49 research outputs found

    Data Structuring Problems in the Bit Probe Model

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    We study two data structuring problems under the bit probe model: the dynamic predecessor problem and integer representation in a manner supporting basic updates in as few bit operations as possible. The model of computation considered in this paper is the bit probe model. In this model, the complexity measure counts only the bitwise accesses to the data structure. The model ignores the cost of computation. As a result, the bit probe complexity of a data structuring problem can be considered as a fundamental measure of the problem. Lower bounds derived by this model are valid as lower bounds for any realistic, sequential model of computation. Furthermore, some of the problems are more suitable for study in this model as they can be solved using less than ww bit probes where ww is the size of a computer word. The predecessor problem is one of the fundamental problems in computer science with numerous applications and has been studied for several decades. We study the colored predecessor problem, a variation of the predecessor problem, in which each element is associated with a symbol from a finite alphabet or color. The problem is to store a subset SS of size n,n, from a finite universe UU so that to support efficient insertion, deletion and queries to determine the color of the largest value in SS which is not larger than x,x, for a given xU.x \in U. We present a data structure for the problem that requires O(klogUloglogUk)O(k \sqrt[k]{{\log U} \over {\log \log U}}) bit probes for the query and O(k2logUloglogU)O(k^2 {{\log U} \over {\log \log U}}) bit probes for the update operations, where UU is the universe size and kk is positive constant. We also show that the results on the colored predecessor problem can be used to solve some other related problems such as existential range query, dynamic prefix sum, segment representative, connectivity problems, etc. The second structure considered is for integer representation. We examine the problem of integer representation in a nearly minimal number of bits so that increment and decrement (and indeed addition and subtraction) can be performed using few bit inspections and fewer bit changes. In particular, we prove a new lower bound of Ω(n)\Omega(\sqrt{n}) for the increment and decrement operation, where nn is the minimum number of bits required to represent the number. We present several efficient data structures to represent integers that use a logarithmic number of bit inspections and a constant number of bit changes per operation

    Concept of Cosmetics in the light of Classical Unani Literature

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    Since very ancient period Unani physicians has paid great attention toward the use of cosmetics. Unani literature is very rich in cosmeceutical formulations taking care of appearance and dealing with cosmetic diseases in humans. In Unani classical text like Kitab-ul-Mansoori, Al-Hawi-fil-Tib, Kamiul-us-Sana, Al-Qanoon-fit-Tib, Zakheera-e-Khwarzam Shahi, the details of cosmetics are mentioned under the headings of Tazeeniyaat. There are several single drugs or compound formulations described in Unani classical text. The use of Unani cosmetics is splendid because of its low cost, no side effect, easily available preparation. There are several Unani cosmeceuticals are described in unani classical text like Solid Cosmeceutical (Ghaza, Ghaliya, Kajal), Semi-solid Cosmeceutical (Tila, Zimad, Ubtan) and Liquid cosmeceutical (Ghusool, Pashoya). Keywords: Unani Medicine, Tazeeniyaat, Ubtan, Ghaza

    Natural selection shapes the evolution of SARS-CoV-2 Omicron in Bangladesh

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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved to give rise to a highly transmissive and immune-escaping variant of concern, known as Omicron. Many aspects of the evolution of SARS-CoV-2 and the driving forces behind the ongoing Omicron outbreaks remain unclear. Substitution at the receptor-binding domain (RBD) in the spike protein is one of the primary strategies of SARS-CoV-2 Omicron to hinder recognition by the host angiotensin-converting enzyme 2 (ACE2) receptor and avoid antibody-dependent defense activation. Here, we scanned for adaptive evolution within the SARS-CoV-2 Omicron genomes reported from Bangladesh in the public database GISAID (www.gisaid.org; dated 2 April 2023). The ratio of the non-synonymous (Ka) to synonymous (Ks) nucleotide substitution rate, denoted as ω, is an indicator of the selection pressure acting on protein-coding genes. A higher proportion of non-synonymous to synonymous substitutions (Ka/Ks or ω > 1) indicates positive selection, while Ka/Ks or ω near zero indicates purifying selection. An equal amount of non-synonymous and synonymous substitutions (Ka/Ks or ω = 1) refers to neutrally evolving sites. We found evidence of adaptive evolution within the spike (S) gene of SARS-CoV-2 Omicron isolated from Bangladesh. In total, 22 codon sites of the S gene displayed a signature of positive selection. The data also highlighted that the receptor-binding motif within the RBD of the spike glycoprotein is a hotspot of adaptive evolution, where many of the codons had ω > 1. Some of these adaptive sites at the RBD of the spike protein are known to be associated with increased viral fitness. The M gene and ORF6 have also experienced positive selection. These results suggest that although purifying selection is the dominant evolutionary force, positive Darwinian selection also plays a vital role in shaping the evolution of SARS-CoV-2 Omicron in Bangladesh

    Identifying the research, advocacy, policy and implementation needs for the prevention and management of respiratory syncytial virus lower respiratory tract infection in low- and middle-income countries

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    Introduction: The high burden of respiratory syncytial virus (RSV) infection in young children disproportionately occurs in low- and middle-income countries (LMICs). The PROUD (Preventing RespiratOry syncytial virUs in unDerdeveloped countries) Taskforce of 24 RSV worldwide experts assessed key needs for RSV prevention in LMICs, including vaccine and newer preventive measures. Methods: A global, survey-based study was undertaken in 2021. An online questionnaire was developed following three meetings of the Taskforce panellists wherein factors related to RSV infection, its prevention and management were identified using iterative questioning. Each factor was scored, by non-panellists interested in RSV, on a scale of zero (very-low-relevance) to 100 (very-high-relevance) within two scenarios: (1) Current and (2) Future expectations for RSV management. Results: Ninety questionnaires were completed: 70 by respondents (71.4% physicians; 27.1% researchers/scientists) from 16 LMICs and 20 from nine high-income (HI) countries (90.0% physicians; 5.0% researchers/scientists), as a reference group. Within LMICs, RSV awareness was perceived to be low, and management was not prioritised. Of the 100 factors scored, those related to improved diagnosis particularly access to affordable point-of-care diagnostics, disease burden data generation, clinical and general education, prompt access to new interventions, and engagement with policymakers/payers were identified of paramount importance. There was a strong need for clinical education and local data generation in the lowest economies, whereas upper-middle income countries were more closely aligned with HI countries in terms of current RSV service provision. Conclusion: Seven key actions for improving RSV prevention and management in LMICs are proposed

    Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

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    In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

    Using robot to serve the NC lathe

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    In 2007, there was a project in HAMK, Riihimäki to integrate the robotic arm to the NC lathe machine. During that project, one company successfully integrated them. In spring 2011 a topic was introduced to us to make a demonstration to automatically load and unload the CNC lathe, using the robot arm, and machines the work pieces. Basically, the objective of this thesis is to make a program for the robotic arm so it can load the CNC machine and retrieve it from the lathe after its being machined for six cycles. Six small aluminum cylindrical pieces were kept on a work table with same distance between them and the robotic arm was taught about their positions precisely. A simple part programming was required for the NC as the main objective was to show a demonstration of a semi-automated production cell. The process could not be made fully automated as the door of the CNC lathe is a manual one. A very sophisticated method was chosen to make a single robotic program for all the six pieces. And, the speed of the robot movements has been frequently changed to establish it as a fast process. All information presented to the reader has been gathered from literature used at HAMK production lab, interviews with the lab employees, discussion with the thesis supervisor, observations made at the lab, books and internet sources. The final result of the work was quite satisfactory as we were able to overcome all the barriers that came during this practical work. Further improvement of this project is still possible which could take a long time but the outcome should be bright
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