Search results for: interval coefficients

Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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The utilization of Large Eddy Simulation (LES) has been extensive in turbulence research. LES concentrates on resolving the significant grid-scale motions while representing smaller scales through subfilter-scale (SFS) models. The deconvolution model, among the available SFS models, has proven successful in LES of engineering and geophysical flows. Nevertheless, the thorough investigation of how sub-filter scale dynamics and filter anisotropy affect SFS modeling accuracy remains lacking. The outcomes of LES are significantly influenced by filter selection and grid anisotropy, factors that have not been adequately addressed in earlier studies. This study examines two crucial aspects of LES: Firstly, the accuracy of direct deconvolution models (DDM) is evaluated concerning sub-filter scale (SFS) dynamics across varying filter-to-grid ratios (FGR) in isotropic turbulence. Various invertible filters are employed, including Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The importance of FGR becomes evident as it plays a critical role in controlling errors for precise SFS stress prediction. When FGR is set to 1, the DDM models struggle to faithfully reconstruct SFS stress due to inadequate resolution of SFS dynamics. Notably, prediction accuracy improves when FGR is set to 2, leading to accurate reconstruction of SFS stress, except for cases involving Helmholtz I and II filters. Remarkably high precision, nearly 100%, is achieved at an FGR of 4 for all DDM models. Furthermore, the study extends to filter anisotropy and its impact on SFS dynamics and LES accuracy. By utilizing the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with anisotropic filters, aspect ratios (AR) ranging from 1 to 16 are examined in LES filters. The results emphasize the DDM’s proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. Notably high correlation coefficients exceeding 90% are observed in the a priori study for the DDM’s reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as filter anisotropy increases. In the a posteriori analysis, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, including velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strainrate tensors, and SFS stress. It is evident that as filter anisotropy intensifies, the results of DSM and DMM deteriorate, while the DDM consistently delivers satisfactory outcomes across all filter-anisotropy scenarios. These findings underscore the potential of the DDM framework as a valuable tool for advancing the development of sophisticated SFS models for LES in turbulence research.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, David Chernobylsky, Omar Durra

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Background: It is crucial to detect the patient’s existing anxiety to assist patients in a perioperative setting which is to be caused by the fear associated with surgical and anesthetic complications. However, the current gold standard for assessing patient anxiety, the STAI, is problematic to use in the preoperative setting, given the duration and concentration required to complete the 40-item questionnaire. Our primary aim in the study is to investigate the correlation of the Yumul Visual Facial Anxiety Scale (VFAS) and Numerical Verbal Rating Scale (NVRS) to State-Trait Anxiety Inventory (STAI) to determine the optimal anxiety scale to use in the perioperative setting. Methods: A clinical study of patients undergoing various surgeries was conducted utilizing each of the preoperative anxiety scales. Inclusion criteria included patients undergoing elective surgeries, while exclusion criteria included patients with anesthesia contraindications, inability to comprehend instructions, impaired judgement, substance abuse history, and those pregnant or lactating. 293 patients were analyzed in terms of demographics, anxiety scale survey results, and anesthesia data via Spearman Coefficients, Chi-Squared Analysis, and Fischer’s exact test utilized for comparative analysis. Results: Statistical analysis showed that VFAS had a higher correlation to STAI than NVRS (rs=0.66, p<0.0001 vs. rs=0.64, p<0.0001). The combined VFAS-Categorization Scores showed the highest correlation with the gold standard (rs=0.72, p<0.0001). Subgroup analysis showed similar results. STAI evaluation time (247.7 ± 54.81 sec) far exceeds VFAS (7.29 ± 1.61 sec), NVRS (7.23 ± 1.60 sec), and Categorization scales (7.29 ± 1.99 sec). Patients preferred VFAS (54.4%), Categorization (11.6%), and NVRS (8.8%). Anesthesiologists preferred VFAS (63.9%), NVRS (22.1%), and Categorization Scales (14.0%). Of note, the top five causes of preoperative anxiety were determined to be waiting (56.5%), pain (42.5%), family concerns (40.5%), no information about surgery (40.1%), or anesthesia (31.6%). Conclusıons: Both VFAS and Categorization tests also take significantly less time than STAI, which is critical in the preoperative setting. Combined VFAS-Categorization Score (VCS) demonstrates the highest correlation to the gold standard, STAI. Among both patients and anesthesiologists, VFAS was the most preferred scale. This forms the basis of the Yumul Faces Anxiety Scale, designed for quick quantization and assessment in the preoperative setting while maintaining a high correlation to the golden standard. Additional studies using the formulated Yumul Faces Anxiety Scale are merited.

Keywords: numerical verbal anxiety scale, preoperative anxiety, state-trait anxiety inventory, visual facial anxiety scale

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Anastasia Schnitzer, Oliver Rehren

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Mental health has become an increasingly important topic in society in recent years, not least due to the challenges posed by the corona pandemic. Along with this, the public has become more and more aware that a lack of enlightenment and proper coping mechanisms may result in a notable risk to develop mental disorders. Yet, there are still many biases against those affected, which are further connected to issues of stigmatization and societal exclusion. One of the main strategies to combat these forms of prejudice and stigma is to induce intergroup contact. More specifically, the Intergroup Contact Theory states engaging in certain types of contact with members of marginalized groups may be an effective way to improve attitudes towards these groups. However, due to the persistent prejudice and stigmatization, affected individuals often do not dare to speak openly about their mental disorders, so that intergroup contact often goes unnoticed. As a result, many people only experience conscious contact with individuals with a mental disorder through media. As an analogy to the Intergroup Contact Theory, the Parasocial Contact Hypothesis proposes that repeatedly being exposed to positive media representations of outgroup members can lead to a reduction of negative prejudices and attitudes towards this outgroup. While there is a growing body of research on the merit of this mechanism, measurements often only consist of 'positive' or 'negative' parasocial contact conditions (or examine the valence or quality of the previous contact with the outgroup); meanwhile, more specific conditions are often neglected. The current study aims to tackle this shortcoming. By scrutinizing the potential of contemporary series as a narrative framework of high quality, we strive to elucidate more detailed aspects of beneficial parasocial contact -for the sake of reducing prejudice and stigma towards individuals with mental disorders. Thus, a two-factorial between-subject online panel study with three measurement points was conducted (N = 95). Participants were randomly assigned to one of two groups, having to watch episodes of either a series with a narrative framework of high (Quality-TV) or low quality (Continental-TV), with one-week interval in-between the episodes. Suitable series were determined with the help of a pretest. Prejudice and stigma towards people with mental disorders were measured at the beginning of the study, before and after each episode, and in a final follow-up one week after the last two episodes. Additionally, parasocial interaction (PSI), quality of contact (QoC), and transportation were measured several times. Based on these data, multivariate multilevel analyses were performed in R using the lavaan package. Latent growth models showed moderate to high increases in QoC and PSI as well as small to moderate decreases in stigma and prejudice over time. Multilevel path analysis with individual and group levels further revealed that a qualitative narrative framework leads to a higher quality of contact experience, which then leads to lower prejudice and stigma, with effects ranging from moderate to high.

Keywords: prejudice, quality of contact, parasocial contact, narrative framework

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Authors: Syed Benazir Firdaus, Debosree Ghosh, Aindrila Chattyopadhyay, Kuladip Jana, Debasish Bandyopadhyay

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Gastro-toxic effect of piroxicam, a classical non-steroidal anti-inflammatory drug (NSAID), has restricted its use in arthritis and similar diseases. The present study aims to find if a combination of melatonin and Murraya koenigii leaf extract therapy can protect against piroxicam induced ulcerative damage in rats. For this study, rats were divided into four groups namely control group where rats were orally administered distilled water, only combination treated group, piroxicam treated group and combination pre-administered piroxicam treated group. Each group of rats consisted of six animals. Melatonin at a dose of 20mg/kg body weight and antioxidant rich Murraya koenigii leaf extract at a dose of 50 mg /kg body weight were successively administered at 30 minutes interval one hour before oral administration of piroxicam at a dose of 30 mg/kg body weight to Wistar rats in the combination pre-administered piroxicam treated group. The rats of the animal group which was only combination treated were administered both the drugs respectively without piroxicam treatment whereas the piroxicam treated animal group was administered only piroxicam at 30mg/kg body weight without any pre-treatment with the combination. Macroscopic examination along with histo-pathological study of gastric tissue using haemotoxylin-eosin staining and alcian blue dye staining showed protection of the gastric mucosa in the combination pre-administered piroxicam treated group. Determination of adherent mucus content biochemically and collagen content through Image J analysis of picro-sirius stained sections of rat gastric tissue also revealed protective effects of the combination in piroxicam mediated toxicity. Gelatinolytic activity of piroxicam was significantly reduced by pre-administration of the drugs which was well exhibited by the gelatin zymography study of the rat gastric tissue. Mean ulcer index determined from macroscopic study of rat stomach reduced to a minimum (0±0.00; Mean ± Standard error of mean and number of animals in the group=6) indicating the absence of ulcer spots on pre-treatment of rats with the combination. Gastro-friendly prostaglandin (PGE2) which otherwise gets depleted on piroxicam treatment was also well protected when the combination was pre-administered in the rats prior to piroxicam treatment. The requirement of the individual drugs in low doses in this combinatorial therapeutic approach will possibly minimize the cost of therapy as well as it will eliminate the possibility of any pro-oxidant side effects on the use of high doses of antioxidants. Beneficial activity of this combination therapy in the rat model raises the possibility that similar protective actions might be also observed if it is adopted by patients consuming NSAIDs like piroxicam. However, the introduction of any such therapeutic approach is subject to future studies in human.

Keywords: gastro-protective action, melatonin, Murraya koenigii leaf extract, piroxicam

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Authors: Maciej Czarnecki

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Even though growth is one of the most important strategic objectives for many enterprises, we know relatively little about this phenomenon. This research contributes to broaden our knowledge of managerial consequences of growth. Scales for measuring organizational development and growing pains were developed. Conceptual model of connections among growth, organizational development, growing pains, selected development factors and financial performance were examined. The research process contained literature review, 20 interviews with managers, examination of 12 raters’ opinions, pilot research and 7 point Likert scale questionnaire research on 138 Polish enterprises employing 50-249 people which increased their employment at least by 50% within last three years. Factor analysis, Pearson product-moment correlation coefficient, student’s t-test and chi-squared test were used to develop scales. High Cronbach’s alpha coefficients were obtained. The verification of correlations among the constructs was carried out with factor correlations, multiple regressions and path analysis. When the enterprise grows, it is necessary to implement changes in its structure, management practices etc. (organizational development) to meet challenges of growing complexity. In this paper, organizational development was defined as internal changes aiming to improve the quality of existing or to introduce new elements in the areas of processes, organizational structure and culture, operational and management systems. Thus; H1: Growth has positive effects on organizational development. The main thesis of the research is that if organizational development does not catch up　with growing complexity of growing enterprise, growing pains will arise (lower work comfort, conflicts, lack of control etc.). They will exert a negative influence on the financial performance and may result in serious organizational crisis or even bankruptcy. Thus; H2: Growth has positive effects on growing pains, H3: Organizational development has negative effects on growing pains, H4: Growing pains have negative effects on financial performance, H5: Organizational development has positive effects on financial performance. Scholars considered long lists of factors having potential influence on organizational development. The development of comprehensive model taking into account all possible variables may be beyond the capacity of any researcher or even statistical software used. After literature review, it was decided to increase the level of abstraction and to include following constructs in the conceptual model: organizational learning (OL), positive organization (PO) and high performance factors (HPF). H1a/b/c: OL/PO/HPF has positive effect on organizational development, H2a/b/c: OL/PO/HPF has negative effect on growing pains. The results of hypothesis testing: H1: partly supported, H1a/b/c: supported/not supported/supported, H2: not supported, H2a/b/c: not supported/partly supported/not supported, H3: supported, H4: partly supported, H5: supported. The research seems to be of a great value for both scholars and practitioners. It proved that OL and HPO matter for organizational development. Scales for measuring organizational development and growing pains were developed. Its main finding, though, is that organizational development is a good way of improving financial performance.

Keywords: organizational development, growth, growing pains, financial performance

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Authors: Johan Buermans, Kristel Crombé, Niek Desmet, Laura Dittrich, Andrei Goriaev, Yurii Kovtun, Daniel López-Rodriguez, Sören Möller, Per Petersson, Maja Verstraeten

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The International Thermonuclear Experimental Reactor (ITER) will rely on three sources of external heating to produce and sustain a plasma; Neutral Beam Injection (NBI), Ion Cyclotron Resonance Heating (ICRH), and Electron Cyclotron Resonance Heating (ECRH). ECRH is a way to heat the electrons in a plasma by resonant absorption of electromagnetic waves. The energy of the electrons is transferred indirectly to the ions by collisions. The electron cyclotron heating system can be directed to deposit heat in particular regions in the plasma (https://www.iter.org/mach/Heating). Electron Cyclotron Resonance Heating (ECRH) at the fundamental resonance in X-mode is limited by a low cut-off density. Electromagnetic waves cannot propagate in the region between this cut-off and the Upper Hybrid Resonance (UHR) and cannot reach the Electron Cyclotron Resonance (ECR) position. Higher harmonic heating is hence preferred in heating scenarios nowadays to overcome this problem. Additional power deposition mechanisms can occur above this threshold to increase the plasma density. This includes collisional losses in the evanescent region, resonant power coupling at the UHR, tunneling of the X-wave with resonant coupling at the ECR, and conversion to the Electron Bernstein Wave (EBW) with resonant coupling at the ECR. A more profound knowledge of these deposition mechanisms can help determine the optimal plasma production scenarios. Several ECRH experiments are performed on the TOroidally MAgnetized System (TOMAS) to identify the conditions for Electron Bernstein Wave (EBW) heating. Density and temperature profiles are measured with movable Triple Langmuir Probes in the horizontal and vertical directions. Measurements of the forwarded and reflected power allow evaluation of the coupling efficiency. Optical emission spectroscopy and camera images also contribute to plasma characterization. The influence of the injected power, magnetic field, gas pressure, and wave polarization on the different deposition mechanisms is studied, and the contribution of the Electron Bernstein Wave is evaluated. The TOMATOR 1D hydrogen-helium plasma simulator numerically describes the evolution of current less magnetized Radio Frequency plasmas in a tokamak based on Braginskii’s legal continuity and heat balance equations. This code was initially benchmarked with experimental data from TCV to determine the transport coefficients. The code is used to model the plasma parameters and the power deposition profiles. The modeling is compared with the data from the experiments.

Keywords: electron Bernstein wave, Langmuir probe, plasma characterization, TOMAS

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Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: Lei Li, Ping Yin, Haneen Khreis

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Stroke is the second leading cause of death and a third leading cause of death and disability worldwide in 2019. Given the significant role of environmental factors in stroke development and progression, it is essential to investigate the effect of air pollution on stroke occurrence while considering the modifying effects of meteorological variables. This study aimed to evaluate the association between short-term exposure to air pollution and the incidence of stroke subtypes in Shenzhen, China, and to explore the potential interactions of meteorological factors with air pollutants. The study analyzed data from January 1, 2006, to December 31, 2014, including 88,214 cases of ischemic stroke and 30,433 cases of hemorrhagic stroke among residents of Shenzhen. Using a time-stratified case–crossover design with conditional quasi-Poisson regression, the study estimated the percentage changes in stroke morbidity associated with short-term exposure to nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter less than 10 mm in aerodynamic diameter (PM10), carbon monoxide (CO), and ozone (O₃). A five-day moving average of air pollution was applied to capture the cumulative effects of air pollution. The estimates were further stratified by sex, age, education level, and season. The additive and multiplicative interaction between air pollutants and meteorologic variables were assessed by the relative excess risk due to interaction (RERI) and adding the interactive term into the main model, respectively. The study found that NO₂ was positively associated with ischemic stroke occurrence throughout the year and in the cold season (November through April), with a stronger effect observed among men. Each 10 μg/m³ increment in the five-day moving average of NO₂ was associated with a 2.38% (95% confidence interval was 1.36% to 3.41%) increase in the risk of ischemic stroke over the whole year and a 3.36% (2.04% to 4.69%) increase in the cold season. The harmful effect of CO on ischemic stroke was observed only in the cold season, with each 1 mg/m³ increment in the five-day moving average of CO increasing the risk by 12.34% (3.85% to 21.51%). There was no statistically significant additive interaction between individual air pollutants and temperature or relative humidity, as demonstrated by the RERI. The interaction term in the model showed a multiplicative antagonistic effect between NO₂ and temperature (p-value=0.0268). For hemorrhagic stroke, no evidence of the effects of any individual air pollutants was found in the whole population. However, the RERI indicated a statistically additive and multiplicative interaction of temperature on the effects of PM10 and O₃ on hemorrhagic stroke onset. Therefore, the insignificant conclusion should be interpreted with caution. The study suggests that environmental NO₂ and CO might increase the morbidity of ischemic stroke, particularly during the cold season. These findings could help inform policy decisions aimed at reducing air pollution levels to prevent stroke and other health conditions. Additionally, the study provides valuable insights into the interaction between air pollution and meteorological variables, which underscores the need for further research into the complex relationship between environmental factors and health.

Keywords: air pollution, meteorological variables, interactive effect, seasonal pattern, stroke

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Authors: C. A. Sharma, Birendra P. Singh

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We recovered 40 well preserved ribbon-shaped, meandering specimens of S. ningqiangensis from the Earthy Dolomite Member (Krol Group) and calcareous siltstone beds of the Earthy Siltstone Member (Tal Group) showing closely spaced annulations that lacked branching. The beginning and terminal points are indistinguishable. In certain cases, individual specimens are characterized by irregular, low-angle to high-angle sinuosity. It has been variously described as body fossil, ichnofossil and algae. Detailed study of this enigmatic fossil is needed to resolve the long standing controversy regarding its phylogenetic and stratigraphic placements, which will be an important contribution to the evolutionary history of metazoans. S. ningqiangensis has been known from the late Neoproterozoic (Ediacaran) of southern and central China (Sichuan, Shaanxi, Quinghai and Guizhou provinces and Ningxia Hui Autonomous region), Siberian platform and across Pc/C Boundary from latest Neoprterozoic to earliest Cambrian of northern India. Shaanxilithes is considered an Ediacaran organism that spans the Precambrian–Cambrian boundary, an interval marked by significant taphonomic and ecological transformations that include not only innovation but also probable extinction. All the past well constrained finds of S. ningqiangensis are restricted to Ediacaran age. However, due to the new recoveries of the fossil from Nigalidhar Syncline, the stratigraphic status of S. ningqiangensis-bearing Earthy Siltstone Member of the Shaliyan Formation of the Tal Group (Cambrian) is rendered uncertain, though the overlying Chert Member in the adjoining Korgai Syncline has yielded definite early Cambrian acritarchs. The moot question is whether the Earthy Siltstone Member represents an Ediacaran or an early Cambrian age?. It would be interesting to find if Shaanxilithes, so far known from Ediacaran sequences, could it transgress to the early Cambrian or in simple words could it withstand the Pc/C Boundary event? GC-MS data shows the S. ningqiangensis structure is formed by hydrocarbon organic compounds which are filled with inorganic elements filler like silica, Calcium, phosphorus etc. The S. ningqiangensis structure is a mixture of organic compounds of high molecular weight, containing several saturated rings with hydrocarbon chains having an occasional isolated carbon-carbon double bond and also containing, in addition, to small amounts of nitrogen, sulfur and oxygen. Data also revealed that the presence of nitrogen which would be either in the form of peptide chains means amide/amine or chemical form i.e. nitrates/nitrites etc. The formula weight and the weight ratio of C/H shows that it would be expected for algae derived organics, since algae produce fatty acids as well as other hydrocarbons such as cartenoids.

Keywords: GC-MS Analysis, lesser himalaya, Pc/C Boundary, shaanxilithes

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Krzysztof Skiba

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This paper discusses the CFD simulation of a flow around a rotor of a Vertical Axis Wind Turbine. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed and avoid a costly preparation of a model or a prototype for a bench test. CFD simulation enables us to compare characteristics of aerodynamic forces acting on rotor working surfaces and define operational parameters like torque or power generated by a turbine assembly. This research focused on the rotor with the blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on adjusting angular aperture α of the top and bottom parts of the blades mounted on an axis. If this angular aperture α increases, the working surface which absorbs wind kinetic energy also increases. The operation of turbines is characterized by parameters like the angular aperture of blades, power, torque, speed for a given wind speed. These parameters have an impact on the efficiency of assemblies. The distribution of forces acting on the working surfaces in our turbine changes according to the angular velocity of the rotor. Moreover, the resultant force from the force acting on an advancing blade and retreating blade should be as high as possible. This paper is part of the research to improve an efficiency of a rotor assembly. Therefore, using simulation, the courses of the above parameters were studied in three full rotations individually for each of the blades for three angular apertures of blade working surfaces, i.e. 30 °, 60 °, 90 °, at three wind speeds, i.e. 4 m / s, 6 m / s, 8 m / s and rotor speeds ranging from 100 to 500 rpm. Finally, there were created the characteristics of torque coefficients and power as a function of time for each blade separately and for the entire rotor. Accordingly, the correlation between the turbine rotor power as a function of wind speed for varied values of rotor rotational speed. By processing this data, the correlation between the power of the turbine rotor and its rotational speed for each of the angular aperture of the working surfaces was specified. Finally, the optimal values, i.e. of the highest output power for given wind speeds were read. The research results in receiving the basic characteristics of turbine rotor power as a function of wind speed for the three angular apertures of the blades. Given the nature of rotor operation, the growth in the output turbine can be estimated if angular aperture of the blades increases. The controlled adjustment of angle α enables a smooth adjustment of power generated by a turbine rotor. If wind speed is significant, this type of adjustment enables this output power to remain at the same level (by reducing angle α) with no risk of damaging a construction. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

Procedia PDF Downloads 184

Authors: M. Venegas, M. De Vega, N. García-Hernando

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Absorption cooling chillers have received growing attention over the past few decades as they allow the use of low-grade heat to produce the cooling effect. The combination of this technology with solar thermal energy in the summer period can reduce the electricity consumption peak due to air-conditioning. One of the main components, the absorber, is designed for simultaneous heat and mass transfer. Usually, shell and tubes heat exchangers are used, which are large and heavy. Cooling water from a cooling tower is conventionally used to extract the heat released during the absorption and condensation processes. These are clear inconvenient for the generalization of the absorption technology use, limiting its benefits in the contribution to the reduction in CO2 emissions, particularly for the H2O-LiBr solution which can work with low heat temperature sources as provided by solar panels. In the present work a promising new technology is under study, consisting in the use of membrane contactors in adiabatic microchannel mass exchangers. The configuration here proposed consists in one or several modules (depending on the cooling capacity of the chiller) that contain two vapour channels, separated from the solution by adjacent microporous membranes. The solution is confined in rectangular microchannels. A plastic or synthetic wall separates the solution channels between them. The solution entering the absorber is previously subcooled using ambient air. In this way, the need for a cooling tower is avoided. A model of the configuration proposed is developed based on mass and energy balances and some correlations were selected to predict the heat and mass transfer coefficients. The concentration and temperatures along the channels cannot be explicitly determined from the set of equations obtained. For this reason, the equations were implemented in a computer code using Engineering Equation Solver software, EES™. With the aim of minimizing the absorber volume to reduce the size of absorption cooling chillers, the ratio between the cooling power of the chiller and the absorber volume (R) is calculated. Its variation is shown along the solution channels, allowing its optimization for selected operating conditions. For the case considered the solution channel length is recommended to be lower than 3 cm. Maximum values of R obtained in this work are higher than the ones found in optimized horizontal falling film absorbers using the same solution. Results obtained also show the variation of R and the chiller efficiency (COP) for different ambient temperatures and desorption temperatures typically obtained using flat plate solar collectors. The configuration proposed of adiabatic membrane-based absorber using ambient air to subcool the solution is a good technology to reduce the size of the absorption chillers, allowing the use of low temperature solar heat and avoiding the need for cooling towers.

Keywords: adiabatic absorption, air-cooled, membrane, solar thermal energy

Procedia PDF Downloads 258

Authors: Roberta Martino, Viviana Ventre

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Every day we face choices whose consequences are deferred in time. These types of choices are the intertemporal choices and play an important role in the social, economic, and financial world. The Discounted Utility Model is the mathematical model of reference to calculate the utility of intertemporal prospects. The discount rate is the main element of the model as it describes how the individual perceives the indeterminacy of subsequent periods. Empirical evidence has shown a discrepancy between the behavior expected from the predictions of the model and the effective choices made from the decision makers. In particular, the term temporal inconsistency indicates those choices that do not remain optimal with the passage of time. This phenomenon has been described with hyperbolic models of the discount rate which, unlike the linear or exponential nature assumed by the discounted utility model, is not constant over time. This paper explores the problem of inconsistency by tracing the decision-making process through the concept of impatience. The degree of impatience and the degree of decrease of impatience are two parameters that allow to quantify the weight of emotional factors and cognitive limitations during the evaluation and selection of alternatives. In fact, although the theory assumes perfectly rational decision makers, behavioral finance and cognitive psychology have made it possible to understand that distortions in the decision-making process and emotional influence have an inevitable impact on the decision-making process. The degree to which impatience is diminished is the focus of the first part of the study. By comparing consistent and inconsistent preferences over time, it was possible to verify that some anomalies in the discounted utility model are a result of the combination of cognitive bias and emotional factors. In particular: the delay effect and the interval effect are compared through the concept of misperception of time; starting from psychological considerations, a criterion is proposed to identify the causes of the magnitude effect that considers the differences in outcomes rather than their ratio; the sign effect is analyzed by integrating in the evaluation of prospects with negative outcomes the psychological aspects of loss aversion provided by Prospect Theory. An experiment implemented confirms three findings: the greatest variation in the degree of decrease in impatience corresponds to shorter intervals close to the present; the greatest variation in the degree of impatience occurs for outcomes of lower magnitude; the variation in the degree of impatience is greatest for negative outcomes. The experimental phase was implemented with the construction of the hyperbolic factor through the administration of questionnaires constructed for each anomaly. This work formalizes the underlying causes of the discrepancy between the discounted utility model and the empirical evidence of preference reversal.

Keywords: decreasing impatience, discount utility model, hyperbolic discount, hyperbolic factor, impatience

Procedia PDF Downloads 81

Authors: Emmanuel O. Ezim, Idowu A. Olayinka, Michael Oladunjoye, Izuchukwu I. Obiadi

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Monitoring of reservoir properties prior to well placements and production is a requirement for optimisation and efficient oil and gas production. This is usually done using well log analyses and 3-D seismic, which are often prone to errors. However, 4-D (Time-lapse) seismic, incorporating numerous 3-D seismic surveys of the same field with the same acquisition parameters, which portrays the transient changes in the reservoir due to production effects over time, could be utilised because it generates better resolution. There is, however dearth of information on the applicability of this approach in the Niger Delta. This study was therefore designed to apply 4-D seismic, well-log and geologic data in monitoring of reservoirs in the EK field of the Niger Delta. It aimed at locating bypassed accumulations and ensuring effective reservoir management. The Field (EK) covers an area of about 1200km2 belonging to the early (18ma) Miocene. Data covering two 4-D vintages acquired over a fifteen-year interval were obtained from oil companies operating in the field. The data were analysed to determine the seismic structures, horizons, Well-to-Seismic Tie (WST), and wavelets. Well, logs and production history data from fifteen selected wells were also collected from the Oil companies. Formation evaluation, petrophysical analysis and inversion alongside geological data were undertaken using Petrel, Shell-nDi, Techlog and Jason Software. Well-to-seismic tie, formation evaluation and saturation monitoring using petrophysical and geological data and software were used to find bypassed hydrocarbon prospects. The seismic vintages were interpreted, and the amounts of change in the reservoir were defined by the differences in Acoustic Impedance (AI) inversions of the base and the monitor seismic. AI rock properties were estimated from all the seismic amplitudes using controlled sparse-spike inversion. The estimated rock properties were used to produce AI maps. The structural analysis showed the dominance of NW-SE trending rollover collapsed-crest anticlines in EK with hydrocarbons trapped northwards. There were good ties in wells EK 27, 39. Analysed wavelets revealed consistent amplitude and phase for the WST; hence, a good match between the inverted impedance and the good data. Evidence of large pay thickness, ranging from 2875ms (11420 TVDSS-ft) to about 2965ms, were found around EK 39 well with good yield properties. The comparison between the base of the AI and the current monitor and the generated AI maps revealed zones of untapped hydrocarbons as well as assisted in determining fluids movement. The inverted sections through EK 27, 39 (within 3101 m - 3695 m), indicated depletion in the reservoirs. The extent of the present non-uniform gas-oil contact and oil-water contact movements were from 3554 to 3575 m. The 4-D seismic approach led to better reservoir characterization, well development and the location of deeper and bypassed hydrocarbon reservoirs.

Keywords: reservoir monitoring, 4-D seismic, well placements, petrophysical analysis, Niger delta basin

Procedia PDF Downloads 99

Authors: Rochelle Daley, Eric Garraway, Catherine Murphy

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Crime is a major problem in Jamaica as well as the high number of unsolved violent crimes. The introduction of forensic entomology in criminal investigations has the potential to decrease the number of unsolved violent crimes through the estimation of PMI (post-mortem interval) or time since death. Though it has great potential, forensic entomology requires data from insects specific to a geographical location to be credibly applied in legal investigations. It is a relatively new area of study in the Caribbean, with multiple pioneer research opportunities. Of critical importance in forensic entomology is the ability to identify the species of interest. Larvae are commonly collected at crime scenes and a means of rapid identification is crucial. Moreover, a low-cost method is critical in countries with limited budget available for crime fighting. Sarcophagids are one of the most important colonisers of a carcass however, they are difficult to distinguish using morphology due to their similarities, however, there is a lack of research on the larvae of this family. This research contributes to that, having identified the larvae of three species from the family Sarcophagidae: Peckia nicasia, Peckia chrysostoma and Blaesoxipha plinthopyga; important agents in flesh decomposition. Adults of Sarcophidae are also difficult to differentiate, often requiring study of the genitalia; the use of larvae in species identification is important in such cases. Adult Sarcophagids were attracted using bottle traps baited with pig liver. These adults larviposited and the larvae were collected and colonises (generation 2 and 3) reared at room temperature for morphological work (n=50). The posterior ends of the larvae from segments 9 or 10 were removed and mounted posterior end upwards to allow study using a light microscope at magnification X200 (posterior cavity and intersegmental spine bands) and X640 (anterior and posterior spiracle). The remaining sections of the larvae were cleared in 10 % KOH and the cephalopharyngeal skeleton dissected out and measured at different points. The cephalopharyngeal skeletons show observable differences in the shapes and sizes of the mouth hooks as well as the length of the ventral cornua. The most notable difference between species is in the general shape of the anal segments and the shape of the posterior spiracles. Intersegmental spine bands of these larvae become less pigmented and visible as the larvae change instars. Spine bands along with anterior spiracle are not recommended as features for species distinction. Larvae can potentially be used to distinguish Sarcophagids to the level of species, with observable differences in the anal segments and the cephalopharyngeal skeletons. However, this method of identification should be tested by comparing these morphological features with other Jamaican Sarcophagids to further support this conclusion.

Keywords: 3rd instar larval morphology, forensic entomology, Jamaica, Sarcophagidae

Procedia PDF Downloads 117

Authors: Thimira Pasas P, Nirmala Priyadarshani M, Ishani R

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Obesity is a global health issue. Early identification is essential to plan interventions and intervene than to reduce the worsening of obesity and its consequences on the health issues of the individual. Childhood obesity is multifactorial, with both modifiable and unmodifiable risk factors. A genetically susceptible individual (unmodifiable), when placed in an obesogenic environment (modifiable), is likely to become obese in onset and progression. The present study was conducted to identify the age of onset of childhood obesity and the influence of modifiable risk factors for childhood obesity among school children living in a suburban area of Sri Lanka. The study population was aged 11-12 years of Piliyandala Educational Zone. Data were collected from 11–12-year-old school children attending government schools in the Piliyandala Educational Zone. They were using a validated, pre-tested self-administered questionnaire. A stratified random sampling method was performed to select schools and to select a representative sample to include all 3 types of government schools of students due to the prevailing pandemic situation, information from the last school medical inspection on data from 2020used for this purpose. For each obese child identified, 2 non-obese children were selected as controls. A single representative from the area was selected by using a systematic random sampling method with a sampling interval of 3. Data was collected using a validated, pre-tested self-administered questionnaire and the Child Health Development Record of the child. An introduction, which included explanations and instructions for filing the questionnaire, was carried out as a group activity prior to distributing the questionnaire among the sample. The results of the present study aligned with the hypothesis that the age of onset of childhood obesity and prediction must be within the first two years of child life. A total of 130 children (66 males: 64 females) participated in the study. The age of onset of obesity was seen to be within the first two years of life. The risk of obesity at 11-12 years of age was Obesity risk was identified at 3-time s higher among females who underwent rapid weight gain within their infancy period. Consuming milk prior to breakfast emerged as a risk factor that increases the risk of obesity by three times. The current study found that the drink before breakfast tends to increase the obesity risk by 3-folds, especially among obese females. Proper monitoring must be carried out to identify the rapid weight gain, especially within the first 2 years of life. Consumption of mug milk before breakfast tends to increase the obesity risk by 3 times. Identification of the confounding factors, proper awareness of the mothers/guardians and effective proper interventions need to be carried out to reduce the obesity risk among school children in the future.

Keywords: childhood obesity, school children, age of onset, weight gain, feeding pattern, activity level

Procedia PDF Downloads 118

Authors: Giulia Bonaldo, Alberto Vaccheri, Ottavio D'Annibali, Domenico Motola

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The Human Papilloma Virus (HPV) was shown to be the cause of different types of carcinomas, first of all of the cervical intraepithelial neoplasia. Since the early 80s to today, thanks first to the preventive screening campaigns (pap-test) and following to the introduction of HPV vaccines on the market; the number of new cases of cervical cancer has decreased significantly. The HPV vaccines currently approved are three: Cervarix® (HPV2 - virus type: 16 and 18), Gardasil® (HPV4 - 6, 11, 16, 18) and Gardasil 9® (HPV9 - 6, 11, 16, 18, 31, 33, 45, 52, 58), which all protect against the two high-risk HPVs (6, 11) that are mainly involved in cervical cancers. Despite the remarkable effectiveness of these vaccines has been demonstrated, in the recent years, there have been many complaints about their risk-benefit profile due to Adverse Events Following Immunization (AEFI). The purpose of this study is to provide a support about the ongoing discussion on the safety profile of HPV vaccines based on real life data deriving from spontaneous reports of suspected AEFIs collected in the Vaccine Adverse Events Reporting System (VAERS). VAERS is a freely-available national vaccine safety surveillance database of AEFI, co-administered by the Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA). We collected all the reports between January 2007 to December 2017 related to the HPV vaccines with a brand name (HPV2, HPV4, HPV9) or without (HPVX). A disproportionality analysis using Reporting Odds Ratio (ROR) with 95% confidence interval and p value ≤ 0.05 was performed. Over the 10-year period, 54889 reports of AEFI related to HPV vaccines reported in VAERS, corresponding to 224863 vaccine-event pairs, were retrieved. The highest number of reports was related to Gardasil (n = 42244), followed by Gardasil 9 (7212) and Cervarix (3904). The brand name of the HPV vaccine was not reported in 1529 cases. The two events more frequently reported and statistically significant for each vaccine were: dizziness (n = 5053) ROR = 1.28 (CI95% 1.24 – 1.31) and syncope (4808) ROR = 1.21 (1.17 – 1.25) for Gardasil. For Gardasil 9, injection site pain (305) ROR = 1.40 (1.25 – 1.57) and injection site erythema (297) ROR = 1.88 (1.67 – 2.10) and for Cervarix, headache (672) ROR = 1.14 (1.06 – 1.23) and loss of consciousness (528) ROR = 1.71 (1.57 – 1.87). In total, we collected 406 reports of death and 2461 cases of permanent disability in the ten-year period. The events consisting of incorrect vaccine storage or incorrect administration were not considered. The AEFI analysis showed that the most frequently reported events are non-serious and listed in the corresponding SmPCs. In addition to these, potential safety signals arose regarding less frequent and severe AEFIs that would deserve further investigation. This already happened with the referral of the European Medicines Agency (EMA) for the adverse events POTS (Postural Orthostatic Tachycardia Syndrome) and CRPS (Complex Regional Pain Syndrome) associated with anti-papillomavirus vaccines.

Keywords: adverse drug reactions, pharmacovigilance, safety, vaccines

Procedia PDF Downloads 136

Authors: Niyongabo Elyse

Abstract:

Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

Procedia PDF Downloads 27

Authors: Ines Raies, Eric Kohler, Marc Fleury, Béatrice Ledésert

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In this work, the impact of clay minerals on the formation damage of sandstone reservoirs is studied to provide a better understanding of the problem of deep geothermal reservoir permeability reduction due to fine particle dispersion and migration. In some situations, despite the presence of filters in the geothermal loop at the surface, particles smaller than the filter size (<1 µm) may surprisingly generate significant permeability reduction affecting in the long term the overall performance of the geothermal system. Our study is carried out on cores from a Triassic reservoir in the Paris Basin (Feigneux, 60 km Northeast of Paris). Our goal is to first identify the clays responsible for clogging, a mineralogical characterization of these natural samples was carried out by coupling X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). The results show that the studied stratigraphic interval contains mostly illite and chlorite particles. Moreover, the spatial arrangement of the clays in the rocks as well as the morphology and size of the particles, suggest that illite is more easily mobilized than chlorite by the flow in the pore network. Thus, based on these results, illite particles were prepared and used in core flooding in order to better understand the factors leading to the aggregation and deposition of this type of clay particles in geothermal reservoirs under various physicochemical and hydrodynamic conditions. First, the stability of illite suspensions under geothermal conditions has been investigated using different characterization techniques, including Dynamic Light Scattering (DLS) and Scanning Transmission Electron Microscopy (STEM). Various parameters such as the hydrodynamic radius (around 100 nm), the morphology and surface area of aggregates were measured. Then, core-flooding experiments were carried out using sand columns to mimic the permeability decline due to the injection of illite-containing fluids in sandstone reservoirs. In particular, the effects of ionic strength, temperature, particle concentration and flow rate of the injected fluid were investigated. When the ionic strength increases, a permeability decline of more than a factor of 2 could be observed for pore velocities representative of in-situ conditions. Further details of the retention of particles in the columns were obtained from Magnetic Resonance Imaging and X-ray Tomography techniques, showing that the particle deposition is nonuniform along the column. It is clearly shown that very fine particles as small as 100 nm can generate significant permeability reduction under specific conditions in high permeability porous media representative of the Triassic reservoirs of the Paris basin. These retention mechanisms are explained in the general framework of the DLVO theory

Keywords: geothermal energy, reinjection, clays, colloids, retention, porosity, permeability decline, clogging, characterization, XRD, SEM-EDS, STEM, DLS, NMR, core flooding experiments

Procedia PDF Downloads 146

Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

Abstract:

Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

Procedia PDF Downloads 48

Authors: Tahisa M. Pedroso, Hérida R. N. Salgado

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The microbiological turbidimetric assay allows the determination of potency of the drug, by measuring the turbidity (absorbance), caused by inhibition of microorganisms by ertapenem sodium. Ertapenem sodium (ERTM), a synthetic antimicrobial agent of the class of carbapenems, shows action against Gram-negative, Gram-positive, aerobic and anaerobic microorganisms. Turbidimetric assays are described in the literature for some antibiotics, but this method is not described for ertapenem. The objective of the present study was to develop and validate a simple, sensitive, precise and accurate microbiological assay by turbidimetry to quantify ertapenem sodium injectable as an alternative to the physicochemical methods described in the literature. Several preliminary tests were performed to choose the following parameters: Staphylococcus aureus ATCC 25923, IAL 1851, 8 % of inoculum, BHI culture medium, and aqueous solution of ertapenem sodium. 10.0 mL of sterile BHI culture medium were distributed in 20 tubes. 0.2 mL of solutions (standard and test), were added in tube, respectively S1, S2 and S3, and T1, T2 and T3, 0.8 mL of culture medium inoculated were transferred to each tube, according parallel lines 3 x 3 test. The tubes were incubated in shaker Marconi MA 420 at a temperature of 35.0 °C ± 2.0 °C for 4 hours. After this period, the growth of microorganisms was inhibited by addition of 0.5 mL of 12% formaldehyde solution in each tube. The absorbance was determined in Quimis Q-798DRM spectrophotometer at a wavelength of 530 nm. An analytical curve was constructed to obtain the equation of the line by the least-squares method and the linearity and parallelism was detected by ANOVA. The specificity of the method was proven by comparing the response obtained for the standard and the finished product. The precision was checked by testing the determination of ertapenem sodium in three days. The accuracy was determined by recovery test. The robustness was determined by comparing the results obtained by varying wavelength, brand of culture medium and volume of culture medium in the tubes. Statistical analysis showed that there is no deviation from linearity in the analytical curves of standard and test samples. The correlation coefficients were 0.9996 and 0.9998 for the standard and test samples, respectively. The specificity was confirmed by comparing the absorbance of the reference substance and test samples. The values obtained for intraday, interday and between analyst precision were 1.25%; 0.26%, 0.15% respectively. The amount of ertapenem sodium present in the samples analyzed, 99.87%, is consistent. The accuracy was proven by the recovery test, with value of 98.20%. The parameters varied did not affect the analysis of ertapenem sodium, confirming the robustness of this method. The turbidimetric assay is more versatile, faster and easier to apply than agar diffusion assay. The method is simple, rapid and accurate and can be used in routine analysis of quality control of formulations containing ertapenem sodium.

Keywords: ertapenem sodium, turbidimetric assay, quality control, validation

Procedia PDF Downloads 372

Authors: Danilo F. Rodrigues, Hérida Regina N. Salgado

Abstract:

Introduction: The emergence of resistant microorganisms to a large number of clinically approved antimicrobials has been increasing, which restrict the options for the treatment of bacterial infections. As a strategy, drugs with high antimicrobial activities are in evidence. Stands out a class of antimicrobial, the cephalosporins, having as fourth generation cefepime (CEF) a semi-synthetic product which has activity against various Gram-positive bacteria (e.g. oxacillin resistant Staphylococcus aureus) and Gram-negative (e.g. Pseudomonas aeruginosa) aerobic. There are few studies in the literature regarding the development of microbiological methodologies for the analysis of this antimicrobial, so researches in this area are highly relevant to optimize the analysis of this drug in the industry and ensure the quality of the marketed product. The development of microbiological methods for the analysis of antimicrobials has gained strength in recent years and has been highlighted in relation to physicochemical methods, especially because they make possible to determine the bioactivity of the drug against a microorganism. In this context, the aim of this work was the development and validation of a microbiological method for quantitative analysis of CEF in powder lyophilized for injectable solution by turbidimetric assay. Method: For performing the method, Staphylococcus aureus ATCC 6538 IAL 2082 was used as the test microorganism and the culture medium chosen was the Casoy broth. The test was performed using temperature control (35.0 °C ± 2.0 °C) and incubated for 4 hours in shaker. The readings of the results were made at a wavelength of 530 nm through a spectrophotometer. The turbidimetric microbiological method was validated by determining the following parameters: linearity, precision (repeatability and intermediate precision), accuracy and robustness, according to ICH guidelines. Results and discussion: Among the parameters evaluated for method validation, the linearity showed results suitable for both statistical analyses as the correlation coefficients (r) that went 0.9990 for CEF reference standard and 0.9997 for CEF sample. The precision presented the following values 1.86% (intraday), 0.84% (interday) and 0.71% (between analyst). The accuracy of the method has been proven through the recovery test where the mean value obtained was 99.92%. The robustness was verified by the parameters changing volume of culture medium, brand of culture medium, incubation time in shaker and wavelength. The potency of CEF present in the samples of lyophilized powder for injectable solution was 102.46%. Conclusion: The turbidimetric microbiological method proposed for quantification of CEF in lyophilized powder for solution for injectable showed being fast, linear, precise, accurate and robust, being in accordance with all the requirements, which can be used in routine analysis of quality control in the pharmaceutical industry as an option for microbiological analysis.

Keywords: cefepime hydrochloride, quality control, turbidimetric assay, validation

Procedia PDF Downloads 337

Authors: Jean-Philippe Amat, Timothée Vergne, Aymeric Hans, Bénédicte Ferry, Pascal Hendrikx, Jackie Tapprest, Barbara Dufour, Agnès Leblond

Abstract:

The surveillance of infectious diseases is necessary to describe their occurrence and help the planning, implementation and evaluation of risk mitigation activities. However, the exact number of detected cases may remain unknown whether surveillance is based on serological tests because identifying seroconversion may be difficult. Moreover, incomplete detection of cases or outbreaks is a recurrent issue in the field of disease surveillance. This study addresses these two issues. Using a viral animal disease as an example (equine viral arteritis), the goals were to establish suitable rules for identifying seroconversion in order to estimate the number of cases and outbreaks detected by a surveillance system in France between 2006 and 2013, and to assess the sensitivity of this system by estimating the total number of outbreaks that occurred during this period (including unreported outbreaks) using a capture-recapture model. Data from horses which exhibited at least one positive result in serology using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of the annual antibody titers and the location of the subjects (towns). A consensus among multidisciplinary experts (specialists in the disease and its laboratory diagnosis, epidemiologists) was reached to consider seroconversion as a change in antibody titer from negative to at least 32 or as a three-fold or greater increase. The number of seroconversions was counted for each town and modeled using a unilist zero-truncated binomial (ZTB) capture-recapture model with R software. The binomial denominator was the number of horses tested in each infected town. Using the defined rules, 239 cases located in 177 towns (outbreaks) were identified from 2006 to 2013. Subsequently, the sensitivity of the surveillance system was estimated as the ratio of the number of detected outbreaks to the total number of outbreaks that occurred (including unreported outbreaks) estimated using the ZTB model. The total number of outbreaks was estimated at 215 (95% credible interval CrI95%: 195-249) and the surveillance sensitivity at 82% (CrI95%: 71-91). The rules proposed for identifying seroconversion may serve future research. Such rules, adjusted to the local environment, could conceivably be applied in other countries with surveillance programs dedicated to this disease. More generally, defining ad hoc algorithms for interpreting the antibody titer could be useful regarding other human and animal diseases and zoonosis when there is a lack of accurate information in the literature about the serological response in naturally infected subjects. This study shows how capture-recapture methods may help to estimate the sensitivity of an imperfect surveillance system and to valorize surveillance data. The sensitivity of the surveillance system of equine viral arteritis is relatively high and supports its relevance to prevent the disease spreading.

Keywords: Bayesian inference, capture-recapture, epidemiology, equine viral arteritis, infectious disease, seroconversion, surveillance

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Authors: Giulia Colonna, Jocelyn Hoye, Bart de Laat, Gelsina Stanley, Jose Key, Alaaddin Ibrahimy, Sule Tinaz, Evan D. Morris

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Parkinson’s disease (PD) is the second most common neurodegenerative disease and affects approximately 1% of the world’s population. Increasing evidence suggests that aerobic physical exercise can be beneficial in mitigating both motor and non-motor symptoms of the disease. In a recent pilot study of the role of exercise on PD, we sought to confirm exercise intensity by monitoring heart rate (HR). For this purpose, we asked participants to wear a chest strap heart rate monitor (Polar Electro Oy, Kempele). The device sometimes proved uncomfortable. Looking forward to larger clinical trials, it would be convenient to employ a more comfortable and user friendly device. The Fitbit Charge 4 (Fitbit Inc) is a potentially comfortable, user-friendly solution since it is a wrist-worn heart rate monitor. Polar H10 has been used in large trials, and for our purposes, we treated it as the gold standard for the beat-to-beat period (R-R interval) assessment. In previous literature, it has been shown that Fitbit Charge 4 has comparable accuracy to Polar H10 in healthy subjects. It has yet to be determined if the Fitbit is as accurate as the Polar H10 in subjects with PD or in clinical populations, generally. Goal: To compare the Fitbit Charge 4 to the Polar H10 for monitoring HR in PD subjects engaging in an intensive exercise program. Methods: A total of 596 exercise sessions from 11 subjects (6 males) were collected simultaneously by both devices. Subjects with early-stage PD (Hoehn & Yahr <=2) were enrolled in a 6 months exercise training program designed for PD patients. Subjects participated in 3 one-hour exercise sessions per week. They wore both Fitbit and Polar H10 during each session. Sessions included rest, warm-up, intensive exercise, and cool-down periods. We calculated the bias in the HR via Fitbit under rest (5min) and intensive exercise (20min) by comparing the mean HR during each of the periods to the respective means measured by the Polar (HRFitbit – HRPolar). We also measured the sensitivity and specificity of Fitbit for detecting HRs that exceed the threshold for intensive exercise, defined as 70% of an individual’s theoretical maximum HR. Different types of correlation between the two devices were investigated. Results: The mean bias was 1.68 bpm at rest and 6.29 bpm during high intensity exercise, with an overestimation by Fitbit in both conditions. The mean bias of Fitbit across both rest and intensive exercise periods was 3.98 bpm. The sensitivity of the device in identifying high intensity exercise sessions was 97.14 %. The correlation between the two devices was non-linear, suggesting a saturation tendency of Fitbit to saturate at high values of HR. Conclusion: The performance of Fitbit Charge 4 is comparable to Polar H10 for assessing exercise intensity in a cohort of PD subjects. The device should be considered a reasonable replacement for the more cumbersome chest strap technology in future similar studies of clinical populations.

Keywords: fitbit, heart rate measurements, parkinson’s disease, wrist-wearable devices

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Authors: Mikko Salminen, Niklas Ravaja

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Previous studies have shown that emotional intelligence (EI) has an important role in leadership and social interaction. On the other hand, physiological synchronization between two interacting participants has been related to, for example, intensity of the interaction, and interestingly also to empathy. It is suggested that the amount of covariation in physiological signals between the two interacting persons would also be related to how the discussion is perceived subjectively. To study the interrelations between physiological synchronization, emotional intelligence, and subjective perception of the interaction, performance review discussions between real manager – subordinate dyads were studied using psychophysiological measurements and self-reports. The participants consisted of 40 managers, of which 24 were female, and 78 of their subordinates, of which 45 were female. The participants worked in various fields, for example banking, education, and engineering. The managers had a normal performance review discussion with two subordinates, except two managers who, due to scheduling issues, had discussion with only one subordinate. The managers were on average 44.5 years old, and the subordinates on average 45.5 years old. Written consent, in accordance with the Declaration of Helsinki, was obtained from all the participants. After the discussion, the participants filled a questionnaire assessing their emotions during the discussion. This included a self-assessment manikin (SAM) scale for the emotional valence during the discussion, with a 9-point graphical scale representing a manikin whose facial expressions ranged from smiling and happy to frowning and unhappy. In addition, the managers filled EI360, a 37-item self-report trait emotional intelligence questionnaire. The psychophysiological activity of the participants was recorded using two Varioport-B portable recording devices. Cardiac activity (ECG, electrocardiogram) was measured with two electrodes placed on the torso. Inter-beat interval (IBI, time between two successive heart beats) was calculated from the ECG signals. The facial muscle activation (EMG, electromyography) was recorded on three sites of the left side of the face: zygomaticus major (cheek muscle), orbicularis oculi (periocular muscle), and corrugator supercilii (frowning muscle). The facial-EMG signals were rectified and smoothed, and cross-coherences were calculated between members of each dyad, for all the three EMG signals, for the baseline and discussion periods. The values were natural-log transformed to normalize the distributions. Higher cross-coherence during the discussion between the manager’s and the subordinate’s zygomatic muscles was related to more positive valence self-reported emotions, F(1; 66,137) = 7,051; p=0,01. Thus, synchronized cheek muscle activation, either due to synchronous smiling or talking, was related to more positive perception of the discussion. In addition, higher IBI synchronization between the manager and the subordinate during the discussion was related to the manager’s higher self-reported emotional intelligence, F(1; 27,981)=4,58; p=0,041. That is, the EI was related to synchronous cardiac activity and possibly to similar physiological arousal levels. The results imply that the psychophysiological synchronization could be a potentially useful index in the study of social interaction and a valuable tool in the coaching of leadership skills in organizational contexts.

Keywords: emotional intelligence, leadership, psychophysiology, social interaction, synchronization

Procedia PDF Downloads 300

Authors: Lenuta Kloetzer, Alexandra C. Blaga, Dan Cascaval, Alexandra Tucaliuc, Anca I. Galaction

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Rosmarinic acid, an ester of caffeic acid and 3-(3,4-dihydroxyphenyl) lactic acid, is considered a valuable compound for the pharmaceutical and cosmetic industries due to its antimicrobial, antioxidant, antiviral, anti-allergic, and anti-inflammatory effects. It can be obtained by extraction from vegetable or animal materials, by chemical synthesis and biosynthesis. Indifferent of the method used for rosmarinic acid production, the separation and purification process implies high amount of raw materials and laborious stages leading to high cost for and limitations of the separation technology. This study focused on separation of rosmarinic acid by synergic reactive extraction with a mixture of two extractants, one acidic (acid di-(2ethylhexyl) phosphoric acid, D2EHPA) and one with basic character (Amberlite LA-2). The studies were performed in experimental equipment consisting of an extraction column where the phases’ mixing was made by mean of a perforated disk with 45 mm diameter and 20% free section, maintained at the initial contact interface between the aqueous and organic phases. The vibrations had a frequency of 50 s⁻¹ and 5 mm amplitude. The extraction was carried out in two solvents with different dielectric constants (n-heptane and dichloromethane) in which the extractants mixture of varying concentration was dissolved. The pH-value of initial aqueous solution was varied between 1 and 7. The efficiency of the studied extraction systems was quantified by distribution and synergic coefficients. For calculating these parameters, the rosmarinic acid concentration in the initial aqueous solution and in the raffinate have been measured by HPLC. The influences of extractants concentrations and solvent polarity on the efficiency of rosmarinic acid separation by synergic extraction with a mixture of Amberlite LA-2 and D2EHPA have been analyzed. In the reactive extraction system with a constant concentration of Amberlite LA-2 in the organic phase, the increase of D2EHPA concentration leads to decrease of the synergic coefficient. This is because the increase of D2EHPA concentration prevents the formation of amine adducts and, consequently, affects the hydrophobicity of the interfacial complex with rosmarinic acid. For these reasons, the diminution of synergic coefficient is more important for dichloromethane. By maintaining a constant value of D2EHPA concentration and increasing the concentration of Amberlite LA-2, the synergic coefficient could become higher than 1, its highest values being reached for n-heptane. Depending on the solvent polarity and D2EHPA amount in the solvent phase, the synergic effect is observed for Amberlite LA-2 concentrations over 20 g/l dissolved in n-heptane. Thus, by increasing the concentration of D2EHPA from 5 to 40 g/l, the minimum concentration value of Amberlite LA-2 corresponding to synergism increases from 20 to 40 g/l for the solvent with lower polarity, namely, n-heptane, while there is no synergic effect recorded for dichloromethane. By analysing the influences of the main factors (organic phase polarity, extractant concentration in the mixture) on the efficiency of synergic extraction of rosmarinic acid, the most important synergic effect was found to correspond to the extractants mixture containing 5 g/l D2EHPA and 40 g/l Amberlite LA-2 dissolved in n-heptane.

Keywords: Amberlite LA-2, di(2-ethylhexyl) phosphoric acid, rosmarinic acid, synergic effect

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Authors: Benjamin O. Ehigie, Aderemi Alarape, Nyitor Shenge, Sylvester A. Okhakhume, Timileyin Fashola, Fiyinfunjah Dosumu

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Organisational citizenship behaviour (OCB) is a construct in industrial and organisational behaviour that explains a person's voluntary commitment within an organisation, which is outside the scope of his or her contractual tasks. To attain organisational effectiveness the human factor of production is inevitable, hence the importance of employee behaviour. While the concept of organisational citizenship behavior is mostly discussed in the context of the workplace, it is reasoned that the idea could be reflective in relation to national commitment. Many developing countries in Africa, including Nigeria, suffer economic hardship today not necessarily due to poor resources but bad management of the resources. The mangers of their economies are not committed to the tenets of economic growth but engrossed in fraud, corruption, bribery, and other economic vices. It is this backdrop that necessitated the development and validation of the Ibadan-Nigeria Citizenship Behaviour (I-NCB) Scale. The study adopted a cross-sectional survey (online) research design, using 2404 postgraduate students in the Premier University of the country, with 99.2% being Nigerians and 0.8% non-Nigerians. Gender composition was 1,439 (60%) males and 965 (40%) females, 1201 (50%) were employed while 1203 50% unemployed, 74.2% of the employed were in public paid employment, 19.5% in private sector, and 6.3% were self-employed. Through literature review, 78 items were generated. Using 10 lecturers and 21 students, content and face validity were established respectively. Data collected were subjected to reliability and factor analytic statistics at p < .05 level of significance. Results of the content and face validity at 80% level of item acceptance resulted to 60 items; this was further reduced to 50 after item-total correlation using r=.30 criterion. Divergent validity of r= -.28 and convergent validity of r= .44 were obtained by correlating the I-NCB scale with standardized Counterproductive work behaviour (CWB) scale and Organisational Citizenship Behaviour (OCB) scale among the workers. The reliability coefficients obtained were; Cronbach alpha of internal consistency (α = 0.941) and split-half reliability of r = 0.728. Factor analyses of the I-NCB scale with principal component and varimax rotation yielded five factors when Eigenvalue above 1 were extracted. The factors which accounted for larger proportions of the total variance were given factor names as; Altruistic, Attachment, Affective, Civic responsibility and Allegiance. As much as there are vast journals on citizenship behaviour in organisations, there exists no standardized tool to measure citizenship behaviour of a country. The Ibadan-Nigeria Citizenship Behaviour (I-NCB) scale was consequently developed. The scale could be used to select personnel into political positions and senior administrative positions among career workers in Nigeria, with the aim of determining national commitment to service.

Keywords: counterproductive work behaviour, CWB, Nigeria Citizenship Behaviour, organisational citizenship behaviour, OCB, Ibadan

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Authors: Maria Debora Braga, Luigi Riso, Maria Grazia Zoia

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Risk-based approaches to asset allocation are portfolio construction methods that do not rely on the input of expected returns for the asset classes in the investment universe and only use risk information. They include the Minimum Variance Strategy (MV strategy), the traditional (volatility-based) Risk Parity Strategy (SRP strategy), the Most Diversified Portfolio Strategy (MDP strategy) and, for many, the Equally Weighted Strategy (EW strategy). All the mentioned approaches were based on portfolio volatility as a reference risk measure but in 2023, the Kurtosis-based Risk Parity strategy (KRP strategy) and the Minimum Kurtosis strategy (MK strategy) were introduced. Understandably, they used the fourth root of the portfolio-fourth moment as a proxy for portfolio kurtosis to work with a homogeneous function of degree one. This paper contributes mainly theoretically and methodologically to the framework of risk-based asset allocation approaches with two steps forward. First, a new and more flexible objective function considering a linear combination (with positive coefficients that sum to one) of portfolio volatility and portfolio kurtosis is used to alternatively serve a risk minimization goal or a homogeneous risk distribution goal. Hence, the new basic idea consists in extending the achievement of typical risk-based approaches’ goals to a combined risk measure. To give the rationale behind operating with such a risk measure, it is worth remembering that volatility and kurtosis are expressions of uncertainty, to be read as dispersion of returns around the mean and that both preserve adherence to a symmetric framework and consideration for the entire returns distribution as well, but also that they differ from each other in that the former captures the “normal” / “ordinary” dispersion of returns, while the latter is able to catch the huge dispersion. Therefore, the combined risk metric that uses two individual metrics focused on the same phenomena but differently sensitive to its intensity allows the asset manager to express, in the context of an objective function by varying the “relevance coefficient” associated with the individual metrics, alternatively, a wide set of plausible investment goals for the portfolio construction process while serving investors differently concerned with tail risk and traditional risk. Since this is the first study that also implements risk-based approaches using a combined risk measure, it becomes of fundamental importance to investigate the portfolio effects triggered by this innovation. The paper also offers a second contribution. Until the recent advent of the MK strategy and the KRP strategy, efforts to highlight interesting properties of risk-based approaches were inevitably directed towards the traditional MV strategy and SRP strategy. Previous literature established an increasing order in terms of portfolio volatility, starting from the MV strategy, through the SRP strategy, arriving at the EQ strategy and provided the mathematical proof for the “equalization effect” concerning marginal risks when the MV strategy is considered, and concerning risk contributions when the SRP strategy is considered. Regarding the validity of similar conclusions when referring to the MK strategy and KRP strategy, the development of a theoretical demonstration is still pending. This paper fills this gap.

Keywords: risk parity, portfolio kurtosis, risk diversification, asset allocation

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