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Authors: Abdullahi, Sagiru Hamza; Advisor: -; Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Uba, Sani; Umar, Abdullahi Bello (2022) - Four QSAR models were developed from the training set data using genetic function algorithm (GFA) coupled with multi linear regression (MLR), and their expressions are presented below:Model 1
Y = 0.342327907 * apol + 0.002006877 * ATSC8m + 0.021947183 * ATSC7s − 2.110146447 * SM1_Dzm − 0.027702443 * SpAbs_Dzs + 0.122940438 * ZMIC4 − 9.882891756.
Model 2
Y = 0.333966562 * apol + 0.001909583 * ATSC8m + 0.019049122 * ATSC7s − 2.079324191 * SM1_DzZ − 0.027112784 * SpAbs_Dzs + 0.119956742 * ZMIC4 − 9.456381109.
Model 3
Y = 0.342932868 * apol + 0.002004154 * ATSC8m + 0.021734174 * ATSC7s − 2.067273713 * SM1_Dzm − 0.027821824 * SpAD_Dzs + 0.122642435 * ZMIC4 − 9.889860694.
Model 4
Y = 0.334437304 * apol + 0.001906343 * ATSC8m + 0.018877487 * ATSC7s − 2.033875692 * SM1_DzZ − 0...
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Authors: Ghimire C.P.; Advisor: -; Participants: Bruijnzeel L.A.; Lubczynski M.W.; Zwartendijk B.W.; Odongo V.O.; Ravelona M.; Meerveld H.J.V (2018.) - The Ec exhibited a plateau-shaped relation with vapour pressure deficit (VPD), which was attributed to stomatal closure at high VPD. Vapour pressure deficit was the major driver of variation in Ec, during both the wet and the dry season. Overall water use of the trees was modest, possibly reflecting low site fertility after three swidden cultivation cycles. The observed contrast in gs response to soil water and climatic conditions for the trees and shrubs underscores the need to take root distributions into account when modelling transpiration from regenerating tropical forests.
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Authors: Koeva M.; Advisor: -; Participants: Crommelinck S.; Stöcker C.; Crompvoets J. (2018.) - The project consists of a four-year work plan, €3.9M funding, and eight consortium partners collaborating with stakeholders from different case study locations in Ethiopia, Kenya, and Rwanda that cover different land uses such as urban, peri-urban, rural smallholder, and (former) pastoralists. Major technical tasks include tool development, prototyping, and demonstration for local, national, regional, and international interest groups. However, equal emphasis is placed on needs assessment, as well as governance, capacity and business modelling.
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Authors: Zevenbergen J.; Advisor: -; Participants: Vries W.T.D.; Bennett R. (2018.) - Measuring the interventions is no trivial task: isolating meaningful dependent and independent variables is an ongoing challenge. Socio-technical approaches are needed as are skilled personnel to implement them. This suggests substantial changes to social capacity, embodied in scaled capacity building programs: to reap the rewards of well-designed interventions, integrated capacity development activities are needed at individual, crossorganizational, and societal levels. When all the above changes coalesce in a harmonious fashion, 'responsible land administration' appears more readily achievable.
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Authors: Hosseinyalamdary S.; Advisor: -; Participants: - (2018.) - In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.
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Authors: Martinez J.; Advisor: -; Participants: - (2019.) - As a result, trends in improving the quality of life and reducing inequalities between neighbourhood areas are visualized. Three main outcomes have been found: divergence, convergence and maintenance of the status quo. The paper concludes reflecting on the emerging patterns and critically exploring how these mappings and representations can be used to better inform policy makers and potentially improve community well-being.
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Authors: van Oudenhoven, A.P.E.; Advisor: -; Participants: Schröter, M.; Drakou, E.G. (2018) - We synthesized 16 criteria for ES indicator selection and organized them according to the widely used categories of credibility, salience, legitimacy (CSL). We propose to consider additional criteria related to feasibility (F), as CSL criteria alone often seem to produce indicators which are unachievable in practice. Considering CSLF together requires a combination of scientific knowledge, communication skills, policy and governance insights and on-field experience. In conclusion, we present a checklist to evaluate CSLF of your ES indicators. This checklist helps to detect and mitigate critical shortcomings in an early phase of the development process, and aids the development of effective indicators to inform actual policy decisions.
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Authors: Alam, Saruar; Advisor: -; Participants: Sayem, Mohammad; Bello, Martiniano; Mou, Sadia Islam; Faruqui, Nairita Ahsan; Hossain, Faruk; Hasan, Md. Kamrul (2022) - The polymorphism data are available in several databases. NCBI dbSNP houses extensive data for different genes, and NCBI has the largest database that helps analyze single nucleotide polymorphisms. 581 SNPs have been found for cellular tumor antigen p53 (NCBI Reference Sequence: NP_000537.3). Among them, 420 SNPs were found to be missense or non-synonymous. Among 581, there were 435 SNPs in 3′UTR and 112 in 5′UTR regions. Only the missense, 3′ (3 prime), and 5′ (5 prime) UTR SNPs have been selected for further analysis.
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Authors: Ugbe, Fabian Audu; Advisor: -; Participants: Shallangwa, Gideon Adamu; Uzairu, Adamu; Abdulkadir, Ibrahim (2022) - Theoretical modeling of thirty-six arylimidamide-azole derivatives was conducted to establish a quantitative relationship between their structures and their inhibitory activities. As a result, a five-descriptor QSAR model was built (Eq. 13) with the descriptors well described in Table 4. The outcome of the internal and external validation assessment conducted on the built model is available in Table 5. The computed descriptors, observed activities (pIC50), and the predicted activities together with their residuals are presented in Table 6. Also, a plot of predicted activities versus experimental activities for the training set and test set is shown in Fig. 1, while Fig. 2 shows the plot of standardized residuals against experimental activities (pIC50).
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Authors: Ojewumi, Emmanuel Omotayo; Advisor: -; Participants: Omoba, Olufunmilayo Sade; Awolu, Olugbenga Olufemi (2022) - Proximate composition (g/100 g) of modified Tacca flour
The proximate composition of the native and modified tacca flour is presented in Table 1. The moisture content of all the samples ranged from 7.34 to 10.14%; total ash from 1.19 to 2.59%; crude protein from 5.56 to 14.08%; crude fibre from 1.23 to 2.91%; and carbohydrate content from 68.86 to 82.10%. The energy values ranged from 347.69 to 381.06 kcal/ 100 g.
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