102 research outputs found
Hydraulic simulations to evaluate and predict design and operation of the Chashma Right Bank Canal
No full textIrrigation systems / Irrigation canals / Flow control / Velocity / Canal regulation techniques / Hydraulics / Simulation models / Design / Operations / Crop-based irrigation / Distributary canals / Water delivery / Policy / Protective irrigation / Water allocation / Water requirements / Sedimentation / Water distribution / Equity / Water conveyance / Pakistan / Chashma Right Bank Canal
A Khatri-Rao product tensor network for efficient symmetric MIMO Volterra identification
No full textThe identification of symmetric tensor network MIMO Volterra models has been studied earlier via the computation of a Moore-Penrose pseudoinverse in tensor network form. The current state of the art requires the construction of a tensor network of a repeated Khatri-Rao product of a matrix with itself. This construction has a computational complexity that is dominated by one singular value decomposition (SVD) of an RI × IN matrix, where N is the number of measurements, I depends linearly on the number of inputs and input lags and R is the maximal tensor network rank. In this article, we prove an alternative method for constructing this tensor network without any computation whatsoever. The pseudoinverse can then be computed through an orthogonalization of the newly proposed tensor network. Furthermore, the proposed algorithm allows for the recursive identification of symmetric Volterra models of increasing degree D, which reduces the computation to one SVD of a RI × N matrix per step. Through numerical experiments we demonstrate how the proposed algorithm enables up to ten times faster identification of symmetric tensor network MIMO Volterra systems.Team Kim Batselie
Mukaria Distant
No full text<i>Mukaria</i> Distant new record <p> <i>Mukaria</i> Distant 1908: 269. Type species: <i>M. penthimioides</i> Distant</p> <p> <b>Distribution.</b> Oriental.</p> <p> <b>Remarks.</b> Although this genus is recorded for the first time from Pakistan its current presence is uncertain as its food plant, bamboo (from which the following species was collected), is now unknown to the first author in Pakistan.</p>Published as part of <i>Khatri, Imran & Webb, Michael D., 2011, On the identity of Benglebra Mahmood & Ahmad, and other Mukariini (Hemiptera: Cicadellidae: Deltocephalinae) from Bangladesh and Pakistan, pp. 14-22 in Zootaxa 2885</i> on page 18, DOI: <a href="http://zenodo.org/record/202933">10.5281/zenodo.202933</a>
Monobazus Distant
No full textMonobazus Distant Remarks. A review of this genus is in preparation by the second author and C.A. Viraktamath. Monobazus dissimilis (Distant), comb. nov. (Plate 1, d; Fig. 4). Deltocephalus fuscovarius Distant. Syn. nov. Material examined. Pakistan: 213, 4 Ƥ, Sindh Prov., Tando Jam, 7.xi.07. India: several specimens from throughout India and Sri Lanka, including the syntypeƤ of Xestocephalus dissimilis and 2 Ƥ syntypes of Deltocephalus fuscovarius (BMNH). Remarks. This species is similar to Osbornellus (Mavromoustaca) macchiae (see below) in having a pair of long basal paraphyses of the aedeagus (Figs 4 k-m) but these are dorsal rather than ventral and its subgenital plate is distinctive in being very long with its apical part digitate and lightly sclerotised, macrosetae relatively slender, and with both marginal and dorsal long fine setae.Published as part of Khatri, Imran & Webb, Michael D., 2010, The Deltocephalinae leafhoppers of Pakistan (Hemiptera, Cicadellidae), pp. 1-47 in Zootaxa 2365 on page 7, DOI: 10.5281/zenodo.19365
Mapping the structure and development of Science using co-citation analysis
No full textCo-citation analysis is a unique method used for studying the cognitive structure of science andassessing the research productivity. It is a research tool for examining the intellectual development and structure of the scientific discipline. This paper illustrates principles, techniques and applications of co-citation analysis. It also introduces the newly emerging co-citation analysis softwares,especially SciVal Spotlight and CiteSpace. Co-citation analysis is based on grouping together the papers that are frequently cited in pairs. Combined with single-link clustering and multidimensional scaling techniques, co-citation analysis can literally map the structure of specialized research areas as well as science as a whole
Marketing Strategies in Financial Services of Emerging Economies: A Case Study on the Indian Banking Industry
No full textSince 1991, after liberalization came about, India through social reforms had opened its market doors to foreign trade and investments by relaxing their government norms and regulations (www.indhistory.com, Manghirmalani,2008) . This brought about the start of the financial service sector which started dominating the growth of the economy and became the largest contributor to the country’s GDP in the time to follow. (www.mapsofindia.com).Today, the Indian financial services sector forms the second largest component in the entire services sector in a government budget. Thus, explaining the latent dormancy in this sector
Marketing Strategies in Financial Services of Emerging Economies: A Case Study on the Indian Banking Industry
No full textSince 1991, after liberalization came about, India through social reforms had opened its market doors to foreign trade and investments by relaxing their government norms and regulations (www.indhistory.com, Manghirmalani,2008) . This brought about the start of the financial service sector which started dominating the growth of the economy and became the largest contributor to the country’s GDP in the time to follow. (www.mapsofindia.com).Today, the Indian financial services sector forms the second largest component in the entire services sector in a government budget. Thus, explaining the latent dormancy in this sector
Risk and Uncertainty Analysis for Sustainable Urban Water Systems
No full textLong-term future planning is not a new approach in urban water management (UWM). However, the conventional ‘stationary approach’ of infrastructure planning and decision-making, where the future is assumed as the continuation of historical observation, will not work in the rapidly changing environment. This is because the current and future change pressures, such as climate change, urbanisation, population growth, deterioration of infrastructure systems, and changes in socioeconomic conditions are always uncertain. Uncertainty in future change pressures stems from two quite different sources: incomplete knowledge and unknowable knowledge. Incomplete knowledge is due to lack of information and understanding of a system. Unknowable knowledge is due to the inherent indeterminacy of future human societies and both natural and built systems.Water ManagementCivil Engineering and Geoscience
Robustness Assessment Method for Future Climate Uncertainties
No full textEnergy-efficient buildings tend to cause thermal discomfort due to overheating during summers. With the advent of climate change and increasing outdoor temperatures, the risk of overheating will be exacerbated. Henceforth, the building design must be future proof or robust for climate change. Passive design strategies applied to the building envelope are crucial in reducing the energy demand and provide thermal comfort. However, it is essential to determine their performance in the presence of climate uncertainties, especially in the early design stage. Therefore, the paper illustrates an assessment method for investigating the robustness of the building envelope in curbing the risk of overheating in future climate change scenarios of 2050 and 2085. The study focused on educational buildings as thermal discomfort due to overheating affects students' productivity. The study analysed the performance of different passive design strategies applicable at building envelope in reducing overheating risk and evaluated the robustness using the statistical method of “best-case and worst-case scenario”. The robustness assessment method found fixed or dynamic shading, reduced window to wall ratios, albedo effect of the building envelope, and mixed-mode ventilation strategy with P.C.M. panels as the most robust design solutions. However, ventilative cooling would have limited application towards the latter part of the centuryBuilding ServicesBuilding PhysicsBuilding Product Innovatio
Determining epitope specificity of T-cell receptors with Transformers
No full textTransformers have dominated the field of natural language processing due to their competency in learning complex relationships within a sequence. Reusing a pre-trained transformer for a downstream task is known as Trans-fer learning. Transfer learning restricts the transformer to a fixed vocabulary; modification in transformer implementation will extend the utility of the transformer. Implementing transformers for complex biological problems can be beneficial in addressing the complexities in the biological sequences. One such biological problem is to capture the specificity of diverse T-cell repertoire to the unique antigens (i.e., immunogenic pathogenic elements). Using transformers to assess the relationship between T-cell receptors and antigen at the sequence level can provide us with better insights into the processes involved in these precise and complex immune responses in humans and murine. In this work, we determined the specificity of multiple TCR to unique antigens by classifying the CDR3 re-gions of TCR sequences to a particular antigen. For this problem, we used three pre-trained auto-encoder (ProtBERT, ProtALBERT, ProtELECTRA) and one pre-trained auto-regressive (ProtXLNet) transformer model wherein, to adapt to the challenges of the complex biological problem at hand, we implemented modifications in the transformers chosen here. We used the VDJdb to obtain the biological data for training and testing the selected transformers. After pre-processing data, we predicted the TCR specificity for 25 antigens (classes) in a multi-class setting. Transformers could predict the specificity of TCRs to an antigen with just the CDR3 sequences from the TCRB chain (weighted F1 score 0.48), the data that was unseen by the transformers. With additional features incorpo-rated, i.e., gene names for TCRs, the weighted F1 improved to 0.55 in the best performing transformer. We demon-strated that different modifications in transformers recognized out-of-vocabulary features with these results. When com-paring the AUC from the transformer model to other previously developed methods for the same biological problem such as TCRGP, TCRDist and DeepTCR, we observed that the transformers outperformed the previously available methods. To exemplify, the MCMV epitope family that suffered from restricted performance in TCRGP due to fewer training samples (~100 samples) showed 10% improvement in AUC with transformers under similar training samples. Transformer's proficiency in learning from fewer data combined with holistic modifications in transformers implementations proves that we can extend its capabilities to explore other biological settings. Further ingenuity in utiliz-ing the full potential of transformers either through attention head visualization or introducing additional features can fur-ther extend T-cell research avenues.Computer Science | Data Science and Technolog
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