapsule-embedded bacteria (M-Embed) was 90%, which was significantly increased by 17% compared to the germination percentage (73%) of no coating treatment (CK). Root growth was also significantly increased by coating with M-Embed. Chlorophyll, peroxidase, superoxide dismutase, catalase, proline, hydrogen peroxide and malondialdehyde levels indicated that the M-Embed had the best positive effects under salt stress conditions.DiscussionTherefore, embedding microorganisms in suitable capsule materials provides effective protection for the survival of the microorganism and this seed coating can alleviate salt stress in wheat. This process will benefit the development of sustainable agriculture in coastal regions with saline soils

Identification and characterization of circular RNAs in mammary gland tissue from sheep at peak lactation and during the nonlactating period

Circular RNAs are a class of noncoding RNA with a widespread occurrence in eukaryote tissues, and with some having been demonstrated to have clear biological function. In sheep, little is known about the role of circular RNAs in mammary gland tissue, and therefore an RNA sequencing approach was used to compare mammary gland tissue expression of circular RNAs in 9 Small Tail Han sheep at peak lactation, and subsequently when they were not lactating. These 9 sheep had their RNA pooled for analysis into 3 libraries from peak lactation and 3 from the nonlactating period. A total of 3,278 and 1,756 circular RNAs were identified in the peak lactation and nonlactating mammary gland tissues, respectively, and the expression and identity of 9 of them was confirmed using reverse transcriptase-polymerase chain reaction analysis and DNA sequencing. The type, chromosomal location and length of the circular RNAs identified were ascertained. Forty upregulated and one downregulated circular RNAs were characterized in the mammary gland tissue at peak lactation compared with the nonlactating mammary gland tissue. Gene ontology enrichment analysis revealed that the parental genes of these differentially expressed circular RNAs were related to molecular function, binding, protein binding, ATP binding, and ion binding. Five differentially expression circular RNAs were selected for further analysis to predict their target microRNAs, and some microRNAs reportedly associated with the development of the mammary gland were found in the constructed circular RNA–microRNA network. This study reveals the expression profiles and characterization of circular RNAs at 2 key stages of mammary gland activity, thereby providing an improved understanding of the roles of circular RNAs in the mammary gland of sheep

Molecular Cloning and Characterization of Two Genes Encoding Dihydroflavonol-4-Reductase from Populus trichocarpa

Dihydroflavonol 4-reductase (DFR, EC 1.1.1.219) is a rate-limited enzyme in the biosynthesis of anthocyanins and condensed tannins (proanthocyanidins) that catalyzes the reduction of dihydroflavonols to leucoanthocyanins. In this study, two full-length transcripts encoding for PtrDFR1 and PtrDFR2 were isolated from Populus trichocarpa. Sequence alignment of the two PtrDFRs with other known DFRs reveals the homology of these genes. The expression profile of PtrDFRs was investigated in various tissues of P. trichocarpa. To determine their functions, two PtrDFRs were overexpressed in tobacco (Nicotiana tabacum) via Agrobacterium-mediated transformation. The associated color change in the flowers was observed in all 35S:PtrDFR1 lines, but not in 35S:PtrDFR2 lines. Compared to the wild-type control, a significantly higher accumulation of anthocyanins was detected in transgenic plants harboring the PtrDFR1. Furthermore, overexpressing PtrDFR1 in Chinese white poplar (P. tomentosa Carr.) resulted in a higher accumulation of both anthocyanins and condensed tannins, whereas constitutively expressing PtrDFR2 only improved condensed tannin accumulation, indicating the potential regulation of condensed tannins by PtrDFR2 in the biosynthetic pathway in poplars

Enhancing Personalized Trip Recommendation with Attractive Routes

Personalized trip recommendation tries to recommend a sequence of point of interests (POIs) for a user. Most of existing studies search POIs only according to the popularity of POIs themselves. In fact, the routes among the POIs also have attractions to visitors, and some of these routes have high popularity. We term this kind of route as Attractive Route (AR), which brings extra user experience. In this paper, we study the attractive routes to improve personalized trip recommendation. To deal with the challenges of discovery and evaluation of ARs, we propose a personalized Trip Recommender with POIs and Attractive Route (TRAR). It discovers the attractive routes based on the popularity and the Gini coefficient of POIs, then it utilizes a gravity model in a category space to estimate the rating scores and preferences of the attractive routes. Based on that, TRAR recommends a trip with ARs to maximize user experience and leverage the tradeoff between the time cost and the user experience. The experimental results show the superiority of TRAR compared with other state-of-the-art methods

ACM: Accuracy-Aware Collaborative Monitoring for Software-Defined Network-Wide Measurement

Software-defined measurement (SDM) is a simple and efficient way to deploy measurement tasks and collect measurement data. With SDM, it is convenient for operators to implement fine-grained network-wide measurements at the flow level, from which many important functions can benefit. The prior work provides mechanisms to distribute flows to monitors, such that each monitor can identify its non-overlapped subset of flows to measure, and a certain global performance criterion is optimized, such as load balance or flow coverage. Many applications of network management can benefit from a function that can find large flows efficiently, such as congestion control by dynamically scheduling large flows, caching of forwarding table entries, and network capacity planning. However, the current network-wide measurements neglect the diversity of different flows as they treat large flows and small flows equally. In this paper, we present a mechanism of accuracy-aware collaborative monitoring (ACM) to improve the measurement accuracies of large flows in network-wide measurements at the flow level. The structure of the sketch is an approximate counting algorithm, and a high-measurement accuracy can be achieved by merging the results from multiple monitors with sketches, which is termed as collaborative monitoring. The core idea of our method is to allocate more monitors to large flows and achieve the load balance to provide accuracy-aware monitoring. We modeled our problem as an integer–linear programming problem, which is NP-hard. Thus, we propose an approximation algorithm, named the improved longest processing time algorithm (iLPTA); we proved that its approximation ratio is (12+nl). We propose a two-stage online distribution algorithm (TODA). Moreover, we proved that its approximation ratio is (1+nl−1). The iLPTA is an offline approximation algorithm used to assign monitors for each flow, which prove the validity and feasibility of the core idea. The TODA is an online algorithm that attempts to achieve the load balance by selecting the monitor with the smallest load to a large flow. Our extensional experiment results verify the effectiveness of our proposed algorithms

Safe and Efficient Recovery Technique of Horizontal Isolated Pillar under Loose Tailings Backfill; A Case Study in a Zinc-Lead Mine

The presence of loose medium backfill above the horizontal pillar will technically hinder the efficient recovery of the pillar since the improper design and preserved roof protection layer height will potentially lead to casualties and equipment damage caused by large area collapse of filled tailings as well as roof fall accidents. In this study, a safe and efficient technique for the recovery of isolated pillars under loose tailings backfill was carried out via field investigation, theoretical analysis, numerical simulation, and analytic hierarchy process using the isolated pillars in the 855 middle sublevel of Hongling Zinc-Lead Mine, Chifeng, Inner Mongolia, as a practical engineering background. Current studies have revealed that the optimal scheme for an isolated horizontal pillar recovered via the cut-and-fill stoping of a drift vertical to ore body strike involves preserving a 1.0-m roof protection layer above the crown pillar combined with a spaced mining extraction sequence. This design minimizes ore dilution and losses during the pillar extraction process under safe operation. Our research results provide theoretical and technical support for the safe and efficient recovery of isolated pillars under loose tailings backfill in similar mines

Safe and Efficient Recovery Technique of Horizontal Isolated Pillar under Loose Tailings Backfill; A Case Study in a Zinc-Lead Mine

The presence of loose medium backfill above the horizontal pillar will technically hinder the efficient recovery of the pillar since the improper design and preserved roof protection layer height will potentially lead to casualties and equipment damage caused by large area collapse of filled tailings as well as roof fall accidents. In this study, a safe and efficient technique for the recovery of isolated pillars under loose tailings backfill was carried out via field investigation, theoretical analysis, numerical simulation, and analytic hierarchy process using the isolated pillars in the 855 middle sublevel of Hongling Zinc-Lead Mine, Chifeng, Inner Mongolia, as a practical engineering background. Current studies have revealed that the optimal scheme for an isolated horizontal pillar recovered via the cut-and-fill stoping of a drift vertical to ore body strike involves preserving a 1.0-m roof protection layer above the crown pillar combined with a spaced mining extraction sequence. This design minimizes ore dilution and losses during the pillar extraction process under safe operation. Our research results provide theoretical and technical support for the safe and efficient recovery of isolated pillars under loose tailings backfill in similar mines