An Automatic Commercial Search Application for TV Broadcasting Using Audio Fingerprinting

Nowadays, TV advertising is an important part of our daily life. However, it is usually hard for organizations that produce and pay for the advertisements to confirm whether their commercials are broadcasted as required in time and frequency. Consequently, a multimedia file search problem arises and it has drawn more and more attention in the past decade. In this thesis, we propose an automatic commercial search scheme using audio fingerprinting and implement it in a PC-based application. Our commercial search algorithm is composed of two parts: one for audio feature extraction and another for database search. For the first part, although the video stream of TV broadcast contains a great deal of intuitive information, we decide to ignore it because it takes much more storage and computations to process. For the audio stream, we have to extract proper audio features which can represent its characteristics and store them in a database for identification. We choose the Normalized Spectral Subband Centroids (NSSCs) as our audio fingerprints and preprocess the known commercials to build the database. For the second part, we apply a three-step process to search for any matches as the user requests, which comprises candidate search, decision-making and time verification. This process is performed for every N1 (N1=15 in our application) frames if the search result is negative. Once a match is confirmed, we skip the frames left in the commercial and use the frame after it to start a new process. Our experiment results are satisfactory based on the commercial and TV program data in our database. Moreover, it shows that our PC-based application is robust against degradation during real broadcast and recording

Self-Supervised Texture Image Anomaly Detection By Fusing Normalizing Flow and Dictionary Learning

A common study area in anomaly identification is industrial images anomaly detection based on texture background. The interference of texture images and the minuteness of texture anomalies are the main reasons why many existing models fail to detect anomalies. We propose a strategy for anomaly detection that combines dictionary learning and normalizing flow based on the aforementioned questions. The two-stage anomaly detection approach already in use is enhanced by our method. In order to improve baseline method, this research add normalizing flow in representation learning and combines deep learning and dictionary learning. Improved algorithms have exceeded 95$\%$ detection accuracy on all MVTec AD texture type data after experimental validation. It shows strong robustness. The baseline method's detection accuracy for the Carpet data was 67.9%. The article was upgraded, raising the detection accuracy to 99.7%

Proteomic analysis of the biomass hydrolytic potentials of Penicillium oxalicum lignocellulolytic enzyme system

Additional file 2: Table S1. The functional annotations of proteins identified in the proteome of SP. Mass spectrometry-based proteomics study was performed to comprehensively dissect the lignocellulolytic enzyme profile of SP. Accession, Protein name, PSM, Calc. MW, CBM, Calc. pI and CAZy family of identified proteins were shown

Antiferromagnetic metal phase in an electron-doped rare-earth nickelate

Long viewed as passive elements, antiferromagnetic materials have emerged as promising candidates for spintronic devices due to their insensitivity to external fields and potential for high-speed switching. Recent work exploiting spin and orbital effects has identified ways to electrically control and probe the spins in metallic antiferromagnets, especially in noncollinear or noncentrosymmetric spin structures. The rare earth nickelate NdNiO3 is known to be a noncollinear antiferromagnet where the onset of antiferromagnetic ordering is concomitant with a transition to an insulating state. Here, we find that for low electron doping, the magnetic order on the nickel site is preserved while electronically a new metallic phase is induced. We show that this metallic phase has a Fermi surface that is mostly gapped by an electronic reconstruction driven by the bond disproportionation. Furthermore, we demonstrate the ability to write to and read from the spin structure via a large zero-field planar Hall effect. Our results expand the already rich phase diagram of the rare-earth nickelates and may enable spintronics applications in this family of correlated oxides.Comment: 25 pages, 4 figure

Serum Fetuin-A Associates with Type 2 Diabetes and Insulin Resistance in Chinese Adults

Previous studies have demonstrated that fetuin-A is related to insulin resistance among subjects with normal glucose tolerance but not patients with type 2 diabetes. There are limited data available concerning fetuin-A and insulin resistance in Chinese. We aimed to study the association of fetuin-A with insulin resistance among participants with or without type 2 diabetes in a large sample size of adults aged 40 and older.A community-based cross-sectional study was performed among 5,227 Chinese adults. The average age of our study was 61.5±9.9 years. Serum fetuin-A concentrations were not significantly different between male and female (296.9 vs. 292.9 mg/l, p = 0.11). Compared with the lowest quartile, the highest quartile of serum fetuin-A revealed a significant higher proportion of type 2 diabetic patients (34.8% vs. 27.3%, p<0.0001). In the multinomial logit models, the risk of type 2 diabetes was associated with each one quartile increase of serum fetuin-A concentrations when referenced not only to normal glucose tolerance (OR 1.24, 95% CI 1.07-1.43, p = 0.004) but also to impaired glucose regulation (OR 1.25, 95% CI 1.08-1.44, p = 0.003, respectively), after adjustment for age, sex, community, current smoking, and current drinking. The logistic regression analysis showed that fetuin-A were associated with elevated HOMA-IR and fasting serum insulin both among the participants with or without type 2 diabetes in the full adjusted analysis. There was no significant association between elevated serum fetuin-A concentrations and impaired glucose regulation (all p≥0.12).Higher fetuin-A concentrations were associated with type 2 diabetes and insulin resistance in middle aged and elderly Chinese

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Neurological Manifestations in Familial Mediterranean Fever

Familial Mediterranean fever (FMF) is an autoinflammatory disease caused by mutations of the MEFV gene. The main clinical manifestations are recurrent fever and serous inflammation in various parts of the body. Some patients with FMF may also develop neurological manifestations such as epilepsy, demyelinating disease, aseptic meningitis. As neurological manifestations are rare in patients with FMF, the association between the two is often overlooked in clinical practice. In this paper, we reviewed the neurological manifestations of FMF and their relationship with genotypes, so as to deepen the understanding of the clinical manifestations of FMF and provide help for the diagnosis and treatment of patients with neurological manifestations

Predicting Cooling Loads for the Next 24 Hours Based on General Regression Neural Network: Methods and Results

Predicting cooling load for the next 24 hours is essential for the optimal control of air-conditioning systems that use thermal cool storage. This study investigated modeling methods of applying the general regression neural network (GRNN) technology to predict load. The single stage (SS) and double stage (DS) prediction methods were introduced. Two SS and two DS models were set up for forecasting the next 24 hours' cooling load. Measured data collected from two five star hotels located in Sanya, China, were used to train and test these models. The results demonstrate that the SS method, which can eliminate the necessity for measuring and predicting meteorological data, is much simpler and reliable for predicting the cooling load in practical applications

Metformin-loaded PLGA microspheres combined with an in situ-formed injectable SA/BG hydrogel alleviate rotator cuff muscle degeneration

Rotator cuff tears are a prevalent musculoskeletal problem that affect many individuals and may result in substantial social and health-related expenses. Moreover, the muscular fat infiltration and dystrophy associated with rotator cuff tears have been persistent challenges in rotator cuff surgical repair and postoperative rehabilitation. In this study, an in situ-formed injectable sodium alginate (SA) and bioglass (BG) hydrogel consisting of poly (lactic-co-glycolic acid) (PLGA) microspheres containing metformin (SA/BG-PLGA-Met) was developed for the prevention of muscular fat infiltration and dystrophy. Metformin and silicon ions were slowly released by the combined hydrogel, resulting in long-term biological effects. Moreover, the hydrogel displayed excellent degradability and biocompatibility. Extracts of SA/BG-PLGA-Met inhibited the adipogenesis of 3T3-L1 cells and stimulated the myogenic differentiation of C2C12 cells in vitro. In a mouse model of rotator cuff degeneration, the SA/BG-PLGA-Met hydrogel inhibited fat infiltration and dystrophy of the supraspinatus muscle. Overall, the SA/BG-PLGA-Met hydrogel, as a novel biomaterial, has great clinical potential for preventing rotator cuff muscle fat infiltration and atrophy