Search results for: bar model method

Authors: M. Insiat Islam Rabby, M. Mahbubur Rahman, Eshanul Islam, A. K. M. Sadrul Islam

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The numerical and simulative analysis of laminar heat exchange convection of aluminum oxide (Al₂O₃) - water nanofluid for the developed region through two parallel plates is presented in this present work. The second order single phase energy equation, mass and momentum equation are solved by using finite volume method with the ANSYS FLUENT 16 software. The distance between two parallel plates is 4 mm and length is 600 mm. Aluminum oxide (Al₂O₃) is used as nanoparticle and water is used as the base/working fluid for the investigation. At the time of simulation 1% to 5% volume concentrations of the Al₂O₃ nanoparticles are used for mixing with water to produce nanofluid and a wide range of interval of Reynolds number from 500 to 1100 at constant heat flux 500 W/m² at the channel wall has also been introduced. The result reveals that for increasing the Reynolds number the Nusselt number and heat transfer coefficient are increased linearly and friction factor decreased linearly in the developed region for both water and Al₂O₃-H₂O nanofluid. By increasing the volume fraction of Al₂O₃-H₂O nanofluid from 1% to 5% the value of Nusselt number increased rapidly from 0.7 to 7.32%, heat transfer coefficient increased 7.14% to 31.5% and friction factor increased very little from 0.1% to 4% for constant Reynolds number compared to pure water. At constant heat transfer coefficient 700 W/m2-K the pumping power advantages have been achieved 20% for 1% volume concentration and 62% for 3% volume concentration of nanofluid compared to pure water.

Keywords: convective heat transfer, pumping power, constant heat flux, nanofluid, nanoparticles, volume concentration, thermal conductivity

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Authors: Getiye Dejenu Kibret, Daniel Demant, Andrew Hayen

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Introduction: In Ethiopia, more than half of newborn babies do not have access to Emergency Obstetric and Neonatal Care (EmONC) services. Understanding the effect of distance to health facilities on service use and neonatal survival is crucial to recommend policymakers and improve resource distribution. We aimed to investigate the effect of distance to health services on maternal service use and neonatal mortality. Methods: We implemented a data linkage method based on geographic coordinates and calculated straight-line (Euclidean) distances from the Ethiopian 2016 demographic and health survey clusters to the closest health facility. We computed the distance in ESRI ArcGIS Version 10.3 using the geographic coordinates of DHS clusters and health facilities. Generalised Structural Equation Modelling (GSEM) was used to estimate the effect of distance on neonatal mortality. Results: Poor geographic accessibility to health facilities affects maternal service usage and increases the risk of newborn mortality. For every ten kilometres (km) increase in distance to a health facility, the odds of neonatal mortality increased by 1.33% (95% CI: 1.06% to 1.67%). Distance also negatively affected antenatal care, facility delivery and postnatal counselling service use. Conclusions: A lack of geographical access to health facilities decreases the likelihood of newborns surviving their first month of life and affects health services use during pregnancy and immediately after birth. The study also showed that antenatal care use was positively associated with facility delivery service use and that both positively influenced postnatal care use, demonstrating the interconnectedness of the continuum of care for maternal and neonatal care services. Policymakers can leverage the findings from this study to improve accessibility barriers to health services.

Keywords: acessibility, distance, maternal health service, neonatal mortality

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Authors: Muhammad Shoaib

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Every society has a set of beliefs, norms, values, folkways, mores and laws. All the principles, customs, traditions and procedures of societies are directly or indirectly related to the religion of the society and changed with the passage of time by the mediation of democratic values attitudes and mass media influence. The main objective of the present study is to examine the effects of rational thinking values on forgiveness attitude by the mediation of democratic values and mass media attitude among family members. As many other developing settings, Pakistani society is undergoing a rapid and multifaceted social change, in which traditional thinking coexists and often clashes with modern thinking. Rational thinking attitude has great effects on the forgiveness attitude among family members as well as all the members of Pakistani society. For the present study 520 respondents were sampled from two urban areas of Punjab province; Lahore and Faisalabad, through proportionate random sampling technique. A survey method was used as a technique of data collection and an interview schedule was administered to collect information from the respondents. The results support that the net of other factors, favorable democratic values attitudes are positively associated rational thinking attitudes. The results also provide support that all other things equal, mass media attitudes also have a significant positive effect on rational thinking attitudes. Favorable democratic values attitudes have a significant net positive effect and the effect of mass media attitudes is positive and statistically highly significant. It shows that the effects of both democratic values attitudes and mass media attitudes diminish in magnitude when the rational thinking attitudes scale is included. However, the effect of democratic values remains highly significant. In comparison, the effect of mass media attitudes is only marginally significant.

Keywords: rationality, forgiveness, democratic values, mass media, attitudes, Pakistan

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Authors: Nikhil Kumar, Asish Bandyopadhyay

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Laser welding process is a capable technology for forming the automobile, microelectronics, marine and aerospace parts etc. In the present work, a mathematical and statistical approach is adopted to study the laser welding of AISI 304 stainless steel. A robotic control 500 W pulsed Nd:YAG laser source with 1064 nm wavelength has been used for welding purpose. Butt joints are made. The effects of welding parameters, namely; laser power, scanning speed and pulse width on the seam width and depth of penetration has been investigated using the empirical models developed by response surface methodology (RSM). Weld quality is directly correlated with the weld geometry. Twenty sets of experiments have been conducted as per central composite design (CCD) design matrix. The second order mathematical model has been developed for predicting the desired responses. The results of ANOVA indicate that the laser power has the most significant effect on responses. Microstructural analysis as well as hardness of the selected weld specimens has been carried out to understand the metallurgical and mechanical behaviour of the weld. Average micro-hardness of the weld is observed to be higher than the base metal. Higher hardness of the weld is the resultant of grain refinement and δ-ferrite formation in the weld structure. The result suggests that the lower line energy generally produce fine grain structure and improved mechanical properties than the high line energy. The combined effects of input parameters on responses have been analyzed with the help of developed 3-D response surface and contour plots. Finally, multi-objective optimization has been conducted for producing weld joint with complete penetration, minimum seam width and acceptable welding profile. Confirmatory tests have been conducted at optimum parametric conditions to validate the applied optimization technique.

Keywords: ANOVA, laser welding, modeling and optimization, response surface methodology

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Authors: Hijratullah Sharifzada, You Wang, Said Ikram Sadat, Hamza Javed, Khalid Akhunzada, Sidra Javed, Sadiq Khan

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In the construction industry, safety is of paramount importance given the complex and dynamic nature of construction sites, which are prone to various hazards like falls from heights, being hit by falling objects, and structural collapses. Traditional safety management strategies such as manual inspections and safety training have shown significant limitations. This study presents an intelligent monitoring and analysis system for construction site safety based on an image dataset. A specifically designed Construction Site Safety Image Dataset, comprising 10 distinct classes of objects commonly found on sites, is utilized and divided into training, validation, and test subsets. InceptionV3 and MobileNetV2 are chosen as pre-trained models for feature extraction and are modified through truncation and compression to better suit the task. A Feature Fusion architecture is introduced, integrating these modified models along with a Squeeze-and-Excitation block. Experimental results demonstrate that the proposed model achieves a mean Average Precision (mAP) of 0.81 at an IoU threshold of 0.5, with high accuracies for classes like "Safety Cone" (91%) and "Machinery" (93%) but relatively lower accuracy for "Vehicle" (57%). The training process exhibits smooth convergence, and compared to prior methods such as YOLOv4 and SSD, the proposed framework shows superiority in precision and recall. Despite its achievements, the system has limitations, including reliance on visual data and dataset imbalance. Future research directions involve incorporating multi-modal data, conducting real-world deployments, and optimizing for edge deployment, aiming to further enhance construction site safety.

Keywords: construction site safety, intelligent monitoring system, image dataset, InceptionV3, MobileNetV2, feature fusion, squeeze-and-excitation block, mean average precision, object detection

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Authors: Mohammed H. Karim, Bestoon M. Faraj

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Introduction: instrument separation is a common challenge in the endodontic field. Various techniques and technologies have been developed to improve the retrieval success rate. This study aimed to compare the effectiveness of a Dynamic Navigation System (DNS) and a three-dimensional microscope in retrieving broken rotary NiTi files when using trepan burs and the extractor system. Materials and Methods: Thirty maxillary first bicuspids with sixty separate roots were split into two comparable groups based on a comprehensive Cone-Beam Computed Tomography (CBCT) analysis of the root length and curvature. After standardised access opening, glide paths, and patency attainment with the K file (sizes 10 and 15), the teeth were arranged on 3D models (three per quadrant, six per model). Subsequently, controlled-memory heat-treated NiTi rotary files (#25/0.04) were notched 4 mm from the tips and fractured at the apical third of the roots. The C-FR1 Endo file removal system was employed under both guidance to retrieve the fragments, and the success rate, canal aberration, treatment time and volumetric changes were measured. The statistical analysis was performed using IBM SPSS software at a significance level of 0.05. Results: The microscope-guided group had a higher success rate than the DNS guidance, but the difference was insignificant (p > 0.05). In addition, the microscope-guided drills resulted in a substantially lower proportion of canal aberration, required less time to retrieve the fragments and caused a minor change in the root canal volume (p < 0.05). Conclusion: Although dynamically guided trephining with the extractor can retrieve separated instruments, it is inferior to three-dimensional microscope guidance regarding treatment time, procedural errors, and volume change.

Keywords: dynamic navigation system, separated instruments retrieval, trephine burs and extractor system, three-dimensional video microscope

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Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: Abdullahi Garba Abu, Muhammad Bello Sada, Aminu Abubakar

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Facebook and Twitter/X platforms are preferred and largely patronized by Youths in Nigeria. The simplicity and popularity of Facebook and Twitter/X have made them preferred social networking sites for Youths to handle or execute different political activities in favor of their chosen candidates or political parties. This is largely related to their interest in using the platform for the purposes of participation in 2023 political activities and general elections. The two Social Networking Sites were used to vigorously pursue party activities on the eve of the 2023 general elections. Youths engaged the two platforms in campaigning for their candidates and political parties and succeeded in reaching a wide audience, shared the policies and manifestos of their parties, engaged with supporters and even posted advertising campaigns for specific demographics. However, the utilization of Facebook and Twitter /X platforms during the 2023 elections was largely seen in two lights: positive and negative lights/intentions. Therefore, this research investigates the motivating factors for which largely Nigerian Youths engage Facebook and Twitter platforms in political activities, with reference to the 2023 general elections. The research uses a survey method through which it reaches out to respondents from all six geo-politial zones. The research found that Nigerian Youths utilize the two social media sites to campaign for politicians voluntarily based on their belief in the capabilities of the candidates. It also found out that Youths were lured into using Facebook and Twitter/X sites to campaign through tribal, religious, and ethnic factors. More so, the research found out that eagerness to share political materials in support of candidates made Youths in Nigeria share unverifiable content on Facebook and Twitter sites.

Keywords: Facebook, Twitter/X, Nigerian youths, 2023 elections

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Authors: Yixin Yan, Miao Yan, Irini Angelidaki, Ioannis Fotidis

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Ammonia, which derives from the degradation of urea and protein-substrates, is the major toxicant of the commercial anaerobic digestion reactors causing loses of up to 1/3 of their practical biogas production, which reflects directly on the overall revenue of the plants. The current experimental work is aiming to alleviate the ammonia inhibition in anaerobic digestion (AD) process by developing an innovative bioaugmentation method of ammonia tolerant methanogenic consortia. The ammonia tolerant consortia were cultured in batch reactors and immobilized together with biochar in agar (customized inocula). Three continuous stirred-tank reactors (CSTR), fed with the organic fraction of municipal solid waste at a hydraulic retention time of 15 days and operated at thermophilic (55°C) conditions were assessed. After an ammonia shock of 4 g NH4+-N L-1, the customized inocula were bioaugmented into the CSTR reactors to alleviate ammonia toxicity effect on AD process. Recovery rate of methane production and methanogenic activity will be assessed to evaluate the bioaugmentation performance, while 16s rRNA gene sequence will be used to reveal the difference of microbial community changes through bioaugmentation. At the microbial level, the microbial community structures of the four reactors will be analysed to find the mechanism of bioaugmentation. Changes in hydrogen formation potential will be used to predict direct interspecies electron transfer (DIET) between ammonia tolerant methanogens and syntrophic bacteria. This experimental work is expected to create bioaugmentation inocula that will be easy to obtain, transport, handled and bioaugment in AD reactors to efficiently alleviate the ammonia toxicity, without alternating any of the other operational parameters including the ammonia-rich feedstocks.

Keywords: artisanal fishing waste, acidogenesis, volatile fatty acids, pH, inoculum/substrate ratio

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Authors: Wegene Demeke

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Background: The demand for healthcare services is growing in developing and developed countries. Information and communication technology is used to facilitate healthcare services. In the case of developing countries, implementing telemedicine is aimed at providing healthcare for people living in remote areas where health service is not accessible. The implementations of telemedicine in developing countries are unsuccessful. For example, the recent study indicates that 90% of telemedicine projects are abandoned or failed in developing countries. Several researchers reported the technological challenges as the main factor for the non-adoption of telemedicine. However, this research reports the health professionals’ perspectives arising from technical, social and organizational factors that are considered as key elements for the setting and running of telemedicine in Ethiopia. The importance and significance of telemedicine for healthcare is growing. For example, the use of telemedicine in the current pandemic situation becomes an essential strategic element in providing healthcare services in developed countries. Method: Qualitative and quantitative exploratory research methods used to collect data to find factors affecting the adoption of Information and communication technologies for telemedicine use. The survey was distributed using emails and Google forms. The email addresses were collected from personal contact and publicly available websites in Ethiopia. The thematic analysis used to build the barriers and facilitators factors for establishing telemedicine services. A survey questionnaire with open-and-close questions was used to collect data from 175 health professionals. Outcome: The result of this research will contribute to building the key barriers and facilitators factors of telemedicine from the health professional perspectives in developing countries. The thematic analysis provides barriers and facilitators factors arising from technical, organizational, and social sources.

Keywords: telemedicine, ICT, developing country, Ethiopia, health service

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Authors: Nilesh Bandekar, Sumita Dasgupta, Luis Alberto Allcahuaman Huaya, Souvik Manna

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Cryptobiosis is a dormant state where all measurable metabolic activities are at a halt, allowing an organism to survive in extreme conditions like low temperature (cryobiosis), extreme drought (anhydrobiosis), etc. This phenomenon is observed especially in tardigrades that can retain this state for decades depending on the abiotic environmental conditions. On returning to favorable conditions, tardigrades re-attain a metabolically active state. In this study, cyanobacteria as a model organism are being chosen to induce cryptobiosis for its effective preservation over a long period of time. Preserving cyanobacteria using this strategy will have multiple space applications because of its ability to produce oxygen. In addition, research has shown the survivability of this organism in space for a certain period of time. Few species of cyanobacterial residents of the soil such as Microcoleus, are able to survive in extreme drought as well. This work specifically focuses on Synechococcus elongatus, an endolith cyanobacteria with multiple benefits. It has the capability to produce 25% oxygen in water bodies. It utilizes carbon dioxide to produce oxygen via photosynthesis and also uses carbon dioxide as an energy source to form glucose via the Calvin cycle. There is a fair possibility of initiating cryptobiosis in such an organism by inducing certain proteins extracted from tardigrades such as Heat Shock Proteins (Hsp27 and Hsp30c) and/or hydrophilic Late Embryogenesis Abundant proteins (LEA). Existing methods like cryopreservation are difficult to execute in space keeping in mind their cost and heavy instrumentation. Also, extensive freezing may cause cellular damage. Therefore, cryptobiosis-induced cyanobacteria for its transportation from Earth to Mars as a part of future terraforming missions on Mars will save resources and increase the effectiveness of preservation. Finally, Cyanobacteria species like Synechococcus elongatus can also produce oxygen and glucose on Mars in favorable conditions and holds the key to terraforming Mars.

Keywords: cryptobiosis, cyanobacteria, glucose, mars, Synechococcus elongatus, tardigrades

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Authors: Rida Batool, Faizah Altaf, Saba Nadeem, Afifa Aslam, Faisal Alamgir, Ghazanfar Abbas

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Today, the need of the hour is to find out alternative renewable energy resources in order to reduce the burden on fossil fuels and prevent alarming environmental degradation. Solid oxide fuel cell (SOFC) is considered a good alternative energy conversion device because it is environmentally benign and supplies energy on demand. The only drawback associated with SOFC is its high operating temperature. In order to reduce operating temperature, different types of composite material are prepared. In this work, titanium doped lanthanum gallium cerate (LGCT) composite is prepared through the co-precipitation method as electrolyte and examined for low temperature SOFCs (LTSOFCs). The structural properties are analyzed by X-Ray Diffractometry (XRD) and Fourier Transform Infrared (FTIR) Spectrometry. The surface properties are investigated by Scanning Electron Microscopy (SEM). The electrolyte LGCT has the formula LGCTO₃ because it showed two phases La.GaO and Ti.CeO₂. The average particle size is found to be (32 ± 0.9311) nm. The ionic conductivity is achieved to be 0.073S/cm at 650°C. Arrhenius plots are drawn to calculate activation energy and found 2.96 eV. The maximum power density and current density are achieved at 68.25mW/cm² and 357mA/cm², respectively, at 650°C with hydrogen. The prepared material shows excellent ionic conductivity at comparatively low temperature, that makes it a potentially good candidate for LTSOFCs.

Keywords: solid oxide fuel cell, LGCTO₃, cerium composite oxide, ionic conductivity, low temperature electrolyte

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: antioxidant activity, corn oil, oxidative deterioration, pomegranate

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Authors: Marziye Hadian, Alireza Jabbari

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Background: Each year, tropical diseases affect large numbers of tropical or subtropical populations and give rise to irreparable financial and human damage. Among these diseases, some are known as Neglected Tropical Disease (NTD) that may cause unusual dangers; however, they have not been appropriately accounted for. Taking into account the priority of eradication of the disease, this study explored the causes of failure to eradicate neglected tropical diseases. Method: This study was a systematized review that was conducted in January 2021 on the articles related to neglected tropical diseases on databases of Web of Science, PubMed, Scopus, Science Direct, Ovid, Pro-Quest, and Google Scholar. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as well as Critical Appraisal Skills Program (CASP) for articles and AACODS (Authority, Accuracy, Coverage, Objectivity, Date, Significance) for grey literature (provides five criteria for judging the quality of grey information) were integrated. Finding: The challenges in controlling and eradicating neglected tropical diseases in four general themes are as follows: shortcomings in disease management policies and programs, environmental challenges, executive challenges in policy disease and research field and 36 sub-themes. Conclusion: To achieve the goals of eradicating forgotten tropical diseases, it seems indispensable to free up financial, human and research resources, proper management of health infrastructure, attention to migrants and refugees, clear targeting, prioritization appropriate to local conditions and special attention to political and social developments. Reducing the number of diseases should free up resources for the management of neglected tropical diseases prone to epidemics as dengue, chikungunya and leishmaniasis. For the purpose of global support, targeting should be accurate.

Keywords: neglected tropical disease, NTD, preventive, eradication

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Authors: Anamika A. Sharma, Arezou Ahmadi R. A., Narendra B. Parihar, Manjusha Sajith

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Introduction: Hemodialysis is the most effective therapeutic technique for patient with ESRD second to renal transplantation. However it is a lifelong therapy which requires frequent hospital, or dialysis centers visits mainly twice and thrice weekly, thus considerably changes the normal way of patient’s living. So this study aimed to Assess Health-Related Quality of life in End-Stage Renal Disease (ESRD) Undergoing Twice and Thrice weekly Hemodialysis. Method: A prospective observational, cross-sectional study was carried out from September 2016 to April 2017 in end-stage renal disease patients undergoing hemodialysis. Socio-demographic and clinical details of patients were obtained from the medical records. WHOQOL-BREF questionnaire was used to Access Health-Related Quality Of Life. Quality of Life scores of Twice weekly and Thrice weekly hemodialysis was analyzed by Kruskal Wallis Test. Results: Majority of respondents were male (72.55%), married (89.31%), employed (58.02%), belong to middle class (71.00%) and resides in rural area (58.78%). The mean ages in the patient undergoing twice weekly and thrice weekly hemodialysis were 51.89 ± 15.64 years and 51.33 ± 15.70 years respectively. Average Quality of Life scores observed in twice weekly and thrice weekly hemodialysis was 52.07 ± 13.30 (p=0.0037) and 52.87 ± 13.47 (p=0.0004) respectively. The hemoglobin of thrice weekly dialysis patients (10.28 gm/dL) was high as compared to twice weekly dialysis (9.23 gm/dL). Patients undergoing thrice weekly dialysis had improved serum urea, serum creatinine values (95.85 mg/dL, 8.32 mg/dL) as compared to twice weekly hemodialysis ( 104.94 mg/dL, 8.68 mg/dL). Conclusion: Our study concluded that there was no significant difference between overall Health-Related Quality Of Life in twice weekly and thrice weekly hemodialysis. Frequent hemodialysis was associated with improved control of hypertension, serum urea, serum creatinine levels.

Keywords: end stage renal disease, health related quality of life, twice weekly hemodialysis, thrice weekly hemodialysis

Procedia PDF Downloads 182

Authors: Mhenga Agneta, Li Zhaomin, Zhang Chao

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When velocity is high enough, gas can entrain fluid and carry to the surface, but as time passes by, velocity drops to a critical point where fluids will start to hold up in the tubing and cause liquid loading which prevents gas production and may lead to the death of the well. Foam injection is widely used as one of the methods to unload liquid. Since wells have different characteristics, it is not guaranteed that foam can be applied in all of them and bring successful results. This research presents a technology to optimize the efficiency of foam to unload liquid by air compression. Two methods are used to explain optimization; (i) mathematical formulas are used to solve and explain the myth of how density and critical velocity could be minimized when air is compressed into foaming agents, then the relationship between flow rates and pressure increase which would boost up the bottom hole pressure and increase the velocity to lift liquid to the surface. (ii) Experiments to test foam carryover capacity and stability as a function of time and surfactant concentration whereby three surfactants anionic sodium dodecyl sulfate (SDS), nonionic Triton 100 and cationic hexadecyltrimethylammonium bromide (HDTAB) were probed. The best foaming agents were injected to lift liquid loaded in a created vertical well model of 2.5 cm diameter and 390 cm high steel tubing covered by a transparent glass casing of 5 cm diameter and 450 cm high. The results show that, after injecting foaming agents, liquid unloading was successful by 75%; however, the efficiency of foaming agents to unload liquid increased by 10% with an addition of compressed air at a ratio of 1:1. Measured values and calculated values were compared and brought about ± 3% difference which is a good number. The successful application of the technology indicates that engineers and stakeholders could bring water flooded gas wells back to production with optimized results by firstly paying attention to the type of surfactants (foaming agents) used, concentration of surfactants, flow rates of the injected surfactants then compressing air to the foaming agents at a proper ratio.

Keywords: air compression, foaming agents, gas well, liquid loading

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Authors: Bergun Meric Bingul, Cigdem Bulgan, Ozlem Tore, Mensure Aydin, Erdal Bal

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The aim of the study was to compare the effects of impact forces and some kinematic parameters with two different straight punch stance positions in boxing. 9 elite boxing athletes from the Turkish National Team (mean age± SD 19.33±2.11 years, mean height 174.22±3.79 cm, mean weight 66.0±6.62 kg) participated in this study as voluntarily. Boxing athletes performed one trial in straight punch technique for each two different stance positions (orthodox and southpaw stances) at sandbag. The trials were recorded at a frequency of 120Hz using eight synchronized high-speed cameras (Oqus 7+), which were placed, approximately at right- angles to one another. The three-dimensional motion analysis was performed with a Motion Capture System (Qualisys, Sweden). Data was transferred to Windows-based data acquisition software, which was QTM (Qualisys Track Manager). 11 segment models were used for determination of the kinematic variables (Calf, leg, punch, upperarm, lowerarm, trunk). Also, the sandbag was markered for calculation of the impact forces. Wand calibration method (with T stick) was used for field calibration. The mean velocity and acceleration of the punch; mean acceleration of the sandbag and angles of the trunk, shoulder, hip and knee were calculated. Stance differences’ data were compared with Wilcoxon test for using SPSS 20.0 program. According to the results, there were statistically significant differences found in trunk angle on the sagittal plane (yz) (p<0.05). There was a significant difference also found in sandbag acceleration and impact forces between stance positions (p < 0.05). Boxing athletes achieved more impact forces and accelerations in orthodox stance position. It is recommended that to use an orthodox stance instead of southpaw stance in straight punch technique especially for creating more impact forces.

Keywords: boxing, impact force, kinematics, straight punch, orthodox, southpaw

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Esraa Mohamed El-Fawal

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A facile solvothermal procedure was applied to fabricate zinc ferrite nanoparticles (ZnFe₂O₄ NPs). Activated carbon (AC) derived from peanut shells is synthesized using a microwave through the chemical activation method. The ZnFe₂O₄-AC composite is then mixed with a cerium-based metal-organic framework (CeMOF) by solid-state adding to formulate ZnFe₂O₄-AC/CeMOF composite. The synthesized photo materials were tested by scanning/transmission electron microscope (SEM/TEM), Photoluminescence (PL), (XRD) X-Ray diffraction, (FTIR) Fourier transform infrared, (UV-Vis/DRS) ultraviolet-visible/diffuse reflectance spectroscopy. The prepared ZnFe₂O₄-AC/CeMOFphotomaterial shows significantly boosted efficiency for photodegradation of methyl orange /methylene blue (MO/MB) compared with the pristine ZnFe₂O₄ and ZnFe₂O₄-AC composite under the irradiation of visible-light. The favorable ZnFe₂O₄-AC/CeMOFphotocatalyst displays the highest photocatalytic degradation efficiency of MB/MO (R: 91.5-88.6%, consecutively) compared with the other as-prepared materials after 30 min of visible-light irradiation. The apparent reaction rate K: 1.94-1.31 min-1 is also calculated. The boosted photocatalytic proficiency is ascribed to the heterojunction at the interface of prepared photo material that assists the separation of the charge carriers. To reach optimization, statistical analysis using response surface methodology was applied. The effect of independent parameters (such as A (pH), B (irradiation time), and (c) initial pollutants concentration on the response function (%)photodegradation of MB/MO dyes (as examples of azodyes) was investigated via using central composite design. At the optimum condition, the photodegradation efficiency (%) of the MB/MO is 99.8-97.8%, respectively. ZnFe2O₄-AC/CeMOF hybrid reveals good stability over four consecutive cycles.

Keywords: azo-dyes, photo-catalysis, zinc ferrite, response surface methodology

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Emmanuel Benjamin, Matthias Blum

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Purpose – We address smallholder farmers’ restricted possibilities to adopt sustainable technologies which have direct and indirect benefits. Smallholders often face little asset endowment due to small farm size und insecure property rights, therefore experiencing constraints in adopting agricultural innovation. A program involving payments for ecosystem services (PES) benefits poor smallholder farmers in developing countries in many ways and has been suggested as a means of easing smallholder farmers’ financial constraints. PES may also provide additional mainstay which can eventually result in more favorable credit contract terms due to the availability of collateral substitute. Results of this study may help to understand the barriers, motives and incentives for smallholders’ participation in PES and help in designing a strategy to foster participation in beneficial programs. Design/methodology/approach – This paper uses a random utility model and a logistic regression approach to investigate factors that influence agroforestry adoption. We investigate non-monetary factors, such as information spillover, that influence the decision to adopt such conservation strategies. We collected original data from non-government-run agroforestry mitigation programs with PES that have been implemented in the Mount Kenya region. Preliminary Findings – We find that spread of information, existing networks and peer involvement in such programs drive participation. Conversely, participation by smallholders does not seem to be influenced by education, land or asset endowment. Contrary to some existing literature, we found weak evidence for a positive correlation between the adoption of agroforestry with PES and age of smallholder, e.g., one increases with the other, in the Mount Kenyan region. Research implications – Poverty alleviation policies for developing countries should target social capital to increase the adoption rate of modern technologies amongst smallholders.

Keywords: agriculture innovation, agroforestry adoption, smallholders, payment for ecosystem services, Sub-Saharan Africa

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Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

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The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

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Authors: JinWoog Lee, SeongHyeok Lee, ChanYong Choi, Yujin Lim, Hojin Cho

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Primary function of the trackbed in a conventional railway track system is to decrease the stresses in the subgrade to be in an acceptable level. A properly designed trackbed layer performs this task adequately. Many design procedures have used assumed and/or are based on critical stiffness values of the layers obtained mostly in the field to calculate an appropriate thickness of the sublayers of the trackbed foundation. However, those stiffness values do not consider strain levels clearly and precisely in the layers. This study proposes a method of computation of stiffness that can handle with strain level in the layers of the trackbed foundation in order to provide properly selected design values of the stiffness of the layers. The shear modulus values are dependent on shear strain level so that the strain levels generated in the subgrade in the trackbed under wheel loading and below plate of Repeated Plate Bearing Test (RPBT) are investigated by finite element analysis program ABAQUS and PLAXIS programs. The strain levels generated in the subgrade from RPBT are compared to those values from RC (Resonant Column) test after some consideration of strain levels and stress consideration. For comparison of shear modulus G obtained from RC test and stiffness moduli Ev2 obtained from RPBT in the field, many numbers of mid-size RC tests in laboratory and RPBT in field were performed extensively. It was found in this study that there is a big difference in stiffness modulus when the converted Ev2 values were compared to those values of RC test. It is verified in this study that it is necessary to use precise and increased loading steps to construct nonlinear curves from RPBT in order to get correct Ev2 values in proper strain levels.

Keywords: modulus, plate load test, resonant column test, trackbed foundation

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Karthik K. R, Viswanath V, Asraff A. K

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The first stage of a new-generation launch vehicle of ISRO makes use of large pressure vessels made of Aluminium alloy AA2219 to store fuel and oxidizer. These vessels have many weld joints that may contain cracks or crack-like defects during their fabrication. These defects may propagate across the vessel during pressure testing or while in service under the influence of tensile stresses leading to catastrophe. Though ductile materials exhibit significant stable crack growth prior to failure, it is not generally acceptable for an aerospace component. There is a need to predict the initiation of stable crack growth. The structural integrity of the vessel from fracture considerations can be studied by constructing the Failure Assessment Diagram (FAD) that accounts for both brittle fracture and plastic collapse. Critical crack sizes of the pressure vessel may be highly conservative if it is predicted from FAD alone. If the J-R curve for material under consideration is available apriori, the critical crack sizes can be predicted to a certain degree of accuracy. In this paper, a novel approach is proposed to predict the integrity of a weld in a pressure vessel made of AA2219 material. Fracture parameter ‘J-integral’ at the crack front, evaluated through finite element analyses, is used in the new procedure. Based on the simulation of tension tests carried out on SCT specimens by NASA, a cut-off value of J-integral value (J?ᵤₜ_ₒ??) is finalised. For the pressure vessel, J-integral at the crack front is evaluated through FE simulations incorporating different surface cracks at long seam weld in a cylinder and in dome petal welds. The obtained J-integral, at vessel level, is compared with a value of J?ᵤₜ_ₒ??, and the integrity of vessel weld in the presence of the surface crack is firmed up. The advantage of this methodology is that if SCT test data of any metal is available, the critical crack size in hardware fabricated using that material can be predicted to a better level of accuracy.

Keywords: FAD, j-integral, fracture, surface crack

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Authors: Pawan Kumar Sharma, J. Stephan Sampath Kumar, D. Manikandavelu, V. Senthil Kumar

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The total amount of productivity in the system is the gross primary productivity. The present study was carried out to understand the relationship between productivity in the cages and water depth. The experiment was conducted in the fish cages installed in the pond at the Directorate of Sustainable Aquaculture, Thanjavur, Tamil Nadu Dr. J. Jayalalithaa Fisheries University, Tamil Nadu (10° 47' 13.1964'' N; 79° 8' 16.1700''E). Primary productivity was estimated by light and dark bottle method. The measurement of primary productivity was done at different depths viz., 20 cm, 40 cm, and 60 cm. Six Biological Oxygen Demand bottles of 300 ml capacity were collected and tagged. The productivity was obtained in mg O2/l/hr. The maximum dissolved oxygen level at 20 cm depth was observed 5.62 ± 0.22 mg/l/hr in the light bottle in pond water while the minimum dissolved oxygen level at 20 cm depth in a cage was observed 3.62 ± 0.18 mg/l/hr in dark bottle. In the same way, the maximum and minimum value of dissolved oxygen was observed at 40, and 60 cm depth and results were compared. A slight change in pH was observed in the cage and pond. The maximum gross primary productivity observed was 1.97 mg/l/hr in pond at 20 cm depth while minimum gross primary productivity observed was 0.82±0.16 mg/l/hr in a cage at 60 cm depth. The community respiration was also variable with the depth in both cage and pond. Maximum community respiration was found 1.50±0.19 mg/l/hr in pond at 20 cm depth. A strong positive linear relationship was observed between primary productivity and fish yields in ponds. The pond primary productivity can contribute substantially to the nutrition of farm-raised aquaculture species, including shrimp. The growth of phytoplankton’s is dependent on the sun light, availability of primary nutrients (N, P, and K) in the water body and transparency, so to increase the primary productivity fertilization through organic manure may be done that will clean to the pond environment also.

Keywords: cage aquaculture, water depth, net primary productivity, gross primary productivity, community respiration

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Authors: Oluwatoyin Joseph Gbadeyan, Sarp Adali, Bright Glen, Bruce Sithole

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Sodium lauryl surfactant concentration optimization, for nanoparticle production, provided the platform for advanced research studies. Different concentrations (0.05 %, 0.1 %, and 0.2 %) of sodium lauryl surfactant was added to snail shells powder during milling processes for producing CaCO3 at smaller particle size. Epoxy nanocomposites prepared at filler content 2 wt.% synthesized with different volumes of sodium lauryl surfactant were fabricated using a conventional resin casting method. Mechanical properties such as tensile strength, stiffness, and hardness of prepared nanocomposites was investigated to determine the effect of sodium lauryl surfactant concentration on nanocomposite properties. It was observed that the loading of the synthesized nano-calcium carbonate improved the mechanical properties of neat epoxy at lower concentrations of sodium lauryl surfactant 0.05 %. Meaningfully, loading of achatina fulica snail shell nanoparticles manufactures, with small concentrations of sodium lauryl surfactant 0.05 %, increased the neat epoxy tensile strength by 26%, stiffness by 55%, and hardness by 38%. Homogeneous dispersion facilitated, by the addition of sodium lauryl surfactant during milling processes, improved mechanical properties. Research evidence suggests that nano-CaCO3, synthesized from achatina fulica snail shell, possesses suitable reinforcement properties that can be used for nanocomposite fabrication. The evidence showed that adding small concentrations of sodium lauryl surfactant 0.05 %, improved dispersion of nanoparticles in polymetrix material that provided mechanical properties improvement.

Keywords: sodium lauryl surfactant, mechanical properties , achatina fulica snail shel, calcium carbonate nanopowder

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Oghenetega Ogodo

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In recent years, as the nature of work and employment relations continue to evolve, the gig economy has experienced rapid growth in various parts of the world. A notable example is ride-hailing services, which offer new sources of livelihood and work for drivers and transform urban mobility. While Kate Meagher contributes to the global discourse on the need to review the social contracts of digital works in Lagos State, it is essential to investigate the influence on urban livelihoods as more organizations, governments, and policymakers integrate this as a tool for economic development. Using the snowball sampling method, this exploratory study provides data on the factors that influence the transition of workers to digital platforms (like Uber and Taxify (Bolt)), satisfaction with working conditions, and the perception as a long-term source of livelihood or a means to an end from fifty respondents in Lagos State. Although the results show the beneficial factors of operating on the platforms, the ripple effects on the livelihoods of digital and traditional transport workers are also evident in the study. A mall intercept survey also shows the level of patronage amongst users/commuters across five (5) shopping malls in Lagos State. The results indicate the role of technology in influencing the choice of commuters to use either the public transportation system or digital platforms. It is essential to promote development policies that support productive activities, decent job creation, entrepreneurship, and innovation, encourage the formalization and growth of all enterprises, ensure access to financial services, and achieve full and productive employment and decent work for all.

Keywords: informal economies, digital technology, transportation policy, economic development

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Pedro Henrique Tertuliano Leoni, Carla Aparecida Arena Ventura, Ana Cristina de Oliveira e Silva, Renata Karina Reis

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Context and significance: Resilience is a protective agent for the physical and mental well-being of nursing professionals. Team members are constantly subjected to high levels of work stress that can negatively impact care performance and users of health services. Stress levels have been exacerbated with the COVID-19 pandemic. Objective: The aim of this study was to analyze the resilience of nursing professionals in Brazil during the COVID-19 pandemic. Method: Cross-sectional study with a quantitative approach carried out with professionals from nursing teams from all regions of Brazil. Data collection took place in the first year of the pandemic between October and December 2020. Data were obtained through an online questionnaire posted on social networks. The information collected included the sociodemographic characterization of the nursing professionals and the Brief Resilient Coping Scale was applied. Student's t-test for independent samples and analysis of variance (ANOVA) were used to compare resilience scores with sociodemographic variables. Results: 8,792 nursing professionals participated in the study, 5,767 (65.6%) were nurses, 7,437 (84.6%) were female and 2,643 (30.1%) were from the Northeast region of Brazil, 5,124 (58.8% ) had low levels of resilience. The results showed a statistically significant difference between the resilience score and the variables: professional category (p<0.001); sex (p = 0.003); age range (p<0.001); region of Brazil (p<0.001); marital status (p=0.029) and providing assistance in a field hospital (p<0.001). Conclusion: Participants in this study had, in general, low levels of resilience. There is an urgent need for actions aimed at promoting the psychological health of nursing professionals inserted in pandemic contexts. Descriptors: Psychological Resilience; Nursing professionals; COVID-19; SARSCoV-2.

Keywords: psychological resilience, nursing professionals, COVID-19, SARS-CoV-2

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