Search results for: personalized medicine application

Authors: Abenezer Nigussie

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Strategic control practice is a critical exercise, as it provides a sturdy influence towards firms or production partners to achieve the full implementation of effective predetermined plans. The importance of strategic control in a company is often measured by observing the relationship between strategic management and organizational performance. The conventional philosophy of strategic control in academia and the industry places significant emphasis on the ability to plan and execute initiatives. In contrast, the same emphasis on strategic management has received less attention in the housing industry. Although the pressures of project performance can often obscure the wider social, economic, and professional context in which strategic management is undertaken, it is these broad contextual areas that make strategic control a vital issue for construction businesses. Rapidly changing social and technological issues are creating an informed environment that will appear very different in the coming decades from what is experienced in today’s companies. Construction project activity is not adequately led by strategic management tools; projects are mostly executed through simple plans and schedules. The issues that this thesis addresses and solves involve the successful accompaniment of the construction project process through these strategic management tools. The second important aspect is an evaluation of project activity, which is mostly done through simple economic and technical valuation. However, during this research, effective strategic management tools are evaluated and suggested for the assessment of project activities. The research introduces a study of the current strategic management practices of construction companies and also presents the concept of strategic management and the areas that companies need to address to compete in the global market. A summary of an industry survey is documented along with the historical research that prompted the investigation of these topics with a focus on the implementation of tools. Strategic management is a concept that concerns making decisions and taking corrective actions to achieve the future goals and objectives of a company. The objective of this paper is to review the practice of strategic management in construction companies. Questionnaires were distributed to major construction companies listed under categories of each project capable of specifying the complete expression of strategic management tools. Findings of the research showed that the majority of development companies practice strategic management tools in the process and implementation of each tool.

Keywords: strategic management, management, analysis, project management

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Authors: Jay Patel

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This Research is about investigating the ‘image’ of the city, and asks whether this ‘image’ holds any significance that can be changed. Kevin Lynch in the book ‘The image of the city’ develops a framework that breaks down the city’s image into five physical elements. These elements (Paths, Edge, Nodes, Districts, and Landmarks), according to Lynch assess the legibility of the urbanscapes, that emerged from his perception-based study in 3 different cities (New Jersey, Los Angeles, and Boston) in the USA. The aim of this research is to investigate whether Lynch’s framework can be applied within an Indian context or not. If so, what are the possibilities and whether the imageability of Indian cities can be depicted through the Lynch’s physical elements or it demands an extension to the framework by either adding or subtracting a physical attribute. For this research project, the walled city of Jaipur was selected, as it is considered one of the futuristic designed cities of all time in India. The other significant reason for choosing Jaipur was that it is a historically planned city with solid historical, touristic and local importance; allowing an opportunity to understand the application of Lynch's elements to the city's image. In other words, it provides an opportunity to examine how the disadvantages of a city's implicit programme (its relics of bygone eras) can be converted into assets by improving the imageability of the city. To obtain data, a structured semi-open ended interview method was chosen. The reason for selecting this method explicitly was to gain qualitative data from the users rather than collecting quantitative data from closed-ended questions. This allowed in-depth understanding and applicability of Kevin Lynch’s framework while assessing what needs to be added. The interviews were conducted in Jaipur that yielded varied inferences that were different from the expected learning outcomes, highlighting the need for extension on Lynch’s physical elements to achieve city’s image. Whilst analyzing the data, there were few attributes found that defined the image of Jaipur. These were categorized into two: a Physical aspect (streets and arcade entities, natural features, temples and temporary/ informal activities) and Associational aspects (History, Culture and Tradition, Medium of help in wayfinding, and intangible aspects).

Keywords: imageability, Kevin Lynch, people’s perception, assessment, associational aspects, physical aspects

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Authors: Jing Jiang, Yuguang Gao, Yang Yu

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Facing increasingly challenging insurance payment pressures, the Chinese healthcare system is undergoing significant transformations, akin to the implementation of DRG payment models by the United States' Medicare. Consequently, there is a pressing need for Chinese hospitals to establish optimizations in departmental operations tailored to the ongoing healthcare payment reforms. This abstract delineates the meticulous construction of a scientifically rigorous and comprehensive index system at the departmental level in China strategically aligned with the evolving landscape of healthcare payment reforms. Methodologically, it integrates key process areas and maturity assessment theories, synthesizing relevant literature and industry standards to construct a robust framework and indicator pool. Employing the Delphi method, consultations with 21 experts were conducted, revealing a collective demonstration of high enthusiasm, authority, and coordination in designing the index system. The resulting model comprises four primary indicators -technical capabilities, cost-effectiveness, operational efficiency, and disciplinary potential- supported by 14 secondary indicators and 23 tertiary indicators with varied coefficient adjustment for department types (platform or surgical). The application of this evaluation system in a Chinese hospital within the northeastern region yielded results aligning seamlessly with the actual operational scenario. In conclusion, the index system comprehensively considers the integrity and effectiveness of structural, process, and outcome indicators and stands as a comprehensive reflection of the collective expertise of the engaged experts, manifesting in a model designed to elevate the operational management of hospital departments. Its strategic alignment with healthcare payment reforms holds practical significance in guiding departmental development positioning, brand cultivation, and talent development.

Keywords: Chinese healthcare system, Delphi method, departmental management, evaluation indicators, hospital operations, weight coefficients

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Authors: Amin Asgarian, Ghyslaine McClure

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Experiences in the past earthquakes have clearly demonstrated the necessity of seismic design and assessment of Non-Structural Components (NSCs) particularly in post-disaster structures such as hospitals, power plants, etc. as they have to be permanently functional and operational. Meeting this objective is contingent upon having proper seismic performance of both structural and non-structural components. Proper seismic design, analysis, and assessment of NSCs can be attained through generation of Floor Design Spectrum (FDS) in a similar fashion as target spectrum for structural components. This paper presents the developed methodology to generate FDS directly from corresponding Uniform Hazard Spectrum (UHS) (i.e. design spectra for structural components). The methodology is based on the experimental and numerical analysis of a database of 27 real Reinforced Concrete (RC) buildings which are located in Montreal, Canada. The buildings were tested by Ambient Vibration Measurements (AVM) and their dynamic properties have been extracted and used as part of the approach. Database comprises 12 low-rises, 10 medium-rises, and 5 high-rises and they are mostly designated as post-disaster\emergency shelters by the city of Montreal. The buildings are subjected to 20 compatible seismic records to UHS of Montreal and Floor Response Spectra (FRS) are developed for every floors in two horizontal direction considering four different damping ratios of NSCs (i.e. 2, 5, 10, and 20 % viscous damping). Generated FRS (approximately 132’000 curves) are statistically studied and the methodology is proposed to generate the FDS directly from corresponding UHS. The approach is capable of generating the FDS for any selection of floor level and damping ratio of NSCs. It captures the effect of: dynamic interaction between primary (structural) and secondary (NSCs) systems, higher and torsional modes of primary structure. These are important improvements of this approach compared to conventional methods and code recommendations. Application of the proposed approach are represented here through two real case-study buildings: one low-rise building and one medium-rise. The proposed approach can be used as practical and robust tool for seismic assessment and design of NSCs especially in existing post-disaster structures.

Keywords: earthquake engineering, operational and functional components, operational modal analysis, seismic assessment and design

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Authors: Cristina Munoz-Shuguli, Francisco Rodriguez, Julio Bruna, M. Jose Galotto, Abel Guarda

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The microbial contamination in fruits due to the presence of fungal is the most important cause of their deterioration and loss. The development of active food packaging materials with antifungal properties has been proposed as an innovative strategy in order to prevent this problem. In this way, natural compounds as the essential oils or their derivatives, also called volatile compounds (VC), can be incorporated in the food packaging materials to control the fungal growth during fruit packaging. However, if the VC is incorporated directly in the packaging material, it is released very fast due to VC high volatility. For this reason, the formation of inclusion complexes through the encapsulation of VC into beta-cyclodextrin (β-CD) and their incorporation in package materials is an alternative to maintain an antifungal atmosphere around the packaged fruits for longer times. In this context, the aim of this work was to develop inclusion complexes based in β-CD and VC (β-CD:VC) for further application in the antifungal food packaging materials development. β-CD:VC inclusion complexes were obtained with two different molar ratios 2:1 and 1:1, through co-precipitation method. The entrapment efficiency of β-CD:VC as well the release of antifungal compound from inclusion complexes exposed to different relative humidity (25, 50, and 97 %) to headspace were determined by gaseous chromatography (GC). Also, thermal and antimicrobial properties of β-CD:VC were determined through thermogravimetric analysis (TGA) and antifungal assays against Botrytis cinerea, respectively. GC results showed that β-CD:VC 2:1 had a higher entrapment efficiency than β-CD:VC 1:1, with values of 75.5 ± 3.71 % and 59.6 ± 1.51 %, respectively. It was probably because during the synthesis of β-CD:VC 1:1, there was less molecular space to the movement of VC molecules. Furthermore, the release of VC from β-CD:VC was directly related with the relative humidity. High amount of VC was released when the inclusion complexes were exposed to high humidity, possibly due to the interactions between the water molecules and the β-CD hydrophilic wall. On the other hand, a better thermal stability of VC in inclusion complexes allowed to verify its effective encapsulation into β-CD. Finally, antimicrobial assays showed that the inclusion complexes had a high antifungal activity at very low concentrations. Therefore, the results obtained in this work allow suggesting the β-CD:VC inclusion complexes as potential candidates to the development of fruit antifungal packaging materials, which activity is relative humidity dependent.

Keywords: Botrytis cinerea, fruit packaging, headspace release, volatile compounds

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Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

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Authors: M. C. O. Ezeibe, F. I. O. Ezeibe

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Reasons viral diseases (including AI, HIV/AIDS, and COVID-19), tumors (including Cancers and Prostrate enlargement), and antimicrobial-resistant infections (AMR) are difficult to cure are features of the pathogens which normal cells do not have or need (biomedical markers) have not been identified; medicines that can counter the markers have not been invented; strategies and mechanisms for their treatments have not been developed. When cells become abnormal, they acquire negative electrical charges, and viruses are either positively charged or negatively charged, while normal cells remain neutral (without electrical charges). So, opposite charges' electrostatic attraction is a treatment mechanism for viral diseases and tumors. Medicines that have positive electrical charges would mop abnormal (infected and tumor) cells and DNA viruses (negatively charged), while negatively charged medicines would mop RNA viruses (positively charged). Molecules of Aluminum-magnesium silicate [AMS: Al₂Mg₃ (SiO₄)₃], an approved medicine and pharmaceutical stabilizing agent, consist of nanoparticles which have both positive electrically charged ends and negative electrically charged ends. The very small size (0.96 nm) of the nanoparticles allows them to reach all cells in every organ. By stabilizing antimicrobials, AMS reduces the rate at which the body metabolizes them so that they remain at high concentrations for extended periods. When drugs remain at high concentrations for longer periods, their efficacies improve. Again, nanoparticles enhance the delivery of medicines to effect targets. Both remaining at high concentrations for longer periods and better delivery to effect targets improve efficacy and make lower doses achieve desired effects so that side effects of medicines are reduced to allow the immunity of patients to be enhanced. Silicates also enhance the immune responses of treated patients. Improving antimicrobial efficacies and enhancing patients` immunity terminate infections so that none remains that could develop resistance. Some countries do not have natural deposits of AMS, but they may have Aluminum silicate (AS: Al₄ (SiO₄)₃) and Magnesium silicate (MS: Mg₂SiO₄), which are also approved medicines. So, AS and MS were used to formulate an AMS-brand, named Medicinal synthetic AMS {Al₄ (SiO₄)₃ + 3Mg₂SiO₄ → 2Al₂Mg₃ (SiO₄)₃}. To overcome the challenge of AMS, AS, and MS being un-absorbable, Dextrose monohydrate is incorporated in MSAMS-formulations for the simple sugar to convey the electrically charged nanoparticles into blood circulation by the principle of active transport so that MSAMS-antimicrobial formulations function systemically. In vitro, MSAMS reduced (P≤0.05) titers of viruses, including Avian influenza virus and HIV. When used to treat virus-infected animals, it cured Newcastle disease and Infectious bursa disease of chickens, Parvovirus disease of dogs, and Peste des petits ruminants disease of sheep and goats. A number of HIV/AIDS patients treated with it have been reported to become HIV-negative (antibody and antigen). COVID-19 patients are also reported to recover and test virus negative when treated with MSAMS. PSA titers of prostate cancer/enlargement patients normalize (≤4) following treatment with MSAMS. MSAMS has also potentiated ampicillin trihydrate, sulfadimidin, cotrimoxazole, piparazine citrate and chloroquine phosphate to achieve ≥ 95 % infection-load reductions (AMR-prevention). At 75 % of doses of ampicillin, cotrimoxazole, and streptomycin, supporting MSAMS-formulations' treatments with antioxidants led to the termination of even already resistant infections.

Keywords: electrical charges, viruses, abnormal cells, aluminum-magnesium silicate

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Authors: Liqin Zhi, Lin Xu, Wenxia Wei, Yaqi Cai

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Recently, replacing some of the methyl groups in polydimethylsiloxanes with other functional groups has been extensively explored to obtain modified polymethylsiloxanes with special properties that enable new industrial applications. Fluorinated polysiloxanes, one type of these modified polysiloxanes, are based on a siloxane backbone with fluorinated groups attached to the side chains of polysiloxanes. As a commercially significant material, poly[methyl(trifluoropropyl)siloxane] (PMTFPS) has sufficient fluorine content to be useful as a fuel-and oil-resistant elastomer, which combines both the chemical and solvent resistance of fluorocarbons and the wide temperature range applicability of organosilicones. PMTFPS products can be used in many applications in which resistance to fuel, oils and hydrocarbon solvents is required, including use as lubricants in bearings, sealants, and elastomers for aerospace and automotive fuel systems. Fluorinated methylsiloxanes, a type of modified methylsiloxane, include tris(trifluoropropyl)trimethylcyclotrisiloxane (D3F) and tetrakis(trifluoropropyl)tetramethylcyclotetrasiloxane (D4F), both of which contain trifluoropropyl groups in the side chains of cyclic methylsiloxanes. D3F, as an important monomer in the manufacture of PMTFPS, is often present as an impurity in PMTFPS. In addition, the synthesis of PMTFPS from D3F could form other fluorinated methylsiloxanes with low molecular weights (such as D4F). The yearly demand and production volumes of D3F increased rapidly all over world. Fluorinated methylsiloxanes might be released into the environment via different pathways during the production and application of PMTFPS. However, there is a lack of data concerning the emission, environmental occurrence and potential environmental impacts of fluorinated methylsiloxanes. Here, we report fluorinated methylsiloxanes (D3F and D4F) in surface water and sediment samples collected near a fluorinated methylsiloxane manufacturing plant in Weihai, China. The concentrations of D3F and D4F in surface water ranged from 3.29 to 291 ng/L and from 7.02 to 168 ng/L, respectively. The concentrations of D3F and D4F in sediment ranged from 11.8 to 5478 ng/g and from 17.2 to 6277 ng/g, respectively. In simulation experiment, the half-lives of D3F and D4F at different pH values (5.2, 6.4, 7.2, 8.3 and 9.2) varied from 80.6 to 154 h and from 267 to 533 h respectively. CF₃(CH₂)₂MeSi(OH)₂ was identified as one of the main hydrolysis products of fluorinated methylsiloxanes. It was also detected in the river samples at concentrations of 72.1-182.9 ng/L. In addition, the slow rearrangement of D3F (spiked concentration = 500 ng/L) to D4F (concentration = 11.0-22.7 ng/L) was also found during 336h hydrolysis experiment.

Keywords: fluorinated methylsiloxanes, environmental matrices, hydrolysis, sediment

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Authors: P. Slepicka, N. Slepickova Kasalkova, I. Michaljanicova, O. Nedela, Z. Kolska, V. Svorcik

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Polymers exposed to laser or plasma treatment or modified with different wet methods which enable the introduction of nanoparticles or biologically active species, such as amino-acids, may find many applications both as biocompatible or anti-bacterial materials or on the contrary, can be applied for a decrease in the number of cells on the treated surface which opens application in single cell units. For the experiments, two types of materials were chosen, a representative of non-biodegradable polymers, polyethersulphone (PES) and polyhydroxybutyrate (PHB) as biodegradable material. Exposure of solid substrate to laser well below the ablation threshold can lead to formation of various surface structures. The ripples have a period roughly comparable to the wavelength of the incident laser radiation, and their dimensions depend on many factors, such as chemical composition of the polymer substrate, laser wavelength and the angle of incidence. On the contrary, biopolymers may significantly change their surface roughness and thus influence cell compatibility. The focus was on the surface treatment of PES and PHB by pulse excimer KrF laser with wavelength of 248 nm. The changes of physicochemical properties, surface morphology, surface chemistry and ablation of exposed polymers were studied both for PES and PHB. Several analytical methods involving atomic force microscopy, gravimetry, scanning electron microscopy and others were used for the analysis of the treated surface. It was found that the combination of certain input parameters leads not only to the formation of optimal narrow pattern, but to the combination of a ripple and a wrinkle-like structure, which could be an optimal candidate for cell attachment. The interaction of different types of cells and their interactions with the laser exposed surface were studied. It was found that laser treatment contributes as a major factor for wettability/contact angle change. The combination of optimal laser energy and pulse number was used for the construction of a surface with an anti-cellular response. Due to the simple laser treatment, we were able to prepare a biopolymer surface with higher roughness and thus significantly influence the area of growth of different types of cells (U-2 OS cells).

Keywords: cell response, excimer laser, polymer treatment, periodic pattern, surface morphology

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Ali Heyder Alatas, D. Xin, L. Nai Ming

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An oil spill emergency can vary in size and complexity, subject to factors such as volume and characteristics of spilled oil, incident location, impacted sensitivities and resources required. A major incident typically involves numerous stakeholders; these include the responsible party, response organisations, government authorities across multiple jurisdictions, local communities, and a spectrum of technical experts. An incident management team will encounter numerous challenges. Factors such as limited access to location, adverse weather, poor communication, and lack of pre-identified resources can impede a response; delays caused by an inefficient response can exacerbate impacts caused to the wider environment, socio-economic and cultural resources. It is essential that all parties work based on defined roles, responsibilities and authority, and ensure the availability of sufficient resources. To promote steadfast coordination and overcome the challenges highlighted, an Incident Management System (IMS) offers an essential tool for oil spill response. It provides clarity in command and control, improves communication and coordination, facilitates the cooperation between stakeholders, and integrates resources committed. Following the preceding discussion, a comprehensive review of existing literature serves to illustrate the application of IMS in oil spill response to overcome common challenges faced in a major-scaled incident. With a primary audience comprising practitioners in mind, this study will discuss key principles of incident management which enables an effective response, along with pitfalls and challenges, particularly, the tension between government and industry; case studies will be used to frame learning and issues consolidated from previous research, and provide the context to link practice with theory. It will also feature the industry approach to incident management which was further crystallized as part of a review by the Joint Industry Project (JIP) established in the wake of the Macondo well control incident. The authors posit that a common IMS which can be adopted across the industry not only enhances response capacity towards a major oil spill incident but is essential to the global preparedness effort.

Keywords: command and control, incident management system, oil spill response, response organisation

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Authors: Jun Sun, Tsz Tin Yu, Maryam Mirabediny, Matthew Lee, Adele Jones, Denis M. O’Carroll, Michael J. Manefield, Björn Åkermark, Biswanath Das, Naresh Kumar

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Reductive defluorination has emerged as a sustainable approach to clean water from Per and polyfluoroalkyl substances (PFASs), also known as forever organic containments. For last few decades, nano zero valent metals (nZVMs) have been intensively applied in the reductive remediation of groundwater contaminated with chlorinated organic compounds due to its low redox potential, easy application, and low production cost. However, there is inadequate information on the effective reductive defluorination of linear or branched PFAS using nZVMs as reductants because of the lack of suitable catalysts. CoII-5,10,15,20-Tetraphenyl-21H,23H-porphyrin (CoTPP) has been recently reported for effective catalyzing reductive defluorination of branched (br-) perfluorooctane sulfonate (PFOS) by using TiIII citrate as reductant. However, the low water solubility of CoTPP limited its applicability. Here, we explored a series of structurally related soluble cobalt porphyrin catalysts based on our previously reported best performing CoTPP. All soluble porphyrins [[meso-tetra(4-carboxyphenyl)porphyrinato]cobalt(III)]Cl·₇H₂O (CoTCPP), [[meso-tetra(4-sulfonatophenyl) porphyrinato]cobalt(III)]·9H2O (CoTPPS), and [[meso-tetra(4-N-methylpyridyl) porphyrinato]cobalt(II)](I)₄·₄H₂O (CoTMpyP) displayed better defluorination efficiencies than CoTPP. Especially, CoTMpyP presented the best defluorination efficiency for br-PFOS (94 %), branched perfluorooctanoic acid (PFOA) (89 %), and 3,7-Perfluorodecanoic acid (PFDA) (60 %) after 1 day at 70 0C. CoTMpyP-nZn0 system showed 88-164 times higher defluorination rate than VB12-nZn0 system in terms of all investigated br-PFASs. The CoTMpyP-nZn0 also performed effectively at room temperature, demonstrating the potential prospect for in-situ reductive systems. Based on the analysis of the intermediate products, the calculated bond dissociation energies (BDEs) and possible first interaction between CoTMpyP and PFAS, degradation pathways of 3,7-PFDA and 6-PFOS are proposed.

Keywords: cationic, soluble porphyrin, cobalt, vitamin b12, pfas, reductive defluorination

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Authors: Batuhan Kocaoglu

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Nowadays digital transformation is a hot topic both in service and production business. For the companies who want to stay alive in the following years, they should change how they do their business. Industry leaders started to improve their ERP (Enterprise Resource Planning) like backbone technologies to digital advances such as analytics, mobility, sensor-embedded smart devices, AI (Artificial Intelligence) and more. Selecting the appropriate technology for the related business problem also is a hot topic. Besides this, to operate in the modern environment and fulfill rapidly changing customer expectations, a digital transformation of the business is required and change the way the business runs, affect how they do their business. Even the digital transformation term is trendy the literature is limited and covers just the philosophy instead of a solid implementation plan. Current studies urge firms to start their digital transformation, but few tell us how to do. The huge investments scare companies with blur definitions and concepts. The aim of this paper to solidify the steps of the digital transformation and offer a roadmap for the companies and academicians. The proposed roadmap is developed based upon insights from the literature review, semi-structured interviews, and expert views to explore and identify crucial steps. We introduced our roadmap in the form of 8 main steps: Awareness; Planning; Operations; Implementation; Go-live; Optimization; Autonomation; Business Transformation; including a total of 11 sub-steps with examples. This study also emphasizes four dimensions of the digital transformation mainly: Readiness assessment; Building organizational infrastructure; Building technical infrastructure; Maturity assessment. Finally, roadmap corresponds the steps with three main terms used in digital transformation literacy as Digitization; Digitalization; and Digital Transformation. The resulted model shows that 'business process' and 'organizational issues' should be resolved before technology decisions and 'digitization'. Companies can start their journey with the solid steps, using the proposed roadmap to increase the success of their project implementation. Our roadmap is also adaptable for relevant Industry 4.0 and enterprise application projects. This roadmap will be useful for companies to persuade their top management for investments. Our results can be used as a baseline for further researches related to readiness assessment and maturity assessment studies.

Keywords: digital transformation, digital business, ERP, roadmap

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Authors: Najmeh Hoseini

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Strokerecovery happens through neuroplasticity, which is highly influenced by the environment, including neuro-rehabilitation. Transcranial direct current stimulation (tDCS) may enhance recovery by modulating neuroplasticity. With tDCS, weak direct currents are applied noninvasively to modify excitability in the cortical areas under its electrodes. Combined with functional activities, this may facilitate motor recovery in neurologic disorders such as stroke. The purpose of this case study was to examine the effect of tDCS combined with 30 minutes of traditional physical therapy (PT)on arm function following a stroke. A 29-year-old male with chronic stroke involving the left middle cerebral artery territory went through the treatment protocol. Design The design included 5 weeks of treatment: 1 week of traditional PT, 2 weeks of sham tDCS combined with traditional PT, and 2 weeks of tDCS combined with traditional PT. PT included functional electrical stimulation (FES) of wrist extensors followed by task-specific functional training. Dual hemispheric tDCS with 1 mA intensity was applied on the sensorimotor cortices for the first 20 min of the treatment combined with FES. Assessments before and after each treatment block included Modified Ashworth Scale, ChedokeMcmaster Arm and Hand inventory, Action Research Arm Test (ARAT), and the Box and Blocks Test. Results showed reduced spasticity in elbow and wrist flexors only after tDCS combination weeks (+1 to 0). The patient demonstrated clinically meaningful improvements in gross motor and fine motor control over the duration of the study; however, components of the ARAT that require fine motor control improved the greatest during the experimental block. Average time improvement compared to baseline was26.29 s for tDCS combination weeks, 18.48 s for sham tDCS, and 6.83 for PT standard of care weeks. Combining dual hemispheric tDCS with the standard of care PT demonstrated improvements in hand dexterity greater than PT alone in this patient case.

Keywords: tDCS, stroke, case study, physical therapy

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Authors: Hassan Qandil

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Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

Procedia PDF Downloads 155

Authors: Zhengming Wu

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NanoFrazor lithography systems were developed as a first true alternative or extension to standard mask-less nanolithography methods like electron beam lithography (EBL). In contrast to EBL they are based on thermal scanning probe lithography (t-SPL). Here a heatable ultra-sharp probe tip with an apex of a few nm is used for patterning and simultaneously inspecting complex nanostructures. The heat impact from the probe on a thermal responsive resist generates those high-resolution nanostructures. The patterning depth of each individual pixel can be controlled with better than 1 nm precision using an integrated in-situ metrology method. Furthermore, the inherent imaging capability of the Nanofrazor technology allows for markerless overlay, which has been achieved with sub-5 nm accuracy as well as it supports stitching layout sections together with < 10 nm error. Pattern transfer from such resist features below 10 nm resolution were demonstrated. The technology has proven its value as an enabler of new kinds of ultra-high resolution nanodevices as well as for improving the performance of existing device concepts. The application range for this new nanolithography technique is very broad spanning from ultra-high resolution 2D and 3D patterning to chemical and physical modification of matter at the nanoscale. Nanometer-precise markerless overlay and non-invasiveness to sensitive materials are among the key strengths of the technology. However, while patterning at below 10 nm resolution is achieved, significantly increasing the patterning speed at the expense of resolution is not feasible by using the heated tip alone. Towards this end, an integrated laser write head for direct laser sublimation (DLS) of the thermal resist has been introduced for significantly faster patterning of micrometer to millimeter-scale features. Remarkably, the areas patterned by the tip and the laser are seamlessly stitched together and both processes work on the very same resist material enabling a true mix-and-match process with no developing or any other processing steps in between. The presentation will include examples for (i) high-quality metal contacting of 2D materials, (ii) tuning photonic molecules, (iii) generating nanofluidic devices and (iv) generating spintronic circuits. Some of these applications have been enabled only due to the various unique capabilities of NanoFrazor lithography like the absence of damage from a charged particle beam.

Keywords: nanofabrication, grayscale lithography, 2D materials device, nano-optics, photonics, spintronic circuits

Procedia PDF Downloads 73

Authors: Hilary Modir, Kyle Dutton, Michelle Swab, Shabnam Asghari

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Since its emergence, the cutaneous manifestations of COVID-19 have been documented in the literature. However, the majority are case reports with significant limitations in appraisal quality, thus leaving the role of dermatological manifestations of COVID-19 erroneously underexplored. The primary aim of this review was to systematically examine clinical patterns of dermatological manifestations as reported in the literature. This study was designed as a systematic review of case reports. The inclusion criteria consisted of all published reports and articles regarding COVID-19 in English, from September 1st, 2019, until June 22nd, 2020. The population consisted of confirmed cases of COVID-19 with associated cutaneous signs and symptoms. Exclusion criteria included research in planning stages, protocols, book reviews, news articles, review studies, and policy analyses. With the collaboration of a librarian, a search strategy was created consisting of a mixture of keyword terms and controlled vocabulary. Electronic databases searched were MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, LILACS, PsycINFO, WHO Global Literature on Coronavirus Disease, Cochrane Library, Campbell Collaboration, Prospero, WHO International Clinical Trials Registry Platform, Australian and New Zealand Clinical Trials Registry, U.S. Institutes of Health Ongoing Trials Register, AAD Registry, OSF preprints, SSRN, MedRxiV and BioRxiV. The study selection featured an initial pre-screening of titles and abstracts by one independent reviewer. Results were verified by re-examining a random sample of 1% of excluded articles. Eligible studies progressed for full-text review by two calibrated independent reviewers. Covidence was used to store and extract data, such as citation information and findings pertaining to COVID-19 and cutaneous signs and symptoms. Data analysis and summarization methodology reflect the framework proposed by PRISMA and recommendations set out by Cochrane and Joanna Brigg’s Institute for conducting systematic reviews. The Oxford Centre for Evidence-Based Medicine’s level of evidence was used to appraise the quality of individual studies. The literature search revealed a total of 1221 articles. After the abstract and full-text screening, only 95 studies met the eligibility criteria, proceeding to data extraction. Studies were divided into 58% case reports and 42% series. A total of 833 manifestations were reported in 723 confirmed COVID-19 cases. The most frequent lesions were 23% maculopapular, 15% urticarial and 13% pseudo-chilblains, with 46% of lesions reporting pruritus, 16% erythema, 14% pain, 12% burning sensation, and 4% edema. The most common lesion locations were 20% trunk, 19.5% lower limbs, and 17.7% upper limbs. The time to resolution of lesions was between one and twenty-one days. In conclusion, over half of the reported cutaneous presentations in COVID-19 positive patients were maculopapular, urticarial and pseudo-chilblains, with the majority of lesions distributed to the extremities and trunk. As this review’s sample size only contained COVID-19 confirmed cases with skin presentations, it becomes difficult to deduce the direct relationship between skin findings and COVID-19. However, it can be correlated that acute onset of skin lesions, such as chilblains-like, may be associated with or may warrant consideration of COVID-19 as part of the differential diagnosis.

Keywords: COVID-19, cutaneous manifestations, cutaneous signs, general dermatology, medical dermatology, Sars-Cov-2, skin and infectious disease, skin findings, skin manifestations

Procedia PDF Downloads 182

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

Procedia PDF Downloads 157

Authors: Tasha L. Golden

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Girls in the U.S. juvenile justice system are most often arrested for truancy, drug use, or running from home, all of which are symptoms of abuse. In fact, some have called this 'The Sexual Abuse to Prison Pipeline.' Such abuse has consequences for girls' health, education, employment, and parenting, often resulting in significant health disparities. Yet when arrested, girls rarely encounter services designed to meet their unique needs. Instead, they are expected to cope with a system that was historically designed for males. In fact, even literature advocating for increased gender equity frequently fails to include girls’ voices and firsthand accounts. In response to these combined injustices, public health researchers launched a trauma-informed creative writing intervention in a southern juvenile detention facility. The program was designed to improve the health of detained girls, while also establishing innovative methods of both data collection and social justice advocacy. Girls’ poems and letters were collected and coded, adding rich qualitative data to traditional survey responses. In addition, as part of the intervention, these poems are regularly published by international literary publisher Sarabande Books—and distributed to judges, city leaders, attorneys, state representatives, and more. By utilizing a creative medium, girls generated substantial civic engagement with their concerns—thus expanding their influence and improving policy advocacy efforts. Researchers hypothesized that having access to their communities and policy makers would provide its own health benefits for incarcerated girls: cultivating self-esteem, locus of control, and a sense of leadership. This paper discusses the establishment of this intervention, examines findings from its evaluation, and includes several girls’ poems as exemplars. Grounded in social science regarding expressive writing, stigma, muted group theory, and health promotion, the paper theorizes about the application of arts-based advocacy efforts to other social justice endeavors.

Keywords: advocacy, public health, social justice, women’s health

Procedia PDF Downloads 171

Authors: Mahtab Makaremi Masouleh, Günter Wozniak

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This research is part of an interdisciplinary project, promoting the design of a light temporary installable textile defence system against flood. In case river water levels increase abruptly especially in winter time, one can expect massive extra load on a textile protective structure in term of impact as a result of floating debris and even tree trunks. Estimation of this impulsive force on such structures is of a great importance, as it can ensure the reliability of the design in critical cases. This fact provides the motivation for the numerical analysis of a fluid structure interaction application, comprising flexible slender shaped and free-surface water flow, where an accelerated heavy flotsam tends to approach the membrane. In this context, the analysis on both the behavior of the flexible membrane and its interaction with moving flotsam is conducted by finite elements based solvers of the explicit solver and implicit Abacus solver available as products of SIMULIA software. On the other hand, a study on how free surface water flow behaves in response to moving structures, has been investigated using the finite volume solver of Star CCM+ from Siemens PLM Software. An automatic communication tool (CSE, SIMULIA Co-Simulation Engine) and the implementation of an effective partitioned strategy in form of an implicit coupling algorithm makes it possible for partitioned domains to be interconnected powerfully. The applied procedure ensures stability and convergence in the solution of these complicated issues, albeit with high computational cost; however, the other complexity of this study stems from mesh criterion in the fluid domain, where the two structures approach each other. This contribution presents the approaches for the establishment of a convergent numerical solution and compares the results with experimental findings.

Keywords: co-simulation, flexible thin structure, fluid-structure interaction, implicit coupling algorithm, moving flotsam

Procedia PDF Downloads 389

Authors: Cristiane R. Magalhaes

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Advances in Information and Communication Technologies (ICT) have led to changes in different sectors particularly in architecture, engineering, construction, and operation (AECO) industry. In this context, the advent of BIM (Building Information Modeling) has brought a number of opportunities in the field of the digital architectural design process bringing integrated design concepts that impact on the development, elaboration, coordination, and management of ventures. The project scope has begun to contemplate, from its original stage, the third dimension, by means of virtual environments (VEs), composed of models containing different specialties, substituting the two-dimensional products. The possibility to simulate the construction process of a venture in a VE starts at the beginning of the design process offering, through new technologies, many possibilities beyond geometrical digital modeling. This is a significant change and relates not only to form, but also to how information is appropriated in architectural and engineering models and exchanged among professionals. In order to achieve the main objective of this work, the Design Science Research Method will be adopted to elaborate an artifact containing strategies for the application and use of ICTs from BIM flows, with pre-construction cut-off to the execution of the building. This article intends to discuss and investigate how BIM can be extended to the site acting as a protagonist and link between the Virtual Environments and the Real-World, as well as its contribution to the integration of the value chain and the consequent increase of efficiency in the production of the building. The virtualization of the design process has reached high levels of development through the use of BIM. Therefore it is essential that the lessons learned with the virtual models be transposed to the actual building production increasing precision and efficiency. Thus, this paper discusses how the Fourth Industrial Revolution has impacted on property developments and how BIM could be the propellant acting as the main fuel and link between the virtual environment and the real production for the structuring of flows, information management and efficiency in this process. The results obtained are partial and not definite up to the date of this publication. This research is part of a doctoral thesis development, which focuses on the discussion of the impact of digital transformation in the construction of residential buildings in Brazil.

Keywords: building information modeling, building production, digital transformation, ICT

Procedia PDF Downloads 124

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

Procedia PDF Downloads 186

Authors: Maria Luisa de la Torre, Javier Aroba, Jose Miguel Davila, Aguasanta M. Sarmiento

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Steel is one of the most widely used materials in polymetallic sulfide mining installations. One of the main problems suffered by these facilities is the economic losses due to the corrosion of this material, which is accelerated and aggravated by the contact with acid waters generated in these mines when sulfides come into contact with oxygen and water. This generation of acidic water, in turn, is accelerated by the presence of acidophilic bacteria. In order to gain a more detailed understanding of this corrosion process and the interaction between steel and acidic water, a laboratory experiment was carried out in which carbon steel plates were introduced into four different solutions for 27 days: distilled water (BK), which tried to assimilate the effect produced by rain on this material, an acid solution from a mine with a high Fe2+/Fe3+ (PO) content, another acid solution of water from another mine with a high Fe3+/Fe2+ (PH) content and, finally, one that reproduced the acid mine water with a high Fe2+/Fe3+ content but in which there were no bacteria (ST). Every 24 hours, physicochemical parameters were measured, and water samples were taken to carry out an analysis of the dissolved elements. The results of these measurements were processed using an explainable AI model based on fuzzy logic. It could be seen that, in all cases, there was an increase in pH, as well as in the concentrations of Fe and, in particular, Fe(II), as a consequence of the oxidation of the steel plates. Proportionally, the increase in Fe concentration was higher in PO and ST than in PH because Fe precipitates were produced in the latter. The rise of Fe(II) was proportionally much higher in PH, especially in the first hours of exposure, because it started from a lower initial concentration of this ion. Although to a lesser extent than in PH, the greater increase in Fe(II) also occurred faster in PO than in ST, a consequence of the action of the catalytic bacteria. On the other hand, Cu concentrations decreased throughout the experiment (with the exception of distilled water, which initially had no Cu, as a result of an electrochemical process that generates a precipitation of Cu together with Fe hydroxides. This decrease is lower in PH because the high total acidity keeps it in solution for a longer time. With the application of an artificial intelligence tool, it has been possible to evaluate the effects of steel corrosion in mining environments, corroborating and extending what was obtained by means of classical statistics.

Keywords: acid mine drainage, artificial intelligence, carbon steel, corrosion, fuzzy logic

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Authors: Tasnuba Binte Jamal, Khan Mahmud Amanat

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Carbon Fiber-Reinforced Polymer (CFRP) composite materials have proven to have valuable properties and suitability to be used in the construction of new buildings and in upgrading the existing ones due to its effectiveness, ease of implementation and many more. In the present study, a numerical finite element investigation has been conducted using ANSYS 18.1 to study the behavior of square HSS AISC sections under eccentric compressive loading strengthened with CFRP materials. A three-dimensional finite element model for square HSS section using shell element was developed. Application of CFRP strengthening was incorporated in the finite element model by adding an additional layer of shell elements. Both material and geometric nonlinearities were incorporated in the model. The developed finite element model was applied to simulate experimental studies done by past researchers and it was found that good agreement exists between the current analysis and past experimental results, which established the acceptability and validity of the developed finite element model to carry out further investigation. Study was then focused on some selected non-compact AISC square HSS columns and the effects of number of CFRP layers, amount of eccentricities and cross-sectional geometry on the strength gain of those columns were observed. Load was applied at a distance equal to the column dimension and twice that of column dimension. It was observed that CFRP strengthening is comparatively effective for smaller eccentricities. For medium sized sections, strengthening tends to be effective at smaller eccentricities as well. For relatively large AISC square HSS columns, with increasing number of CFRP layers (from 1 to 3 layers) the gain in strength is approximately 1 to 38% to that of unstrengthened section for smaller eccentricities and slenderness ratio ranging from 27 to 54. For medium sized square HSS sections, effectiveness of CFRP strengthening increases approximately by about 12 to 162%. The findings of the present study provide a better understanding of the behavior of HSS sections strengthened with CFRP subjected to eccentric compressive load.

Keywords: CFRP strengthening, eccentricity, finite element model, square hollow section

Procedia PDF Downloads 145

Authors: Eman H. El-Gamal, Maher E. Saleh, Mohamed Rashad, Ibrahim Elsokkary, Mona M. Abd El-Latif

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Biochar application to calcareous soils could potentially influence the nitrogen dynamics that affect the bioavailability of plants. This study was carried out to investigate the effect of incubation periods on the changes of nitrogen levels (total nitrogen TN and exchangeable ammonium NH₄⁺ and nitrate NO₃⁻) in biochar-treated calcareous soil. The incubation course was extended to 144 days at 30 ± 3 ℃ and at 50% of soil water holding capacity (WHC). Two types of biochars were obtained by pyrolysis at 500 ℃ from rice husk (RHB) and sugarcane bagasse (SCBB). The experiment was planned in a factorial experimental design with three factors (6 periods '24 days for each period' × 3 biochar types 'un-amended, RHB and SCBB' × 3 nitrogen fertilizers 'control, ammonium nitrate; AN and animal manure; AM') in a completely randomized design. The results obtained showed that the highest level of TN was found in the first 24 days of the incubation period in all treatments. However, the amount of TN was decreased with proceeding incubation period up to 144 days and reached to the lowest level at the end of incubation with values of change rate was 17.5, 16.6, and 14.6 g kg⁻¹ day⁻¹ for the un-amended, RHB and SCBB treated soil, respectively. The values of change rate in biochar-soils treated with nitrogen fertilizers were decreased gradually through the whole incubation time from 127.22 to 12.45 g kg⁻¹ day⁻¹ and from 65.00 to 13.43 g kg⁻¹ day⁻¹ for AN and AM respectively, in the case of RHB-soil. While in SCBB-soil, these values were decreased from 70.83 to 12.13 g kg⁻¹ day⁻¹ and from 59.17 to 11.48 g kg⁻¹ day⁻¹ for AN and AM treatments, respectively. The lowest concentration of exchangeable NH₄⁺ was generally found through the period from 24-48 days of incubation. However, the addition of nitrogen fertilizers, enhanced NH₄⁺ production through incubation periods. In the case of RHB-soil, the value of change rate in NH₄⁺ level in the first 24 days of incubation was 0.43 mg kg⁻¹ day⁻¹ and with the addition of AN and AM this value increased to 1.54 and 4.38 mg kg⁻¹ day⁻¹, respectively. In the case of SCBB-soil, the value of change rate in NH₄⁺ level was 0.29 mg kg⁻¹ day⁻¹ which increased to 1.04 mg kg⁻¹ day⁻¹ at the end of incubation, and due to the addition of AN and AM this value increased to 2.78 and 1.90 mg kg⁻¹ day⁻¹ in the first 24 days of incubation period, respectively. However, as compared to the control treatment, the lowest rate of change in NH₄⁺ level was found at the end of incubation. On the other hand, incubation of all biochars-amended soil and treated with AN and AM decreased the concentration levels of NO₃⁻, especially through the first 24-72 days of incubation period. As a result, the values of change rate in NO₃⁻ concentrations in all treatments were almost negative.

Keywords: ammonium nitrate, animal manure, biochar, rice husk, sugarcane bagasse

Procedia PDF Downloads 134

Authors: I. Sinnarasa, Y. Thimont, L. Presmanes, A. Barnabé

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The thermoelectricity is a promising technique to overcome the issues in recovering waste heat to electricity without using moving parts. In fact, the thermoelectric (TE) effect defines as the conversion of a temperature gradient directly into electricity and vice versa. To optimize TE materials, the power factor (PF = σS² where σ is electrical conductivity and S is Seebeck coefficient) must be increased by adjusting the carrier concentration, and/or the lattice thermal conductivity Kₜₕ must be reduced by introducing scattering centers with point defects, interfaces, and nanostructuration. The PF does not show the advantages of the thin film because it does not take into account the thermal conductivity. In general, the thermal conductivity of the thin film is lower than the bulk material due to their microstructure and increasing scattering effects with decreasing thickness. Delafossite type oxides CuᴵMᴵᴵᴵO₂ received main attention for their optoelectronic properties as a p-type semiconductor they exhibit also interesting thermoelectric (TE) properties due to their high electrical conductivity and their stability in room atmosphere. As there are few proper studies on the TE properties of Mg-doped CuCrO₂ thin films, we have investigated, the influence of the annealing temperature on the electrical conductivity and the Seebeck coefficient of Mg-doped CuCrO₂ thin films and calculated the PF in the temperature range from 40 °C to 220 °C. For it, we have deposited Mg-doped CuCrO₂ thin films on fused silica substrates by RF magnetron sputtering. This study was carried out on 300 nm thin films. The as-deposited Mg doped CuCrO₂ thin films have been annealed at different temperatures (from 450 to 650 °C) under primary vacuum. Electrical conductivity and Seebeck coefficient of the thin films have been measured from 40 to 220 °C. The highest electrical conductivity of 0.60 S.cm⁻¹ with a Seebeck coefficient of +329 µV.K⁻¹ at 40 °C have been obtained for the sample annealed at 550 °C. The calculated power factor of optimized CuCrO₂:Mg thin film was 6 µW.m⁻¹K⁻² at 40 °C. Due to the constant Seebeck coefficient and the increasing electrical conductivity with temperature it reached 38 µW.m⁻¹K⁻² at 220 °C that was a quite good result for an oxide thin film. Moreover, the degenerate behavior and the hopping mechanism of CuCrO₂:Mg thin film were elucidated. Their high and constant Seebeck coefficient in temperature and their stability in room atmosphere could be a great advantage for an application of this material in a high accuracy temperature measurement devices.

Keywords: thermoelectric, oxides, delafossite, thin film, power factor, degenerated semiconductor, hopping mode

Procedia PDF Downloads 199

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

Procedia PDF Downloads 163

Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

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Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

Procedia PDF Downloads 82

Authors: Gonzalo Reyes, Magdalena Walczak, Esteban Ramos-Moore, Jorge Ramos-Grez

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Metal additive manufacture technologies have gained strong support and acceptance as a promising and alternative method to manufacture high performance complex geometry products. The main purpose of the present work is to study the microstructure and phase transformation temperatures of Cu-Al-Ni shape memory alloys fabricated from a direct laser additive process using metallic powders as precursors. The potential application is to manufacture self-centering seismic dampers for earthquake protection of buildings out of a copper based alloy by an additive process. In this process, the Cu-Al-Ni alloy is melted, inside of a high temperature and vacuum chamber with the aid of a high power fiber laser under inert atmosphere. The laser provides the energy to melt the alloy powder layer. The process allows fabricating fully dense, oxygen-free Cu-Al-Ni specimens using different laser power levels, laser powder interaction times, furnace ambient temperatures, and cooling rates as well as modifying concentration of the alloying elements. Two sets of specimens were fabricated with a nominal composition of Cu-13Al-3Ni and Cu-13Al-4Ni in wt.%, however, semi-quantitative chemical analysis using EDX examination showed that the specimens’ resulting composition was closer to Cu-12Al-5Ni and Cu-11Al-8Ni, respectively. In spite of that fact, it is expected that the specimens should still possess shape memory behavior. To confirm this hypothesis, phase transformation temperatures will be measured using DSC technique, to look for martensitic and austenitic phase transformations at 150°C. So far, metallographic analysis of the specimens showed defined martensitic microstructures. Moreover, XRD technique revealed diffraction peaks corresponding to (0 0 18) and (1 2 8) planes, which are too associated with the presence of martensitic phase. We conclude that it would be possible to obtain fully dense Cu-Al-Ni alloys having shape memory effect behavior by direct laser fabrication process, and to advance into fabrication of self centering seismic dampers by a controllable metal additive manufacturing process.

Keywords: Cu-Al-Ni alloys, direct laser fabrication, shape memory alloy, self-centering seismic dampers

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Authors: Azariah Sosa, Carlos Renedo Sanchez

Abstract:

The development of a new motorway north of Auckland (New Zealand) includes steep rock cuts, from 63 up to 85 degrees, in an interbedded sandstone and siltstone rock mass of the geological unit Waitemata Group (Pakiri Formation), which shows sub-horizontal bedding planes, various sub-vertical joint sets, and a diverse weathering profile. In this kind of rock mass -that can be classified as a weak rock- the definition of the stable maximum geometry is not only governed by discontinuities and defects evident in the rock but is important to also consider the global stability of the rock slope, including (in the analysis) the rock mass characterisation, influence of the groundwater, the geological evolution, and the weathering processes. Depending on the weakness of the rock and the processes suffered, the global stability could, in fact, be a more restricting element than the potential instability of individual blocks through discontinuities. This paper discusses those elements that govern the stability of the rock slopes constructed in a rock formation with favourable bedding and distribution of discontinuities (horizontal and vertical) but with a weak behaviour in terms of global rock mass characterisation. In this context, classifications as Q-Slope and slope stability assessment methodology (SSAM) have been demonstrated as important tools which complement the assessment of the global stability together with the analytical tools related to the wedge-type failures and limit equilibrium methods. The paper focuses on the applicability of these two new empirical classifications to evaluate the slope stability in 18 already excavated rock slopes in the Pakiri formation through comparison between the predicted and observed stability issues and by reviewing the outcome of analytical methods (Rocscience slope stability software suite) compared against the expected stability determined from these rock classifications. This exercise will help validate such findings and correlations arising from the two empirical methods in order to adjust the methods to the nature of this specific kind of rock mass and provide a better understanding of the long-term stability of the slopes studied.

Keywords: Pakiri formation, Q-slope, rock slope stability, SSAM, weak rock

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