Characterization of Linear Low-Density Polyethylene/ Poly(vinyl alcohol) Blends and Their Biodegradability by Vibrio sp. Isolated from Marine Benthic Environment

Increasing amounts of plastic waste in the environment have become a problem of gigantic proportions. The case of linear low-density polyethylene (LLDPE) is especially significant as it is widely used for packaging and other applications. This synthetic polymer is normally not biodegradable until it is degraded into low molecular mass fragments that can be assimilated by microorganisms. Blends of nonbiodegradable polymers and biodegradable commercial polymers such as poly (vinyl alcohol) (PVA) can facilitate a reduction in the volume of plastic waste when they undergo partial degradation. Further, the remaining fragments stand a greater chance of undergoing biodegradation in a much shorter span of time. In this investigation, LLDPE was blended with different proportions of PVA (5–30%) in a torque rheometer. Mechanical, thermal, and biodegradation studies were carried out on the blends. The biodegradability of LLDPE/PVA blends has been studied in two environments: (1) in a culture medium containing Vibrio sp. and (2) soil environment, both over a period of 15 weeks. Blends exposed to culture medium degraded more than that exposed to soil environment. Changes in various properties of LLDPE/PVA blends before and after degradation were monitored using Fourier transform infrared spectroscopy, a differential scanning calorimeter (DSC) for crystallinity, and scanning electron microscope (SEM) for surface morphology among other things. Percentage crystallinity decreased as the PVA content increased and biodegradation resulted in an increase of crystallinity in LLDPE/PVA blends. The results prove that partial biodegradation of the blends has occurred holding promise for an eventual biodegradable product

Analysis of Stochastic Volatility Sequences Generated by Product Autoregressive Models

The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis

Process Improvement of Coir Pith Degradation Involving White Rot Fungi By Substitution of Urea With Nitrogen Fixing Bacteria and Application of Biodegraded Coir Pith as Plant Growth Medium

In this study, a novel improved technology could be developed to convert the recalcitrant coir pith into environmental friendly organic manure. The standard method of composting involves the substitution of urea with nitrogen fixing bacteria viz. Azotobacter vinelandii and Azospirillum brasilense leading to the development of an improved method of coir pith. The combined action of the microorganisms could enhance the biodegradation of coir pith. In the present study, Pleurotus sajor caju, an edible mushroom which has the ability to degrade coir pith, and the addition of nitrogen fixing bacteria like Azotobacter vinelandii and Azospirillum brasilense could accelerate the action of the fungi on coir pith. The use of these microorganisms brings about definite changes in the NPK, Ammonia, Organic Carbon and Lignin contents in coir pith. This study will encourage the use of biodegraded coir pith as organic manure for agri/horti purpose to get better yields and can serve as a better technology to solve the problem of accumulated coir pith in coir based industries

Influence of Major Operational Parameters on Aerobic Granulation for the Treatment of Wastewater

Effective solids-liquid separation is the basic concept of any wastewater treatment system. Biological treatment methods involve microorganisms for the treatment of wastewater. Conventional activated sludge process (ASP) poses the problem of poor settleability and hence require a large footprint. Biogranulation is an effective biotechnological process which can overcome the drawbacks of conventional ASP to a great extent. Aerobic granulation represents an innovative cell immobilization strategy in biological wastewater treatment. Aerobic granules are selfimmobilized microbial aggregates that are cultivated in sequencing batch reactors (SBRs). Aerobic granules have several advantages over conventional activated sludge flocs such as a dense and compact microbial structure, good settleability and high biomass retention. For cells in a culture to aggregate, a number of conditions have to be satisfied. Hence aerobic granulation is affected by many operating parameters. The organic loading rate (OLR) helps to enrich different bacterial species and to influence the size and settling ability of granules. Hence, OLR was argued as an influencing parameter by helping to enrich different bacterial species and to influence the size and settling ability of granules. Hydrodynamic shear force, caused by aeration and measured as superficial upflow air velocity (SUAV), has a strong influence and hence it is used to control the granulation process. Settling time (ST) and volume exchange ratio (VER) are also two key influencing factors, which can be considered as selection pressures responsible for aerobic granulation based on the concept of minimal settling velocity. Hence, these four parameters - OLR, SUAV, ST and VER- were selected as major influencing parametersfor the present study. Influence of these four parameters on aerobic granulation was investigated in this work

Model Diagnostics in the presence of measurement error

The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Social Structural Determinants of Education among Tribes in Kerala

The study is focused on education of tribes particularly the problem of high dropout rate existing among the tribal students at school level. Scheduled Tribe is one of the marginalized communities experiencing high level of educational deprivation. The analysis of the study shows that the extent of deprivation existing among STs of Kerala is much higher compared to that of other communities. The present study covered tribes of three tribal predominant districts of Kerala such as Idukki, Palakkad and Wayanad. Out of the 35 tribal communities in the State, 17 of them are concentrated in these districts. Tribes concentrated in Idukki include Muthuvans, Malai Arayan, Uraly, Mannan and Hill Pulaya. The present study analyzed dropouts situation in tribal areas of Kerala by conducting Field Survey among dropout and non-dropout students at school level. High dropouts among STs persist due to many problems which are of structural in nature. Important problems faced by the tribal students that have been analyzed, this can be classified as economic, social, cultural and institutional. It is found that there exists high correlation between Income and expenditure of the family with the well-being of individuals. Significant economic factors are poverty and financial indebtedness of the family. Some of the common cultural factors of tribes are Nature of Habitation, Difference in Dialect and Medium of Instruction etc. Social factors analyzed in the study are illiteracy of parents, migration of family, family environment, motivation by parents, activities engaged in for helping the family and students’ lack of interest in studies. The analysis showed that all these factors except migration of the family, are affecting the education of tribal students. Apart from social, economic and cultural factors, there are a few institutional factors which will also influence the education of tribal students. Institutional factors analyzed in the study include students’ absenteeism, irregularity of teachers, attitude of non-tribal teachers and non-tribal students, infrastructure facilities and accessibility to school. The study found irregularity of students and accessibility to school as significant factors which determine the dropout of the students.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Biochemical Characterization and Bio-evaluation of Collagen and Collagen Peptides Extracted and Purified from Fish Skin: In vitro and In vivo Studies on Antiarthritic and Wound Healing Properties

In fish processing plants, there is huge amount of skin that is left as the waste. When this skin is taken and processed into fish collagen, it will save large amount of money that is used for extraction of collagen from other animal s.Fish collagen can be used as an alternative to replace mammalian collagen, especially collagen extracted from bovine, when we consider the outbreak of bovine spongiform encephalopathy (BSE), transmissible spongiform encephalopathy (TSE) and the foot - and-mouth disease (FMD) issues. BSE and TSE are progressive neurological disorders affecting cattles caused by proteinacious infectious particles called prions.The study aims in producing collagen that has been extracted from fish skin to replace other animal collagen so as to overcome the problem of other animal collagen issues. Also the study utilized the abandoned fish waste produced by fish processing industry since bone, skin, fin and scales of fish can be a useful source of collagen.

Anisotropic adaptive resolution of boundary layers for heat conduction problems

We deal with the numerical solution of heat conduction problems featuring steep gradients. In order to solve the associated partial differential equation a finite volume technique is used and unstructured grids are employed. A discrete maximum principle for triangulations of a Delaunay type is developed. To capture thin boundary layers incorporating steep gradients an anisotropic mesh adaptation technique is implemented. Computational tests are performed for an academic problem where the exact solution is known as well as for a real world problem of a computer simulation of the thermoregulation of premature infants.

Efficient mining of association rules based on formal concept analysis

Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, TITANIC, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.

Analytical Study of Light Propagation in Highly Nonlinear Media

The present dissertation is devoted to the construction of exact and approximate analytical solutions of the problem of light propagation in highly nonlinear media. It is demonstrated that for many experimental conditions, the problem can be studied under the geometrical optics approximation with a sufficient accuracy. Based on the renormalization group symmetry analysis, exact analytical solutions of the eikonal equations with a higher order refractive index are constructed. A new analytical approach to the construction of approximate solutions is suggested. Based on it, approximate solutions for various boundary conditions, nonlinear refractive indices and dimensions are constructed. Exact analytical expressions for the nonlinear self-focusing positions are deduced. On the basis of the obtained solutions a general rule for the single filament intensity is derived; it is demonstrated that the scaling law (the functional dependence of the self-focusing position on the peak beam intensity) is defined by a form of the nonlinear refractive index but not the beam shape at the boundary. Comparisons of the obtained solutions with results of experiments and numerical simulations are discussed.

A Comparative Study on Internationalization and the Role of International Offices at Selected Middle Eastern and German Universities

Internationalization of higher education has become one of the most important policies for institutions of higher education worldwide. Though universities are international by nature, the need for intensified quality activities of international nature has promoted internationalization to be under spotlight of researchers, administrators and policy makers and to be an area for research. Each institution follows its certain way to govern its international affairs. Most Universities, especially in the 'Developed World' started to plan it strategically. This study explores the meanings and importance of internationalization especially that it means different things to different people. It also studies the rationales behind internationalizing higher education. It focuses on the four main prevailing rationales; political, cultural/social, economic/financial, and academic on both national and institutional levels. With the increasing need to strategically plan, the study explores internationalization strategies in terms of how to develop them, what are their approaches and types, and their components and dimensions. Damascus University has witnessed an overwhelming development of its international relations and activities. Therefore, it started to face a problem of how to deal with this increasing load especially that its International Office is the only unit that deals with the international issues. In order to study the internationalization phenomenon at Damascus University, the 2WH approach, which asks the what, why, and how questions, is used and in order to define the International Office's role in the internationalization process of the University, it studies it and the international offices of Kassel University, and Humboldt University in Germany, The University of Jordan, and Al Baath University in Syria using the 'SOCIAL' approach that studies and analyses the situation, organization, challenges, involvement, ambitions, and limitations of these offices. The internationalization process at the above-mentioned Universities is studied and compared in terms of its meaning, rationales for both the institution and its academic staff, challenges and strategic planning. Then a comparison is made among the international offices of the Universities to identify their approaches, what led to their success and what led to their failure in their practices. The aim is to provide Damascus University and its International Office with some good practices and, depending on the experiences of the professionals of the case-studies, a suggested guidance to the work of this Office and the University in general is given. The study uses the interviews with the different officials and stakeholders of the case-studies as the main method of collecting the information in addition to site visits, studying their official documents and their websites. The study belongs to qualitative research that has an action dimension in it since the recommendations will be applied in the International Office. The study concludes with few learned lessons for Damascus University and its International Office depending on the comparison that was done according to a set of dimensions. Finally a reflection on the relationship between internationalization of higher education and politics, the impact of politics on Middle Eastern Universities, and institutional internationalization strategies are presented.

Prevalence of intestinal parasites in small ruminants and their senstivity to treatments with ethnobotanical remedies in Cholistan, Pakistan

Livestock production contributes substantially to the livelihoods of poor rural farmers in Pakistan; strengthening pastoral communities plays an imperative role in the country’s thrive for poverty alleviation. Intestinal helminths constitute a major threat for pastoral livestock keepers in the whole country because chronic infestation leads to distinct losses in livestock productivity, particularly the growth of young animals. Synthetic anthelmintics have long been considered the only effective way of controlling this problem but high prices, side effects and chemical residues/toxicity problems, or development of resistance, lead to their very limited use in many pastoral systems. Additionally, poor pastoralists in remote areas of Pakistan hardly have access to appropriate anthelmintic drugs, which are also relatively expensive due to the long routes of transportation. The search for new and more sustainable ways of supporting livestock keepers in remote areas has given rise to studies of ethno-botanicals or traditional plant-based remedies to be used in livestock health care. Plant-based remedies are cheap or free of cost, environmentally safe and generally create no problem of drug resistance; they thus might substitute allopathic drugs. Furthermore, these remedies are easily available in remote areas and simple to prepare and/or administer. Cholistan desert is a quite poor region of Pakistan and the majority of its inhabitants are practicing a nomadic life. The region’s total livestock population (1.29 million heads) is almost twice that of the human population. Livestock husbandry is the primordial occupation of the communities and traditionally wealth assessment was based on the number of animals, especially goats and sheep, owned by an individual. Fortunately, about 60% of this desert region is richly endowed with highly adapted grasses, shrubs and trees. This natural flora has a rich heritage of scientifically unexplored botanical pharmacopoeia. Against this background, the present research project that was conducted under the umbrella of the International Center for Development and Decent Work at Kassel University, focused on a development aspect: in the Cholistan desert region it was firstly examined how pastoralists manage their livestock, which major health problems they face for the different animal species, and which of the naturally occurring plants they use for the treatment of animal diseases (Chapter 2). For this purpose, a baseline survey was carried out across five locations in Cholistan, using a structured questionnaire to collect data from 100 livestock farmers (LF) and 20 local healers (LH). Most of LF and LH were illiterate (66%; 70%). On average, LH had larger herds (109 animals) than LF (85 animals) and were more experienced in livestock husbandry and management. On average LF spent about 163 Euro per year on the treatment of their livestock, with a huge variability in expenditures. Eighty-six traditional remedies based on 64 plants belonging to 43 families were used. Capparaceae was the botanical family with the largest number of species used (4), followed by Chenopodiaceae, Poaceae, Solanaceae and Zygophyllaceae (3). The plants Capparis decidua (n=55 mentions), Salsola foetida (n=52), Suaeda fruticosa (n=46), Haloxylon salicornicum (n=42) and Haloxylon recurvum (n=39) were said to be most effective against the infestations with gastrointestinal parasites. Aerial parts (43%), leaves (26%), fruits (9%), seeds and seed oils (9%) were the plant parts frequently used for preparation of remedies, while flowers, roots, bulbs and pods were less frequently used (<5%). Common preparations were decoction, jaggery and ball drench; oral drug administration was very common. There was some variation in the doses used for different animal species depending on age, size and physical condition of the animal and severity of the disease. In a second step the regionally most prevalent gastrointestinal parasites of sheep and goats were determined (Chapter 3) in 500 animals per species randomly chosen from pastoral herds across the previously studied five localities. Standard parasitological techniques were applied to identify the parasites in faecal samples manually collected at the rectum. Overall helminth prevalence was 78.1% across the 1000 animals; pure nematode infestations were most prevalent (37.5%), followed by pure trematode (7.9%), pure cestode (2.6%) and pure protozoa infestations (0.8%). Mixed infestations with nematodes and trematodes occurred in 6.4% of all animals, mixed nematode-cestode infestations in 3.8%, and all three groups were found in 19.1% of the sheep and goats. In goats more males (81.1%) than females (77.0%) were infested, the opposite was found in sheep (73.6% males, 79.5% females). Parasites were especially prevalent in suckling goats (85.2%) and sheep (88.5%) and to a lesser extent in young (goats 80.6%, sheep 79.3%) and adult animals (goats 72.8%, sheep 73.8%). Haemonchus contortus, Trichuris ovis and Paramphistomum cervi were the most prevalent helminths. In a third step the in vitro anthelmintic activity of C. decidua, S. foetida, S. fruticosa, H. salicornicum and H. recurvum (Chapter 2) was investigated against adult worms of H. contortus, T. ovis and P. cervi (Chapter 3) via adult motility assay (Chapter 4). Various concentrations ranging from 7.8 to 500 mg dry matter/ml of three types of extracts of each plant, i.e. aqueous, methanol, and aqueous-methanol (30:70), were used at different time intervals to access their anthelmintic activity. Levamisol (0.55 mg/ml) and oxyclozanide (30 mg/ml) served as positive and phosphate-buffered saline as negative control. All extracts exhibited minimum and maximum activity at 2 h and 12 h after parasite exposure; the 500 mg/ml extract concentrations were most effective. Plant species (P<0.05), extract type (P<0.01), parasite species (P<0.01), extract concentration (P<0.01), time of exposure (P<0.01) and their interactions (P<0.01) had significant effects on the number of immobile/dead helminths. From the comparison of LC50 values it appeared that the aqueous extract of C. decidua was more potent against H. contortus and T. ovis, while the aqueous extract of S. foetida was effective against P. cervi. The methanol extracts of H. recurvum were most potent against all three types of parasites, and its aqueous-methanol extract was also very effective against T. ovis and P. cervi. Based on these result it is concluded that the aqueous extract of C. decidua, as well as the methanol and aqueous-methanol extract of H. recurvum have the potential to be developed into plant-based drugs for treatment against H. contortus, T. ovis and P. cervi infestations. Further studies are now needed to investigate the in vivo anthelmintic activity of these plants and plant extracts, respectively, in order to develop effective, cheap and locally available anthelmintics for pastoralists in Cholistan and neighboring desert regions. This will allow developing tangible recommendations for plant-based anthelminthic treatment of sheep and goat herds, and by this enable pastoralists to maintain healthy and productive flocks at low costs and probably even manufacture herbal drugs for marketing on a regional scale.

Semi-algebraic methods for symbolic analysis of complex reaction networks

The identification of chemical mechanism that can exhibit oscillatory phenomena in reaction networks are currently of intense interest. In particular, the parametric question of the existence of Hopf bifurcations has gained increasing popularity due to its relation to the oscillatory behavior around the fixed points. However, the detection of oscillations in high-dimensional systems and systems with constraints by the available symbolic methods has proven to be difficult. The development of new efficient methods are therefore required to tackle the complexity caused by the high-dimensionality and non-linearity of these systems. In this thesis, we mainly present efficient algorithmic methods to detect Hopf bifurcation fixed points in (bio)-chemical reaction networks with symbolic rate constants, thereby yielding information about their oscillatory behavior of the networks. The methods use the representations of the systems on convex coordinates that arise from stoichiometric network analysis. One of the methods called HoCoQ reduces the problem of determining the existence of Hopf bifurcation fixed points to a first-order formula over the ordered field of the reals that can then be solved using computational-logic packages. The second method called HoCaT uses ideas from tropical geometry to formulate a more efficient method that is incomplete in theory but worked very well for the attempted high-dimensional models involving more than 20 chemical species. The instability of reaction networks may lead to the oscillatory behaviour. Therefore, we investigate some criterions for their stability using convex coordinates and quantifier elimination techniques. We also study Muldowney's extension of the classical Bendixson-Dulac criterion for excluding periodic orbits to higher dimensions for polynomial vector fields and we discuss the use of simple conservation constraints and the use of parametric constraints for describing simple convex polytopes on which periodic orbits can be excluded by Muldowney's criteria. All developed algorithms have been integrated into a common software framework called PoCaB (platform to explore bio- chemical reaction networks by algebraic methods) allowing for automated computation workflows from the problem descriptions. PoCaB also contains a database for the algebraic entities computed from the models of chemical reaction networks.