Deep features-based speech emotion recognition for smart affective services

Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we present a study of speech emotion recognition based on the features extracted from spectrograms using a deep convolutional neural network (CNN) with rectangular kernels. Typically, CNNs have square shaped kernels and pooling operators at various layers, which are suited for 2D image data. However, in case of spectrograms, the information is encoded in a slightly different manner. Time is represented along the x-axis and y-axis shows frequency of the speech signal, whereas, the amplitude is indicated by the intensity value in the spectrogram at a particular position. To analyze speech through spectrograms, we propose rectangular kernels of varying shapes and sizes, along with max pooling in rectangular neighborhoods, to extract discriminative features. The proposed scheme effectively learns discriminative features from speech spectrograms and performs better than many state-of-the-art techniques when evaluated its performance on Emo-DB and Korean speech dataset.

     

Discovery of Five New Ethylene-Forming Enzymes for Clean Production of Ethylene in E. coli

Ethylene is an essential platform chemical with a conjugated double bond, which can produce many secondary chemical products through copolymerisation. At present, ethylene production is mainly from petroleum fractionation and cracking, which are unsustainable in the long term, and harmful to our environment. Therefore, a hot research field is seeking a cleaner method for ethylene production. Based on the model ethylene-forming enzyme (Efe) {"type":"entrez-protein","attrs":{"text":"AAD16440.1","term_id":"4323597","term_text":"AAD16440.1"}}AAD16440.1 (6vp4.1.A) from Pseudomonas syringae pv. phaseolicol, we evaluated five putative Efe protein sequences using the data derived from phylogenetic analyses and the conservation of their catalytic structures. Then, pBAD expression frameworks were constructed, and relevant enzymes were expressed in E. coli BL21. Finally, enzymatic activity in vitro and in vivo was detected to demonstrate their catalytic activity. Our results show that the activity in vitro measured by the conversion of α-ketoglutarate was from 0.21–0.72 μmol ethylene/mg/min, which varied across the temperatures. In cells, the activity of the new Efes was 12.28–147.43 μmol/gDCW/h (DCW, dry cellular weight). Both results prove that all the five putative Efes could produce ethylene.     

Blocking the PCNA/NKp44 Checkpoint to Stimulate NK Cell Responses to Multiple Myeloma

Simple SummaryMembrane-associated PCNA is expressed on the surface of human MM cell lines and primary MM cells. Mab 14-25-9 interacts with membrane-associated PCNA and blocks its binding to NK-expressed NKp44, thus activating NK function. We showed that mAb 14-25-9 can serve as an immune checkpoint blocker, enhancing the function of NK cells on target human MM cell lines and primary cells.AbstractMultiple Myeloma (MM) is a devastating malignancy that evades immune destruction using multiple mechanisms. The NKp44 receptor interacts with PCNA (Proliferating Cell Nuclear Antigen) and may inhibit NK cells’ functions. Here we studied in vitro the expression and function of PCNA on MM cells. First, we show that PCNA is present on the cell membrane of five out of six MM cell lines, using novel anti-PCNA mAb developed to recognize membrane-associated PCNA. Next, we stained primary bone marrow (BM) mononuclear cells from MM patients and showed significant staining of membrane-associated PCNA in the fraction of CD38⁺CD138⁺ BM cells that contain the MM cells. Importantly, blocking of the membrane PCNA on MM cells enhanced the activity of NK cells, including IFN-γ-secretion and degranulation. Our results highlight the possible blocking of the NKp44-PCNA immune checkpoint by the mAb 14-25-9 antibody to enhance NK cell responses against MM, providing a novel treatment option.     

Influence of Y~(3+),Yb~(3+),Gd~(3+) cations on structural and electromagnetic properties of CuFe_2O_4 nanoferrites prepared via one step sol-gel method

Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications.     

Toward the modeling of data provenance in scientific publications

In this paper, we implement a provenance-aware system for documenting publications, called PADS. It employs a three-layered provenance hierarchy, which can output diverse types of provenance data related to the research life cycle. From this, we generate different profiles for research ventures, reviewers, and authors. PADS employs the standard Open Provenance Model (OPM) specification for capturing provenance data, and stores this data as ontological instances. We show that data is retrieved without any apparent delay in the execution time of the queries. We also demonstrate how this data can be used to make useful recommendations to the organizers, in order to manage upcoming research ventures.     

Analysis of optimized signal processing algorithms for smart antenna system

By the exponential increase in cellular communication area, the user demands and with their side problems also tend to increase. Several techniques such as cell splitting, frequency reuse, diversity and so on have already been applied to overcome these problems. In all these procedures, smart antenna is one of the best techniques used to boost capacities, enlarge bandwidth, raise the SIR ratios, minimize the effects of fading and improve MIMO communications. An ordinary antenna array which can turn up into a smart antenna array is due to the signal processing algorithms, which consists of angle of arrival (AOA) estimations and Beamforming. In this paper, I will discuss and analyse about the MUSIC algorithm for AOA estimation and least mean squares algorithm for Beamforming.     

A group theoretic approach to construct cryptographically strong substitution boxes

In this paper, we present a method to construct a substitution box used in encryption applications. The proposed algorithm for the construction of substitution box relies on the linear fractional transform method. The design methodology is simple, while the confusion-creating ability of the new substitution box is complex. The strength of the proposed substitution box is evaluated, and an insight is provided to quantify the confusion-creating ability. In addition, tests are performed to assess the vulnerability of the encrypted data to algebraic and statistical attacks. The substitution box is critically analyzed by strict avalanche criterion, bit independent criterion, differential approximation probability test, linear approximation probability test, non-linearity test, and majority logic criterion. The performance of the proposed substitution box is also compared with those of some of the well-known counterparts including AES, APA, Gray, S₈, Skipjack, Xyi, and prime of residue substitution boxes. It is apparent that the performance, in terms of confusion-creating ability, of the new substitution box is better than those of some of the existing non-linear components used in encryption systems. The majority logic criterion is applied to these substitution boxes to further evaluate the strength and usefulness.