An overview of smart packaging technologies for monitoring safety and quality of meat and meat products

The food packaging sector has experienced much development since its inception. In the past few decades, innovations in packaging sector have led to the development of smart packaging (SP) systems that carve a niche in a highly competitive food industry. SP systems have great potential for improving the shelf‐life, and safety of food products apart from their basic roles of protecting the products against unwanted biological, chemical, and physical damage and keeping them clean. Indicators and sensors, SP components, are used for real‐time monitoring of meat quality and subsequently inform the retailers and consumers about the freshness, microbiological, temperature, and shelf life status of the products. Barcodes and radio‐frequency identification tags are employed in meat packaging for real‐time information about the authenticity, and traceability of the products in the supply chain. Recently, innovations in SP technologies resulted in fast, sensitive, and effective detection, sensing, and record keeping of freshness, microbiological, and shelf life status of meat and meat products. The SP system shows promise for extensive utilization in the meat industry in response to the consumer appreciation for safe, and quality meat products, as well as their waste reduction notions. This paper gives an updated overview of ongoing scientific research, and recent technological advances that offer the perspectives of developing smart meat packaging systems that are capable of monitoring the physical, microbial, and chemical changes of the package contents from producer to the point of sale and even beyond, and remediating potential adverse reactions.     

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.

     

Coherent control of symmetric and asymmetric diffraction grating via relative phase

ABSTRACT

We present a theoretical model to realize the symmetric and asymmetric diffraction grating in a four-level atomic medium. The proposed atomic medium follows a double lambda configuration where four fields interact with it. We get control over symmetric and asymmetric behavior of the diffraction grating by manipulating the relative phase of the fields. Interestingly, the symmetric and asymmetric diffraction grating become prominent when the vortex beam is used instead of the plane wave. Enhanced first, second, and third-order diffraction gratings are achieved via the vortex beam. Further, we find control over asymmetric diffraction gratings by the relative phase of the fields. Coherent control of asymmetric diffraction grating in negative and positive diffracted angles is also achieved via the relative phase.     

Synthesis and application of magnetite polyacrylamide amino-amidoxime nano-composites as adsorbents for water pollutants

In this work, we aimed to develop a feasible method for in situ preparation of a magnetite ionic polymer nanocomposite at room temperature. For this purpose, acrylonitrile (AN) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) monomers were copolymerized and crosslinked using different monomer mol ratios in the presence of N,N-methylenebisacrylamide (MBA) as crosslinker to produce ionic crosslinked polymers P(AN-co-AMPS. The nitrile groups were converted to amine amidoxime by reacting with hydroxylamine to increase the adsorption characteristics of the ionic polymers. The produced polymers were swelled in iron cations produced from the reaction of ferric chloride and potassium iodide, followed by reaction with an ammonium hydroxide solution to produce magnetite nano-polymer composites. We performed FT-IR and XRD analysis to determine the chemical and crystalline structures, and assessed the morphologies and magnetite content using SEM, TEM and TGA analyses. We investigated the adsorption capacity and mechanism of the prepared magnetite nano-composites as adsorbents for methylene blue, Co²⁺ and Ni²⁺ cations from water.     

Theranostic Interpolation of Genomic Instability in Breast Cancer

Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. “Omics” technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.     

The Therapeutic Potential of Exosomes in Soft Tissue Repair and Regeneration

Soft tissue defects are common following trauma and tumor extirpation. These injuries can result in poor functional recovery and lead to a diminished quality of life. The healing of skin and muscle is a complex process that, at present, leads to incomplete recovery and scarring. Regenerative medicine may offer the opportunity to improve the healing process and functional outcomes. Barriers to regenerative strategies have included cost, regulatory hurdles, and the need for cell-based therapies. In recent years, exosomes, or extracellular vesicles, have gained tremendous attention in the field of soft tissue repair and regeneration. These nanosized extracellular particles (30–140 nm) can break the cellular boundaries, as well as facilitate intracellular signal delivery in various regenerative physiologic and pathologic processes. Existing studies have established the potential of exosomes in regenerating tendons, skeletal muscles, and peripheral nerves through different mechanisms, including promoting myogenesis, increasing tenocyte differentiation and enhancing neurite outgrowth, and the proliferation of Schwann cells. These exosomes can be stored for immediate use in the operating room, and can be produced cost efficiently. In this article, we critically review the current advances of exosomes in soft tissue (tendons, skeletal muscles, and peripheral nerves) healing. Additionally, new directions for clinical applications in the future will be discussed.     

Monte Carlo study of ion-induced secondary electron emission from SiO2

Here we describe a recently developed direct Monte Carlo program to study kinetic electron emission from SiO₂ target. The program includes excitation of the target electrons (by projectile ions, recoiling target atoms and fast primary electrons), subsequent transport and escape of these electrons from the target surface. The program can be used to calculate the electron yields, distribution of electron excitation points in the target and other physical parameters of the emitted electrons. In order to demonstrate the capabilities of this program, we report a study on the kinetic electron emission from SiO₂ induced by fast (1-10 keV) rare gas ions. The calculated kinetic electron yield for various ion energies and masses is in good agreement with the predictions of most frequently applied theoretical model. In addition, the effects of projectile energy, mass and impact angle on the depth distribution of electron excitation points and average escape depth of the outgoing electrons were investigated. It is important to mention that the existing experimental techniques are not capable to measure these parameters.     

Variation in patient dose due to differences in calibration and dosimetry protocols

For precise and accurate patient dose delivery,the dosimetry system must be calibrated properly according to the recommendations of standard dosimetry protocols such as TG-51 and TRS-398. However, the dosimetry protocol followed by a calibration laboratory is usually different from the protocols that are followed by different clinics, which may result in variations in the patient dose.Our prime objective in this study was to investigate the effect of the two protocols on dosimetry measurements.Dose measurements were performed for a Co-60 teletherapy unit and a high-energy Varian linear accelerator with 6 and 15 MV photon and 6, 9, 12, and 15 MeV electron beams, following the recommendations and procedures of the AAPM TG-51 and IAEA TRS-398 dosimetry protocols. The dosimetry systems used for this study were calibrated in a Co-60 radiation beam at the Secondary Standard Dosimetry Laboratory(SSDL) PINSTECH,Pakistan, following the IAEA TRS-398 protocol. The ratio of the measured absorbed doses to water in clinical setting,D_w(TG-51/TRS-398), was 0.999 and 0.997 for 6 and15 MV photon beams,whereas these ratios were 1.013,1.009, 1.003, and 1.000 for 6, 9, 12, and 15 MeV electron beams, respectively. This difference in the absorbed dosesto-water D_w ratio may be attributed mainly due to beam quality(K_Q) and ion recombination correction factor.