Nutrient intake, digestibility and performance of Gaddi kids supplemented with tea seed or tea seed saponin extract

Objective

An experiment was conducted to determine the nutrient intake, digestibility, microbial protein synthesis, haemato-biochemical attributes, immune response and growth performance of Gaddi kids fed with oat fodder based basal diet supplemented with either tea seed or tea seed saponin (TSS) extract.

Methods

Eighteen male kids, 7.03±0.16 months of age and 19.72±0.64 kg body weight, were distributed into three groups, T₀ (control), T₁, and T₂, consisting of 6 animals each in a completely randomized design. The kids were fed a basal diet consisting of concentrate mixture and oat fodder (50:50). Animals in group III (T₂) were supplemented with TSS at 0.4% of dry matter intake (DMI), and group II (T₁) were supplemented with tea seed at 2.6% of DMI to provide equivalent dose of TSS as in T₂. Two metabolism trials were conducted, 1st after 21 days and 2nd after 90 days of feeding to evaluate the short term and long term effects of supplementation.

Results

The tea seed (T₁) or TSS (T₂) supplementation did not affect DMI as well as the digestibility of dry matter, organic matter, crude protein, neutral detergent fibre, and acid detergent fibre. Nutritive value of diet and plane of nutrition were also comparable for both the periods. However, the average daily gain and feed conversion ratio (FCR) were improved (p<0.05) for T₁ and T₂ as compared to T₀. The microbial protein supply was also higher (p<0.05) for T₁ and T₂ for both the periods. There was no effect of supplementation on most blood parameters. However, the triglyceride and low density lipoprotein cholesterol levels decreased (p<0.05) and high density lipoprotein-cholesterol level increased (p<0.05) in T₂ as compared with T₀ and T₁. Supplementation also did not affect the cell mediated and humoral immune response in goats.

Conclusion

Tea seed at 2.6% of DMI and TSS at 0.4% DMI can be fed to Gaddi goats to improve growth rate, FCR and microbial protein synthesis.

Effect of replacing oat fodder with fresh and chopped oak leaves on in vitro rumen fermentation, digestibility and metabolizable energy

AIM

A study was conducted to evaluate the effect of replacing oat fodder (OF) with fresh oak leaves (FOL) or chopped oak leaves (COL) on rumen fermentation and digestibility through in vitro gas production technique (IVGPT).

MATERIALS AND METHODS

Nine different diets were prepared by mixing OF with oak leaves (either FOL or COL) in different ratios (100:0, 75:25, 50:50, 25:75, and 0:100). The rations were evaluated through Hohenheim IVGPT with 200 mg substrate and 30 ml of buffered rumen liquor. All the syringes were incubated at 39°C for 24 h in buffered rumen liquor of cattle. After 24 h, the total gas production was recorded, and the contents were analyzed for in vitro methane production, protozoa no. and ammonia-N.

RESULTS

Chopping (p<0.01) reduced the tannin fractions as well as non-tannin phenol. Increase in levels of oak decreased total gas production, methane, organic matter (OM) digestibility, and metabolizable energy (ME) values. The polyphenol content of the substrate did not show any significant difference on the protozoal count.

CONCLUSION

In vitro studies revealed that the addition of oak leaves reduced the methane production and ammonia nitrogen levels; however, it also decreased the OM digestibility and ME values linearly as the level of the oak leaves increased in the diet. Chopping was effective only at lower inclusion levels. Further studies, especially in vivo studies, are needed to explore the safe inclusion levels of oak leaves in the diet of ruminants.

Prediction of age and gender using digital radiographic method: A retrospective study

Aim and Objective:

To investigate age, sex based on gonial angle, width and breadth of the ramus of the mandible by digital orthopantomograph.

Materials and Methods:

A total of 200 panoramic radiographic images were selected. The age of the individuals ranged between 4 and 75 years of both the gender - males (113) and females (87) and selected radiographic images were measured using KLONK image measurement software tool with linear, angular measurement. The investigated radiographs were collected from the records of SRM Dental College, Department of Oral Medicine and Radiology. Radiographs with any pathology, facial deformities, if no observation of mental foramen, congenital deformities, magnification, and distortion were excluded.

Results:

Mean, median, standard deviation, derived to check the first and third quartile, linear regression is used to check age and gender correlation with angle of mandible, height and width of the ramus of mandible.

Conclusion:

The radiographic method is a simpler and cost-effective method of age identification compared with histological and biochemical methods. Mandible is strongest facial bone after the skull, pelvic bone. It is validatory to predict age and gender by many previous studies. Radiographic and tomographic images have become an essential aid for human identification in forensic dentistry forensic dentists can choose the most appropriate one since the validity of age and gender estimation crucially depends on the method used and its proper application.

Prediction of User Interests for Providing Relevant Information Using Relevance Feedback and Re-ranking

Predicting user interest based on their browsing pattern is useful in relevant information retrieval. In such a scenario, queries must be unambiguous and precise. For a broad-topic and ambiguous query, different users may with different interests may search for information from the internet. The inference and analysis of user search goals using rules will be helpful to enhance the relevancy and user experience. A major deficiency of generic search system is that they have static model which is to be applied for all the users and hence are not adaptable to individual users. User interest is important when performing clustering so that it is possible to enhance the personalization. In this paper, a new approach is proposed to infer user interests based on their queries and fast profile logs and to provide relevant information to users based on personalization. For this purpose, a framework is designed to analyze different user profiles and interests while query processing including relevance analysis. Implicit Feedback sessions are also constructed from user profiles based on mouse and button clicks made in their current and past queries. In addition, browsing behaviors of users are analyzed using rules and also using the feedback sessions. Temporary documents are generated in this work for representing the feedback sessions effectively. Finally, personalization is made based on browsing behavior and relevant information is provided to the users. From the experiments conducted in this work, it is observed that the proposed model provide most accurate and relevant contents to the users when compared with other related work.

A Swarm Optimization approach for clinical knowledge mining

BACKGROUND AND OBJECTIVES

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm.

METHODS

WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization.

RESULTS

Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively.

CONCLUSION

WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy.

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests

BACKGROUNDS AND OBJECTIVES

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis.

METHODS

Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert.

RESULTS

The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model.

CONCLUSION

The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests.

Forensic radiology in dentistry

Radiography can play an important part in forensic odontology, mainly to establish identification. This may take the precise form of comparison between antemortem and postmortem radiographs. Radiographs may also be taken to determine the age of a minor victim and even help in the assessment of the sex and ethnic group. Comparable radiographs are an essential factor to confirm identification in a mass disaster.

An Ontology Based Framework for Intelligent Web Based e-Learning

E-Learning is a fast, just-in-time, and non-linear learning process, which is now widely applied in distributed and dynamic environments such as the World Wide Web. Ontology plays an important role in capturing and disseminating the real world knowledge for effective human computer interactions. However, engineering of domain ontologies is very labor intensive and time consuming. Some machine learning methods have been explored for automatic or semi-automatic discovery of domain ontologies. Nevertheless, both the accuracy and the computational efficiency of these methods need to be improved. While constructing large scale ontology for real-world applications such as e-learning, the ability to monitor the progress of students' learning performance is a critical issue. In this paper, a system is proposed for analyzing students' knowledge level obtained using Kolb's classification based on the students level of understanding and their learning style using cluster analysis. This system uses fuzzy logic and clustering algorithms to arrange their documents according to the level of their performance. Moreover, a new domain ontology discovery method is proposed uses contextual information of the knowledge sources from the e-Learning domain. This proposed system constructs ontology to provide an effective assistance in e-Learning. The proposed ontology discovery method has been empirically tested in an e-Learning environment for teaching the subject Database Management Systems. The salient contributions of this paper are the use of Jaccard Similarity measure and K-Means clustering algorithm for clustering of learners and the use of ontology for concept understanding and learning style identification. This helps in adaptive e-learning by providing suitable suggestions for decision making and it uses decision rules for providing intelligent e-Learning.

Seroprevalence of rubella among pregnant women in Khartoum state, Sudan

Rubella vaccine is not included in the Sudanese national immunization programme, and data on prevalence of rubella among women of childbearing age are inadequate. The objective of this cross-sectional study was to determine the seroprevalence of rubella among pregnant women in Khartoum state, Sudan. A total of 500 pregnant women who visited 7 antenatal clinics from November 2008 to March 2009 were examined for the presence of rubella IgG antibodies using ELISA. Rubella IgG antibodies were detected in 95.1% (95% Cl: 93.2%-97.0%) of women. This seroprevalence was significantly associated with education level, but not with age, residence area, occupation or parity. We presume this high seroprevalence indicates a high circulation of wild rubella virus in Khartoum state. Similar studies in other Sudanese states would be important for informing a decision to introduce rubella vaccine to Sudan.

Novel use of laryngeal mask airway classic excel™ for bronchoscopy and tracheal intubation

The usage frequency and scope of supraglottic airway devices in anesthesia has expanded since the original laryngeal mask airway (LMA) prototype was invented by Dr Archie Brain in the early 1980s. Today, anesthesiologists are spoilt-for-choice with more than thirty options. The LMA Classic Excel™ was introduced to anesthesia practice in 2009; designed with an epiglottic elevating bar and a removable airway connector to facilitate tracheal intubation using the LMA as a conduit. We present a case report of a women diagnosed with papillary carcinoma of thyroid, who underwent bronchoscopic assessment of the trachea and subsequent intubation for an en-bloc dissection and removal of thyroid gland through the LMA Classic Excel™.