Solar photocatalytic mineralization of isoproturon over TiO2/HY composite systems

The present investigation covers immobilization of titanium dioxide over HY support for the treatment of isoproturon pesticide. Catalysts are characterized by XRD, SEM–EDAX, TEM, BET surface area and UV–vis DRS. A detailed photocatalytic degradation study under solar light in aqueous suspensions with parameters like loading of TiO₂ over HY, amount of the catalyst, concentration of substrate, pH effect, durability of the catalyst and comparison between suspended TiO₂ and supported systems are reported. Mineralization of isoproturon is monitored by total organic carbon, chemical oxygen demand and a plausible mechanism is proposed for photocatalytic degradation based on degradation products.     

Development of a Tool Database Management System

This paper describes a systematic approach to the design and development of a tool management system for the valve production unit of Bharat Heavy Electricals Limited (BHEL) located in Trichirapalli, India. The salient features of the design and development of a centralised database for tools that contains information regarding tooling, tool location, allo-cation, tool flow, tool storage and retrieval, parts, machines, etc. are discussed. It is estimated that the system being developed will significantly reduce the downtime of machines due to unavailability of the appropriate tools.     

SABOS-Net: Self-supervised attention based network for automatic organ segmentation of head and neck CT images

The segmentation of Organs At Risk (OAR) in Computed Tomography (CT) images is an essential part of the planning phase of radiation treatment to avoid the adverse effects of cancer radiotherapy treatment. Accurate segmentation is a tedious task in the head and neck region due to a large number of small and sensitive organs and the low contrast of CT images. Deep learning-based automatic contouring algorithms can ease this task even when the organs have irregular shapes and size variations. This paper proposes a fully automatic deep learning-based self-supervised 3D Residual UNet architecture with CBAM(Convolution Block Attention Mechanism) for the organ segmentation in head and neck CT images. The Model Genesis structure and image context restoration techniques are used for self-supervision, which can help the network learn image features from unlabeled data, hence solving the annotated medical data scarcity problem in deep networks. A new loss function is applied for training by integrating Focal loss, Tversky loss, and Cross-entropy loss. The proposed model outperforms the state-of-the-art methods in terms of dice similarity coefficient in segmenting the organs. Our self-supervised model could achieve a 4% increase in the dice score of Chiasm, which is a small organ that is present only in a very few CT slices. The proposed model exhibited better accuracy for 5 out of 7 OARs than the recent state-of-the-art models. The proposed model could simultaneously segment all seven organs in an average time of 0.02 s. The source code of this work is made available at https://github.com/seeniafrancis/SABOSNet .     

Simultaneous speech coding and de-noising in a dictionary based quantized CS framework

Speech compression or speech coding is inevitable for effective communication of speech signals in resource limited scenarios and researcher’s have been working on achieving lower and lower transmission bit rates (BR) without much compromise on the quality of speech. Medium BR hybrid speech coding schemes have gained much interest in the recent years with most of them based on CELP, the basic medium bit-rate coding scheme. In this work, we provide an insight to the capabilities of compressive sensing (CS) in speech processing and propose a novel idea in the quantized framework. Three major aspects demonstrated in this paper are (1) Inherent de-noising of noisy speech by the CS based coder along with compression (2) Quantization of CS measurements to achieve medium transmission bit-rates and (3) Enhancement of quality and compression performance of the coder with better sparse representations of speech using dictionaries. The results indicate that the proposed scheme offers better compression in comparison with basic Gaussian codebook CELP. The CS scheme has the added advantage of inherent noise suppression and provides more robustness to background noise in comparison with parameter extraction based medium bit-rate speech coding systems.     

Solid state manipulation of lornoxicam for cocrystals – physicochemical characterization

Context: Lornoxicam is an analgesic and anti-inflammatory drug of choice and belongs to Class II (low solubility) of BCS (Biopharmaceutical Classification System). Thus bioavailabilities problems are predominant.

Objective: Through crystal engineering approach, a method was developed for obtaining multi-component cocrystals of lornoxicam using pharmaceutically acceptable compounds as guests.

Materials and methods: Lornoxicam guest-free form was obtained from solution crystallization. Supramolecular synthon approach indicated that lornoxicam was in orthorhombic form. Further presence of intermolecular hydrogen bonding with layered structures was identified. Solvent drop grinding method permitted the formation of cocrystals of lornoxicam with catechol, resorcinol, benzoic acid, hydroxyquinone and 2,4 dihydroxy benzoic acid, all are capable of forming hydrogen bonding.

Results and discussion: Lornoxicam cocrystals exhibited the difference in melting points and decomposition characteristics. The analysis of infrared (IR) indicated the shifting of characteristic bands of lornoxicam. The XPRD (X-Ray Powder Diffraction) pattern indicated the crystallinity of cocrystals and significant difference in 2θ value of intense peaks. Differential scanning calorimetry spectra of cocrystals denoted the changes in fusion endotherms, which are in agreements with melting points. The pH solubility profile of lornoxicam showed sigmoidal curve, which substantiated the pK_a-dependent solubility. Lornoxicam cocrystals also exhibited a similar pH-solubility profile. Thus pairing of lornoxicam and coformers in the solution at high pH media was assumed. The in vitro dissolution studies of cocrystals were conducted at pH 4.0. The rapid rate of dissolution of cocrystals was observed in initial 10?min. The extent of dissolution was enhanced by 20% on account of cocrystallization.

Conclusion: The lornoxicam cocrystals were obtained with improved physicochemical characteristics.     

Kinetics of cumene synthesis over ferrisilicate of MFI structure

Benzene isopropylation over medium port ferrisilicate to obtain cumene has been studied. Effects of reaction conditions on cumene selectivity are discussed. Based on the reaction network, various models were derived and fitted to kinetic data. A simple stoichiometric model represented the kinetic data significantly better than other models. Estimated activation energy values indicated that benzene alkylation is faster than cumene isomerisation to n-propylbenzene.     

An adaptive propagation prediction program for land mobile radiosystems

This paper describes the development of an adaptive RF propagation prediction program for land mobile radio systems. The program, which allows the user to specify transmitted signal strength, carrier frequency, base station antenna height, and mobile vehicle antenna height also provides the information necessary to determine a level of confidence for its predictions. In lieu of detailed topographical data (which is unavailable for many regions), the program makes use of data files containing the results of received signal strength measurements previously taken within the geographic region of interest at various locations, various carrier frequencies (measurements were taken at 453, 922, 1310, 1430, and 1920 MHz), and various base station antenna heights. This paper concludes by providing examples of results illustrating the performance of the adaptive propagation prediction program, showing that the proposed program yields significant improvement in propagation prediction and level of confidence when compared to currently available tools     

Equality between Functionals in the Presence of Coproducts

We consider the lambda calculus obtained from the simply typed calculus by adding products, coproducts, and a terminal type. We prove the following theorem: The equations provable in this calculus are precisely those true in any set-theoretic model with an infinite base type.