Search results for: distributed randomized algorithms

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

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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: Mohammed Sabbah, Prospero Di Pierro, Raffaele Porta

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Protein-based edible films and coatings have attracted an increasing interest in recent years since they might be used to protect pharmaceuticals or improve the shelf life of different food products. Among them, several plant proteins represent an abundant, inexpensive and renewable raw source. These natural biopolymers are used as film forming agents, being able to form intermolecular linkages by various interactions. However, without the addition of a plasticizing agent, many biomaterials are brittle and, consequently, very difficult to be manipulated. Plasticizers are generally small and non-volatile organic additives used to increase film extensibility and reduce its crystallinity, brittleness and water vapor permeability. Plasticizers normally act by decreasing the intermolecular forces along the polymer chains, thus reducing the relative number of polymer-polymer contacts, producing a decrease in cohesion and tensile strength and thereby increasing film flexibility allowing its deformation without rupture. The most commonly studied plasticizers are polyols, like glycerol (GLY) and some mono or oligosaccharides. In particular, GLY not only increases film extensibility but also migrates inside the film network often causing the loss of desirable mechanical properties of the material. Therefore, replacing GLY with a different plasticizer might help to improve film characteristics allowing potential industrial applications. To improve film properties, it seemed of interest to test as plasticizers some cationic small molecules like polyamines (PAs). Putrescine, spermidine (SPD), and spermine are PAs widely distributed in nature and of particular interest for their biological activities that may have some beneficial health effects. Since PAs contains amino instead of hydroxyl functional groups, they are able to trigger ionic interactions with negatively charged proteins. Bitter vetch (Vicia ervilia; BV) is an ancient grain legume crop, originated in the Mediterranean region, which can be found today in many countries around the world. This annual Vicia genus shows several favorable features, being their seeds a cheap and abundant protein source. The main objectives of this study were to investigate the effect of different concentrations of SPD on the mechanical and permeability properties of films prepared with native or heat denatured BV proteins in the presence of different concentrations of SPD and/or GLY. Therefore, a BV seed protein concentrate (BVPC), containing about 77% proteins, was used to prepare film forming solutions (FFSs), whereas GLY and SPD were added as film plasticizers, either singly or in combination, at various concentrations. Since a primary plasticizer is generally defined as a molecule that when added to a material makes it softer, more flexible and easier to be processed, our findings lead to consider SPD as a possible primary plasticizer of protein-based films. In fact, the addition of millimolar concentrations of SPD to BVPC FFS allowed obtaining handleable biomaterials with improved properties. Moreover, SPD can be also considered as a secondary plasticizer, namely an 'extender', because of its ability even to enhance the plasticizing performance of GLY. In conclusion, our studies indicate that innovative edible protein-based films and coatings can be obtained by using PAs as new plasticizers.

Keywords: edible films, glycerol, plasticizers, polyamines, spermidine

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Shawn Baker-Garcia, Janna O. Schaeffer

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As the global and national communities and governments strive to address ongoing and evolving threats to humanity and pervasive or emerging “shared” global priorities on environmental, economic, political, and security, it is more urgent than ever before to understand each other, communicate effectively with one another, identify models of cooperation that yield improved, mutually reinforcing outcomes across and within cultures. It is within the backdrop of this reality that the presentation examines whether cultural training as we have approached it in recent decades is sufficiently meeting our current needs and what changes may be applied to foster better and more productive and sustainable intercultural interactions. Domestic and global relations face multiple challenges to peaceable cooperation. The last two years, in particular, have been defined by a travel-restricted COVID-19 pandemic yielding increased intercultural interactions over virtual platforms, polarized politics dividing nations and regions, and the commensurate rise in weaponized social and traditional media communication. These societal and cultural fissures are noticeably challenging our collective and individual abilities to constructively interact both at home and abroad. It is within this pressure cooker environment that the authors believe it is time to reexamine existing and broadly accepted inter- and cross- cultural training approaches and concepts to determine their level of effectiveness in setting conditions for optimal human understanding and relationships both in the national and international context. In order to better understand the amount and the type of intercultural training practitioners professionally engaging in international partnership building have received throughout their careers and its perceived effectiveness, a survey was designed and distributed to US and international professionals presently engaged in the fields of diplomacy, military, academia, and international business. The survey questions were deigned to address the two primary research questions investigators posed in this exploratory study. Research questions aimed to examine practitioners’ view of the role and effectiveness of current and traditional cultural training and education as a means to fostering improved communication, interactions, understanding, and cooperation among inter, cross, or multi-cultural communities or efforts.Responses were then collected and analyzed for themes present in the participants’ reflections. In their responses, the practitioners identified the areas of improvement and desired outcomes in regards to intercultural training and awareness raising curricular approaches. They also raised issues directly and indirectly pertaining to the role of foreign language proficiency in intercultural interactions and a need for a solid grasp on cultural and regional issues (regional expertise) to facilitate such an interaction. Respondents indicated knowledge, skills, abilities, and capabilities that the participants were not trained on but learned through ad hoc personal and professional intercultural interactions, which they found most valuable and wished they had acquired prior to the intercultural experience.

Keywords: cultural training, improved communication, intercultural competence, international cooperation

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Authors: Alexandra Sargent, Sarah Ferris, Ioannis Theofanous

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The Abbott RealTime High Risk HPV test (RealTime HPV) is one of five assays clinically validated and approved by the English NHS Cervical Screening Programme (CSP) for HPV triage of low grade dyskaryosis and test-of-cure of treated Cervical Intraepithelial Neoplasia. The assay is a highly automated multiplex real-time PCR test for detecting 14 high risk (hr) HPV types, with simultaneous differentiation of HPV 16 and HPV 18 versus non-HPV 16/18 hrHPV. An endogenous internal control ensures sample cellularity, controls extraction efficiency and PCR inhibition. The original cervical specimen collected in SurePath (SP) liquid-based cytology (LBC) medium (BD Diagnostics) and the SP post-gradient cell pellets (SPG) after cytological processing are both CE marked for testing with the RealTime HPV test. During the 2011 NHSCSP validation of new tests only the original aliquot of SP LBC medium was investigated. Residual sample volume left after cytology slide preparation is low and may not always have sufficient volume for repeat HPV testing or for testing of other biomarkers that may be implemented in testing algorithms in the future. The SPG samples, however, have sufficient volumes to carry out additional testing and necessary laboratory validation procedures. This study investigates the correlation of RealTime HPV results of cervical specimens collected in SP LBC medium from women with low grade cytological abnormalities observed with matched pairs of original SP LBC medium and SP post-gradient cell pellets (SPG) after cytology processing. Matched pairs of SP and SPG samples from 750 women with borderline (N = 392) and mild (N = 351) cytology were available for this study. Both specimen types were processed and parallel tested for the presence of hrHPV with RealTime HPV according to the manufacturer´s instructions. HrHPV detection rates and concordance between test results from matched SP and SPGCP pairs were calculated. A total of 743 matched pairs with valid test results on both sample types were available for analysis. An overall-agreement of hrHPV test results of 97.5% (k: 0.95) was found with matched SP/SPG pairs and slightly lower concordance (96.9%; k: 0.94) was observed on 392 pairs from women with borderline cytology compared to 351 pairs from women with mild cytology (98.0%; k: 0.95). Partial typing results were highly concordant in matched SP/SPG pairs for HPV 16 (99.1%), HPV 18 (99.7%) and non-HPV16/18 hrHPV (97.0%), respectively. 19 matched pairs were found with discrepant results: 9 from women with borderline cytology and 4 from women with mild cytology were negative on SPG and positive on SP; 3 from women with borderline cytology and 3 from women with mild cytology were negative on SP and positive on SPG. Excellent correlation of hrHPV DNA test results was found between matched pairs of SP original fluid and post-gradient cell pellets from women with low grade cytological abnormalities tested with the Abbott RealTime High-Risk HPV assay, demonstrating robust performance of the test with both specimen types and reassuring the utility of the assay for cytology triage with both specimen types.

Keywords: Abbott realtime test, HPV, SurePath liquid based cytology, surepath post-gradient cell pellet

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Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

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A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

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Authors: Giorgi Chichinadze, David Shengelia, Tamara Tsutsunava, Nikoloz Maisuradze, Giorgi Beridze

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The Jalovchat gabbro intrusive is exposed on the northern and southern slopes of Main Range zone of the Greater Caucasus, on an area about 25km2. It is intruded in Precambrian crystalline schists and amphibolites intensively metamorphose them along the contact zone. The intrusive is represented by hornblende-bearing gabbro, gabbro-norites and norites including thin vein bodies of gabbro-pegmatites, anorthosites and micro-gabbros. Especially should be noted the veins of gabbro-pegmatites with the gigantic (up to 0.5m) hornblende crystals. From this point of view, the Jalovchat gabbroid intrusive is particularly interesting and by its unusual composition has no analog in the Caucasus overall. The comprehensive petrologic and geochemical study of the intrusive was carried out by the authors. The results of investigations are following. Amphiboles correspond to magnesiohastingsite and magnesiohornblende. In hastingsite and hornblende as a result of isovalent isomorphism of Fe2+ by Mg, content of the latter has been increased. By AMF and Na20+K diagrams the intrusive rocks correspond to tholeiitic basalts or to basalts close to it by composition. According to ACM-AMF double diagram the samples distributed in the fields of MORB and alkali cumulates. In TiO2/FeO+Fe2O3, Zr/Y-Zr and Ti-Cr/Ni diagrams and Ti-Cr-Y triangular diagram samples are arranged in the fields of island-arc and mid-oceanic basalts or along the trends reflecting mid-oceanic ridges or island arcs. K2O/TiO2 diagram shows that these rocks belong to normal and enriched MORB type. According to Th/Nb/Y ratio, the Jalovchat intrusive composition corresponds to depleted mantle, but by Sm/Y-Ce/Sm - to the MORB area. Th/Y and Nb/Y ratios coincide with the MORB composition, Th/Yb-Ta/Yb and La/Nb-Ti ratios correspond to N MORB, and Rb/Y and N/Y - to the lower crust formations. Exceptional are Ce/Pb-Ce and Nb/Th-Nb diagrams, showing the area of primitive mantle. Spidergrams are characterized by almost horizontal trend, weakly expressed Eu minimums and by a slight depletion of light REE. Similar are characteristic of typical tholeiit basalts. In comparison to MORB spidergrams, they are characterized by depletion of light REE. Their correlation to the spidergrams of Jalovchat intrusive proves that they are more depleted. The above cited points to the gradual depletion of mantle with the light REE in geological time. The RE and REE diagrams reveal unexpected regularity. In particular, petro-geochemical characteristics of Jalovchat gabbroid intrusive predominantly correspond to MORB, that usually is an anomalous phenomenon, since in ‘ophiolitic’ section magmatic formations represented mainly by gigantic prismatic hornblende-bearing gabbro and gabbro-pegmatite are not indicated. On the basis of petro-mineralogical and petro-geochemical data analysis, the authors consider that the Jalovchat intrusive belongs to the subduction geodynamic type. In the depleted mantle rich in water the MORB rock system has subducted, where the favorable conditions for crystallization of hornblende and especially for its gigantic crystals occurred. It is considered that the Jalovchat intrusive was formed in deep horizons of the Earth’s crust as a result of crystallization of water-bearing Bajocian basalt magma.

Keywords: The Greater Caucasus, gabbro-pegmatite, hornblende-bearing gabbro, petrogenesis

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Authors: Avi Shrivastava

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Our world continues to grapple with a lot of social issues. Economic growth and scientific advancements have not completely eradicated poverty, homelessness, discrimination and bias, gender inequality, health issues, mental illness, addiction, and other social issues. So, how do we improve the human condition in a world driven by advanced technology? The answer is simple: we will have to leverage technology to address some of the most important social challenges of the day. AI, or artificial intelligence, has emerged as a critical tool in the battle against issues that deprive marginalized and disadvantaged groups of the right to enjoy benefits that a society offers. Social work professionals can transform their lives by harnessing it. The lack of reliable data is one of the reasons why a lot of social work projects fail. Social work professionals continue to rely on expensive and time-consuming primary data collection methods, such as observation, surveys, questionnaires, and interviews, instead of tapping into AI-based technology to generate useful, real-time data and necessary insights. By leveraging AI’s data-mining ability, we can gain a deeper understanding of how to solve complex social problems and change lives of people. We can do the right work for the right people and at the right time. For example, AI can enable social work professionals to focus their humanitarian efforts on some of the world’s poorest regions, where there is extreme poverty. An interdisciplinary team of Stanford scientists, Marshall Burke, Stefano Ermon, David Lobell, Michael Xie, and Neal Jean, used AI to spot global poverty zones – identifying such zones is a key step in the fight against poverty. The scientists combined daytime and nighttime satellite imagery with machine learning algorithms to predict poverty in Nigeria, Uganda, Tanzania, Rwanda, and Malawi. In an article published by Stanford News, Stanford researchers use dark of night and machine learning, Ermon explained that they provided the machine-learning system, an application of AI, with the high-resolution satellite images and asked it to predict poverty in the African region. “The system essentially learned how to solve the problem by comparing those two sets of images [daytime and nighttime].” This is one example of how AI can be used by social work professionals to reach regions that need their aid the most. It can also help identify sources of inequality and conflict, which could reduce inequalities, according to Nature’s study, titled The role of artificial intelligence in achieving the Sustainable Development Goals, published in 2020. The report also notes that AI can help achieve 79 percent of the United Nation’s (UN) Sustainable Development Goals (SDG). AI is impacting our everyday lives in multiple amazing ways, yet some people do not know much about it. If someone is not familiar with this technology, they may be reluctant to use it to solve social issues. So, before we talk more about the use of AI to accomplish social work objectives, let’s put the spotlight on how AI and social work can complement each other.

Keywords: social work, artificial intelligence, AI based social work, machine learning, technology

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Authors: J. Desbrieres, M. Popa, C. Peptu, S. Bacaita

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Because of their favorable properties (non-toxicity, biodegradability, mucoadhesivity etc.), polysaccharides were studied as biomaterials and as pharmaceutical excipients in drug formulations. These formulations may be produced in a wide variety of forms including hydrogels, hydrogel based particles (or capsules), films etc. In these formulations, the polysaccharide based materials are able to provide local delivery of loaded therapeutic agents but their delivery can be rapid and not easily time-controllable due to, particularly, the burst effect. This leads to a loss in drug efficiency and lifetime. To overcome the consequences of burst effect, systems involving liposomes incorporated into polysaccharide hydrogels may appear as a promising material in tissue engineering, regenerative medicine and drug loading systems. Liposomes are spherical self-closed structures, composed of curved lipid bilayers, which enclose part of the surrounding solvent into their structure. The simplicity of production, their biocompatibility, the size and similar composition of cells, the possibility of size adjustment for specific applications, the ability of hydrophilic or/and hydrophobic drug loading make them a revolutionary tool in nanomedicine and biomedical domain. Drug delivery systems were developed as hydrogels containing chitosan or carboxymethylcellulose (CMC) as polysaccharides and gelatin (GEL) as polypeptide, and phosphatidylcholine or phosphatidylcholine/cholesterol liposomes able to accurately control this delivery, without any burst effect. Hydrogels based on CMC were covalently crosslinked using glutaraldehyde, whereas chitosan based hydrogels were double crosslinked (ionically using sodium tripolyphosphate or sodium sulphate and covalently using glutaraldehyde). It has been proven that the liposome integrity is highly protected during the crosslinking procedure for the formation of the film network. Calcein was used as model active matter for delivery experiments. Multi-Lamellar vesicles (MLV) and Small Uni-Lamellar Vesicles (SUV) were prepared and compared. The liposomes are well distributed throughout the whole area of the film, and the vesicle distribution is equivalent (for both types of liposomes evaluated) on the film surface as well as deeper (100 microns) in the film matrix. An obvious decrease of the burst effect was observed in presence of liposomes as well as a uniform increase of calcein release that continues even at large time scales. Liposomes act as an extra barrier for calcein release. Systems containing MLVs release higher amounts of calcein compared to systems containing SUVs, although these liposomes are more stable in the matrix and diffuse with difficulty. This difference comes from the higher quantity of calcein present within the MLV in relation with their size. Modeling of release kinetics curves was performed and the release of hydrophilic drugs may be described by a multi-scale mechanism characterized by four distinct phases, each of them being characterized by a different kinetics model (Higuchi equation, Korsmeyer-Peppas model etc.). Knowledge of such models will be a very interesting tool for designing new formulations for tissue engineering, regenerative medicine and drug delivery systems.

Keywords: controlled and delayed release, hydrogels, liposomes, polysaccharides

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Authors: Domenico Carmelo Mongelli

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The context is that of great uncertainty in the 27 countries belonging to the European Union which has adopted an epochal measure: the elimination of internal combustion engines for the traction of road vehicles starting from 2035 with complete replacement with electric vehicles. If on the one hand there is great concern at various levels for the unpreparedness for this change, on the other the Scientific Community is not preparing accurate studies on the problem, as the scientific literature deals with single aspects of the issue, moreover addressing the issue at the level of individual countries, losing sight of the global implications of the issue for the entire EU. The aim of the research is to fill these gaps: the technological, plant engineering, environmental, economic and employment aspects of the energy transition in question are addressed and connected to each other, comparing the current situation with the different scenarios that could exist in 2035 and in the following years until total disposal of the internal combustion engine vehicle fleet for the entire EU. The methodologies adopted by the research consist in the analysis of the entire life cycle of electric vehicles and batteries, through the use of specific databases, and in the dynamic simulation, using specific calculation codes, of the application of the results of this analysis to the entire EU electric vehicle fleet from 2035 onwards. Energy balance sheets will be drawn up (to evaluate the net energy saved), plant balance sheets (to determine the surplus demand for power and electrical energy required and the sizing of new plants from renewable sources to cover electricity needs), economic balance sheets (to determine the investment costs for this transition, the savings during the operation phase and the payback times of the initial investments), the environmental balances (with the different energy mix scenarios in anticipation of 2035, the reductions in CO2eq and the environmental effects are determined resulting from the increase in the production of lithium for batteries), the employment balances (it is estimated how many jobs will be lost and recovered in the reconversion of the automotive industry, related industries and in the refining, distribution and sale of petroleum products and how many will be products for technological innovation, the increase in demand for electricity, the construction and management of street electric columns). New algorithms for forecast optimization are developed, tested and validated. Compared to other published material, the research adds an overall picture of the energy transition, capturing the advantages and disadvantages of the different aspects, evaluating the entities and improvement solutions in an organic overall picture of the topic. The results achieved allow us to identify the strengths and weaknesses of the energy transition, to determine the possible solutions to mitigate these weaknesses and to simulate and then evaluate their effects, establishing the most suitable solutions to make this transition feasible.

Keywords: engines, Europe, mobility, transition

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Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Arsyam Mawardi, Sony Suhandono, Azzania Fibriani, Fifi Fitriyah Masduki

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Malaria is an infectious disease caused by Plasmodium sp. This disease has a high prevalence in Indonesia, especially in Jayapura. The vaccine that is currently being developed has not been effective in overcoming malaria. This is due to the high polymorphism in the Plasmodium genome especially in areas that encode Plasmodium surface proteins. Merozoite Surface Protein 1 (MSP1) Plasmodium falciparum is a surface protein that plays a role in the invasion process in human erythrocytes through the interaction of Glycophorin A protein receptors and sialic acid in erythrocytes with Reticulocyte Binding Proteins (RBP) and Duffy Adhesion Protein (DAP) ligands in merozoites. MSP1 can be targeted to be a specific antigen and predicted epitope area which will be used for the development of diagnostic and malaria vaccine therapy. MSP1 consists of 17 blocks, each block is dimorphic, and has been marked as the K1 and MAD20 alleles. Exceptions only in block 2, because it has 3 alleles, among others K1, MAD20 and RO33. These polymorphisms cause allelic variations and implicate the severity of patients infected P. falciparum. In addition, polymorphism of MSP1 in Jayapura isolates has not been reported so it is interesting to be further identified and projected as a specific antigen. Therefore, in this study, we analyzed the allele polymorphism as well as detected the MSP1 epitope antigen candidate on block 2 P. falciparum. Clinical samples of selected malaria patients followed the consecutive sampling method, examining malaria parasites with blood preparations on glass objects observed through a microscope. Plasmodium DNA was isolated from the blood of malarial positive patients. The block 2 MSP1 gene was amplified using PCR method and cloned using the pGEM-T easy vector then transformed to TOP'10 E.coli. Positive colonies selection was performed with blue-white screening. The existence of target DNA was confirmed by PCR colonies and DNA sequencing methods. Furthermore, DNA sequence analysis was done through alignment and formation of a phylogenetic tree using MEGA 6 software and insilico analysis using IEDB software to predict epitope candidate for P. falciparum. A total of 15 patient samples have been isolated from Plasmodium DNA. PCR amplification results show the target gene size about ± 1049 bp. The results of MSP1 nucleotide alignment analysis reveal that block 2 MSP1 genes derived from the sample of malarial patients were distributed in four different allele family groups, K1 (7), MAD20 (1), RO33 (0) and MSP1_Jayapura (10) alleles. The most commonly appears of the detected allele is MSP1_Jayapura single allele. There was no significant association between sex variables, age, the density of parasitemia and alel variation (Mann Whitney, U > 0.05), while symptomatic signs have a significant difference as a trigger of detectable allele variation (U < 0.05). In this research, insilico study shows that there is a new epitope antigen candidate from the MSP1_Jayapura allele and it is predicted to be recognized by B cells with 17 amino acid lengths in the amino acid sequence 187 to 203.

Keywords: epitope candidate, insilico analysis, MSP1 P. falciparum, polymorphism

Procedia PDF Downloads 158

Authors: Rizwana Tabassum

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Introductive Statement: Delay in budget releases is often cited as one of the biggest bottlenecks to smooth and efficient service delivery. While budget release from the ministry of finance to the line ministries has been expedited by simplifying the procedure, budget distribution within the line ministries remains one of the major causes of slow budget utilization. While the budget preparation is a bottom-up process where all DDOs submit their proposals to their controlling officers (such as Upazila Civil Surgeon sends it to Director General Health), who consolidate the budget proposals in iBAS++ budget preparation module, the approved budget is not disaggregated by all DDOs. Instead, it is left to the discretion of the controlling officers to distribute the approved budget to their sub-ordinate offices over the course of the year. Though there are some need-based criteria/formulae to distribute the approved budget among DDOs in some sectors, there is little evidence that these criteria are actually used. This means that majority of the DDOs don’t know their yearly allocations upfront to enable yearly planning of activities and expenditures. This delays the implementation of critical activities and the payment to the suppliers of goods and services and sometimes leads to undocumented arrears to suppliers for essential goods/services. In addition, social sector budgets are fragmented because of the vertical programs and externally financed interventions that pose several management challenges at the level of the budget holders and frontline service providers. Slow procurement processes further delay the provision of necessary goods and services. For example, it takes an average of 15–18 months for drugs to reach the Upazila Health Complex and below, while it should not take more than 9 months in procuring and distributing these. Aim of the Study: This paper aims to investigate the budget distribution practices of an emerging economy, Bangladesh. The paper identifies challenges of timely distribution and ways to deal with problems as well. Methodology: The study draws conclusions on the basis of document analysis which is a branch of the qualitative research method. Major Findings: Upon approval of the National Budget, the Ministry of Finance is required to distribute the budget to budget holders at the department level; however, budget is distributed to drawing and disbursing officers much later. Conclusions: Timely and predictable budget releases assist completion of development schemes on time and on budget, with sufficient recurrent resources for effective operation. ADP implementation is usually very low at the beginning of the fiscal year and expedited dramatically during the last few months, leading to inefficient use of resources. The timely budget release will resolve this issue and deliver economic benefits faster, better, and more reliably. This will also give the project directors/DDOs the freedom to think and plan the budget execution in a predictable manner, thereby ensuring value for money by reducing time overrun and expediting the completion of capital investments, and improving infrastructure utilization through timely payment of recurrent costs.

Keywords: budget distribution, challenges, digitization, emerging economy, service delivery

Procedia PDF Downloads 57

Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

Procedia PDF Downloads 46

Authors: G. Magalhães-Mota, C. Magro, S. Sério, E. Mateus, P. A. Ribeiro, A. B. Ribeiro, M. Raposo

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Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol], belonging to the class of Pharmaceuticals and Personal Care Products (PPCPs), is a broad-spectrum antimicrobial agent and bactericide. Because of its antimicrobial efficacy, it is widely used in personal health and skin care products, such as soaps, detergents, hand cleansers, cosmetics, toothpastes, etc. However, it has been considered to disrupt the endocrine system, for instance, thyroid hormone homeostasis and possibly the reproductive system. Considering the widespread use of triclosan, it is expected that environmental and food safety problems regarding triclosan will increase dramatically. Triclosan has been found in river water samples in both North America and Europe and is likely widely distributed wherever triclosan-containing products are used. Although significant amounts are removed in sewage plants, considerable quantities remain in the sewage effluent, initiating widespread environmental contamination. Triclosan undergoes bioconversion to methyl-triclosan, which has been demonstrated to bio accumulate in fish. In addition, triclosan has been found in human urine samples from persons with no known industrial exposure and in significant amounts in samples of mother's milk, demonstrating its presence in humans. The action of sunlight in river water is known to turn triclosan into dioxin derivatives and raises the possibility of pharmacological dangers not envisioned when the compound was originally utilized. The aim of this work is to detect low concentrations of triclosan in an aqueous complex matrix through the use of a sensor array system, following the electronic tongue concept based on impedance spectroscopy. To achieve this goal, we selected the appropriate molecules to the sensor so that there is a high affinity for triclosan and whose sensitivity ensures the detection of concentrations of at least nano-molar. Thin films of organic molecules and oxides have been produced by the layer-by-layer (LbL) technique and sputtered onto glass solid supports already covered by gold interdigitated electrodes. By submerging the films in complex aqueous solutions with different concentrations of triclosan, resistance and capacitance values were obtained at different frequencies. The preliminary results showed that an array of interdigitated electrodes sensor coated or uncoated with different LbL and films, can be used to detect TCS traces in aqueous solutions in a wide range concentration, from 10⁻¹² to 10⁻⁶ M. The PCA method was applied to the measured data, in order to differentiate the solutions with different concentrations of TCS. Moreover, was also possible to trace a curve, the plot of the logarithm of resistance versus the logarithm of concentration, which allowed us to fit the plotted data points with a decreasing straight line with a slope of 0.022 ± 0.006 which corresponds to the best sensitivity of our sensor. To find the sensor resolution near of the smallest concentration (Cs) used, 1pM, the minimum measured value which can be measured with resolution is 0.006, so the ∆logC =0.006/0.022=0.273, and, therefore, C-Cs~0.9 pM. This leads to a sensor resolution of 0.9 pM for the smallest concentration used, 1pM. This attained detection limit is lower than the values obtained in the literature.

Keywords: triclosan, layer-by-layer, impedance spectroscopy, electronic tongue

Procedia PDF Downloads 227

Authors: Sajmina Khatun, Monika Pebam, Aravind Kumar Rengan

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Photothermal therapy, a subset of nanomedicine, takes advantage of light-absorbing agents to generate localized heat, selectively eradicating cancer cells. This innovative approach minimizes damage to healthy tissues and offers a promising avenue for targeted cancer treatment. Unlike conventional therapies, photothermal therapy harnesses the power of light to combat malignancies precisely and effectively, showcasing its potential to revolutionize cancer treatment paradigms. The combined strengths of nanomedicine and photothermal therapy signify a transformative shift toward more effective, targeted, and tolerable cancer treatments in the medical landscape. Utilizing natural products becomes instrumental in formulating diverse bioactive medications owing to their various pharmacological properties attributed to the existence of phenolic structures, triterpenoids, and similar compounds. Hyptis suaveolens, commonly known as pignut, stands as an aromatic herb within the Lamiaceae family and represents a valuable therapeutic plant. Flourishing in swamps and alongside tropical and subtropical roadsides, these noxious weeds impede the development of adjacent plants. Hyptis suaveolens ranks among the most globally distributed alien invasive species. The present investigation revealed that a versatile, biodegradable liposome nanosystem (HIL NPs), incorporating bioactive molecules from Hyptis suaveolens, exhibits effective bioavailability to cancer cells, enabling tumor ablation upon near-infrared (NIR) laser exposure. The components within the nanosystem, specifically the bioactive molecules from Hyptis, function as anticancer agents, aiding in the photothermal ablation of highly metastatic lung cancer cells. Despite being a prolific weed impeding neighboring plant growth, Hyptis suaveolens showcases therapeutic benefits through its bioactive compounds. The obtained HIL NPs, characterized as a photothermally active liposome nanosystem, demonstrate a pronounced fluorescence absorption peak in the NIR range and achieve a high photothermal conversion efficiency under NIR laser irradiation. Transmission electron microscopy (TEM) and particle size analysis reveal that HIL NPs possess a spherical shape with a size of 141 ± 30 nm. Moreover, in vitro assessments of HIL NPs against lung cancer cell lines (A549) indicate effective anticancer activity through a combined cytotoxic effect and hyperthermia. Tumor ablation is facilitated by apoptosis induced by the overexpression of ɣ-H2AX, arresting cancer cell proliferation. Consequently, the multifunctional and biodegradable nanosystem (HIL NPs), incorporating bioactive compounds from Hyptis, provides valuable perspectives for developing an innovative therapeutic strategy originating from a challenging weed. This approach holds promise for potential applications in both bioimaging and the combined use of phyto-photothermal therapy for cancer treatment.

Keywords: bioactive liposome, hyptis suaveolens, photothermal therapy, lung cancer

Procedia PDF Downloads 60

Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

Procedia PDF Downloads 267

Authors: Hafsa Memona, Farkhanda Manzoor

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Cockroaches are termed as medically important pests because of their wide distribution in human habitation including houses, hospitals, food industries and kitchens. They may harbor multiple drug resistant pathogenic bacteria and protozoan parasites on their external surfaces, disseminate on human food and cause serious diseases and allergies to human. Hence, they are regarded as mechanical vector in human habitation due to their nocturnal activity and nutritional behavior. Viable eggs and dormant cysts of parasites can hitch a ride on cockroaches. Ova and cysts of parasitic organism may settle into the crevices and cracks between thorax and head. There are so many fissures and clefts and crannies on a cockroach which provide site for these organisms. This study aimed with identifying role of cockroaches in mechanically transmitting and disseminating gastrointestinal parasites in two environmental settings; hospitals and houses in urban area of Lahore. Totally, 250 adult cockroaches were collected from houses and hospitals by sticky traps and food baited traps and screened for parasitic load. All cockroaches were captured during their feeding time in natural habitat. Direct wet smear, 1% lugols iodine and modified acid-fast bacilli staining were used to identify the parasites from the body surfaces of cockroaches. Among human habitation two common species of cockroaches were collected i.e. P. americana and B. germanica. The results showed that 112 (46.8%) cockroaches harbored at least one human intestinal parasite on their body surfaces. The cockroaches from hospital environment harboured more parasites than houses. 47 (33.57%) cockroaches from houses and 65 (59.09%) from hospitals were infected with parasitic organisms. Of these, 76 (67.85%) were parasitic protozoans and 36(32.15%) were pathogenic and non-pathogenic intestinal parasites. P. americana harboured more parasites as compared to B. germanica in both environment. Most common human intestinal parasites found on cockroaches include ova of Ascaris lumbricoides (giant roundworm), Trichuris trichura (whipworm), Anchylostoma deodunalae (hookworm), Enterobius vermicularis (pinworm), Taenia spp. and Strongyloides stercoralis (threadworm). The cysts of protozoans’ parasites including Balantidium coli, Entomoeba hystolitica, C. parvum, Isospora belli, Giardia duodenalis and C. cayetenensis were isolated and identified from cockroaches. Both experimental sites were significantly different in carriage of parasitic load on cockroaches. Difference in the hygienic condition of the environments, including human excrement disposal, variable habitat interacted, indoor and outdoor species, may account for the observed variation in the parasitic carriage rate of cockroaches among different experimental site. Thus a finding of this study is that Cockroaches are uniformly distributed in human habitation and act as a mechanical vector of pathogenic parasites that cause common illness such as diarrhea and bowel disorders. This fact contributes to epidemiological chain therefore control of cockroaches will significantly lessen the prevalence of illness in human. Effective control strategies will reduce the public health burden of the gastro-intestinal parasites in the developing countries.

Keywords: cockroaches, health risks, hospitals, houses, parasites, protozoans, transmission

Procedia PDF Downloads 260

Authors: Sujoy Khan

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There is a rising concern with increasing allergies affecting both adults and children in rural and urban India. Recent report on adults in a densely populated North Indian city showed sensitization rates for house dust mite, parthenium, and cockroach at 60%, 40% and 18.75% that is now comparable to allergy prevalence in cities in the United States. Data from patients residing in the eastern part of India is scarce. A retrospective study (over 2 years) was done on patients with allergic rhinitis and asthma where allergen-specific IgE levels were measured to see the aero-allergen sensitization pattern in a large metropolitan city of East India. Total IgE and allergen-specific IgE levels were measured using ImmunoCAP (Phadia 100, Thermo Fisher Scientific, Sweden) using region-specific aeroallergens: Dermatophagoides pteronyssinus (d1); Dermatophagoides farinae (d2); cockroach (i206); grass pollen mix (gx2) consisted of Cynodon dactylon, Lolium perenne, Phleum pratense, Poa pratensis, Sorghum halepense, Paspalum notatum; tree pollen mix (tx3) consisted of Juniperus sabinoides, Quercus alba, Ulmus americana, Populus deltoides, Prosopis juliflora; food mix 1 (fx1) consisted of Peanut, Hazel nut, Brazil nut, Almond, Coconut; mould mix (mx1) consisted of Penicillium chrysogenum, Cladosporium herbarum, Aspergillus fumigatus, Alternaria alternate; animal dander mix (ex1) consisted of cat, dog, cow and horse dander; and weed mix (wx1) consists of Ambrosia elatior, Artemisia vulgaris, Plantago lanceolata, Chenopodium album, Salsola kali, following manufacturer’s instructions. As the IgE levels were not uniformly distributed, median values were used to represent the data. 92 patients with allergic rhinitis and asthma (united airways disease) were studied over 2 years including 21 children (age < 12 years) who had total IgE and allergen-specific IgE levels measured. The median IgE level was higher in 2016 than in 2015 with 60% of patients (adults and children) being sensitized to house dust mite (dual positivity for Dermatophagoides pteronyssinus and farinae). Of 11 children in 2015, whose total IgE ranged from 16.5 to >5000 kU/L, 36% of children were polysensitized (≥4 allergens), and 55% were sensitized to dust mites. Of 10 children in 2016, total IgE levels ranged from 37.5 to 2628 kU/L, and 20% were polysensitized with 60% sensitized to dust mites. Mould sensitivity was 10% in both of the years in the children studied. A consistent finding was that ragweed sensitization (molecular homology to Parthenium hysterophorus) appeared to be increasing across all age groups, and throughout the year, as reported previously by us where 25% of patients were sensitized. In the study sample overall, sensitizations to dust mite, cockroach, and parthenium were important risks in our patients with moderate to severe asthma that reinforces the importance of controlling indoor exposure to these allergens. Sensitizations to dust mite, cockroach and parthenium allergens are important predictors of asthma morbidity not only among children but also among adults in Eastern India.

Keywords: aAeroallergens, asthma, dust mite, parthenium, rhinitis

Procedia PDF Downloads 172

Authors: Maria Ledinskaya

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This paper is part case study and part literature review. It seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation by looking at their practical application on a recent conservation project at the Sainsbury Centre for Visual Arts. The author outlines the advantages of leaner and more agile conservation practices in today’s faster, less certain, and more budget-conscious museum climate where traditional project structures are no longer as relevant or effective. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre by private collectors Michael and Joyce Morris. It was a medium-sized conservation project of moderate complexity, planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown conditions and materials, unconfirmed budget. The project was later impacted by the COVID-19 pandemic, introducing indeterminate lockdowns, budget cuts, staff changes, and the need to accommodate social distancing and remote communications. The author, then a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. The paper examines the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, including the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics. Although not intentionally planned as such, the Morris Project had a number of Agile and Lean features which were instrumental to its successful delivery. These key features are identified as distributed decision-making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point in favour of a hybrid model, which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: agile project management, conservation, hybrid project management, lean project management, waterfall project management

Procedia PDF Downloads 47

Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

Procedia PDF Downloads 74

Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Bhupendra Kumar Poudel, Sadhana Amatya, Tirtha Maiya Shrestha, Bharatmani Pokhrel, Mohan Prasad Amatya

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Background: H. salicifolia is a dense, branched, multipurpose, deciduous, nitrogen fixing, thorny willow-like small to moderate tree, restricted to the Himalaya. Among the two species of Nepal (Hippophae salicifolia and H. tibetana), it has been traditionally used as food additive, anticancer (bark), and treating toothache, tooth inflammation (anti-inflammatory) and radiation injury; while people of Western Nepal have largely undermined its veiled treasure by using it for fuel, wood and soil stabilization only. Therefore, the main objective of this study was to explore biological properties (analgesic, antidiabetic, cytotoxic and anti-inflammatory properties of this plant. Methodology: The transverse section of leaves and stems were viewed under microscope. Extracts obtained from soxhlation subjected to tests for phytochemical and biological studies. Rats (used to study antidiabetic and anti-inflammatory properties) and mice (used to study analgesic, CNS depressant, muscle relaxant and locomotor properties) were assumed to be normally distributed; then ANOVA and post hoc tukey test was used to find significance. The data obtained were analyzed by SPSS 17 and Excel 2007. Results and Conclusion: Pharmacognostical analysis revealed the presence of long stellate trichomes, double layered vascular bundle 5-6 in number and double layered compact sclerenchyma. The preliminary phytochemical screening of the extracts was found to exhibit the positive reaction tests for glycoside, steroid, tannin, flavonoid, saponin, coumarin and reducing sugar. The brine shrimp lethality bioassay tested in 1000, 100 and 10 ppm revealed cytotoxic activity inherent in methanol, water, chloroform and ethyl acetate extracts with LC50 (μg/ml) values of 61.42, 99.77, 292.72 and 277.84 respectively. The cytotoxic activity may be due to presence of tannins in the constituents. Antimicrobial screening of the extracts by cup diffusion method using Staphylococcus aereus, Escherichia coli and Pseudomonas aeruginosa against standard antibiotics (oxacillin, gentamycin and amikacin respectively) portrayed no activity against the microorganisms tested. The methanol extract of the stems and leaves showed various pharmacological properties: and antidiabetic, anti-inflammatory, analgesic [chemical writhing method], CNS depressant, muscle relaxant and locomotor activities in a dose-dependent fashion, indicating the possibility of the presence of different constituents in the stems and leaves responsible for these biological activities. All the effects when analyzed by post hoc tukey test were found to be significant at 95% confidence level. The antidiabetic activity was presumed to be due to flavonoids present in extract. Therefore, it can be concluded that this plant’s secondary metabolites possessed strong antidiabetic, anti-inflammatory and cytotoxic activity which could be isolated for further investigation.

Keywords: Hippophae salicifolia, constituents, antidiabetic, inflammatory, brine shrimp

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 47

Authors: Elmira Aliyeva, Dadash Huseynov, Robert Hoogendoorn, Salomon Kroonenberg

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The Kura River is the major water artery in the Southern Caucasus; it is a third river in the Caspian Sea basin in terms of length and size of the catchment area, the second in terms of the water budget, and the first in the volume of sediment load. Understanding of major controls on the Kura fluvial- deltaic system is valuable for efficient management of the highly populated river basin and coastal zone. We have studied grain size of sediments accumulated in the river channels and delta and dated by 210Pb method, astrophotographs, old topographic and geological maps, and archive data. At present time sediments are supplied by the Kura River to the Caspian Sea through three distributary channels oriented north-east, south-east, and south-west. The river is dominated by the suspended load - mud, silt, very fine sand. Coarse sediments are accumulated in the distributaries, levees, point bar, and delta front. The annual suspended sediment budget in the time period 1934-1952 before construction of the Mingechavir water reservoir in 1953 in the Kura River midstream area was 36 mln.t/yr. From 1953 to 1964, the suspended load has dropped to 12 mln.t/yr. After regulation of the Kura River discharge the volume of suspended load transported via north-eastern channel reduced from 35% of the total sediment amount to 4%, and through the main south-eastern channel increased from 65% to 96% with further fall to 56% due to creation of new south-western channel in 1964. Between 1967-1976 the annual sediment budget of the Kura River reached 22,5 mln. t/yr. From 1977 to 1986, the sediment load carried by the Kura River dropped to 17,6 mln.t/yr. The historical data show that between 1860 and 1907, during relatively stable Caspian Sea level two channels - N and SE, appear to have distributed an equal amount of sediments as seen from the bilateral geometry of the delta. In the time period 1907-1929, two new channels - E and NE, appeared. The growth of three delta lobes - N, NE, and SE, and rapid progradation of the delta has occurred on the background of the Caspian Sea level rise as a result of very high sediment supply. Since 1929 the Caspian Sea level decline was followed by the progradation of the delta occurring along the SE channel. The eastern and northern channels have been silted up. The slow rate of progradation at its initial stage was caused by the artificial reduction in the sediment budget. However, the continuous sea-level fall has brought to this river bed gradient increase, high erosional rate, increase in the sediment supply, and more rapid progradation. During the subsequent sea-level rise after 1977 accompanied by the decrease in the sediment budget, the southern part of the delta has turned into a complex of small, shallow channels oriented to the south. The data demonstrate that behaviour of the Kura fluvial – deltaic system and variations in the sediment budget besides anthropogenic regulation are strongly governed by the Caspian Sea level very rapid changes.

Keywords: anthropogenic control on sediment budget, Caspian sea-level variations, Kura river sediment load, morphology of the Kura river delta, sedimentation in the Kura river delta

Procedia PDF Downloads 129

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 334

Authors: B. Neethu, Diptesh Das

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The present study investigates the performance of a semi-active controller using magneto-rheological dampers (MR) for seismic response reduction of a multi-span bridge. The application of structural control to the structures during earthquake excitation involves numerous challenges such as proper formulation and selection of the control strategy, mathematical modeling of the system, uncertainty in system parameters and noisy measurements. These problems, however, need to be tackled in order to design and develop controllers which will efficiently perform in such complex systems. A control algorithm, which can accommodate un-certainty and imprecision compared to all the other algorithms mentioned so far, due to its inherent robustness and ability to cope with the parameter uncertainties and imprecisions, is the sliding mode algorithm. A sliding mode control algorithm is adopted in the present study due to its inherent stability and distinguished robustness to system parameter variation and external disturbances. In general a semi-active control scheme using an MR damper requires two nested controllers: (i) an overall system controller, which derives the control force required to be applied to the structure and (ii) an MR damper voltage controller which determines the voltage required to be supplied to the damper in order to generate the desired control force. In the present study a sliding mode algorithm is used to determine the desired optimal force. The function of the voltage controller is to command the damper to produce the desired force. The clipped optimal algorithm is used to find the command voltage supplied to the MR damper which is regulated by a semi active control law based on sliding mode algorithm. The main objective of the study is to propose a robust semi active control which can effectively control the responses of the bridge under real earthquake ground motions. Lumped mass model of the bridge is developed and time history analysis is carried out by solving the governing equations of motion in the state space form. The effectiveness of MR dampers is studied by analytical simulations by subjecting the bridge to real earthquake records. In this regard, it may also be noted that the performance of controllers depends, to a great extent, on the characteristics of the input ground motions. Therefore, in order to study the robustness of the controller in the present study, the performance of the controllers have been investigated for fourteen different earthquake ground motion records. The earthquakes are chosen in such a way that all possible characteristic variations can be accommodated. Out of these fourteen earthquakes, seven are near-field and seven are far-field. Also, these earthquakes are divided into different frequency contents, viz, low-frequency, medium-frequency, and high-frequency earthquakes. The responses of the controlled bridge are compared with the responses of the corresponding uncontrolled bridge (i.e., the bridge without any control devices). The results of the numerical study show that the sliding mode based semi-active control strategy can substantially reduce the seismic responses of the bridge showing a stable and robust performance for all the earthquakes.

Keywords: bridge, semi active control, sliding mode control, MR damper

Procedia PDF Downloads 108

Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

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Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

Procedia PDF Downloads 56

Authors: Welder A. Baldassini, Jon J. Ramsey, Marcos R. Chiaratti, Amália S. Chaves, Renata H. Branco, Sarah F. M. Bonilha, Dante P. D. Lanna

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With increased production costs there is a need for animals that are more efficient in terms of meat production. In this context, the role of mitochondrial DNA (mtDNA) on physiological processes in liver, muscle and adipose tissues may account for inter-animal variation in energy expenditures and heat production. The purpose this study was to investigate if the amounts of mtDNA in liver, muscle and adipose tissue (subcutaneous and visceral depots) of Nellore bulls are associated with residual feed intake (RFI) and estimated heat production (EHP). Eighteen animals were individually fed in a feedlot for 90 days. RFI values were obtained by regression of dry matter intake (DMI) in relation to average daily gain (ADG) and mid-test metabolic body weight (BW). The animals were classified into low (more efficient) and high (less efficient) RFI groups. The bulls were then randomly distributed in individual pens where they were given excess feed twice daily to result in 5 to 10% orts for 90 d with diet containing 15% crude protein and 2.7 Mcal ME/kg DM. The heart rate (HR) of bulls was monitored for 4 consecutive days and used for calculation of EHP. Electrodes were fitted to bulls with stretch belts (POLAR RS400; Kempele, Finland). To calculate oxygen pulse (O2P), oxygen consumption was obtained using a facemask connected to the gas analyzer (EXHALYZER, ECOMedics, Zurich, Switzerland) and HR were simultaneously measured for 15 minutes period. Daily oxygen (O2) consumption was calculated by multiplying the volume of O2 per beat by total daily beats. EHP was calculated multiplying O2P by the average HR obtained during the 4 days, assuming 4.89 kcal/L of O2 to measure daily EHP that was expressed in kilocalories/day/kilogram metabolic BW (kcal/day/kg BW0.75). Blood samples were collected between days 45 and 90th after the beginning of the trial period in order to measure the concentration of hemoglobin and hematocrit. The bulls were slaughtered in an experimental slaughter house in accordance with current guidelines. Immediately after slaughter, a section of liver, a portion of longissimus thoracis (LT) muscle, plus a portion of subcutaneous fat (surrounding LT muscle) and portions of visceral fat (kidney, pelvis and inguinal fat) were collected. Samples of liver, muscle and adipose tissues were used to quantify mtDNA copy number per cell. The number of mtDNA copies was determined by normalization of mtDNA amount against a single copy nuclear gene (B2M). Mean of EHP, hemoglobin and hematocrit of high and low RFI bulls were compared using two-sample t-tests. Additionally, the one-way ANOVA was used to compare mtDNA quantification considering the mains effects of RFI groups. We found lower EHP (83.047 vs. 97.590 kcal/day/kgBW0.75; P < 0.10), hemoglobin concentration (13.533 vs. 15.108 g/dL; P < 0.10) and hematocrit percentage (39.3 vs. 43.6 %; P < 0.05) in low compared to high RFI bulls, respectively, which may be useful traits to identify efficient animals. However, no differences were observed between the mtDNA content in liver, muscle and adipose tissue of Nellore bulls with high and low RFI.

Keywords: bioenergetics, Bos indicus, feed efficiency, mitochondria

Procedia PDF Downloads 221