Glomus tumour of finger tip: a case report

Glomus tumour is usually benign tumour usually accounts for a small percentage of hand tumours. Sometimes diagnosis may be delayed for years which cause significant morbidity to the patient. I present here a case of a 40 year old female with one year history of pain in her right ring finger which was diagnosed as glomus tumour and was surgically removed and was histopathological result was consistent with glomus tumour

An unusual case of ptosis

Blepharophimosis is a condition where the patient has bilateral ptosis with reduced lid size, vertically and horizontally. The nasal bridge is flat and there is hypoplastic orbital rim. Here I am presenting a case of a father & son with blepahrophimosis which could be a part of an uncommon condition called BPES (Blepharophimosis, Ptosis, Epicanthus Inversus, Telecanthus)

Idiopathic hypertrophic pachymeningitis

Idiopathic hypertrophic pachymeningitis is a rare form of granulomatous meningitis. It is mainly a diagnosis by exclusion. Here we are presenting a case of a young female presented with multiple cranial nerve palsies who was diagnosed to have hypertrophic pachymeningitis with the help of MRI brain. All available investigations showed negative results and so possibility of Idiopathic Hypertrophic Pachymeningitis was considered. The patient responded well to steroid therapy

A rare manifestation of Escherichia coli septicemia

Escherichia coli (E. coli) is an uncommon pathogen of adult bacterial meningitis. In adult patients it carries a high mortality. We are reporting a case of 65 year old diabetic male presented with fever, abdominal pain & altered sensorium. On evaluation he was found to have E. coli meningitis secondary to septicaemia following UTI by same organism. He was started on Meropenem, but later changed to Imipenem according to culture & sensitivity results. Patient responded well to treatment and got discharged after 2 weeks of hospital stay

A new procedure for misbehavior detection in vehicular ad-hoc networks using machine learning

Misbehavior detection in vehicular ad hoc networks (VANETs) is performed to improve the traffic safety and driving accuracy. All the nodes in the VANETs communicate to each other through message logs. Malicious nodes in the VANETs can cause inevitable situation by sending message logs with tampered values. In this work, various machine learning algorithms are used to detect the primarily five types of attacks namely, constant attack, constant offset attack, random attack, random offset attack, and eventual attack. Firstly, each attack is detected by different machine learning algorithms using binary classification. Then, the new procedure is created to do the multi classification of the attacks on best chosen algorithm from different machine learning techniques. The highest accuracy in case of binary classification is obtained with Naïve Bayes (100%), decision tree (100%), and random forest (100%) in type1 attack, decision tree (100%) in type2 attack, and random forest (98.03%, 95.56%, and 95.55%) in Type4, Type8 and Type16 attack respectively. In case of new procedure for multi-classification, the highest accuracy is obtained with random forest (97.62%) technique. For this work, VeReMi dataset (a public repository for the malicious node detection in VANETs) is used

Bio-Hydrometallurgy for Extraction of Nonferrous Metals

The advent of microbial leaching process has opened scope for supplementing the availability of different non-ferrous metals globally, and has made the exploitation of poor grade and discarded ores/tailings, refractory ores, dirty concentrates and complex resources possible for metal recovery. The importance of various types of micro organisms has been recognised in the origin of minerals and metals beneath earth crust and in dissolution of various sulfidic and oxidic ores and concentrates. Since over a decade, Acidithiobacillus ferrooxidans has been commercially exploited in recovery of copper and uranium from ores, and gold and silver from refractory sulfide / arsenopyrite concentrates. Biotechnology is poised to have an explicit role in mineral processing in the next millennium

Bioreactor Leaching of Uranium from a Low Grade Indian Ore

Bio-leaching studies were carried out in a 2L bioreactor- BIOSTAT-B® equipped with a PLC based controller at 20-40% (w/v) pulp density using enriched culture of A.ferrooxi-dans for Turamdih uranium ore (Jharkhand, India). With the enriched culture of Aferrooxidans adapted on Fe(II) at pH 2.0, 35°C and 20% (w/v) pulp density, a 98.3% uranium recovery was recorded in 14 days. The leaching of uranium in the bioreactor improved the dissolution rate by reduc-ing the time from 40 days in shake flask as per our ear-lier studies to 14 days. While investigating the import- ance of biogenic Fe (III) in the bio-leaching process a maximum recovery of 84.7% (1308 was observed at pH 2.0 and 20% (w/v) pulp density in 10h as compared to the uranium leaching of 38.3% in the control experiments. On raising the pulp density to 30%, uranium bio-recovery increased to 87.6% in 10/i at pH 2.0 with <76,um size material. This showed a distinct advantage because of better mixing of slurry in the bioreactor with auto-controlled conditions that improved the kinetics

Correlation and prediction of dynamic human isolated joint strength from lean body mass

A relationship between a person's lean body mass and the amount of maximum torque that can be produced with each isolated joint of the upper extremity was investigated. The maximum dynamic isolated joint torque (upper extremity) on 14 subjects was collected using a dynamometer multi-joint testing unit. These data were reduced to a table of coefficients of second degree polynomials, computed using a least squares regression method. All the coefficients were then organized into look-up tables, a compact and convenient storage/retrieval mechanism for the data set. Data from each joint, direction and velocity, were normalized with respect to that joint's average and merged into files (one for each curve for a particular joint). Regression was performed on each one of these files to derive a table of normalized population curve coefficients for each joint axis, direction, and velocity. In addition, a regression table which included all upper extremity joints was built which related average torque to lean body mass for an individual. These two tables are the basis of the regression model which allows the prediction of dynamic isolated joint torques from an individual's lean body mass