Search results for: sequence alignment problem

Authors: Xiaoqin Wang, Li Yin

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Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Mrinal Jana, Geetanjali Panda

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In this paper a methodology is developed to solve a nonlinear fractional programming problem in which the coefficients of the objective function and constraints are interval parameters. This model is transformed into a general optimization problem and relation between the original problem and the transformed problem is established. Finally the proposed methodology is illustrated through a numerical example.

Keywords: fractional programming, interval valued function, interval inequalities, partial order relation

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Authors: M. Kolotylo, H. Zheng, R. Parente, R. Dahiya

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Large number of organizations, frequently motivated by budget and cost cuts, outsource their Information Technology (IT) positions every year. Although the objective of reduction in financial obligations is often not accomplished, many buyer companies still manage to benefit from outsourcing projects. Knowledge Transfer (KT), being one of the major processes that take place during IT outsourcing partnership, may exert a strong impact on the performance of the parties involved, particularly that of the buyer. Research, however, lacks strong conceptual basis for the possible benefits that KT from supplier may bring to the buyer; and for the mechanisms that may be adopted by the buyer to maximize such benefit. This paper aims to fill this gap by proposing a conceptual framework of organizational learning and development of dynamic capabilities enabled by KT from the supplier to the buyer. The study examines buyer-supplier relationships in the context of IT outsourcing transactions, and theorizes how KT from the supplier to the buyer helps the performance of the buyer. It warrants that more research is carried out in order to explicate and provide evidence regarding the role that KT plays in strategic improvements for the buyer. The paper proposes to take up a two-fold approach to the research: conceptual development that utilizes logical argumentation and interpretive historical research, as well as a qualitative case study which aims to capture and understand the complex processes involved. Thus, the study provides a comprehensive visualization of the dynamics of the conditions under which participation in IT outsourcing partnership might be of benefit to the buyer company. The framework demonstrates the mechanisms involved in buyer’s achievement of strategic alignment through organizational learning enabled by KT from the supplier. It highlights that organizational learning involves a balance between exploitation of assets and exploration of new possibilities, and further notes that the dynamic capabilities mediate the effect of organizational learning on firm performance. The paper explicates in what ways managers can leverage outsourcing projects to execute strategy, which would enable their organization achieve better performance. The study concludes that organizational learning enables the firm to develop IT capabilities of strategic planning, IT integration, and IT relationships in the outsourcing context, and that IT capabilities developed through the organizational learning would help the firm in achieving strategic alignment.

Keywords: dynamic capabilities, it outsourcing, knowledge transfer, organizational learning, strategic alignment

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Authors: K. Ali, M. F. Qamar, M. A. Zaman, M. Younus, I. Khan, S. Ehtisham-ul-Haque, R. Tamkeen, M. I. Rashid, Q. Ali

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This study centers on molecular identification of Haemonchus contortus and isolation of Benz-imidazoles (BZ) resistant strains. Different abattoirs’ of two geographic regions of Punjab (Pakistan) were frequently visited for the collection of worms. Out of 1500 (n=1500) samples that were morphologically confirmed as H. contortus, 30 worms were subjected to molecular procedures for isolation of resistant strains. Resistant worms (n=8) were further subjected to DNA gene sequencing. Bio edit sequence alignment editor software was used to detect the possible mutation, deletion, replacement of nucleotides. Genetic diversity was noticed and genetic variation existing in β-tubulin isotype 1 of the H. contortus population of small ruminants of different regions considered in this study. H. contortus showed three different type of genetic sequences. 75%, 37.5%, 25% and 12.5% of the studied samples showed 100% query cover and identity with isolates and clones of China, UK, Australia and other countries, respectively. Interestingly the neighbor countries such as India and Iran haven’t many similarities with the Pakistani isolates. Thus, it suggests that population density of same genetic makeup H. contortus is scattered worldwide rather than clustering in a single region.

Keywords: Haemonchus contortus, Benzimidazole resistant, β-tubulin-1 gene, abattoirs

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: F. Berna Benli, Özgür Keskin

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Lately, many mathematicians have been studied the statistical convergence of a sequence of fuzzy numbers. We know that Lambda-statistically convergence is a kind of convergence between ordinary convergence and statistical convergence. In this paper, we will introduce the new kind of convergence such as λ-levelwise statistical convergence. Then, we will define the concept of the λ-levelwise statistical cluster and limit points of a sequence of fuzzy numbers. Also, we will discuss the relations between the sets of λ-levelwise statistical cluster points and λ-levelwise statistical limit points of sequences of fuzzy numbers. This work has been extended in this paper, where some relations have been considered such that when lambda-statistical limit inferior and lambda-statistical limit superior for lambda-statistically convergent sequences of fuzzy numbers are equal. Furthermore, lambda-statistical boundedness condition for different sequences of fuzzy numbers has been studied.

Keywords: fuzzy number, λ-levelwise statistical cluster points, λ-levelwise statistical convergence, λ-levelwise statistical limit points, λ-statistical cluster points, λ-statistical convergence, λ-statistical limit points

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Authors: Srishty Gulati, Anju Singh, Shrikant Kukreti

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The manifestation of structural polymorphism in DNA depends on the sequence and surrounding environment. Ample of folded DNA structures have been found in the cellular system out of which DNA hairpins are very common, however, are indispensable due to their role in the replication initiation sites, recombination, transcription regulation, and protein recognition. We enumerate this approach in our study, where the two base substitutions and change in temperature embark destabilization of DNA structure and misbalance the equilibrium between two structures of a sequence present at the overlapping region of the human COMT gene and MIR4761 gene. COMT and MIR4761 gene encodes for catechol-O-methyltransferase (COMT) enzyme and microRNAs (miRNAs), respectively. Environmental changes and errors during cell division lead to genetic abnormalities. The COMT gene entailed in dopamine regulation fosters neurological diseases like Parkinson's disease, schizophrenia, velocardiofacial syndrome, etc. A 19-mer deoxyoligonucleotide sequence 5'-AGGACAAGGTGTGCATGCC-3' (COMT19) is located at exon-4 on chromosome 22 and band q11.2 at the intersection of COMT and MIR4761 gene. Bioinformatics studies suggest that this sequence is conserved in humans and few other organisms and is involved in recognition of transcription factors in the vicinity of 3'-end. Non-denaturating gel electrophoresis and CD spectroscopy of COMT sequences indicate the formation of hairpin type DNA structures. Temperature-dependent CD studies revealed an unusual shift in the slipped DNA-Hairpin DNA equilibrium with the change in temperature. Also, UV-thermal melting techniques suggest that the two base substitutions on the complementary strand of COMT19 did not affect the structure but reduces the stability of duplex. This study gives insight about the possibility of existing structurally polymorphic transient states within DNA segments present at the intersection of COMT and MIR4761 gene.

Keywords: base-substitution, catechol-o-methyltransferase (COMT), hairpin-DNA, structural polymorphism

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Authors: Rajkumar Ghosh

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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: Md. Ahsan Ayub, Kazi A. Kalpoma, Humaira Tasnim Proma, Syed Mehrab Kabir, Rakib Ibna Hamid Chowdhury

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Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework.

Keywords: arc consistency (AC), backjumping algorithm (BJ), backtracking algorithm (BT), constraint satisfaction problem (CSP), forward checking (FC), least constrained values (LCV), maintaining arc consistency (MAC), minimum remaining values (MRV), N-Queens problem

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Authors: Hsi Wei

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Does the language we speak affect the way we think? This question has been discussed for a long time from different aspects. In this article, the issue is examined with an experiment on how speakers of different languages tend to do different sequencing when it comes to the size of general objects. An essential difference between the usage of English and Mandarin is the way we sequence the size of places or objects. In English, when describing the location of something we may say, for example, ‘The pen is inside the trashcan next to the tree at the park.’ In Mandarin, however, we would say, ‘The pen is at the park next to the tree inside the trashcan.’ It’s clear that generally English use the sequence of small to big while Mandarin the opposite. Therefore, the experiment was conducted to test if the difference of the languages affects the speakers’ ability to do the different sequencing. There were two groups of subjects; one consisted of English native speakers, another of Mandarin native speakers. Within the experiment, three nouns were showed as a group to the subjects as their native languages. Before they saw the nouns, they would first get an instruction of ‘big to small’, ‘small to big’, or ‘repeat’. Therefore, the subjects had to sequence the following group of nouns as the instruction they get or simply repeat the nouns. After completing every sequencing and repetition in their minds, they pushed a button as reaction. The repetition design was to gather the mere reading time of the person. As the result of the experiment showed, English native speakers reacted more quickly to the sequencing of ‘small to big’; on the other hand, Mandarin native speakers reacted more quickly to the sequence ‘big to small’. To conclude, this study may be of importance as a support for linguistic relativism that the language we speak do shape the way we think.

Keywords: language, linguistic relativism, size, sequencing

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Sandeep Vasaikar, Lary Obi

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Rapid and discriminative genotyping methods are useful for determining the clonality of the isolates in nosocomial or household outbreaks. Multilocus sequence typing (MLST) is a nucleotide sequence-based approach for characterising bacterial isolates. The genetic diversity and the clinical relevance of the drug-resistant Klebsiella isolates from Mthatha are largely unknown. For this reason, prospective, experimental study of the molecular epidemiology of Klebsiella isolates from patients being treated in Mthatha over a three-year period was analysed. Methodology: PCR amplification and sequencing of the drug-resistance-associated genes, and multilocus sequence typing (MLST) using 7 housekeeping genes mdh, pgi, infB, FusAR, phoE, gapA and rpoB were conducted. A total of 32 isolates were analysed. Results: The percentages of multidrug-resistant (MDR), extensively drug-resistance (XDR) and pandrug-resistant (PDR) isolates were; MDR 65.6 % (21) and XDR and PDR with 0 % each. In this study, K. pneumoniae was 19/32 (59.4 %). MLST results showed 22 sequence types (STs) were identified, which were further separated by Maximum Parsimony into 10 clonal complexes and 12 singletons. The most dominant group was Klebsiella pneumoniae with 23/32 (71.8 %) isolates, Klebsiella oxytoca as a second group with 2/32 (6.25 %) isolates, and a single (3.1 %) K. varricola as a third group while 6 isolates were of unknown sequences. Conclusions/significance: A phylogenetic analysis of the concatenated sequences of the 7 housekeeping genes showed that strains of K. pneumoniae form a distinct lineage within the genus Klebsiella, with K. oxytoca and K. varricola its nearest phylogenetic neighbours. With the analysis of 7 genes were determined 1 K. variicola, which was mistakenly identified as K. pneumoniae by phenotypic methods. Two misidentifications of K. oxytoca were found when phenotypic methods were used. No significant differences were observed between ESBL blaCTX-M, blaTEM and blaSHV groups in the distribution of Sequence types (STs) or Clonal complexes (CCs).

Keywords: phylogenetic analysis, phylogeny, klebsiella phylogenetic, klebsiella

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Authors: Avent Grange, Frederic Bertrand, Jean-Baptiste Droin, Amandine Marrel, Jean-Henry Ferrasse, Olivier Boutin

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CEA and its industrial partners are designing a gas Power Conversion System (PCS) based on a Brayton cycle for the ASTRID Sodium-cooled Fast Reactor. Investigations of control and regulation requirements to operate this PCS during operating, incidental and accidental transients are necessary to adapt core heat removal. To this aim, we developed a methodology to optimize the thermal-hydraulic behavior of the reactor during normal operations, incidents and accidents. This methodology consists of a multi-objective optimization for a specific sequence, whose aim is to increase component lifetime by reducing simultaneously several thermal stresses and to bring the reactor into a stable state. Furthermore, the multi-objective optimization complies with safety and operating constraints. Operating, incidental and accidental sequences use specific regulations to control the thermal-hydraulic reactor behavior, each of them is defined by a setpoint, a controller and an actuator. In the multi-objective problem, the parameters used to solve the optimization are the setpoints and the settings of the controllers associated with the regulations included in the sequence. In this way, the methodology allows designers to define an optimized and specific control strategy of the plant for the studied sequence and hence to adapt PCS piloting at its best. The multi-objective optimization is performed by evolutionary algorithms coupled to surrogate models built on variables computed by the thermal-hydraulic system code, CATHARE2. The methodology is applied to a loss of off-site power sequence. Three variables are controlled: the sodium outlet temperature of the sodium-gas heat exchanger, turbomachine rotational speed and water flow through the heat sink. These regulations are chosen in order to minimize thermal stresses on the gas-gas heat exchanger, on the sodium-gas heat exchanger and on the vessel. The main results of this work are optimal setpoints for the three regulations. Moreover, Proportional-Integral-Derivative (PID) control setting is considered and efficient actuators used in controls are chosen through sensitivity analysis results. Finally, the optimized regulation system and the reactor control procedure, provided by the optimization process, are verified through a direct CATHARE2 calculation.

Keywords: gas power conversion system, loss of off-site power, multi-objective optimization, regulation, sodium fast reactor, surrogate model

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Authors: Ti-Jun Xiao, Zhe Xu

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Controllability is one of the fundamental issues in control systems. In this paper, we study the controllability of second order evolutional control systems in Hilbert spaces with memory and boundary controls, which model dynamic behaviors of some viscoelastic materials. Transferring the control problem into a moment problem and showing the Riesz property of a family of functions related to Cauchy problems for some integrodifferential equations, we obtain a general boundary controllability theorem for these second order evolutional control systems. This controllability theorem is applicable to various concrete 1D viscoelastic systems and recovers some previous related results. It is worth noting that Riesz sequences can be used for numerical computations of the control functions and the identification of new Riesz sequence is of independent interest for the basis-function theory. Moreover, using the Riesz sequences, we obtain the existence and uniqueness of (weak) solutions to these second order evolutional control systems in Hilbert spaces. Finally, we derive the exact boundary controllability of a viscoelastic beam equation, as an application of our abstract theorem.

Keywords: evolutional control system, controllability, boundary control, existence and uniqueness

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Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: R. B. Mishra

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Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: hiden markov model, believe desire intention, neural activation, simulation

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Authors: Bilal Wadood, Suleman Khan, Sajjad Ahmed

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The Late Cretaceous strata (Mughal Kot Formation) exposed in Central Indus Basin, Pakistan is evaluated for establishing sequence stratigraphic framework and potential of hydrocarbon accumulation. The petrographic studies and SEM analysis were carried out to infer the hydrocarbon potential of the rock unit. The petrographic details disclosed 4 microfacies including Pelagic Mudstone, OrbitoidalWackestone, Quartz Arenite, and Quartz Wacke. The lowermost part of the rock unit consists of OrbitoidalWackestone which shows deposition in the middle shelf environment. The Quartz Arenite and Quartz Wacke suggest deposition on the deep slope settings while the Pelagic Mudstone microfacies point toward deposition in the distal deep marine settings. Based on the facies stacking patterns and cyclicity in the chronostratigraphic context, the strata is divided into two 3rd order cycles. One complete sequence i.e Transgressive system tract (TST), Highstand system tract (HST) and Lowstand system tract (LST) are again replaced by another Transgressive system tract and Highstant system tract with no markers of sequence boundary. The LST sands are sandwiched between TST and HST shales but no potential porosity/permeability values have been determined. Microfacies and SEM studies revealed very fewer chances for hydrocarbon accumulation and overall reservoir potential is characterized as low.

Keywords: cycle, deposition, microfacies, reservoir

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Authors: Saarah Juman, Ilona Johnson, Stephen Richmond, Brett Duane, Sheelagh Rogers

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Introduction: Researchers suggest that within 50 years or less, the available supply of a range of metals will be exhausted, potentially leading to increases in resource conflict and largescale production shortages. The healthcare, dental and orthodontic sectors will undoubtedly be affected as stainless steel instruments are generally heavily relied on. Although changing orthodontic archwires are unavoidable and necessary to allow orthodontic tooth movement through the progression of an archwire sequence with fixed appliances, they are thought to be manufactured in excess of what is needed. Furthermore, orthodontic archwires require trimming extraorally to allow safe intraoral insertion, thus contributing to unnecessary waste of natural resources. Currently, there is no evidence to support the optimisation of archwire length according to orthodontic fixed appliance stage. As such, this study aims to quantify archwire excess (extraoral archwire trimmings) for different stages of orthodontic fixed appliance treatment. Methodology: This prospective, observational, quantitative study observed trimmings made extraorally against pre-treatment study models by clinicians over a 3-month period. Archwires were categorised into one of three categories (initial aligning, sequence, working/finishing arcwhires) within the orthodontic fixed appliance archwire sequence. Data collection included archwire material composition and the corresponding length and weight of excess archwire. Data was entered using a Microsoft Excel spreadsheet and imported into statistical software to obtain simple descriptive statistics. Results: Measurements were obtained for a total of 144 archwires. Archwire materials included nickel titanium and stainless steel. All archwires observed required extraorally trimming to allow safe intraoral insertion. The manufactured lengths of orthodontic initial aligning, sequence, and working/finishing arcwhires were at least 31%, 26%, and 39% in excess, respectively. Conclusions: Orthodontic archwires are manufactured to be excessively long at all orthodontic archwire sequence stages. To conserve natural resources, this study’s findings support the optimisation of orthodontic archwire lengths by manufacturers according to the typical stages of an orthodontic archwire sequence.

Keywords: archwire, orthodontics, sustainability, waste

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Authors: Daphne Meza, Louie Abejar, David A. Rubenstein, Wei Yin

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Endothelial cell (ECs) morphology and function is highly impacted by the mechanical stresses these cells experience in vivo. Any change in the mechanical environment can trigger pathological EC responses. A detailed understanding of EC morphological response and function upon subjection to individual and simultaneous mechanical stimuli is needed for advancement in mechanobiology and preventive medicine. To investigate this, a programmable device capable of simultaneously applying physiological fluid shear stress (FSS) and cyclic strain (CS) has been developed, characterized and validated. Its validation was performed both experimentally, through tracer tracking, and theoretically, through the use of a computational fluid dynamics model. The effectiveness of the device was evaluated through EC morphology changes under mechanical loading conditions. Changes in cell morphology were evaluated through: cell and nucleus elongation, cell alignment and junctional actin production. The results demonstrated that the combined FSS-CS stimulation induced visible changes in EC morphology. Upon simultaneous fluid shear stress and biaxial tensile strain stimulation, cells were elongated and generally aligned with the flow direction, with stress fibers highlighted along the cell junctions. The concurrent stimulation from shear stress and biaxial cyclic stretch led to a significant increase in cell elongation compared to untreated cells. This, however, was significantly lower than that induced by shear stress alone, indicating that the biaxial tensile strain may counteract the elongating effect of shear stress to maintain the shape of ECs. A similar trend was seen in alignment, where the alignment induced by the concurrent application of shear stress and cyclic stretch fell in between that induced by shear stress and tensile stretch alone, indicating the opposite role shear stress and tensile strain may play in cell alignment. Junctional actin accumulation was increased upon shear stress alone or simultaneously with tensile stretch. Tensile stretch alone did not change junctional actin accumulation, indicating the dominant role of shear stress in damaging EC junctions. These results demonstrate that the shearing-stretching device is capable of applying well characterized dynamic shear stress and tensile strain to cultured ECs. Using this device, EC response to altered mechanical environment in vivo can be characterized in vitro.

Keywords: cyclic stretch, endothelial cells, fluid shear stress, vascular biology

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Authors: Sujeet Kumar Singh, Shiv Prasad Yadav

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This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example.

Keywords: triangular intuitionistic fuzzy number, linear programming problem, multi objective linear programming problem, fuzzy mathematical programming, membership function

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Authors: Syeda Qamarunnisa, Ishrat Jamil, Abid Azhar, Zabta K. Shinwari, Syed Irtifaq Ali

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A phylogenetic analysis of family Solanaceae was conducted using sequence data from the chloroplast intergenic atpB-rbcL spacer. Sequence data was generated from 17 species representing 09 out of 14 genera of Solanaceae from Pakistan. Cladogram was constructed using maximum parsimony method and results indicate that Solanaceae is mainly divided into two subfamilies; Solanoideae and Cestroideae. Four major clades within Solanoideae represent tribes; Physaleae, Capsiceae, Datureae and Solaneae are supported by high bootstrap value and the relationships among them are not corroborating with the previous studies. The findings established that subfamily Cestroideae comprised of three genera; Cestrum, Lycium, and Nicotiana with high bootstrap support. Position of Nicotiana inferred with atpB-rbcL sequence is congruent with traditional classification, which placed the taxa in Cestroideae. In the current study Lycium unexpectedly nested with Nicotiana with 100% bootstrap support and identified as a member of tribe Nicotianeae. Expanded sampling of other genera from Pakistan could be valuable towards improving our understanding of intrafamilial relationships within Solanaceae.

Keywords: systematics, solanaceae, phylogenetics, intergenic spacer, tribes

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Authors: Benjamin Lee Warren

Abstract:

Many problems exist in additive number theory which is essential to determine the primes that are the sum of two elements from a given single-variable polynomial sequence, and most of them are unattackable in the present day. Here, we determine solutions for this problem to a few certain sequences (certain binomial coefficients and power sums) using only elementary algebra and some algebraic factoring methods (as well as Euclid’s Lemma and Faulhaber’s Formula). In particular, we show that there are finitely many primes as sums of two of these types of elements. Several cases are fully illustrated, and bounds are presented for the cases not fully illustrated.

Keywords: binomial coefficients, power sums, primes, algebra

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Authors: Jafar Ahmadi, Zhohreh Asiaban, Sedigheh Fabriki Ourang

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Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max, and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.

Keywords: BES1/BZR1, brassinosteroids, phylogenetic analysis, transcription factor

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Authors: Parisi L., Hamili D., Azlan N.

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The aim of this study was to design and simulate a particular type of Asynchronous State Machine (ASM), namely a ‘traffic light controller’ (TLC), operated at a frequency of 0.5 Hz. The design task involved two main stages: firstly, designing a 4-bit binary counter using J-K flip flops as the timing signal and subsequently, attaining the digital logic by deploying ASM design process. The TLC was designed such that it showed a sequence of three different colours, i.e. red, yellow and green, corresponding to set thresholds by deploying the least number of AND, OR and NOT gates possible. The software Multisim was deployed to design such circuit and simulate it for circuit troubleshooting in order for it to display the output sequence of the three different colours on the traffic light in the correct order. A clock signal, an asynchronous 4-bit binary counter that was designed through the use of J-K flip flops along with an ASM were used to complete this sequence, which was programmed to be repeated indefinitely. Eventually, the circuit was debugged and optimized, thus displaying the correct waveforms of the three outputs through the logic analyzer. However, hazards occurred when the frequency was increased to 10 MHz. This was attributed to delays in the feedback being too high.

Keywords: asynchronous state machine, traffic light controller, circuit design, digital electronics

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Authors: Ching-Shoei Chiang

Abstract:

The Malfatti’s Problem solves the problem of fitting 3 circles into a right triangle such that these 3 circles are tangent to each other, and each circle is also tangent to a pair of the triangle’s sides. This problem has been extended to any triangle (called general Malfatti’s Problem). Furthermore, the problem has been extended to have 1+2+…+n circles inside the triangle with special tangency properties among circles and triangle sides; we call it extended general Malfatti’s problem. In the extended general Malfatti’s problem, call it Tri(Tn), where Tn is the triangle number, there are closed-form solutions for Tri(T₁) (inscribed circle) problem and Tri(T₂) (3 Malfatti’s circles) problem. These problems become more complex when n is greater than 2. In solving Tri(Tn) problem, n>2, algorithms have been proposed to solve these problems numerically. With a similar idea, this paper proposed an algorithm to find the radii of circles with the same tangency properties. Instead of the boundary of the triangle being a straight line, we use a convex circular arc as the boundary and try to find Tn circles inside this convex circular triangle with the same tangency properties among circles and boundary Carc. We call these problems the Carc(Tn) problems. The CPU time it takes for Carc(T16) problem, which finds 136 circles inside a convex circular triangle with specified tangency properties, is less than one second.

Keywords: circle packing, computer-aided geometric design, geometric constraint solver, Malfatti’s problem

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Authors: Ahemd Sameer, Braj Bhushan

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The objective of our study was to compare wayfinding strategies to remember route while navigation in an unfamiliar homogenous environment. Two videos developed using free ware Trimble Sketchup© each having nine identical turns (3 right, 3 left, 3 straight) with no distinguishing feature at any turn. Thirt-two male post-graduate students of IIT Kanpur participated in the study. The experiment was conducted in three phases. In the first phase participant generated a list of personally known items to be used as landmarks. In the second phase participant saw the first video and was required to remember the sequence of turns. In the second video participant was required to imagine a landmark from the list generated in the first phase at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. In the third phase, which was 20 minutes after the second phase, participants again recalled the sequence of turns. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: Wayfinding, Landmark, Homogenous Environment, Memory

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Authors: P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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Oxide based memristors were fabricated in order to establish its potential applications in analog/digital electronics. BaTiO₃-BiFeO₃ (BT-BFO) was employed as an active material, whereas platinum (Pt) and Nb-doped SrTiO₃ (Nb:STO) were served as a top and bottom electrodes, respectively. Piezoelectric force microscopy (PFM) was utilized to present the ferroelectricity and repeatable polarization inversion in the BT-BFO, demonstrating its effectiveness for resistive switching. The fabricated memristors exhibited excellent electrical characteristics, such as hysteresis current-voltage (I-V), high on/off ratio, high retention time, cyclic endurance, and low operating voltages. The band-alignment between the active material BT-BFO and the substrate Nb:STO was experimentally investigated using X-Ray photoelectron spectroscopy, and it attributed to staggered heterojunction alignment. An energy band diagram was proposed in order to understand the electrical transport in BT-BFO/Nb:STO heterojunction. It was identified that the I-V curves of these memristors have several discontinuities. Curve fitting technique was utilized to analyse the I-V characteristic, and the obtained I-V equations were found to be parabolic. Utilizing this analysis, a non-linear BT-BFO memristors equivalent circuit model was developed. Interestingly, the obtained equivalent circuit of the BT-BFO memristors mimics the identical electrical performance, those obtained in the fabricated devices. Based on the developed equivalent circuit, a finite state machine (FSM) design was proposed. Efforts were devoted to fabricate the same FSM, and the results were well matched with those in the simulated FSM devices. Its multilevel noise filtering and immunity to external noise characteristics were also studied. Further, the feature of variable negative resistance was established by controlling the current through the memristor.

Keywords: band alignment, finite state machine, polarization inversion, resistive switching

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Authors: Noppadon Phumeechanya, Panita Wannapiroon

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The purpose of this research is to design the ubiquitous scaffold learning environment using problem-based learning activities that enhance problem-solving skills and context awareness, and to evaluate the suitability of the ubiquitous scaffold learning environment using problem-based learning activities. We divide the research procedures into two phases. The first phase is to design the ubiquitous scaffold learning environment using problem-based learning activities, and the second is to evaluate the ubiquitous scaffold learning environment using problem-based learning activities. The sample group in this study consists of five experts selected using the purposive sampling method. We analyse data by arithmetic mean and standard deviation. The research findings are as follows; the ubiquitous scaffold learning environment using problem-based learning activities consists of three major steps, the first is preparation before learning. This prepares learners to acknowledge details and learn through u-LMS. The second is the learning process, where learning activities happen in the ubiquitous learning environment and learners learn online with scaffold systems for each step of problem solving. The third step is measurement and evaluation. The experts agree that the ubiquitous scaffold learning environment using problem-based learning activities is highly appropriate.

Keywords: ubiquitous learning environment scaffolding, learning activities, problem-based learning, problem-solving skills, context awareness

Procedia PDF Downloads 476