Deep learning based Brain Tumour Classification based on Recursive Sigmoid Neural Network based on Multi-Scale Neural Segmentation

Brain tumours are malignant tissues in which cells replicate rapidly and indefinitely, and tumours grow out of control. Deep learning has the potential to overcome challenges associated with brain tumour diagnosis and intervention. It is well known that segmentation methods can be used to remove abnormal tumour areas in the brain. It is one of the advanced technology classification and detection tools. Can effectively achieve early diagnosis of the disease or brain tumours through reliable and advanced neural network classification algorithms. Previous algorithm has some drawbacks, an automatic and reliable method for segmentation is needed. However, the large spatial and structural heterogeneity between brain tumors makes automated segmentation a challenging problem. Image tumors have irregular shapes and are spatially located in any part of the brain, making their segmentation is inaccurate for clinical purposes a challenging task. In this work, propose a method Recursive SigmoidNeural Network based on Multi-scale Neural Segmentation (RSN2-MSNS) for image proper segmentation. Initially collets the image dataset from standard repository for brain tumour classification.  Next, pre-processing method that targets only a small part of an image rather than the entire image. This approach reduces computational time and overcomes the over complication. Second stage, segmenting the images based on the Enhanced Deep Clustering U-net (EDCU-net) for estimating the boundary points in the brain tumour images. This method can successfully colour histogram values are evaluating segment complex images that contain both textured and non-textured regions. Third stage, Feature extraction for extracts the features from segmenting images using Convolution Deep Feature Spectral Similarity (CDFS2) scaled the values from images extracting the relevant weights based on its threshold limits. Then selecting the features from extracting stage, this selection is based on the relational weights. And finally classified the features based on the Recursive Sigmoid Neural Network based on Multi-scale Neural Segmentation (RSN2-MSNS) for evaluating the proposed brain tumour classification model consists of 1500 trainable images and the proposed method achieves 97.0% accuracy. The sensitivity, specificity, detection accuracy and F1 measures were 96.4%, 952%, and 95.9%, respectively

The potential of Empty Fruit Bunch (EFB) biochar produced from Modification of Gas Burner (MGB) as a soil amendment at different temperature level as compared to Top Lid Updraft (TLUD) and muffle furnace heating / Syed Ahmad Ibrahim Al-Kired S. Hasan

Top-Lid Updraft (TLUD) stove and muffle furnace heating is one of the methods to produce biochar trough slow pyrolysis process. However, there is a limitation involve the TLUD stove and muffle furnace heating which are poorly designed may result in high gas emission and more costing in term of operation and maintenance respectively. The new method of slow pyrolysis to produce biochar which is “Modification of Gas Burner (MGB)” has innovated to overcome the problem. The purposes of this study were to investigate the physco-chemical properties of Empty Fruit Bunch (EFB) biochar produce from MGB at three different temperatures and to compare their properties with TLUD stove and muffle furnace heating. Sample of EFB used in this study was collected from Serting Hillir Oil Palm Mill, Negeri Sembilan, Malaysia. Biochar from dried EFB was produce from MGB at three different range of temperature and different type of slow pyrolysis process (MGB, TLUD stove and muffle furnace). The experiment outcome show the increasing temperature of biochar produced from MGB will increase the total ash, pH and EC value of the biochar. For the three different type of pyrolysis process, the results showed that biochar produce form MGB, TLUD stove and muffle furnace heating has high in pH ranging from 9.1 to 10.4. Between these three method , TLUD stove has a lower ash content, pH and EC value, phosphorus and potassium compared to MGB400 and muffle furnace heating. It is was found that EFB biochar that produced from MGB400 which is compatible with muffle furnace in term of physical and chemical properties has a potential as a new soil amendment with low cost of production

MEDIA MIX MODELING COMPARISON OF INTERACTION MODEL TO SIMPLE LOG-LINEAR MODEL

The objective of current study is to compare a new model for media mix problem with popular model named as simple log linear model. A modified approach proposed to improve the results of media mix model from simple log linear method includes the simultaneous effect of different media variables on sales. The combined effect caused by various media variables shows a synergy in the curve for sales and hence considering it makes the model much effective and accurate

The cost of radiology procedures using Activity Based Costing (ABC) for development of cost weights in implementation of casemix system in Malaysia

Presently there is a gross lack of information on cost and cost weights in many developing countries that implement casemix system. Furthermore, studies that employed Activity Based Costing method (ABC) to estimate the costs of radiology procedures were rarely done in developing countries, including Malaysia. The main objective of this study is to determine the costs of radiology procedures for each group in casemix system, in order to develop cost weights to be used in the implementation of the casemix system. An economic evaluation study was conducted in all units in the Department of Radiology in the first teaching hospital using the casemix system in Malaysia. From the 25,754 cases, 16,173 (62.8%) of them were from medical discipline. Low One Third and High One Third (L3H3) method was employed to trim the outlier cases. Output from the trimming, 15,387 cases were included in the study. The results revealed that the total inpatients’ charges of all the radiology procedures was RM1,820,533.00 while the cost imputed using ABC method was RM2,970,505.54. The biggest cost component were human resources in Radiology Unit (Mobile) (57.5%), consumables (78.5%) of Endovascular Interventional Radiology (EIR) Unit, equipment (81.4%) of Magnetic Resonance Imaging (MRI) Unit, reagents (68.1%) of Medical Nuclear Unit. The one highest radiology cost weight, was for Malaysia Diagnosis Related Group (MY-DRG®) B-4-11-II (Hepatobiliary and Pancreas Neoplasms with severity level II, 2.8301). The method of calculation of the cost of procedures need to be revised by the hospital as findings from this study showed that the cost imposed to patient is lower than the actual cost

Biological Remediation of Cyanide: a Review

Cyanide and its complexes are produced by industries all over the world as waste or effluents. Biodegradation is considered to be the cheapest and the most effective method to get rid of cyanide in the environment. Several studies on different types of microorganisms that can degrade cyanide in the environment have been carried out. Hydrolytic, oxidative, reductive, and substitutive/transfer reactions are some of the common pathways used by microorganisms in cyanide degradation. Biodegradation of cyanide can occur aerobically or an-aerobically depending on the environmental conditions. Immobilised enzymes or microorganisms prove to be very effective method of degradation. Microorganisms such as Klebsiella oxytoca, Corynebacterium nitrophilous, Brevibacterium nitrophilous, Bacillus spp., Pseudomonas spp. and Rhodococcus UKMP-5M have been reported to be very effective in biodegradation of cyanide

Acoustical & thermodynamic properties of some ternary systems of 1-pentanol in n-hexane solution with various organic compounds using ultrasonic technique

943-952The thermo-physical parameters like density, ultrasonic velocity and viscosity have been experimentally measured for the ternary liquid mixtures of 1-pentanol with N,N dimethyl formamide (N,N-DMF) / o-methoxy phenol or 2-methoxy phenol (OMP) / m-methoxy phenol or 3-methoxy phenol (MMP) in n-hexane medium at various temperatures like 303 K, 308 K and 313 K. Certain acoustical and thermodynamic parameters such as cohesive energy, available volume, viscous relaxation time, Lennard Jones potential, free energy of activation, Gibb’s free energy and entropy are calculated from the experimental data. The variation of these parameters with respect to different concentrations ranging from 0.001 M to 0.01 M at different temperatures viz. 303 K, 308 K and 313 K and at fixed frequency of 2 MHz for the three ternary systems namely OMP + 1-pentanol+n-hexane, N,N-DMF+ 1-pentanol+n-hexane and MMP + 1-pentanol+n-hexane have been discussed in terms of molecular interactions under the influence of ultrasonic sound. The role of thermodynamic parameters in the stability of the charge transfer complexes and the hydrogen bonded complexes are predicted

Acoustical & thermodynamic properties of some ternary systems of 1-pentanol in n-hexane solution with various organic compounds using ultrasonic technique

The thermo-physical parameters like density, ultrasonic velocity and viscosity have been experimentally measured for the ternary liquid mixtures of 1-pentanol with N,N dimethyl formamide (N,N-DMF) / o-methoxy phenol or 2-methoxy phenol (OMP) / m-methoxy phenol or 3-methoxy phenol (MMP) in n-hexane medium at various temperatures like 303 K, 308 K and 313 K. Certain acoustical and thermodynamic parameters such as cohesive energy, available volume, viscous relaxation time, Lennard Jones potential, free energy of activation, Gibb’s free energy and entropy are calculated from the experimental data. The variation of these parameters with respect to different concentrations ranging from 0.001 M to 0.01 M at different temperatures viz. 303 K, 308 K and 313 K and at fixed frequency of 2 MHz for the three ternary systems namely OMP + 1-pentanol+n-hexane, N,N-DMF+ 1-pentanol+n-hexane and MMP + 1-pentanol+n-hexane have been discussed in terms of molecular interactions under the influence of ultrasonic sound. The role of thermodynamic parameters in the stability of the charge transfer complexes and the hydrogen bonded complexes are predicted

Peer-assisted learning (PAL): An innovation aimed at engaged learning for undergraduate medical students

Objective: To evaluate the effectiveness of Peer Assisted Learning in teaching at undergraduate level and to assess its effects on Peer Leaders and Peer Learners.Methods: The cross-sectional study was conducted at the Aga Khan University, Karachi, from May to October 2017, and comprised Peer Learners who were trained by faculty members in workshops and pre-run of experiments. Students were divided into two groups; Group A had Peer Learners taught by Peer Leaders, and Group B had those taught by trained lab technologists. Knowledge of the groups was assessed by a quiz using Kahoot. Post-session feedback questionnaires were also filled by the participants. Data was analysed using SPSS 23.Results: There were 10 Peer Leaders with a mean age of 19.5±0.85 years, and 62 Peer Learners with a mean age of 19.08±0.81 years. Among the learners, there were 35(56.5%) males and 27(43.5%) females. Post-session assessment showed a significant difference in the test performance by the two groups (p\u3c0.05). Feedback indicated that the learners found Peer Leaders more accessible than lab staff, leading to enhanced understanding of the subject.Conclusions: Peer-Assisted Learning was found to promote learning by creating an informal student-friendly learning environment

Repurposing potential of posaconazole and grazoprevir as inhibitors of SARS-CoV-2 helicase

As the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic engulfs millions worldwide, the quest for vaccines or drugs against the virus continues. The helicase protein of SARS-CoV-2 represents an attractive target for drug discovery since inhibition of helicase activity can suppress viral replication. Using in silico approaches, we have identified drugs that interact with SARS-CoV-2 helicase based on the presence of amino acid arrangements matching binding sites of drugs in previously annotated protein structures. The drugs exhibiting an RMSD of ≤ 3.0 Å were further analyzed using molecular docking, molecular dynamics (MD) simulation, and post-MD analyses. Using these approaches, we found 12 drugs that showed strong interactions with SARS-CoV-2 helicase amino acids. The analyses were performed using the recently available SARS-CoV-2 helicase structure (PDB ID: 5RL6). Based on the MM-GBSA approach, out of the 12 drugs, two drugs, namely posaconazole and grazoprevir, showed the most favorable binding energy, - 54.8 and - 49.1 kcal/mol, respectively. Furthermore, of the amino acids found conserved among all human coronaviruses, 10/11 and 10/12 were targeted by, respectively, grazoprevir and posaconazole. These residues are part of the crucial DEAD-like helicase C and DEXXQc_Upf1-like/ DEAD-like helicase domains. Strong interactions of posaconazole and grazoprevir with conserved amino acids indicate that the drugs can be potent against SARS-CoV-2. Since the amino acids are conserved among the human coronaviruses, the virus is unlikely to develop resistance mutations against these drugs. Since these drugs are already in use, they may be immediately repurposed for SARS-CoV-2 therapy