સ્વામિનારાયણ સંપ્રદાયના તત્વજ્ઞાન દ્વારા ભારતીય ઉદ્યોગકર્તાઓની સંચાલકીય સમસ્યાઓના ઉકેલનો અભ્યાસ

ભારત સૌથી પ્રાચીન અને વૈદિક સંસ્કૃતિ અને વિચારધારા ધરાવતું સુસંસ્કૃત રાષ્ટ્ર છે. સૌ પ્રથમ ભારતે સમગ્ર વિશ્ર્વને માનવજીવનની શરૂઆતમાં સંસ્કારીતા અને શ્રેષ્ઠતમ વિચારોની રજૂઆત આપી. મર્યાદિત વ્યાપારક્ષેત્રમાંથી ઉત્તરોત્તર બ્રિટીશ શાસકોના નેજા નીચે વિશાળપાયા પર ઉત્પાદન ખરીદ-વેંચાણ અને સંચાલકિય કામગીરી અસ્તિત્વમાં આવી. તેમજ બ્રિટીશ શાસકોના શાસનમાં ભારતની આર્થિક, સામાજિક, રાજકિય પરિસ્થિતિ વધુ વિકટ બની અને ઔદ્યોગિક ક્રાંતિના મંડાણ થતા ગૃહઉદ્યોગો અને નાનાપાયાના ધંધા-ઉદ્યોગોનો રકાસ થયો. આઝાદી પછી પણ ભારતમાં પરદેશી વિચારધારા અમલમાં રહેતા ભારત દેશે વિકાસ તો કર્યો તેની સાથે અમેરિકન સંચાલન વિચારધારા અને જાપાનીઝ સંચાલન વિચારધારા જેવી વિદેશી વિચારધારાનો વિકાસ થયો, પરંતુ સૌથી મોટી સમસ્યાએ થઈ કે આપણા મૂલ્યો, સિધ્ધાંતો, રીતિનીતિ વગેરેમાં મુળ વૈદિકમૂલ્યો અને સંસ્કારીતા પડી હતી. જ્યારે પરદેશી વિચારધારા સાથે તેનો સુમેળ ન હતો. પરીણામે આવી વિષમ પરિસ્થિતિ સર્જાતા ધંધાકીય પર્યાવરણને પરદેશી વિચારધારા માફ્ક ન આવી અને કુદરતી, માનવીય અને બૌધ્ધિક શક્તિ હોવા છતાં ભારતદેશ સંચાલન ક્ષેત્રે અલ્પવિકસિત રહ્યો. પ્રસ્તુત શોધનિબંધ દ્વારા સંશોધકનો ઉદેશ સ્વામિનારાયણ સંપ્રદાયનો ઉદ્ભવ કેવી રીતે થયો તેમજ શ્રીસહજાનંદસ્વામીનું જીવન અને તેમના દ્વારા ભારતની પવિત્રભૂમી પર થયેલ યુગકાર્યને સંક્ષીપ્તમાં સમજવાનો છે. તેમની માનૂષીલીલા, ઐશ્ર્વર્ય, ચારિત્ર્ય, નૈતિકતા, સદ્ગુણયુક્ત આચરણભર જીવન અને કવનના દરેક પાસાની સુક્ષ્મછણાવટ અને તેમણે આપેલ તત્વજ્ઞાન સ્વામિનારાયણ સાહિત્યના અભ્યાસ દ્વારા સંશોધકે રજૂ કરેલ છે

Phytotherapeutic Investigation of Major Herbal Steroids to Explore their Potential as an alternative to synthetic steroids

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Metabolic disposition of a monoterpene ketone, piperitenone, in rats: evidence for the formation of a known toxin,p-cresol

It was shown earlier that the monoterpene ketone, piperitenone (I) is one of the major metabolites of R-(+)-pulegone, a potent hepatotoxin. In the present studies, the metabolic disposition of piperitenone (I) was examined in rats. Piperitenone (I) was administered orally (400 mg/kg of the b. wt./day) to rats for 5 days. The following urinary metabolites were isolated and identified by various spectral analyses: p-cresol (VI), 6,7-dehydromenthofuran (III), p-mentha-1,3,5,8-tetraen-3-ol (IX), p-mentha-1, 3,5-triene-3, 8-diol (X), 5-hydroxypiperitenone (VIII), 7-hydroxypiperitenone (XI), 10-hydroxypiperitenone (XII), and 4-hydroxypiperitenone (VII). Incubation of piperitenone (I) with phenobarbital-induced rat liver microsomes in the presence of NADPH resulted in the formation of five metabolites which have been tentatively identified as metabolites III, VII, VIII, XI, XII, on the basis of gas chromatography retention time and gas chromatography-mass spectrometry analysis. Based on these results, a probable mechanism for the formation of p-cresol from piperitenone (I) via the intermediacy of metabolite III has been proposed

Incidence and distribution of congenital malformations clinically detected at birth: a prospective study at tertiary care hospital

Background: Congenital malformation represents defects in morphogenesis during early fetal life. Congenital anomalies account for 8-15% of perinatal deaths and 13-16% of neonatal deaths in India. The objective was to study overall and individual incidence and distribution of clinically detectable congenital malformations in newborns delivered at a tertiary hospital.Methods: The present study is a prospective study of all the newborns delivered at Obstetrics and Gynecology Department, New Civil Hospital, Surat, Gujarat, India for a period of one year from 1st January 2010 to 31st December 2010. Total 5518 consecutive births including both live born babies and still born babies were examined after taking verbal and written consent of their mothers for a visible structural anomalies to determine the overall incidence and distribution of congenital malformations. Data were statistically analyzed using SPSS software (trial version).Results: A total of 5518 babies were born out of which 75 were twins. Out of total 5518 newborns 5316 were live births and 202 were still births and out of 5316 live births 48 babies were malformed and out of 202 still births 20 babies were malformed. Total numbers of malformed babies were 68, so total point incidence of congenital anomalies turned out to be 1.23%. Out of total 5518 babies, 35 (0.63%) were having central nervous system malformations making its incidence of 6.34/1000 live births which turned out to be highest followed by gastrointestinal system (incidence of malformed babies: 5.44/1000 births) and genitor urinary system (incidence of malformed babies :1.09/1000 births). Commonest anomalies in central nervous system were meningomyelocele followed by hydrocephalus and anencephaly.Conclusions: From present study we conclude that incidence of congenital anomalies of CNS was highest amongst all types of congenital anomalies (meningomyelocele being the commonest). More emphasis should be given on prevention by regular antenatal care and avoidance of known teratogens and probable teratogenic agents

A study on incidence of congenital anomalies in new borns and their association with fetal factors: a prospective study

Background: Congenital malformation represents defects in morphogenesis during early fetal life. Congenital anomalies account for 8–15% of perinatal deaths and 13–16% of neonatal deaths in India. The objective was to study incidence of clinically detectable congenital malformations in new-borns delivered at a tertiary hospital and their association with fetal factors.Methods: The present study is a prospective study of all the newborns delivered at Obstetrics and Gynecology Department, New Civil Hospital, Surat for a period of one year from 1st January 2010 to 31st December 2010. Total 5518 consecutive births including both live born babies and still born babies were examined after taking verbal and written consent of their mothers for a visible structural anomalies to determine the overall incidence and distribution of congenital malformations and their association with fetal factors. Data were statistically analyzed using SPSS software (trial version).Results: A total of 5518 babies were born out of which 75 were twins. Total numbers of malformed babies were 68, so total point incidence of congenital anomalies turned out to be 1.23%. There were 2963 male new-borns, out of that 40 were congenitally malformed (1.34%) and out of 2555 female new-borns 28 were congenitally malformed (1.09%). No significant association was found between congenital malformation and sex of the child. Out of total 5518 new-borns 5316 were live births and 202 were still births and out of 5316 live births 48 babies were malformed and out of 202 still births 20 babies were malformed. Out of total 5518 new-borns 1227 had birth weight less than 1500 grams and out of them 12 (0.97%) babies were congenitally malformed. Out of 5518 new-borns 221 were preterm babies and out of 221 preterm babies 26 (12.32%) babies were congenitally malformed.Conclusions: From present study it has been concluded that congenital anomalies in new-borns were significantly associated with fetal factors like still birth, prematurity and low birth weight

Entropy Based Feature Selection For Multi-Relational Naïve Bayesian Classifier

Current industries data’s are stored in relation structures. In usual approach to mine these data, we often use to join several relations to form a single relation using foreign key links, which is known as flatten. Flatten may cause troubles such as time consuming, data redundancy and statistical skew on data. Hence, the critical issues arise that how to mine data directly on numerous relations. The solution of the given issue is the approach called multi-relational data mining (MRDM). Other issues are irrelevant or redundant attributes in a relation may not make contribution to classification accuracy. Thus, feature selection is an essential data pre- processing step in multi-relational data mining. By filtering out irrelevant or redundant features from relations for data mining, we improve classification accuracy, achieve good time performance, and improve comprehensibility of the models. We had proposed the entropy based feature selection method for Multi-relational Naïve Bayesian Classifier. We have use method InfoDist and Pearson’s Correlation parameters, which will be used to filter out irrelevant and redundant features from the multi-relational database and will enhance classification accuracy. We analyzed our algorithm over PKDD financial dataset and achieved the better accuracy compare to the existing features selection methods