Convective Heat and Mass Transfer in the Spouted Bed of a Porous Hygroscopic Solid

Agricultural Engineerin

Sternoclavicular instability - reconstruction of sternoclavicular ligament using semitendinosus autograft

Background: Injury to the sternoclavicular joint is rare with an incidence of 3% of all the injuries around the shoulder girdle. Most of them heal with conservative treatment. Rarely some progress to chronic instability associated with pain.Methods: We present a small series of 4 such cases of chronic symptomatic sternoclavicular joint instability. We performed reconstruction of the sternoclavicular ligament using semitendinosus autograft, with excellent result, with minimum of 15 months follow up.Results: All the patients returned to pre injury level of activity at the end of 6 months. There was significant improvement in the DASH score following surgery. Our results are comparable with that of Castropil et al, who had performed a similar technique. Conclusions: Reconstruction of sternoclavicular ligament using the semitendinosus autograft is a safe, reproducible and functionally good surgical option in patients with chronic sternoclavicular instability

CFLCA: High Performance based Heart disease Prediction System using Fuzzy Learning with Neural Networks

Human Diseases are increasing rapidly in today’s generation mainly due to the life style of people like poor diet, lack of exercises, drugs and alcohol consumption etc. But the most spreading disease that is commonly around 80% of people death direct and indirectly heart disease basis. In future (approximately after 10 years) maximum number of people may expire cause of heart diseases. Due to these reasons, many of researchers providing enormous remedy, data analysis in various proposed technologies for diagnosing heart diseases with plenty of medical data which is related to heart disease. In field of Medicine regularly receives very wide range of medical data in the form of text, image, audio, video, signal pockets, etc. This database contains raw dataset which consist of inconsistent and redundant data. The health care system is no doubt very rich in aspect of storing data but at the same time very poor in fetching knowledge. Data mining (DM) methods can help in extracting a valuable knowledge by applying DM terminologies like clustering, regression, segmentation, classification etc. After the collection of data when the dataset becomes larger and more complex than data mining algorithms and clustering algorithms (D-Tree, Neural Networks, K-means, etc.) are used. To get accuracy and precision values improved with proposed method of Cognitive Fuzzy Learning based Clustering Algorithm (CFLCA) method. CFLCA methodology creates advanced meta indexing for n-dimensional unstructured data. The heart disease dataset used after data enrichment and feature engineering with UCI machine learning algorithm, attain high level accurate and prediction rate. Through this proposed CFLCA algorithm is having high accuracy, precision and recall values of data analysis for heart diseases detection

Prospective randomised study of cases of pelvic fracture urethral distraction defects managed by early alignment versus initial suprapubic urinary diversion with delayed urethroplasty

Background: In complex pelvic fracture urethral distraction defects (PFUDD), early management prevents incidence of devastating complications such as urinary incontinence, restenosis and urethra cutaneous fistula. The aim of the present study was to study the outcome of patients with PFUDD undergoing early alignment (either by rail roading or endoscopic) compared with initial suprapubic urinary diversion with delayed urethroplasty.Methods: This was a prospective randomized study done at KGMU, Lucknow; having PFUDD during the period from June 2014 to July 2017. Patients with PFUDD were randomized in to two groups. Group A included 22 patients and managed by supra pubic cystostomy followed by delayed urethroplasty. Group B included 23 patients and managed by primary alignment by rail-roading and early endoscopic alignment. Patients were followed up after 6 weeks, 3 months and 6 months for measuring the primary and secondary outcomes during follow up.Results: The most common age group that sustained pelvic fracture urethral distraction defects injury are male of 21-40 years. In group A, stricture was present in all patients at 6 weeks post-surgery. Open urethroplasty was done at 3 months in 60% and 10% patients at 6 months.  In group B, stricture was present in 80% at 6 weeks, 40% at 3 months and 10% at 6 months. The incidence of ED in group A at 6 weeks, 3 months, was 25% patient which reduced to 20% at 6 months. In group B, ED was present in 30% patients 6 weeks, 3 months and which reduced to 25% at 6 months. No incontinence was observed in both groups.Conclusions: Primary realignment has significant benefits compared to SPC as realignment approach is associated with a 50%-55% decrease in stricture formation

Attribute Diversity Determines the Systematicity Gap in VQA

The degree to which neural networks can generalize to new combinations of familiar concepts, and the conditions under which they are able to do so, has long been an open question. In this work, we study the systematicity gap in visual question answering: the performance difference between reasoning on previously seen and unseen combinations of object attributes. To test, we introduce a novel diagnostic dataset, CLEVR-HOPE. We find that while increased quantity of training data does not reduce the systematicity gap, increased training data diversity of the attributes in the unseen combination does. In all, our experiments suggest that the more distinct attribute type combinations are seen during training, the more systematic we can expect the resulting model to be.Comment: 18 pages, 20 figure

Conservation agriculture improves agronomic, economic, and soil fertility indicators for a clay soil in a rainfed Mediterranean climate in Morocco

CONTEXT: Declining rainfall with increasing variability, increasing temperature extremes, and declining soil fertility are threatening crop production and ultimately food security in the rainfed Mediterranean environment in Morocco. Conservation agriculture (CA) practices such as reduced tillage, soil cover, and appropriate crop rotation are recognized as a set of adaptive agricultural systems in such climate-sensitive regions. Systematic evaluation of agronomic, economic, and soil fertility indicators with medium-and long-term adoption of CA in different crop rotations in such variable climatic conditions is needed to drive wider adoption of CA in the region. OBJECTIVE: The objective of this study was to systematically evaluate agronomic, economic, and soil fertility indicators under CA and conventional tillage (CT) using field experimentation (medium-term) and simulation modeling (long-term) for a clay soil of a rainfed Mediterranean environment. METHODS: Methodologies included the following: 1) Field experimentation for 5 years (2015–2019), comparing CA and CT in four major food crops: wheat, barley, lentil, and chickpea, conducted in Merchouch, Morocco. The objective was to determine the effect of CA on crop productivity, yield stability, profitability, precipitation use efficiency, and soil fertility indicators of individual crops and cropping systems. (2) Dynamic simulation modeling to understand the long-term effect of adopting CA and CT under cereal–legume and cereal–cereal rotation systems. Using 5 years of experimental data, we calibrated and validated a Decision Support System for Agrotechnology Transfer (DSSAT) model for four crops; and ran the model for 36 years for two major rotations