Search results for: artificial boundary condition

Authors: Daniel Osieko Okach, Joseph Otieno Ondier, Gerhard Rambold, John Tenhunen, Bernd Huwe, Dennis Otieno

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Increased human activities such as grazing, logging, and agriculture alongside unpredictable rainfall patterns have been detrimental to the ecosystem service delivery, therefore compromising its productivity potential. This study aimed at simulating the impact of drought (50%) and enhanced rainfall (150%) on the future herbaceous CO2 uptake, biomass production and soil C:N dynamics in a humid savanna ecosystem influenced by livestock grazing. Rainfall pattern was predicted using manipulation experiments set up to reduce (50%) and increase (150%) ambient (100%) rainfall amounts in grazed and non-grazed plots. The impact of manipulated rainfall regime on herbaceous CO2 fluxes, biomass production and soil C:N dynamics was measured against volumetric soil water content (VWC) logged every 30 minutes using the 5TE (Decagon Devices Inc., Washington, USA) soil moisture sensors installed (at 20 cm soil depth) in every plots. Herbaceous biomass was estimated using destructive method augmented by standardized photographic imaging. CO2 fluxes were measured using the ecosystem chamber method and the gas analysed using LI-820 gas analyzer (USA). C:N ratio was calculated from the soil carbon and Nitrogen contents (analyzed using EA2400CHNS/O and EA2410 N elemental analyzers respectively) of different plots under study. The patterning of VWC was directly influenced by the rainfall amount with lower VWC observed in the grazed compared to the non-grazed plots. Rainfall variability, grazing and their interaction significantly affected changes in VWC (p < 0.05) and subsequently total biomass and CO2 fluxes. VWC had a strong influence on CO2 fluxes under 50% rainfall reduction in the grazed (r2 = 0.91; p < 0.05) and ambient rainfall in the ungrazed (r2 = 0.77; p < 0.05). The dependence of biomass on VWC across plots was enhanced under grazed (r2 = 0.78 - 0.87; p < 0.05) condition as compared to ungrazed (r2 = 0.44 - 0.85; p < 0.05). The C:N ratio was however not correlated to VWC across plots. This study provides insight on how the predicted trends in humid savanna will respond to changes influenced by rainfall variability and livestock grazing and consequently the sustainable management of such ecosystems.

Keywords: CO2 fluxes, rainfall manipulation, soil properties, sustainability

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Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

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The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, Nutrients removal, saline wastewater, sequencing batch reactor

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Suhaib Radi, Ibrahim Basem Nafadi, Abdullah Ahmed Alsulami, Nawaf Faisal Halabi, Abdulrhman Abdullah Alsubhi, Sami Wesam Maghrabi, Waleed Saad Alshehri

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Background: Kidney stones greatly affect individuals. The range of these effects regarding multiple kidney stone factors (size, presence of obstruction, and modality of treatment) in stone formers with and without diabetes has not been well explored in the literature to the best of the author's knowledge. Our goal is to investigate this unexplored correlation between diabetes and kidney stones by conducting a Cohort retrospective study to precisely evaluate the effects of this condition and the existence of complications in adult individuals with diabetes in Saudi Arabia in comparison to a non-diabetic control group. Methodology: This is a retrospective cohort study aiming to evaluate the range of effects of kidney stones in stone formers in a group of adults diagnosed with type 2 diabetes mellitus and adults without diabetes between 2017 and 2019 in Jeddah, Saudi Arabia. An IRB approval has been granted for this study. The data was analyzed using SPSS. The data was collected from the 1st of December 2022 until the 1st of March 2023. Results: A total of 254 individuals diagnosed with kidney stones were included, 127 of whom were adult individuals with type 2 diabetes, and 127 were non-diabetics. Our study shows that the individuals affected with diabetes were more likely to have larger kidney stones in comparison to individuals without diabetes (13.12 mm vs. 10.53 mm, p-value = 0.03). Moreover, individuals with hypertension and dyslipidemia also had significantly larger stones. On the other hand, no significant difference was found in the presence of obstruction and modality of treatment between the two groups. Conclusion: This study done in Saudi Arabia found that individuals with kidney stones who concurrently had diabetes formed larger kidney stones, and they were also found to have other comorbidities such as HTN, dyslipidemia, obesity, and renal disease. The significance of these findings could assist in the future of primary and secondary prevention of renal stones.

Keywords: kidney stone, type 2 DM, metabolic syndrome, lithotripsy

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Authors: Francisco Fernandez de Castro

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The Conditional Cash Transfer (CCT) model gives monetary transfers to beneficiary families on the condition that they take specific education and health actions. According to the economic rationale of CCTs the poor need incentives to invest in their human capital because they are trapped by a lack of information and misleading beliefs. If left to their own decision, the poor will not be able to choose what is in their best interests. The basic assumption of the CCT model is that the poor need incentives to take care of their own education and health-nutrition. Due to the incentives (income cash transfers and conditionalities), beneficiary families are supposed to attend doctor visits and health talks. Children would stay in the school. These incentivized behaviors would produce outcomes such as better health and higher level of education, which in turn will reduce poverty. Based on a grounded theory approach to conduct a two-year period of qualitative data collection in northern Mexico, this study shows that this explanation is incomplete. In addition to the information failure and inadequate beliefs, there are structural barriers in everyday life of households that make health-nutrition and education investments difficult. In-depth interviews and observation work showed that the program takes for granted local conditions in which beneficiary families should fulfill their co-responsibilities. Data challenged the program’s assumptions and unveiled local obstacles not contemplated in the program’s design. These findings have policy and research implications for the CCT agenda. They bring elements for late programming due to the gap between the CCT strategy as envisioned by policy designers, and the program that beneficiary families experience on the ground. As for research consequences, these findings suggest new avenues for scholarly work regarding the causal mechanisms and social processes explaining CCT outcomes.

Keywords: conditional cash transfers, incentives, poverty, structural barriers

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Authors: S. V. Ukwungwu, A. J. Abbas, G. G. Nasr

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The increasing high price of natural gas and oil with attendant increase in energy demand on world markets in recent years has stimulated interest in recovering residual oil saturation across the globe. In order to meet the energy security, efforts have been made in developing new technologies of enhancing the recovery of oil and gas, utilizing techniques like CO2 flooding, water injection, hydraulic fracturing, surfactant flooding etc. Surfactant flooding however optimizes production but poses risk to the environment due to their toxic nature. Amongst proven records that have utilized other type of bacterial in producing biosurfactants for enhancing oil recovery, this research uses a technique to combine biosurfactants that will achieve a scale of EOR through lowering interfacial tension/contact angle. In this study, three biosurfactants were produced from three Bacillus species from freeze dried cultures using sucrose 3 % (w/v) as their carbon source. Two of these produced biosurfactants were screened with the TEMCO Pendant Drop Image Analysis for reduction in IFT and contact angle. Interfacial tension was greatly reduced from 56.95 mN.m-1 to 1.41 mN.m-1 when biosurfactants in cell-free culture (Bacillus licheniformis) were used compared to 4. 83mN.m-1 cell-free culture of Bacillus subtilis. As a result, cell-free culture of (Bacillus licheniformis) changes the wettability of the biosurfactant treatment for contact angle measurement to more water-wet as the angle decreased from 130.75o to 65.17o. The influence of microbial treatment on crushed rock samples was also observed by qualitative wettability experiments. Treated samples with biosurfactants remained in the aqueous phase, indicating a water-wet system. These results could prove that biosurfactants can effectively change the chemistry of the wetting conditions against diverse surfaces, providing a desirable condition for efficient oil transport in this way serving as a mechanism for EOR. The environmental friendly effect of biosurfactants applications for industrial purposes play important advantages over chemically synthesized surfactants, with various possible structures, low toxicity, eco-friendly and biodegradability.

Keywords: bacillus, biosurfactant, enhanced oil recovery, residual oil, wettability

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Authors: Laura Bickel

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This paper aims to investigate to what extent Merleau-Ponty’s philosophy of body memory serves as a viable resource for the enactive approach to cognitive science and its first-person experience-based research on ‘recurrent depressive disorder’ coded F33 in ICD-10. In pursuit of this goal, the analysis begins by revisiting the neuroreductive paradigm. This paradigm serves biological psychiatry to explain the condition of vital contact in terms of underlying neurophysiological mechanisms. It is demonstrated that the neuroreductive model cannot sufficiently account for the depressed person’s episodical withdrawal in causal terms. The analysis of the irregular loss of vital resonance requires integrating the body as the subject of experience and its phenomenological time. Then, it is shown that the enactive approach to depression as disordered sense-making is a promising alternative. The enactive model of perception implies that living beings do not register pre-existing meaning ‘out there’ but unfold ‘sense’ in their action-oriented response to the world. For the enactive approach, Husserl’s passive synthesis of inner time consciousness is fundamental for what becomes perceptually present for action. It seems intuitive to bring together the enactive approach to depression with the long-standing view in phenomenological psychopathology that explains the loss of vital contact by appealing to the disruption of the temporal structure of consciousness. However, this paper argues that the disruption of the temporal structure is not justified conceptually. Instead, one may integrate Merleau-Ponty’s concept of the past as the unconscious into the enactive approach to depression. From this perspective, the living being’s experiential and biological past inserts itself in the form of habit and bodily skills and ensures action-oriented responses to the environment. Finally, it is concluded that the depressed person’s withdrawal indicates the impairment of this application process. The person suffering from F33 cannot actualize sedimented meaning to respond to the valences and tasks of a given situation.

Keywords: depression, enactivism, neuroreductionsim, phenomenology, temporality

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Authors: Daniel Aberdam

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Haploinsufficiency of PAX6 in humans is the main cause of congenital aniridia, a rare eye disease characterized by reduced visual acuity. Patients have also progressive disorders including cataract, glaucoma and corneal abnormalities making their condition very challenging to manage. Aniridia-related keratopathy (ARK), caused by a combination of factors including limbal stem-cell deficiency, impaired healing response, abnormal differentiation, and infiltration of conjunctival cells onto the corneal surface, affects up to 95% of patients. It usually begins in the first decade of life resulting in recurrent corneal erosions, sub-epithelial fibrosis with corneal decompensation and opacification. Unfortunately, current treatment options for aniridia patients are currently limited. Although animal models partially recapitulate this disease, there is no in vitro cellular model of AKT needed for drug/therapeutic tools screening and validation. We used genome editing (CRISPR/Cas9 technology) to introduce a nonsense mutation found in patients into one allele of the PAX6 gene into limbal stem cells. Resulting mutated clones, expressing half of the amount of PAX6 protein and thus representative of haploinsufficiency were further characterized. Sequencing analysis showed that no off-target mutations were induced. The mutated cells displayed reduced cell proliferation and cell migration but enhanced cell adhesion. Known PAX6 targets expression was also reduced. Remarkably, addition of soluble recombinant PAX6 protein into the culture medium was sufficient to activate endogenous PAX6 gene and, as a consequence, rescue the phenotype. It strongly suggests that our in vitro model recapitulates well the epithelial defect and becomes a powerful tool to identify drugs that could rescue the corneal defect in patients. Furthermore, we demonstrate that the homeotic transcription factor Pax6 is able to be uptake naturally by recipient cells to function into the nucleus.

Keywords: Pax6, crispr/cas9, limbal stem cells, aniridia, gene therapy

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Authors: Abul Hashem

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The experiment was conducted to find out the effect of different levels of Moringa oleifiera leaf extract and synthetic antioxidant (Beta Hydroxyl Anisole) on fresh and preserved beef meatballs. For this purpose, ground beef samples were divided into five treatment groups. They are treated as control, synthetic antioxidant, 0.1%, 0.2% and 0.3% Moringa oleifera leaf extract as T1, T2, T3, T4 and T5, respectively. Five kinds of meatballs were made and biscuit crushed and egg albumin was mixed with beef meatballs and cooking was practiced properly. Proximate analysis, sensory tests (color, flavor, tenderness, juiciness, overall acceptability), cooking loss, pH value, free fatty acids (FFA), thiobarbituric acid values (TBARS), peroxide value(POV) and microbiological examination were determined in order to evaluate the effect of Moringa oleifiera leaf extract as natural antioxidant & antimicrobial activities in comparing to BHA (Beta Hydroxyl Anisole) at first day before freezing and for maintaining meatballs qualities on the shelf life of beef meat balls stored for 60 days under frozen condition. Freezing temperature was -20˚C. Days of intervals of experiment were on 0, 15th, 30th, and 60th days. Dry matter content of all the treatment groups differ significantly (p<0.05). On the contrary, DM content increased significantly (p<0.05) with the advancement of different days of intervals. CP content of all the treatments were increased significantly (p<0.05) among the different treatment groups. EE content at different treatment levels differ significantly (p<0.05). Ash content at different treatment levels was also differ significantly (p<0.05). FFA values, TBARS, POV were decreased significantly (p<0.05) at different treatment levels. Color, odor, tenderness, juiciness, overall acceptability, raw PH, cooked pH were increased at different treatment levels significantly (p<0.05). The cooking loss (%) at different treatment levels were differ significantly (p<0.05). TVC (logCFU/g), TCC (logCFU/g) and TYMC (logCFU/g) was decreased significantly (p<0.05) at different treatment levels comparison to control. Considering CP, tenderness, juiciness, overall acceptability, cooking loss, FFA, POV, TBARS and microbial parameters it can be concluded that Moringa oleifera leaf extract at 0.1%, 0.2% and 0.3% can be used instead of 0.1% synthetic antioxidant BHA in beef meatballs.

Keywords: antioxidant, beef meatball, BHA, moringa leaf extract, quality

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Ines Nitoi, Petruta Oancea, Lucian Constantin, Laurentiu Dinu, Maria Crisan, Malina Raileanu, Ionut Cristea

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2,4,6-Trinitrotoluene (TNT) is the most common pollutant identified in wastewater generated from munitions plants where this explosive is synthesized or handled (munitions load, assembly and pack operations). Due to their toxic and suspected carcinogenic characteristics, nitroaromatic compounds like TNT are included on the list of prioritary pollutants and strictly regulated in EU countries. Since their presence in water bodies is risky for human health and aquatic life, development of powerful, modern treatment methods like photocatalysis are needed in order to assures environmental pollution mitigation. The photocatalytic degradation of TNT was carried out at pH=7.8, in aqueous TiO2 based catalyst suspension, under sunlight irradiation. The enhanced photo activity of catalyst in visible domain was assured by 0.5% Fe doping. TNT degradation experiments were performed using a tubular collector type solar photoreactor (26 UV permeable silica glass tubes series connected), plug in a total recycle loops. The influence of substrate concentration and catalyst dose on the pollutant degradation and mineralization by-products (NO2-, NO3-, NH4+) formation efficiencies was studied. In order to compare the experimental results obtained in various working conditions, the pollutant and mineralization by-products measured concentrations have been considered as functions of irradiation time and cumulative photonic energy Qhν incident on the reactor surface (kJ/L). In the tested experimental conditions, at tens mg/L pollutant concentration, increase of 0,5%-TiO2 dose up to 200mg/L leads to the enhancement of CB degradation efficiency. Since, doubling of TNT content has a negative effect on pollutant degradation efficiency, in similar experimental condition, prolonged irradiation time from 360 to 480 min was necessary in order to assures the compliance of treated effluent with limits imposed by EU legislation (TNT ≤ 10µg/L).

Keywords: wastewater treatment, TNT, photocatalysis, environmental engineering

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Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Salvatore Brischetto, Domenico Cesare

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Major improvements in future aircraft and spacecraft could be those dependent on an increasing use of conventional and unconventional multilayered structures embedding composite materials, functionally graded materials, piezoelectric or piezomagnetic materials, and soft foam or honeycomb cores. Layers made of such materials can be combined in different ways to obtain structures that are able to fulfill several structural requirements. The next generation of aircraft and spacecraft will be manufactured as multilayered structures under the action of a combination of two or more physical fields. In multifield problems for multilayered structures, several physical fields (thermal, hygroscopic, electric and magnetic ones) interact each other with different levels of influence and importance. An exact 3D shell model is here proposed for these types of analyses. This model is based on a coupled system including 3D equilibrium equations, 3D Fourier heat conduction equation, 3D Fick diffusion equation and electric and magnetic divergence equations. The set of partial differential equations of second order in z is written using a mixed curvilinear orthogonal reference system valid for spherical and cylindrical shell panels, cylinders and plates. The order of partial differential equations is reduced to the first one thanks to the redoubling of the number of variables. The solution in the thickness z direction is obtained by means of the exponential matrix method and the correct imposition of interlaminar continuity conditions in terms of displacements, transverse stresses, electric and magnetic potentials, temperature, moisture content and transverse normal multifield fluxes. The investigated structures have simply supported sides in order to obtain a closed form solution in the in-plane directions. Moreover, a layerwise approach is proposed which allows a 3D correct description of multilayered anisotropic structures subjected to field loads. Several results will be proposed in tabular and graphical formto evaluate displacements, stresses and strains when mechanical loads, temperature gradients, moisture content gradients, electric potentials and magnetic potentials are applied at the external surfaces of the structures in steady-state conditions. In the case of inclusions of piezoelectric and piezomagnetic layers in the multilayered structures, so called smart structures are obtained. In this case, a free vibration analysis in open and closed circuit configurations and a static analysis for sensor and actuator applications will be proposed. The proposed results will be useful to better understand the physical and structural behaviour of multilayered advanced composite structures in the case of multifield interactions. Moreover, these analytical results could be used as reference solutions for those scientists interested in the development of 3D and 2D numerical shell/plate models based, for example, on the finite element approach or on the differential quadrature methodology. The correct impositions of boundary geometrical and load conditions, interlaminar continuity conditions and the zigzag behaviour description due to transverse anisotropy will be also discussed and verified.

Keywords: composite structures, 3D shell model, stress analysis, multifield loads, exponential matrix method, layer wise approach

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Authors: Lai Peng, Cristina Pintucci, Dries Seuntjens, José Carvajal-Arroyo, Siegfried Vlaeminck

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Economic incentives drive the implementation of short-cut nitrogen removal processes such as nitritation/denitritation (Nit/DNit) to manage nitrogen in waste streams devoid of biodegradable organic carbon. However, as any biological nitrogen removal process, the potent greenhouse gas nitrous oxide (N2O) could be emitted from Nit/DNit. Challenges remain in understanding the fundamental mechanisms and development of engineered mitigation strategies for N2O production. To provide answers, this work focuses on manure as a model, the biggest wasted nitrogen mass flow through our economies. A sequencing batch reactor (SBR; 4.5 L) was used treating the centrate (centrifuge supernatant; 2.0 ± 0.11 g N/L of ammonium) from an anaerobic digester processing mainly pig manure, supplemented with a co-substrate. Glycerin was used as external carbon source, a by-product of vegetable oil. Out-selection of nitrite oxidizing bacteria (NOB) was targeted using a combination of low dissolved oxygen (DO) levels (down to 0.5 mg O2/L), high temperature (35ºC) and relatively high free ammonia (FA) (initially 10 mg NH3-N/L). After reaching steady state, the process was able to remove 100% of ammonium with minimum nitrite and nitrate in the effluent, at a reasonably high nitrogen loading rate (0.4 g N/L/d). Substantial N2O emissions (over 15% of the nitrogen loading) were observed at the baseline operational condition, which were even increased under nitrite accumulation and a low organic carbon to nitrogen ratio. Yet, higher DO (~2.2 mg O2/L) lowered aerobic N2O emissions and weakened the dependency of N2O on nitrite concentration, suggesting a shift of N2O production pathway at elevated DO levels. Limiting the greenhouse gas emissions (environmental protection) from such a system could be substantially minimized by increasing the external carbon dosage (a cost factor), but also through the implementation of an intermittent aeration and feeding strategy. Promising steps forward have been presented in this abstract, yet at the conference the insights of ongoing experiments will also be shared.

Keywords: mitigation, nitrous oxide, nitritation/denitritation, pig manure

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Authors: Muhammad Naeem, Juho Lee, Jin-Wook Yoo

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In this study, we hypothesized that prolonged gastrointestinal transit at the inflamed colon conferred by a pH-triggered mucoadhesive smart nanoparticulate drug delivery system aids in achieving selective and sustained levels of the drug within the inflamed colon for the treatment of ulcerative colitis. We developed budesonide-loaded pH-sensitive charge-reversal solid lipid nanoparticles (SLNs) using a hot homogenization method. Polyetylenimine (PEI) was used to render SLNs cationic (PEI-SLNs). Eudragit S100 (ES) was coated on PEI-SLNs for pH-trigger charge-reversal SLNs (ES-PEI-SLNs). Therapeutic potential of the prepared SNLs formulation was evaluated in ulcerative colitis in mice. The transmission electron microscopy, zeta size and zeta potential data showed the successful formation of SLNs formulations. SLNs and PEI-SLNs showed burst drug release in acidic pH condition mimicking stomach and early small intestine environment which limiting their application as oral delivery systems. However, ES-PEI-SLNs prevented a burst drug release in acidic pH conditions and showed sustained release at a colonic pH. Most importantly, the surface charge of ES-PEI-SLNs switched from negative to positive in colonic conditions by pH-triggered removal of ES coating and accumulated selectively in inflamed colon. Furthermore, a charge reversal ES-PEI-SLNs showed a superior mitigation of dextran sulfate sodium (DSS)-induced acute colitis in mice as compared to SLNs and PEI-SLNs treated groups. Moreover, histopathological analysis of distal colon sections stained with hematoxylin/eosin and E-cadherin immunostaining revealed attenuated inflammation in an ES-PEI-SLNs-treated group. We also found that ES-PEI-SLNs markedly reduced the myeloperoxidase level and expression of TNF-alpha in colon tissue. Our results suggest that the pH-triggered charge reversal SLNs presented in this study would be a promising approach for ulcerative colitis therapy.

Keywords: solid lipid nanoparticles, stimuli-triggered charge-reversal, ulcerative colitis, methacrylate copolymer, budesonide

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Authors: Chandrakant Gurav, Md Babar, Ajaykumar Asode

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Morphometric analysis is the first stage of any basin analysis. By using these morphometric parameters we give indirect information about the nature and relations of stream with other streams, Geology of the area, groundwater condition and tectonic history of the basin. In the present study, Yelganga, Shivbhadra and Kohilla rivers, tributaries of the Godavari River in Aurangabad district, Maharashtra, India are considered to compare and study their morphometric characters. The linear, areal and relief morphometric aspects of the sub-basins have been assessed and evaluated in GIS environment. For this study, ArcGIS 10.1 software has been used for delineating, digitizing and generating different thematic maps. The Survey of India (SOI) toposheets maps and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) on resolution 30 m downloaded from United States Geological Survey (USGS) have been used for preparation of map and data generation. Geologically, the study area is covered by Central Deccan Volcanic Province (CDVP). It mainly consists of ‘aa’ type of basaltic lava flows of Late (upper) Cretaceous to Early (lower) Eocene age. The total geographical area of Yelganga, Shivbhadra and Kohilla river sub-basins are 185.5 sq. km., 142.6 sq. km and 122.3 sq. km. respectively The stream ordering method as suggested by the Strahler has been employed for present study and found that all the sub-basins are of 5th order streams. The average bifurcation ratio value of the sub-basins is below 5, indicates that there appears to be no strong structural control on drainage development, homogeneous nature of lithology and drainage network is in well-developed stage of erosion. The drainage density of Yelganga, Shivbhadra and Kohilla Sub-basins is 1.79 km/km2, 1.48 km/km2 and 1.89 km/km2 respectively and stream frequency is 1.94 streams/km2, 1.19 streams/km2 and 1.68 streams/km2 respectively, indicating semi-permeable sub-surface. Based on textural ratio values it indicates that the sub-basins have coarse texture. Shape parameters such as form factor ratio, circularity ratio and elongation ratio values shows that all three sub- basins are elongated in shape.

Keywords: GIS, Kohilla, morphometry, Shivbhadra, Yelganga

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Authors: Victor O. Abegunde, Melusi Sibanda

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There is need for a great deal of attention on small-scale agriculture for livelihood and food security because of the expanding global population. Small-scale agriculture has been identified as a major driving force of agricultural and rural development. However, the high dependence of the sector on natural and climatic resources has made small-scale farmers highly vulnerable to the adverse impact of climatic change thereby necessitating the need for embracing practices or concepts that will help absorb shocks from changes in climatic condition. This study examines the strategic position of small-scale farming in South African agriculture and in ensuring food security in the country, the vulnerability of small-scale agriculture to climate change and the potential of the concept of climate-smart agriculture to tackle the challenge of climate change. The study carried out a systematic review of peer-reviewed literature touching small-scale agriculture, climate change, food security and climate-smart agriculture, employing the realist review method. Findings revealed that increased productivity in the small-scale agricultural sector has a great potential of improving the food security of households in South Africa and reducing dependence on food purchase in a context of high food price inflation. Findings, however, also revealed that climate change affects small-scale subsistence farmers in terms of productivity, food security and family income, categorizing the impact on smallholder livelihoods into three major groups; biological processes, environmental and physical processes and impact on health. Analysis of the literature consistently showed that climate-smart agriculture integrates the benefits of adaptation and resilience to climate change, mitigation, and food security. As a result, farming households adopting climate-smart agriculture will be better off than their counterparts who do not. This study concludes that climate-smart agriculture could be a very good bridge linking small-scale agricultural sector and agricultural productivity and development which could bring about the much needed food security.

Keywords: climate change, climate-smart agriculture, food security, small-scale

Procedia PDF Downloads 235

Authors: Xiaoquan Huang, Congcong Li, Tingting Wei, Changcun Bai, Na Liu, Meng Tang

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Silver is often doped on nano-titanium dioxide photocatalysts (Ag-TiO₂) by photodeposition method to improve their utilization of visible-light while increasing the toxicity of TiO₂。 However, it is not known what factors influence this toxicity and how to reduce toxicity while maintaining the maximum catalytic activity. In this study, Ag-TiO₂ photocatalysts were synthesized by the photodeposition method with different silver content (AgC) and photodeposition time (PDT). Characterization and catalytic experiments demonstrated that silver was well assembled on TiO₂ with excellent visible-light catalytic activity, and the size of silver increased with PDT. In vitro, the cell viability of lung epithelial cells A549 and BEAS-2B showed that the higher content and smaller size of silver doping caused higher toxicity. In vivo, Ag-TiO₂ catalysts with lower AgC or larger silver particle size obviously caused less pulmonary pro-inflammatory and pro-fibrosis responses. However, the visible light catalytic activity decreased with the increase in silver size. Therefore, in order to optimize the Ag-TiO₂ photocatalyst with the lowest pulmonary toxicity and highest catalytic performance, response surface methodology (RSM) was further performed to optimize the two independent variables of AgC and PDT. Visible-light catalytic activity was evaluated by the degradation rate of Rhodamine B, the antibacterial property was evaluated by killing log value for Escherichia coli, and cytotoxicity was evaluated by IC50 to BEAS-2B cells. As a result, the RSM model showed that AgC and PDT exhibited an interaction effect on catalytic activity in the quadratic model. AgC was positively correlated with antibacterial activity. Cytotoxicity was proportional to AgC while inversely proportional to PDT. Finally, the optimization values were AgC 3.08 w/w% and PDT 28 min. Under this optimal condition, the relatively high silver proportion ensured the visible-light catalytic and antibacterial activity, while the longer PDT effectively reduced the cytotoxicity. This study is of significance for the safe and efficient application of silver-doped TiO₂ photocatalysts.

Keywords: Ag-doped TiO₂, cytotoxicity, inflammtion, fibrosis, response surface methodology

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Authors: Dong-Gi Lee, Suyeon Cha, Yong-Sun Bahn

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Sterol lipid is essential for cell membrane structure in eukaryotic cells. In mammalian cells, sterol regulatory element binding proteins (SREBPs) act as principal regulators of cellular cholesterol which is essential for proper cell membrane fluidity and structure. SREBP and sterol regulation are related to levels of cellular oxygen because it is a major substrate for sterol synthesis. Upon cellular sterol and oxygen levels are depleted, SREBP is translocated to the Golgi where it undergoes proteolytic cleavage of N terminus, then it travels to the nucleus to play a role as transcription factor. In yeast cells, synthesis of ergosterol is also highly oxygen consumptive, and Sre1 is a transcription factor known to play a central role in adaptation to growth under low oxygen condition and sterol homeostasis in Cryptococcus neoformans. In this study, we observed phenotypes in other strains of Cryptococcus species by constructing hob1Δ and sre1Δ mutants to confirm whether the functions of both genes are conserved in most serotypes. As a result, hob1Δ showed no noticeable phenotype under treatment of antifungal drugs and most environmental stresses in R265 (C. gattii) and XL280 (C. neoformans), suggesting that Hob1 is related to sterol regulation only in H99 (serotype A). On the other hand, the function of Sre1 was found to be conserved in most serotypes. Furthermore, mating experiment of hob1Δ or sre1Δ showed dramatic defects in serotype A (H99) and D (XL280). It revealed that Hob1 and Sre1 related to mating ability in Cryptococcus species, especially cell fusion efficiency. In conclusion, HOB1 and SRE1 play crucial role in regulating sterol-homeostasis and differentiation in C. neoformans, moreover, Hob1 is specific gene in Cryptococcus neoformans. It suggests that Hob1 is considered as potent factor-targeted new safety antifungal drug.

Keywords: cryptococcus neoformans, Hob1, Sre1, sterol regulatory element binding proteins

Procedia PDF Downloads 249

Authors: Bazla Manzoor, Aqsa Yasin

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Pakistan is the country which is progressing by leaps and bounds through agricultural and industrial growth. The main area, which presents the largest income rate through industrial activities, is Faisalabad from the Province of Punjab. Faisalabad’s main occupations include agriculture and industry. As these sectors i.e. agriculture and industry is developing day by day, they are earning much income for the country and generating thousands of job vacancies. On one hand the city, i.e. Faisalabad is on the way of development through industrial growth, while on the other hand this industrial growth is producing a bad impact on the environment. In return, that damaged environment is affecting badly on the people and built environment. This research is chiefly based on one of the above-mentioned factors i.e. adverse environmental impacts on the built structures. Faisalabad is an old city, therefore; it is having many old structures especially from British Era. Many of those structures are still surviving and are functioning as the government, private and public buildings. However, these structures are getting in a poor condition with the passage of time due to bad maintenance and adverse environmental impacts. Bad maintenance is a factor, which can be controlled by financial assistance and management. The factor needs to be seriously considered is the other one i.e. adverse environmental impacts on British Era structures of the city because this factor requires controlled and refined human activities and actions. For this reason, a research was required to conserve the British Era structures of Faisalabad so that these structures can function well. The other reason to conserve them is that these structures are historically important and are the heritage of the city. For doing this research, literature has been reviewed which was present in the libraries of the city. Department of Environment, Town Municipal Administration, Faisalabad Development Authority and Lyallpur Heritage Foundation were visited to collect the existing data available. Various British Era structures were also visited to note down the environmental impacts on them. From all the structures “Clock Tower,” was deeply studied as it is one of the oldest and most important heritage structures of the city because the earlier settlements of the city were planned based on its location by The British Government. The architectural and environmental analyses were done for The Clock Tower. This research study found the deterioration factors of the tower according to which suggestions have been made.

Keywords: lyallpur, heritage, architecture, environment

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Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

Procedia PDF Downloads 51

Authors: Amer Ali, Jessica Cecchinelli, Antonis Charalambous

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Cycling is one of the most environmentally friendly, economic and healthy modes of transport but it needs more efficient cycle infrastructure and more effective safety measures. This paper represents an investigation into the performance and operation of the London Cycle Hire Scheme which started to operate in July 2010 using 5,000 cycles and 315 docking stations and currently has more than 10,000 cycles and over 700 docking stations across London which are available 24/7, 365 days a year. The study, which was conducted during the second half of 2014, consists of two parts; namely, the longitudinal review of the hire scheme between its introduction in 2010 and November 2014, and a field survey in November 2014 in the form of face-face interviews of the users of the cycle scheme to ascertain the existing limitations and difficulties experienced by those users and how it could be improved in terms of capability and safety. The study also includes a correlation between the usage of the cycle scheme and the corresponding weather conditions. The main findings are that on average the number of users (hiring frequency) had increased from just over two millions hires in 2010 to just less than ten millions in 2014. The field survey showed that 80% of the users are satisfied with the performance of the scheme whilst 50% of the users raised concern about the safety level of using the available cycle routes and infrastructure. The study also revealed that a high percentage of the cycle trips were relatively short (less than 30 minutes). Although the weather condition had some effect on cycling, the cost of using the cycle scheme and the main events in London had more effect on the number of cycle hires. The key conclusions are that despite the safety concern and the lack of infrastructure for continuous routes there was an encouraging number of people who opted for cycling as a clean, affordable, and healthy mode of transport. There is a need to expand the scheme by providing more cycles and docking stations and to support that by more well-designed and maintained cycle routes. More details about the development of London Cycle Hire Scheme during the last five years, its performance and the key issues revealed by the surveyed users will be reported in the full version of the paper.

Keywords: cycling mode of transport, london cycle hire scheme, safety, environmental and health benefits, user satisfaction

Procedia PDF Downloads 385

Authors: Tanjil Sowgat, Shamim Kobir

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World is now experiencing the consequences of climate change such as increased heat stress due to high temperature rise. In the context of changing climate, this study intends to find out the planning interventions necessary to adapt to the current heat stress in the planned residential areas of Khulna city. To carry out the study Sonadanga residential area (phase I) of Khulna city has been taken as the study site. This residential neighbourhood covering an area of 30 acres has 206 residential plots. The study area comprises twelve access roads, one park, one playfield, one water body and two street furniture’s. This study conducts visual analysis covering green, open space, water body, footpath, drainage and street trees and furniture and questionnaire survey deals with socio-economic, housing tenancy, experience of heat stress and urban design interventions. It finds that the current state that accelerates the heat stress condition such as lack of street trees and inadequate shading, maximum uses are not within ten minutes walking distance, no footpath for the pedestrians and lack of well-maintained street furniture. It proposes that to adapt to the heat stress pedestrian facilities, buffer sidewalk with landscaping, street trees and open spaces, soft scape, natural and man-made water bodies, green roofing could be effective urban design interventions. There are evidences of limited number of heat stress adaptive planned residential area. Since current sub-division planning practice focuses on rigid land use allocation, it partly addresses the climatic concerns through creating open space and street trees. To better respond to adapt to the heat stress, urban design considerations in the context of sub-division practice would bring more benefits.

Keywords: climate change, urban design, adaptation, heat stress, water-logging

Procedia PDF Downloads 293

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 137

Authors: Chukwu Fidelis Ndubuisi, Madufor Michael Ozims, Asogwa Vivian Ndidiamaka, Egenamba Juliet Ngozi, Okonkwo Stephen C., Kamah Chukwudi David

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Deflection of the vertical is a quantity used in reducing geodetic measurements related to geoidal networks to the ellipsoidal plane; and it is essential in Geoid modeling processes. Computing the deflection of the vertical component of a point in a given area is necessary in evaluating the standard errors along north-south and east-west direction. Using combined approach for the determination of deflection of the vertical component provides improved result but labor intensive without appropriate method. Least square method is a method that makes use of redundant observation in modeling a given sets of problem that obeys certain geometric condition. This research work is aimed to computing the deflection of vertical component of Owerri West local government area of Imo State using geometric method as field technique. In this method combination of Global Positioning System on static mode and precise leveling observation were utilized in determination of geodetic coordinate of points established within the study area by GPS observation and the orthometric heights through precise leveling. By least square using Matlab programme; the estimated deflections of vertical component parameters for the common station were -0.0286 and -0.0001 arc seconds for the north-south and east-west components respectively. The associated standard errors of the processed vectors of the network were computed. The computed standard errors of the North-south and East-west components were 5.5911e-005 and 1.4965e-004 arc seconds, respectively. Therefore, including the derived component of deflection of the vertical to the ellipsoidal model will yield high observational accuracy since an ellipsoidal model is not tenable due to its far observational error in the determination of high quality job. It is important to include the determined deflection of the vertical component for Owerri West Local Government in Imo State, Nigeria.

Keywords: deflection of vertical, ellipsoidal height, least square, orthometric height

Procedia PDF Downloads 206

Authors: Sonu Rana, Jyoti Verma, A. K. Gautam

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In most developing countries like India, the majority of the population heavily relies on agriculture for their livelihood. The yield of agriculture is heavily dependent on uncertain weather conditions like a monsoon, soil fertility, availability of irrigation facilities and fertilizers as well as support from the government. The agricultural yield is quite less compared to the effort put in due to inefficient agricultural facilities and obsolete farming practices on the one hand and lack of knowledge on the other hand, and ultimately agricultural community does not prosper. It is therefore essential for the farmers to improve their harvest yield by the acquisition of related data such as soil condition, temperature, humidity, availability of irrigation facilities, availability of, manure, etc., and adopt smart farming techniques using modern agricultural equipment. Nowadays, using IOT technology in agriculture is the best solution to improve the yield with fewer efforts and economic costs. The primary focus of this work-related is IoT technology in the agriculture field. By using IoT all the parameters would be monitored by mounting sensors in an agriculture field held at different places, will collect real-time data, and could be transmitted by a transmitting device like an antenna. To improve the system, IoT will interact with other useful systems like Wireless Sensor Networks. IoT is exploring every aspect, so the radio frequency spectrum is getting crowded due to the increasing demand for wireless applications. Therefore, Federal Communications Commission is reallocating the spectrum for various wireless applications. An antenna is also an integral part of the newly designed IoT devices. The main aim is to propose a new antenna structure used for IoT agricultural applications and compatible with this new unlicensed frequency band. The main focus of this paper is to present work related to these technologies in the agriculture field. This also presented their challenges & benefits. It can help in understanding the job of data by using IoT and correspondence advancements in the horticulture division. This will help to motivate and educate the unskilled farmers to comprehend the best bits of knowledge given by the huge information investigation utilizing smart technology.

Keywords: smart agriculture, IoT, agriculture technology, data analytics, smart technology

Procedia PDF Downloads 111

Authors: Fariba Tadayon, Elmira Hassanlou, Hasan Bagheri, Mostafa Jafarian

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Heavy metals are released into water, plants, soil, and food by natural and human activities. Lead has toxic roles in the human body and may cause serious problems even in low concentrations, since it may have several adverse effects on human. Therefore, determination of lead in different samples is an important procedure in the studies of environmental pollution. In this work, an ultrasonic assisted-ionic liquid based-liquid-liquid microextraction (UA-IL-DLLME) procedure for the determination of lead in zucchini, pomegranate, and lettuce has been established and developed by using flame atomic absorption spectrometer (FAAS). For UA-IL-DLLME procedure, 10 mL of the sample solution containing Pb2+ was adjusted to pH=5 in a glass test tube with a conical bottom; then, 120 μL of 1-Hexyl-3-methylimidazolium hexafluoro phosphate (CMIM)(PF6) was rapidly injected into the sample solution with a microsyringe. After that, the resulting cloudy mixture was treated by ultrasonic for 5 min, then the separation of two phases was obtained by centrifugation for 5 min at 3000 rpm and IL-phase diluted with 1 cc ethanol, and the analytes were determined by FAAS. The effect of different experimental parameters in the extraction step including: ionic liquid volume, sonication time and pH was studied and optimized simultaneously by using Response Surface Methodology (RSM) employing a central composite design (CCD). The optimal conditions were determined to be an ionic liquid volume of 120 μL, sonication time of 5 min, and pH=5. The linear ranges of the calibration curve for the determination by FAAS of lead were 0.1-4 ppm with R2=0.992. Under optimized conditions, the limit of detection (LOD) for lead was 0.062 μg.mL-1, the enrichment factor (EF) was 93, and the relative standard deviation (RSD) for lead was calculated as 2.29%. The levels of lead for pomegranate, zucchini, and lettuce were calculated as 2.88 μg.g-1, 1.54 μg.g-1, 2.18 μg.g-1, respectively. Therefore, this method has been successfully applied for the analysis of the content of lead in different food samples by FAAS.

Keywords: Dispersive liquid-liquid microextraction, Central composite design, Food samples, Flame atomic absorption spectrometry.

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

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The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

Procedia PDF Downloads 141

Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Yang Gon Seo, Chang-Joon Kim, Dae Hyeok Kim

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It is estimated that 1.5 billion tires are produced worldwide each year which will eventually end up as waste tires representing a major potential waste and environmental problem. Pyrolysis has been great interest in alternative treatment processes for waste tires to produce valuable oil, gas and solid products. The oil and gas products may be used directly as a fuel or a chemical feedstock. The solid produced from the pyrolysis of tires ranges typically from 30 to 45 wt% and have high carbon contents of up to 90 wt%. However, most notably the solid have high sulfur contents from 2 to 3 wt% and ash contents from 8 to 15 wt% related to the additive metals. Upgrading tire pyrolysis products to high-value products has concentrated on solid upgrading to higher quality carbon black and to activated carbon. Hydrogen sulfide and ammonia are one of the common malodorous compounds that can be found in emissions from many sewages treatment plants and industrial plants. Therefore, removing these harmful gasses from emissions is of significance in both life and industry because they can cause health problems to human and detrimental effects on the catalysts. In this work, pyrolytic carbon black from waste tires was used to develop adsorbent with good adsorption capacity for removal of hydrogen and ammonia. Pyrolytic carbon blacks were prepared by pyrolysis of waste tire chips ranged from 5 to 20 mm under the nitrogen atmosphere at 600℃ for 1 hour. Pellet-type adsorbents were prepared by a mixture of carbon black, metal oxide and sodium hydroxide or hydrochloric acid, and their adsorption capacities were estimated by using the breakthrough curve of a continuous fixed bed adsorption column at ambient condition. The adsorbent was manufactured with a mixture of carbon black, iron oxide(III), and sodium hydroxide showed the maximum working capacity of hydrogen sulfide. For ammonia, maximum working capacity was obtained by the adsorbent manufactured with a mixture of carbon black, copper oxide(II), and hydrochloric acid.

Keywords: adsorbent, ammonia, pyrolytic carbon black, hydrogen sulfide, metal oxide

Procedia PDF Downloads 254