Identification of internal cracks in corn seed using convolutional neural networks

The identification of seed quality is very important for which the quality of seed is crucial to the yield and quality of crops. There are two main problems with the acquisition and identification of cracks inside corn seed. One is that most of the methods of near-infrared spectroscopy or X-ray are used to obtain images of cracks inside the seed, the acquisition equipment is expensive and the operation is complicated. The other is the identification of crack images, and the traditional image processing method is usually used which requires professionals to design different model parameters each time, resulting in poor model robustness and low model accuracy. In this study, we originally proposed a simple but effective method to obtain the picture of corn seed internal cracks, which is combined with visible light transmission and ordinary camera acquisition method. We also proposed using the transfer learning methods not only solving the problem of the small scale of our corn seed internal cracks dataset but also avoiding extracting features manually. Our proposed method achieved a promising result, which is able to correctly identify the cracked and intact corn seed 100% in our training stage and testing stage.

Evaluation of in vitro Dissolution Profile and Physicochemical Characterization of Polymer Based Formulations of Sparingly Soluble Rosuvastatin

Rosuvastatin (RVT) is a BCS class II antilipidemic crystalline drug, which exhibits low bioavailability due to its very poor aqueous solubility; therefore, it is challenging to develop a proper formulation of RVT. To enhance solubility and bioavailability of this API, an attempt has been made by implementing solid dispersion technique. Solid dispersion (SD) technique is a solubility enhancing technique where one or more active entities are dispersed in an inert medium (matrix or carrier) at solid state. In this study, different ratios of Kollicoat® IR (KIR) and Kollidon® 90F (KF90) polymers were used with API to prepare various formulations by physical mixing (PM) and SD approaches; here solvent evaporation technique was used whereas methanol was used as solvent which was completely evaporated from the homogenously dispersed system by placing in a water-bath at 60-65°C and then in oven for 30 minutes at 50 °C. Among the formulations, RVT-KF90 SD formulations showed the most promising result in in-vitro study in terms of drug release profile (78.04 – 99.21%) in comparison to pure RVT (63.1%) and physical mixing of RVT with those polymers. USP dissolution apparatus type II was used at 37°C ± 0.5°C with 50 rpm to conduct the in-vitro experiment. The experiment also unraveled that the dissolution of RVT improved with increasing the amounts of polymers. Subsequently, stability of the developed formulations was conducted by Fourier transforms infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) as well as scanning electron microscopy (SEM). The results obtained from FTIR ensured no involvement of any significant drug-excipient interaction. Moreover, the DSC study signified thermal stability at high temperature. Besides, the SEM micrograph illustrated homogenous distribution of RVT in the polymer and transformation of crystal-like RVT into amorphous formulations. Dhaka Univ. J. Pharm. Sci. 20(2): 199-211, 2021 (December)

Assessment of patient satisfaction after levonorgestral containing intrauterine system insertion in women with abnormal uterine bleeding

Background: Abnormal uterine bleeding is a common gynecological complaint affecting 10-30% of reproductive-aged women and it can result from different causes which adversely affects the woman’s quality of life, necessitating its appropriate and adequate management. Among all the pharmacological and surgical management options of AUB. LNG-IUS is emerging as a safer and effective treatment option of AUB. However apprehension about discomfort associated with the use of intrauterine device leads to its untimely removal. Aim of current study was to conduct a prospective qualitative study to observe the level of patient satisfaction with the use of LNG-IUS in patients with abnormal uterine bleeding.Methods: This study was conducted in the department of obstetrics and gynecology, MGM medical college and M.Y. Group of Hospitals, Indore from March 2017- March 2018. Follow up was done at 1, 3, 6 months.Results: In our study, majority of the women (90%) had improvement in their abnormal uterine bleeding along with significant increase in mean hemoglobin level from7.30+1.29 gm% to 8.71+1.27 gm% at the end of six months. 86.66% of these patients were very satisfied with the use of LNG IUS,Conclusions: LNG-IUS is an effective device for medical management of AUB and it should be used as the first line therapy for the same. It should always be considered before surgical interventions. It yields promising result in terms of patient satisfaction.

Treatment outcomes of central retinopathy of prematurity with localization in the Moscow regional perinatal center

BACKGROUND: Ranibizumab is widely used in retinopathy of prematurity. Therefore, it is necessary to evaluate the effectiveness, the risk of complications, and recurrence of the disease by antiangiogenic therapy. AIM: To demonstrate the experience of using anti-VEGF drugs in the Moscow Regional Perinatal Center and the effectiveness of different approaches to retinopathy of prematurity (ROP) treatment in the central retinal zone. MATERIAL AND METHODS: The case histories of 17 deeply premature infants with threshold ROP stages and localization in the posterior pole were retrospectively analyzed. Children were treated with intravitreal VEGF inhibitor (total 9 children), 5 children underwent laser coagulation of the retina, and 3 children received combined treatment (laser and intravitreal administration of a VEGF inhibitor). RESULTS: The average age of development of threshold stages was 35.2 weeks (range: 30.539 weeks) in our study. The frequency of promising outcomes after using anti-VEGF drugs alone or in conjunction with peripheral laser treatment was 100%. In comparison, the only laser treatment generated a promising result in 70% of the eyes. However, ROP relapses after anti-VEGF therapy developed at 37, 43, 44,5 weeks. In addition, 1 out of 9 children developed a recurrence of ROP and required laser treatment 7 weeks after using anti-VEGF. CONCLUSION: The use of anti-VEGF therapy is an effective method for the treatment of ROP of the posterior pole. However, there is the ambiguity of the available recommendations on the further management of children. Therefore, it is necessary to monitor the children who have received antiangiogenic therapy for as long as possible.

Advancement and development in computational chemistry for Colorectal Cancer diagnosis and treatment

: Colorectal cancer is the third most common form of cancer in the world and is a significant cause of death from cancer. To get a cure for colorectal cancer, early diagnosis and screening are necessary, as well as a clear understanding of the molecular basis of the disease. Molecular characterization of mutations associated with cancer provides useful information on the prognosis and reaction to therapy. This review discusses the clinical, molecular, and pathogenic features of the early onset of colorectal cancer, its screening tests, and diagnosis. The recent advances and rapid growth of computational tools in colorectal cancer used for diagnosis as well as screening are outlined in this review, including artificial intelligence, computer aided diagnosis, molecular docking, machine learning, and deep learning. In recent developments, the application of artificial intelligence has proved its excellency and shown a promising result, pointing out the severe need for a multidisciplinary approach to achieve an excellent result.

Evaluating Efficiency of Surfactant-Polymer Flooding with Single Well Chemical Tracer Tests at Kholmogorskoye Field

EOR technologies in general and surfactant-polymer flooding (SP) in particular is considered as a tertiary method for redevelopment of mature oil fields in Western Siberia, with potential to increase oil recovery to 60-70% OOIP. The selection of effective surfactant blend and a polymer for SP flooding a complex and multi-stage process. The selected SP compositions were tested at Kholmogorskoye oilfield in September-December 2020. Two single well tests with partitioning chemical tracers (SWCTT) and the injectivity test were performed. The surfactant and the polymer for chemical EOR were selecting during laboratory studies. Thermal stability, phase behavior, interfacial tension and rheology of SP formulation were investigated, then a prospective chemical design was developed. Filtration experiments were carried out for optimization of slugs and concentrations. Then SWCTT was used to evaluated residual oil saturation after water flooding and after implementation of chemical EOR in the near wellbore areas. The difference between the obtained values is a measure of the efficiency of surfactant-polymer flooding. Pandemic restriction shifted SWCTT to the period when temperature dropped below zero and suitable for winter conditions equipment was required. Two SWCTT were conducted with same surfactant, but different design of slugs in order to prove technical and economic models of SP-flooding. Long-term polymer injectivity was accessed at the third well. Oil saturation of sandstone reservoir after the injection of a surfactant-polymer solution was reduced about 10% points which is around one third of the residual oil after water flooding. Results were compared with other available data such as well logging, lab core flooding experiments, and hydrodynamic simulation. Modeling of SWCTT is ongoing, current interpretation confirms the increase the oil recovery factor after SP-flooding up to 20-25%, which is a promising result. Temperature model of the bottom hole zone was created and verified. The model predicts that temperature of those zones essentially below that average in the reservoir, which is important for interpretation of tracer test and surfactant efficiency. The tested surfactant showed an acceptable efficiency at under-optimum conditions, which is favorable for application of the SP formulation for neighboring field and layers with different reservoir temperatures, but similar water composition. In general, the results of the conducted field tests correlate with the results of the core experiments for the selected surfactant

Investigation of Electrical Properties of TiO2 Nanocomposite Based Polymer

Past research has reported the challenges regarding on degradation and aging due to high localization of electric field at triple point areas of polymeric insulator. The different materials and designs of polymeric insulator have initiated the partial discharge and arching activities which eventually lead to the insulation failures. The compounding of nanomaterials in the polymer shows a promising result to overcome this problem by redistributing the uniformity of electrical field lines on the insulator. In the present work, ethylene-propylene-diene rubber (EPDM) and titanium dioxide (TiO2) is introduced as nano composites that been embedded into insulator’s housing made of 1) silicone rubber (SiR) and 2) Ethylene Propylene Diene Monomer (EPDM) Rubber. Titanium dioxide (TiO2) is a semiconductor material that can be formed in different sizes either micron or nano-sized filler and has high relative permittivity that be able to reduce the high electrical stresses on high voltage equipment. Meanwhile EPDM shows good mechanical profile, excellent resistance properties and low cost. Therefore, it brings to the new opportunity to fabricate the nanocomposite based on both materials which exhibits an improved electrical properties and good distribution of electric field on polymeric outdoor insulators. In depth investigation was carried out to analyze the effect of different nano-filler loading in the compound and behavior of nanocomposites at different polymer base. An 11kV polymeric insulator is modelled to be simulated by using COMSOL Multiphysics software under dry-clean surface conditions to investigate the electric field distribution at terminal ends and along the insulator creepage path. The Electrostatics interface from the AC/DC Module is used in the evaluation of electric field distribution of insulator model correspondingly with the variations in filler percentage in the host matrix.

Prediction of the failure of a human supraspinatus tendon using a NARX network

The modelling of tendon behaviour during failure stages is nonlinear and heavily random. However, the understanding of its behavior during such stages, and development of models that can give an accurate prediction of its behavior during failure can provide a means for developing effective tendon therapies. This study is aimed at demonstrating the capability of an artificial neural network in the modelling of failure phases in tendons. A nonlinear autoregressive with exogenous inputs network is applied to three different tensile test data of the human supraspinatus tendons. Owing to data scarcity, the network was trained using two different test data which were randomly sampled and divided into 50%, 25% and 25% proportions for training, validation and preliminary testing. The third test data were used for the final testing phase. The procedure was cyclically performed for each of the results that have been presented in this study. The neural network predictions are presented as curves fitted over actual test results with corresponding error plots. The results indicate that the network is able to accurately predict the failure behaviour of these tendons with correlations of above 99 % for all tests. This is an excellent and very promising result in the light of the difficulties that most deterministic mechanistic models encounter in the modelling of soft tissue failure behaviour. With further development of this technique, sports and exercise physicians would enhance knowledge in mechanisms of tendon failure and be able to devise more injury preventive strategies.

Person Verification Based on Multimodal Biometric Recognition

Nowadays, person recognition has received significant attention due to broad applications in the security system. However, most person recognition systems are implemented based on unimodal biometrics such as face recognition or voice recognition. Biometric systems that adopted unimodal have limitations, mainly when the data contains outliers and corrupted datasets. Multimodal biometric systems grab researchers’ consideration due to their superiority, such as better security than the unimodal biometric system and outstanding recognition efficiency. Therefore, the multimodal biometric system based on face and fingerprint recognition is developed in this paper. First, the multimodal biometric person recognition system is developed based on Convolutional Neural Network (CNN) and ORB (Oriented FAST and Rotated BRIEF) algorithm. Next, two features are fused by using match score level fusion based on Weighted Sum-Rule. The verification process is matched if the fusion score is greater than the pre-set threshold. The algorithm is extensively evaluated on UCI Machine Learning Repository Database datasets, including one real dataset with state-of-the-art approaches. The proposed method achieves a promising result in the person recognition system.

Elaboration of composite based on the incorporation of marble particles into polymeric framework for the removal of Co(II) and Eu(III)

The incorporation of marble particles into the framework of composite material through the polymerization of acrylic acid (AA) and acrylamide acid (AM) using induced gamma irradiation was performed. The novel poly[AA-AM]-marble composite was characterized by multiple analytical instruments such as: energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD) analysis, differential thermal analysis-thermogravimetric analysis (DTA-TGA), Fourier transformer infrared (FTIR), surface area measurements using Brunauer–Emmett–Teller (BET) method and scanning electron microscope (SEM). Radioisotopes of fission (152+154Eu) and activation products (60Co) are the major environmental threats. Sorption of stable isotopes of cobalt and europium onto the synthesized composite material as the sorbent is applied. Sorption kinetics of Eu3+ and Co2+ were computed. The obtained results were analyzed by pseudo-first- and second-order, intraparticle diffusion, and Elovich kinetic models. It is deduced that the pseudo-second-order was more fitted and a chemisorption mechanism was suggested. The sorption capacity for Eu3+ and Co2+ on the prepared composite material was measured at the contact time (2 h) and pH = 4 (for Eu3+), pH = 6 (for Co2+) and it was found to be 91.2 and 13.1 mg/g, respectively. A promising result for the decontamination of both Eu and Co ions was obtained in various aquatic ecosystem applications such as: river water, tap water and groundwater.