134 research outputs found
Shell-Based Finite Element Modeling of Herøysund Bridge in Norway
No full textThis paper thoroughly examines the application of the Finite Element Method (FEM)
to the numerical modal analysis of Herøysund Bridge, focusing on the theoretical backdrop, the
construction process, and FEM techniques. This work examines the specific applied FEM approaches
and their advantages and disadvantages. This Herøysund Bridge analysis employs a two-pronged
strategy consisting of a 3D–solid model and a shell model. To forecast the physical behavior of a
structure, assumptions, modeling methodologies, and the incorporation of specific components such
as pillars are applied to both approaches. This research also emphasizes the importance of boundary
conditions, examining the structural effects of standard Earth gravity, a post-tensioned load, and a
railing and asphalt load. The Results section thoroughly explores the mode shapes and frequencies
of the 3D–solid and shell models. The conclusion of this work includes findings obtained from the
study, implications for Herøysund Bridge, and a comparison of both modeling strategies. It also
incorporates ideas for future research and guides employing FEM 3D–solid and shell methods to
design and construct more efficient, resilient, and durable bridge structures
Map of study area Dhirkot Azad Jammu and Kashmir, Pakistan.
No full textMap of study area Dhirkot Azad Jammu and Kashmir, Pakistan.</p
An in Vivo Clinical Evaluation of the Primary Stability of Osseointegrated Implants in Type II Diabetes Patients Using Novel Radio Frequency Analysis (RFA)– A Cone Beam Computed Tomography Based Original Research Study
No full textAim: This study aims to evaluate the primary stability of osseointegrated implants in patients with type II diabetes using novel radiofrequency analysis (RFA).
Materials and Methods: The study involved 40 participants aged .20 healthy individuals and 20 with type II diabetes mellitus, who were all missing a mandibular first premolar. Implant primary stability was assessed using Resonance Frequency Analysis (RFA). After placing 20 implants in each group and evaluated stability using the Implant Stability Quotient (ISQ).
Statistical Analysis and Results: This study examined 40 patients with missing mandibular first premolars, split into two groups, 20 healthy individuals (Group 1) and 20 with type II diabetes mellitus (Group 2). Participants, aged 35 to 60, included 25 males and 15 females. The research evaluated dental implant stability using the Implant Stability Quotient (ISQ) via the Osstell device. Group 1 showed higher ISQ values (buccal 80.1 ± 6 Ncm, lingual 72.4 ± 6 Ncm, mesial 69.5 ± 5 Ncm, distal 65.3 ± 3 Ncm) compared to Group 2 (buccal 47.1 ± 3 Ncm, lingual 43.4 ± 5 Ncm, mesial 37.5 ± 3 Ncm, distal 35.3 ± 2 Ncm).
Conclusion: This study concluded thathealthy individuals show better primary stability after dental implants compared to type II diabetes patients. The findings suggest that RFA is a more reliable measure for assessing primary stability, impacting treatment planning and outcomes in dental implantology
Shell based finite element modeling of Herøysund Bridge
No full textThis master's thesis thoroughly examines the application of the Finite Element Method (FEM) to the numerical modal analysis of the Herøysund Bridge, focusing on the theoretical backdrop, construction process, FEM techniques, and Eurocode recommendations for concrete structures. This study aims to demonstrate the utility of FEM in bridge analysis by utilizing ANSYS 2023 R1 to conduct a full numerical investigation of the bridge's technical specifications and design features. The thesis discusses the theoretical background, including the context of applying FEM for bridge design and main bridge construction techniques. It then examines the specific FEM approaches applied and their advantages and disadvantages. The Herøysund Bridge analysis employs a two-pronged strategy consisting of a 3D-Solid Model and a Shell Model. To forecast the physical behavior of a structure, assumptions, modeling methodologies, and the incorporation of specific components such as pillars are applied to both approaches. The document describes the complexity of bridge design from the selection of units and materials through the development of connections and meshes.
The full report also emphasizes the importance of boundary conditions, examining the structural effects of standard earth gravity, post-tensioned load, and railing and asphalt load. The results section thoroughly explores the mode shapes and frequencies for the 3D-Solid and Shell models. The Modal Assurance Criteria analysis compares modal frequencies across several modes, including flexural, transverse bending, and twist modes. The conclusion of the thesis includes findings obtained from the study, implications for the Herøysund Bridge, detailed resonant frequencies of the structure, and a comparison of both modeling strategies. It also incorporates ideas for future research. It also guides employing FEM 3D-Solid and Shell methods to design and construct more efficient, resilient, and durable bridge structures
Computational methods for physiological data
No full textThesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2009.Author is also affiliated with the MIT Dept. of Electrical Engineering and Computer Science. Cataloged from PDF version of thesis.Includes bibliographical references (p. 177-188).Large volumes of continuous waveform data are now collected in hospitals. These datasets provide an opportunity to advance medical care, by capturing rare or subtle phenomena associated with specific medical conditions, and by providing fresh insights into disease dynamics over long time scales. We describe how progress in medicine can be accelerated through the use of sophisticated computational methods for the structured analysis of large multi-patient, multi-signal datasets. We propose two new approaches, morphologic variability (MV) and physiological symbolic analysis, for the analysis of continuous long-term signals. MV studies subtle micro-level variations in the shape of physiological signals over long periods. These variations, which are often widely considered to be noise, can contain important information about the state of the underlying system. Symbolic analysis studies the macro-level information in signals by abstracting them into symbolic sequences. Converting continuous waveforms into symbolic sequences facilitates the development of efficient algorithms to discover high risk patterns and patients who are outliers in a population. We apply our methods to the clinical challenge of identifying patients at high risk of cardiovascular mortality (almost 30% of all deaths worldwide each year). When evaluated on ECG data from over 4,500 patients, high MV was strongly associated with both cardiovascular death and sudden cardiac death. MV was a better predictor of these events than other ECG-based metrics. Furthermore, these results were independent of information in echocardiography, clinical characteristics, and biomarkers.(cont.) Our symbolic analysis techniques also identified groups of patients exhibiting a varying risk of adverse outcomes. One group, with a particular set of symbolic characteristics, showed a 23 fold increased risk of death in the months following a mild heart attack, while another exhibited a 5 fold increased risk of future heart attacks.by Zeeshan Hassan Syed.Ph.D
Habitat Suitability of the Common Leopard (Panthera pardus) in Azad Jammu and Kashmir, Pakistan: A Dual-Model Approach Using MaxEnt and Random Forest
No full textThe common leopard (Panthera pardus) in Azad Jammu and Kashmir (AJ and K), Pakistan, is increasingly threatened by habitat fragmentation and climate change. This study employs a dual-model approach, integrating Maximum Entropy (MaxEnt) and Random Forest algorithms with multi-source remote sensing data to evaluate leopard habitat suitability. Our analysis identifies land cover (LC), fractional vegetation cover (FVC), elevation, temperature seasonality (bio4), and distance to roads (Dist_road) as the most influential habitat predictors. Leopards exhibit a strong preference for mixed forests at elevations between 1000 and 3000 m, with a suitability index of 0.83. The study identifies several unsuitable conditions including: road proximity (<0.08 km), low elevation zones (<1000 m), areas with high temperature seasonality (bio4 > 8 °C), and non-forested land cover types. MaxEnt demonstrated superior habitat prediction accuracy over Random Forest (AUC = 0.912 vs. 0.827). The results highlight a distinct north-to-south suitability gradient, with optimal habitats concentrated in the northern districts (Muzaffarabad, Hattian, Neelum, Bagh, Haveli, Poonch, Sudhnutti) and declining suitability in human-dominated southern areas. Based on these findings, this study underscores the urgency of targeted conservation efforts in the northern districts of AJ and K, where optimal leopard habitats are identified. The findings emphasize the need for habitat connectivity and protection measures to mitigate the impacts of habitat fragmentation and climate change. Future conservation strategies should prioritize the preservation of mixed forests and the establishment of buffer zones around roads to ensure the long-term survival of the common leopard in this region
Ethnobotanical and biochemical study of berberis lycium royle collected from different areas of Azad Jammu and Kashmir
No full textBerberis lycium Royle has a long history of medicinal uses to treat different diseases. It naturally grows on the mountains of Indian subcontinent. Its ethnobotanical and biochemical study from the state of Azad Jammu and Kashmir (AJ&K) was not previously explored. So, the objective of the current study was to explore the ethnobotanical and biochemical properties of the B. lycium Royle population of AJ&K. For this purpose, samples of B. lycium Royle were randomly collected from five districts of Azad Jammu and Kashmir, including thirty-five locations. Demographic features of informants such as plant part used, methods of preparation, modes of administration, conservation status, and ethnomedicinal uses were documented. It was used for treating different diseases such as diabetes, arthritis, joint pain, and stomach ulcer. This plant is very famous for providing medicinal roots, leaves, and fruits which are extensively used in many parts of the world. The biochemical analysis was conducted for total phenolic contents (TPC), chlorophyll contents, and antioxidant activity. The highest level of TPC found was 88.66 ± 1.07 µg/g of gallic acid equivalent phenolic (GAE) from leaves collected from Patikka (Chanjhal), Muzaffarabad District, AJ&K. The highest total chlorophyll contents (3.75 ± 0.53 µg/ml) were found in samples collected from Sathrian, Neelum District. The highest antioxidant activity with lowest IC50 value (33.26 µg/ml) was obtained from the root of sample collected from Bakreyali, Muzaffarabad District, as compared with other districts. The concentration of berberine was found to be 4.76 percent in the root bark of B. lycium Royle, estimated by high-performance liquid chromatography (HPLC). In syrup composition, 0.95 mg/5 ml of berberine was used. Hence, it is concluded that amongst the five districts, the plant parts (stem, fruits, and root) collected from Muzaffarabad District, AJ&K, showed the highest medicinal potential due to its unique climatic conditions
Cable Propelled Gondola System Operation in Icing Conditions
No full textThe scope of this study comprehends problems associated with modern urban vehicles
known as cable propelled gondolas system operations in icing conditions. The aspects
under consideration are problems related to the operations, safety, and maintenance of
cable car systems in harsh climate conditions. The geographical location of the gondola
cars makes them vulnerable to severe weather conditions especially in cold climates of
the northern hemisphere, where icing on its components is an operational, maintenance,
and safety concern. The harsh climate conditions can cause unadorned malfunctions
posing a threat to the integrity the of system as well as a high risk to human safety. The
study basis on the identification of these problems in operational, maintenance and safety
domain including implications the industry faces in the form of severe accidents costing
precious lives and lost capital. Furthermore, it incorporates the ice detection, anti/de-icing
approaches as well as the safety strategies in use nowadays. The massive increase in
operations and dynamic climate conditions gondola cars require serious attention. This
study unsheathes serious underlying problems that severely affect the gondola operations,
makes them prone to major maintenance shutdowns and poses high risk to structural and
human safety. The identified problems in this study and severity of risks draw attention
to need for practicable solutions incorporating de-icing and ice removal techniques for
safe operation of gondolas in cold climates saving time, effort, inconvenience, and
prodigious lost capital
Gene expression patterns of encapsulated microbial cells
No full textTo design hybrid cellular/synthetic devices such as sensors and vaccines, understanding of how the metabolic state of living cells changes upon physical confinement within three-dimensional matrices is vital. We analyze the gene expression patterns of stationary phase Saccharomyces cerevisiae (S. cerevisiae) cells encapsulated within three distinct nanostructured silica matrices and relate those patterns to known naturally occurring metabolic states. It was found that the cells for all three-encapsulated methods enter quiescent states characteristic of response to stress, albeit to different degrees and with differences in detail. By the measure of enrichment of stress-related Gene Ontology categories, we find that the AqS+g encapsulation more amenable to the cells than CDA and SD encapsulation. We hypothesize that this differential response in the AqS+g encapsulation is related to four properties of the encapsulating gel: 1) oxygen permeability, 2) relative softness of the material, 3) development of a protective sheath around individual cells, and 4) the presence of glycerol in the gel, which has been previously noted to serve as a protectant for encapsulated cells and can serve as the sole carbon source for S. cerevisiae under aerobic conditions. This work represents a combination of experiment and analysis aimed at the design and development of 3D encapsulation procedures to induce, and perhaps control, well-defined physiological behaviors.
We also report on the temporal pattern of yeast gene expression patterns during encapsulation in silica matrices via a cell-directed assembly process, and upon release. Three broad classes of patterns are seen. A major shift in expression patterns is seen upon encapsulation, relative to the beginning stationary state, similar to previously reported stress response. Significant continuing shifts are seen by sampling at different intervals during a one week encapsulation. Upon release from encapsulation and reincubation in growth medium, the cells are in a state significantly different from the state prior to encapsulation and similar to the state during encapsulation. Implications are drawn for the use of encapsulated micro-organism as sensors and effectors, and for the persister state of such organisms.
Ordinarily Gene Ontology (GO) enrichment analysis is subject to an arbitrary threshold for defining significance of enriched classes. In this paper, we consider replacing an arbitrary threshold with F-measure optimization to define the p-value that divides “significant enrichment” from “non-significant”. It is found that evaluation of false negatives (essential for computing recall and thus F-measure) requires a heuristic (but reasonable) assumption. We apply F-measure optimization to two sets of genes from different organisms and use Benjamini-Hochberg and random resampling to evaluate the number of false positives. It is found that the uncorrected p- value that produces optimum F-measure varies widely from one data set to another. It is also found that all three methods of FDR calculation diverge from each other within a range of uncorrected p-values that provide F-measure optimum p-values. This study includes in Appendix II a pipeline for using resampling and F-measure optimization to create lists of enriched GO classes that provide for variable weights of precision and recall.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-12-01The student, Zeeshan Fazal, accepted the attached license on 2017-08-14 at 13:34.The student, Zeeshan Fazal, submitted this Dissertation for approval on 2017-08-14 at 13:40.This Dissertation was approved for publication on 2017-08-16 at 15:26.DSpace SAF Submission Ingestion Package generated from Vireo submission #11597 on 2018-03-13 at 10:32:05Made available in DSpace on 2018-03-13T17:28:57Z (GMT). No. of bitstreams: 5
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Assessment of Knowledge of Cardiopulmonary Resuscitation among Pharmacy Students of Mirpur, Azad Jammu & Kashmir
No full textIntroduction: Cardiopulmonary resuscitation (CPR) is the most important lifesaving technique in several emergency situations such as cardiac arrest. In future, being part of health care professionals, pharmacy students are deemed to possess basic skills and expertise which are required to perform CPR. Objective: To access the knowledge of cardiopulmonary among pharmacy students of Mirpur Azad Jammu & Kashmir. Methods: It was a questionnaire-based, descriptive cross-sectional study, conducted among 4th and 5th year students of two Pharmacy institutes of Mirpur AJ&K from November 2018 to January 2019. A pre-tested questionnaire from previous study was used to collect data. It comprised of 13 dichotomous questions with “Yes/No” options, regarding knowledge of CPR. Descriptive statistics was used to unfold the demographic characteristics. Inferential statistics (Kruskal Wallis and Man Whitney) tests were used for evaluating difference between dependent continuous variables and independent variables and Chi-square was applied to determine difference between grouped variables. P-value of less than 0.05 is considered significant. The data was analyzed using SPSS version 20. Result: Overall, 131 out of 150(response rate= 92%) students participated in current study. Gender distribution among the participants was almost equal with 66 males (50.4%) males and 65 (49.6%) females took part in current study. Participants of the age group 21-23 years (n=88, 67.2%) were dominant. Only few students (n=23, 17.6%) reported to have taken training in CPR previously. Eighty-eight (66.7%) had average knowledge of CPR. No significant differences among male and female, 4th and 5th year students of both the institutes were found. Conclusion: The study revealed that knowledge level of CPR is adequate in most of the students of pharmacy. However, further improvements are required to perform CPR in an efficient manner. Thus, training in CPR should be mandatory in the pharmacy curriculum
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