Search results for: image processing of electrical impedance tomography

Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

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Authors: Temitayo Tosin Alawiye

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Plant disease control is important in maintaining plant vigour, grain quantity, abundance of food, feed, and fibre produced by farmers all over the world. Farmers make use of different methods in controlling these diseases but one of the commonly used method is the use of chemicals. However, the continuous and excessive usages of these agrochemicals pose a danger to the environment, man and wildlife. The more the population growth the more the food security challenge which leads to more pressure on agronomic growth. Agricultural waste also known as green waste are the residues from the growing and processing of raw agricultural products such as fruits, vegetables, rice husk, corn cob, mushroom growth medium waste, coconut husk. They are widely used in land bioremediation, crop production and protection which include disease control. These agricultural wastes help the crop by improving the soil fertility, increase soil organic matter and reduce in many cases incidence and severity of disease. The objective was to review the agricultural waste that has worked effectively against certain soil-borne diseases such as Fusarium oxysporum, Pythiumspp, Rhizoctonia spp so as to help minimize the use of chemicals. Climate change is a major problem of agriculture and vice versa. Climate change and agriculture are interrelated. Change in climatic conditions is already affecting agriculture with effects unevenly distributed across the world. It will increase the risk of food insecurity for some vulnerable groups such as the poor in Sub Saharan Africa. The food security challenge will become more difficult as the world will need to produce more food estimated to feed billions of people in the near future with Africa likely to be the biggest hit. In order to surmount this hurdle, smallholder farmers in Africa must embrace climate-smart agricultural techniques and innovations which includes the use of green waste in agriculture, conservative agriculture, pasture and manure management, mulching, intercropping, etc. Training and retraining of smallholder farmers on the use of green energy to mitigate the effect of climate change should be encouraged. Policy makers, academia, researchers, donors, and farmers should pay more attention to the use of green energy as a way of reducing incidence and severity of soilborne plant diseases to solve looming food security challenges.

Keywords: agricultural waste, climate change, green energy, soil borne plant disease

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Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

Procedia PDF Downloads 273

Authors: Thelma Maria Melo Pinheiro, Guilherme Raposo Diniz Vieira, Sidney Matos da Silva, Leonardo Mendonça de Oliveira Queiroz, Mateus Sousa Pinheiro, Danyllo Wenceslau de Oliveira Lopes

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The present article has the objective to describe the regulatory impact analysis (RIA) of the contracting efficiency of the Brazilian transmission system usage. This contracting is made by users connected to the main transmission network and is used to guide necessary investments to supply the electrical energy demand. Therefore, an inefficient contracting of this energy amount distorts the real need for grid capacity, affecting the sector planning accuracy and resources optimization. In order to provide this efficiency, the Brazilian Electricity Regulatory Agency (ANEEL) homologated the Normative Resolution (NR) No. 666, from July 23th of 2015, which consolidated the procedures for the contracting of transmission system usage and the contracting efficiency verification. Aiming for a more efficient and rational transmission system contracting, the resolution established economic incentives denominated as Inefficiency installment for excess (IIE) and inefficiency installment for over-contracting (IIOC). The first one, IIE, is verified when the contracted demand exceeds the established regulatory limit; it is applied to consumer units, generators, and distribution companies. The second one, IIOC, is verified when the distributors over-contract their demand. Thus, the establishment of the inefficiency installments IIE and IIOC intends to avoid the agent contract less energy than necessary or more than it is needed. Knowing that RIA evaluates a regulatory intervention to verify if its goals were achieved, the results from the application of the above-mentioned normative resolution to the Brazilian transmission sector were analyzed through indicators that were created for this RIA to evaluate the contracting efficiency transmission system usage, using real data from before and after the homologation of the normative resolution in 2015. For this, indicators were used as the efficiency contracting indicator (ECI), excess of demand indicator (EDI), and over-contracting of demand indicator (ODI). The results demonstrated, through the ECI analysis, a decrease of the contracting efficiency, a behaviour that was happening even before the normative resolution of 2015. On the other side, the EDI showed a considerable decrease in the amount of excess for the distributors and a small reduction for the generators; moreover, the ODI notable decreased, which optimizes the usage of the transmission installations. Hence, with the complete evaluation from the data and indicators, it was possible to conclude that IIE is a relevant incentive for a more efficient contracting, indicating to the agents that their contracting values are not adequate to keep their service provisions for their users. The IIOC also has its relevance, to the point that it shows to the distributors that their contracting values are overestimated.

Keywords: contracting, electricity regulation, evaluation, regulatory impact analysis, transmission power system

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Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

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Authors: Kitoholi V. Zhimo

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Unlike the cases of cases of homosexuals, haemophilic and or drug users in USA, France, Africa and other countries, in India the first case of HIV/AIDS was detected in heterosexual female sex workers (FSW) in Chennai in 1986. This image played an important role in understanding HIV/AIDS scenario in the country. Similar to popular and dominant metaphors on HIV/AIDS such as ‘gay plague’, ‘new cancer’, ‘lethal disease’, ‘slim disease’, ‘foreign disease’, ‘junkie disease’, etc. around the world, the social construction of the virus was largely attributed to women in India. It was established that women particularly sex workers are ‘carrier’ and ‘transmitter’ of virus and were categorised as High Risk Groups (HRG’s) alongside homosexuals, transgenders and injecting drug users. Recent literature reveals growing rate of HIV infection among housewives since 1997 which revolutionised public health scenario in India. This means shift from high risk group to general public through ‘bridge population’ encompassing long distance truckers and migrant labours who at the expense of their nature of work and mobility comes in contact with HRG’s and transmit the virus to the general public especially women who are confined to the domestic space. As HIV epidemic expands, married women in monogamous relationship/marriage stand highly susceptible to infection with limited control, right and access over their sexual and reproductive health and planning. In context of Nagaland, a small state in North-eastern part of India HIV/AIDS transmission through injecting drug use dominated the early scene of the epidemic. However, paradigm shift occurred with declining trend of HIV prevalence among injecting drug users (IDU’s) over the past years with the introduction of Opioid Substitution Therapy (OST) and easy access/availability of syringes and injecting needles. Reflection on statistical data reveals that out of 36 states and union territories in India, the position of Nagaland in HIV prevalence among IDU’s has significantly dropped down from 6th position in 2003 to 16th position in 2017. The present face of virus in Nagaland is defined by (hetero) sexual mode of transmission which accounts for about 91% of as reported by Nagaland state AIDS control society (NSACS) in 2016 wherein young and married woman were found to be most affected leading to feminization of HIV/AIDS epidemic in the state. Thus, not only is HIV epidemic feminised but emerged victim to domestic violence which is more often accepted as normal part of heterosexual relationship. In the backdrop of these understanding, the present paper based on ethnographic fieldwork explores the plight, lived experiences and images of HIV+ve women with regard to sexual and reproductive rights against the backdrop of patriarchal system in Nagaland.

Keywords: HIV/AIDS, monogamy, Nagaland, sex worker disease, women

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Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

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Authors: Ravshan A. Ibadov, Sardor Kh. Ibragimov

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Objective. The aim of the study was to optimize the protocol of cardiopulmonary resuscitation (CPR) after cardiovascular surgical interventions. Methods. The experience of CPR conducted on patients after cardiovascular surgical interventions in the Department of Intensive Care and Resuscitation (DIR) of the Republican Specialized Scientific-Practical Medical Center of Surgery named after Academician V. Vakhidov is presented. The key to the new approach is the rapid elimination of reversible causes of cardiac arrest, followed by either defibrillation or electrical cardioversion (depending on the situation) before external heart compression, which may damage sternotomy. Careful use of adrenaline is emphasized due to the potential recurrence of hypertension, and timely resternotomy (within 5 minutes) is performed to ensure optimal cerebral perfusion through direct massage. Out of 32 patients, cardiac arrest in the form of asystole was observed in 16 (50%), with hypoxemia as the cause, while the remaining 16 (50%) experienced ventricular fibrillation caused by arrhythmogenic reactions. The age of the patients ranged from 6 to 60 years. All patients were evaluated before the operation using the ASA and EuroSCORE scales, falling into the moderate-risk group (3-5 points). CPR was conducted for cardiac activity restoration according to the American Heart Association and European Resuscitation Council guidelines (Ley SJ. Standards for Resuscitation After Cardiac Surgery. Critical Care Nurse. 2015;35(2):30-38). The duration of CPR ranged from 8 to 50 minutes. The ARASNE II scale was used to assess the severity of patients' conditions after CPR, and the Glasgow Coma Scale was employed to evaluate patients' consciousness after the restoration of cardiac activity and sedation withdrawal. Results. In all patients, immediate chest compressions of the necessary depth (4-5 cm) at a frequency of 100-120 compressions per minute were initiated upon detection of cardiac arrest. Regardless of the type of cardiac arrest, defibrillation with a manual defibrillator was performed 3-5 minutes later, and adrenaline was administered in doses ranging from 100 to 300 mcg. Persistent ventricular fibrillation was also treated with antiarrhythmic therapy (amiodarone, lidocaine). If necessary, infusion of inotropes and vasopressors was used, and for the prevention of brain edema and the restoration of adequate neurostatus within 1-3 days, sedation, a magnesium-lidocaine mixture, mechanical intranasal cooling of the brain stem, and neuroprotective drugs were employed. A coordinated effort by the resuscitation team and proper role allocation within the team were essential for effective cardiopulmonary resuscitation (CPR). All these measures contributed to the improvement of CPR outcomes. Conclusion. Successful CPR following cardiac surgical interventions involves interdisciplinary collaboration. The application of an optimized CPR standard leads to a reduction in mortality rates and favorable neurological outcomes.

Keywords: cardiac surgery, cardiac arrest, resuscitation, critically ill patients

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: Yi-Tung Lin

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Researchers commonly assess implicit self-esteem with the Implicit Association Test (IAT). The IAT’s measure, often referred to as the IAT effect, indicates the strengths of automatic preferences for the self relative to others, which is often considered an index of implicit self-esteem. However, based on the Dual-process theory, the IAT does not rely entirely on the automatic process; it is also influenced by a controlled process. The present study, therefore, analyzed the IAT data with the Quad model, separating four processes on the IAT performance: the likelihood that automatic association is activated by the stimulus in the trial (AC); that a correct response is discriminated in the trial (D); that the automatic bias is overcome in favor of a deliberate response (OB); and that when the association is not activated, and the individual fails to discriminate a correct answer, there is a guessing or response bias drives the response (G). The AC and G processes are automatic, while the D and OB processes are controlled. The AC parameter is considered as the strength of the association activated by the stimulus, which reflects what implicit measures of social cognition aim to assess. The stronger the automatic association between self and positive valence, the more likely it will be activated by a relevant stimulus. Therefore, the AC parameter was used as the index of implicit self-esteem in the present study. Meanwhile, the relationship between implicit self-esteem and depression is not fully investigated. In the cognitive theory of depression, it is assumed that the negative self-schema is crucial in depression. Based on this point of view, implicit self-esteem would be negatively associated with depression. However, the results among empirical studies are inconsistent. The aims of the present study were to examine the psychometric properties of the AC (i.e., test-retest reliability and its correlations with explicit self-esteem and depression) and compare it with that of the IAT effect. The present study had 105 patients with depressive disorders completing the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II and the IAT on the pretest. After at least 3 weeks, the participants completed the second IAT. The data were analyzed by the latent-trait multinomial processing tree model (latent-trait MPT) with the TreeBUGS package in R. The result showed that the latent-trait MPT had a satisfactory model fit. The effect size of test-retest reliability of the AC and the IAT effect were medium (r = .43, p < .0001) and small (r = .29, p < .01) respectively. Only the AC showed a significant correlation with explicit self-esteem (r = .19, p < .05). Neither of the two indexes was correlated with depression. Collectively, the AC parameter was a satisfactory index of implicit self-esteem compared with the IAT effect. Also, the present study supported the results that implicit self-esteem was not correlated with depression.

Keywords: cognitive modeling, implicit association test, implicit self-esteem, quad model

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Authors: Devon Simpson

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Recycled Manure Solids (RMS), attained via centrifugation from Canadian dairy farms, were synthesized into a non-polluting fertilizer by bonding micronutrients (Fe, Zn, and Mn) to cellulose fibers and then assessed for the effectiveness of nutrient recovery in tomatoes. Manure management technology is critical for improving the sustainability of agroecosystems and has the capacity to offer a truly circular economy. The ability to add value to manure byproducts offers an opportunity for economic benefits while generating tenable solutions to livestock waste. The dairy industry is under increasing pressure from new environmental protections such as government restrictions on manure applications, limitations on herd size as well as increased product demand from a growing population. Current systems use RMS as bedding, so there is a lack of data pertaining to RMS use as a fertilizer. This is because of nutrient distribution, where most nutrients are retained in the liquid effluent of the solid-liquid separation. A literature review on the physical and chemical properties of dairy manure further revealed more data for raw manure than centrifuged solids. This research offers an innovative perspective and a new avenue of exploration in the use of RMS. Manure solids in this study were obtained directly from dairy farms in Salmon Arm and Abbotsford, British Columbia, and underwent physical, chemical, and biological characterizations pre- and post-synthesis processing. Samples were sent to A&L labs Canada for analysis. Once characterized and bonded to micronutrients, the effect of synthesized RMS on nutrient recovery in tomatoes was studied in a greenhouse environment. The agricultural research package ‘agricolae’ for R was used for experimental design and data analysis. The growth trials consisted of a randomized complete block design (RCBD) that allowed for analysis of variance (ANOVA). The primary outcome was to measure nutrient uptake, and this was done using an Inductively Coupled Plasma Mass Spectrometer (IC-PMS) to analyze the micronutrient content of both the tissue and fruit of the tomatoes. It was found that treatments containing bonded dairy manure solids had an increased micronutrient concentration. Treatments with bonded dairy manure solids also saw an increase in yield, and a brix analysis showed higher sugar content than the untreated control and a grower standard.

Keywords: aoecosystems, dairy manure, micronutrient fertilizer, manure management, nutrient recovery, nutrient recycling, recycled manure solids, regenerative agricugrlture, sustainable farming

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Authors: R. Khare, R. V. Gelamo, M. A. More, D. J. Late, Chandra Sekhar Rout

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Graphene emerges out as a promising material for various applications ranging from complementary integrated circuits to optically transparent electrode for displays and sensors. The excellent conductivity and atomic sharp edges of unique two-dimensional structure makes graphene a propitious field emitter. Graphene analogues of other 2D layered materials have emerged in material science and nanotechnology due to the enriched physics and novel enhanced properties they present. There are several advantages of using 2D nanomaterials in field emission based devices, including a thickness of only a few atomic layers, high aspect ratio (the ratio of lateral size to sheet thickness), excellent electrical properties, extraordinary mechanical strength and ease of synthesis. Furthermore, the presence of edges can enhance the tunneling probability for the electrons in layered nanomaterials similar to that seen in nanotubes. Here we report electron emission properties of multilayer graphene and effect of plasma (CO2, O2, Ar and N2) treatment. The plasma treated multilayer graphene shows an enhanced field emission behavior with a low turn on field of 0.18 V/μm and high emission current density of 1.89 mA/cm2 at an applied field of 0.35 V/μm. Further, we report the field emission studies of layered WS2/RGO and SnS2/RGO composites. The turn on field required to draw a field emission current density of 1μA/cm2 is found to be 3.5, 2.3 and 2 V/μm for WS2, RGO and the WS2/RGO composite respectively. The enhanced field emission behavior observed for the WS2/RGO nanocomposite is attributed to a high field enhancement factor of 2978, which is associated with the surface protrusions of the single-to-few layer thick sheets of the nanocomposite. The highest current density of ~800 µA/cm2 is drawn at an applied field of 4.1 V/μm from a few layers of the WS2/RGO nanocomposite. Furthermore, first-principles density functional calculations suggest that the enhanced field emission may also be due to an overlap of the electronic structures of WS2 and RGO, where graphene-like states are dumped in the region of the WS2 fundamental gap. Similarly, the turn on field required to draw an emission current density of 1µA/cm2 is significantly low (almost half the value) for the SnS2/RGO nanocomposite (2.65 V/µm) compared to pristine SnS2 (4.8 V/µm) nanosheets. The field enhancement factor β (~3200 for SnS2 and ~3700 for SnS2/RGO composite) was calculated from Fowler-Nordheim (FN) plots and indicates emission from the nanometric geometry of the emitter. The field emission current versus time plot shows overall good emission stability for the SnS2/RGO emitter. The DFT calculations reveal that the enhanced field emission properties of SnS2/RGO composites are because of a substantial lowering of work function of SnS2 when supported by graphene, which is in response to p-type doping of the graphene substrate. Graphene and 2D analogue materials emerge as a potential candidate for future field emission applications.

Keywords: graphene, layered material, field emission, plasma, doping

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Ahmad Abu-Akel, Emilie De Montpellier, Sophie Von Bentivegni, Lyn Luechinger, Alessandro Ishii, Christine Mohr

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Convergent and divergent thinking are two main components of creativity that have been viewed as complementary. While divergent thinking refers to the fluency and flexibility of generating new ideas, convergent thinking refers to the ability to systematically apply rules and knowledge to arrive at the optimal solution or idea. These creativity components have been shown to be susceptible to variation in subclinical expressions of autistic and schizotypal traits within the general population. Research, albeit inconclusively, mainly linked positive schizotypal traits with divergent thinking and autistic traits with convergent thinking. However, cumulative evidence suggests that these trait dimensions can co-occur in the same individual more than would be expected by chance and that their concurrent effect can be diametric and even interactive. The current study aimed at investigating the concurrent effect of these trait dimensions on tasks assessing convergent and divergent thinking abilities. We predicted that individuals with high positive schizotypal traits alone would perform particularly well on the divergent thinking task, whilst those with high autistic traits alone would perform particularly well on the convergent thinking task. Crucially, we also predicted that individuals who are high on both autistic and positive schizotypal traits would perform particularly well on both the divergent and convergent thinking tasks. This was investigated in a non-clinical sample of 142 individuals (Males = 45%; Mean age = 21.45, SD = 2.30), sufficient to minimally observe an effect size f² ≥ .10. Divergent thinking was evaluated using the Alternative Uses Task, and convergent thinking with the Anagrams Task. Autistic and schizotypal traits were respectively assessed with the Autism Quotient Questionnaire (AQ) and the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). Regression analyses revealed that the positive association of autistic traits with convergent thinking scores was qualified with an interaction with positive schizotypal traits. Specifically, positive schizotypal traits were negatively associated with convergent thinking scores when AQ scores were relatively low, but this trend was reversed when AQ scores were high. Conversely, the positive effect of AQ scores on convergent thinking progressively increased with increasing positive schizotypal traits. The results of divergent thinking task are currently being analyzed and will be reported at the conference. The association of elevated autistic and positive schizotypal traits with convergent thinking may represent a unique profile of creative thinkers who are able to simultaneously draw on trait-specific advantages conferred by autistic and positively schizotypal traits such as local and global processing. This suggests that main-effect models can tell an incomplete story regarding the effect of autistic and positive schizotypal traits on creativity-related processes. Future creativity research should consider their interaction and the benefits conferred by their co-presence.

Keywords: autism, schizotypy, convergent thinking, divergent thinking, comorbidity

Procedia PDF Downloads 180

Authors: BoSheng Liu

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The research goal is to re-image a locally-sourced waste product as abuilding material. The author aims to contribute to the compressed stabilized earth block (CSEB) by investigating the promising role of dredged material as an alternative building ingredient in the production of bricks and tiles. Dredged material comes from the sediment deposited near the shore or downstream, where the water current velocity decreases. This sediment needs to be dredged to provide water transportation; thus, there are mounds of the dredged material stored at bay. It is the interest of this research to reduce the filtered un-organic soil in the production of CSEB and replace it with locally dredged material from the Atchafalaya River in Morgan City, Louisiana. Technology and mechanical innovations have evolved the traditional adobe production method, which mixes the soil and natural fiber into molded bricks, into chemically stabilized CSEB made by compressing the clay mixture and stabilizer in a compression chamber with particular loads. In the case of dredged material CSEB (DM-CSEB), cement plays an essential role as the bending agent contributing to the unit strength while sustaining the filtered un-organic soil. Each DM-CSEB unit is made in a compression chamber with 580 PSI (i.e., 4 MPa) force. The research studied the cement content from 5% to 10% along with the range of dredged material mixtures, which differed from 20% to 80%. The material mixture content affected the DM-CSEB's strength and workability during and after its compression. Results indicated two optimal workabilities of the mixture: 27% fine clay content and 63% dredged material with 10% cement, or 28% fine clay content, and 67% dredged material with 5% cement. The final product of DM-CSEB emitted between 10 to 13 times fewer carbon emissions compared to the conventional fired masonry structure. DM-CSEB satisfied the strength requirement given by the ASTM C62 and ASTM C34 standards for construction material. One of the final evaluations tested and validated the material performance by designing and constructing an architectural, conical tile-vault prototype that was 28" by 40" by 24." The vault utilized a computational form-finding approach to generate the form's geometry, which optimized the correlation between the vault geometry and structural load distribution. A series of scaffolding was deployed to create the framework for the tile-vault construction. The final tile-vault structure was made from 2 layers of DM-CSEB tiles jointed by mortar, and the construction of the structure used over 110 tiles. The tile-vault prototype was capable of carrying over 400 lbs of live loads, which further demonstrated the dredged material feasibility as a construction material. The presented case study of Dredged Material Compressed Stabilized Earth Block (DM-CSEB) provides the first impression of dredged material in the clayey mixture process, structural performance, and construction practice. Overall, the approach of integrating dredged material in building material can be feasible, regionally sourced, cost-effective, and environment-friendly.

Keywords: dredged material, compressed stabilized earth block, tile-vault, regionally sourced, environment-friendly

Procedia PDF Downloads 115

Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques, and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then, dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is an arbitrary nonempty closed subset of the real numbers. Then, the dynamic inequalities on time scales have received a lot of attention in the literature and has become a major field in pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on Hardy and Coposon inequalities, using Steklov operator on time scale in double integrals to obtain special cases of time-scale inequalities of Hardy and Copson on high dimensions. The advantage of this study is that it uses the one-dimensional classical Hardy inequality to obtain higher dimensional on time scale versions that will be applied in the solution of the Cauchy problem for the wave equation. In addition, the obtained inequalities have various applications involving discontinuous domains such as bug populations, phytoremediation of metals, wound healing, maximization problems. The proof can be done by introducing restriction on the operator in several cases. The concepts in time scale version such as time scales calculus will be used that allows to unify and extend many problems from the theories of differential and of difference equations. In addition, using chain rule, and some properties of multiple integrals on time scales, some theorems of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of hardy, inequality of coposon, steklov operator

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Authors: L. M. H. Mustonen, S. A. Heikkilä

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The focus of the paper is to describe team teaching as a HAMK’s pedagogical method, and its impacts to the teachers work. Background: Traditionally it is thought that teaching is a job where one mostly works alone. More and more teachers feel that their work is getting more stressful. Solutions to these problems have been sought in Häme University of Applied sciences’ (From now on referred to as HAMK). HAMK has made a strategic change to move to the group oriented working of teachers. Instead of isolated study courses, there are now larger 15 credits study modules. Implementation: As examples of the method, two cases are presented: technical project module and summer studies module, which was integrated into the EU development project called Energy Efficiency with Precise Control. In autumn 2017, technical project will be implemented third time. There are at least three teachers involved in it and it is the first module of the new students. Main focus is to learn the basic skills of project working. From communicational viewpoint, they learn the basics of written and oral reporting and the basics of video reporting skills. According to our quality control system, the need for the development is evaluated in the end of the module. There are always some differences in each implementation but the basics are the same. The other case summer studies 2017 is new and part of a larger EU project. For the first time, we took a larger group of first to third year students from different study programmes to the summer studies. The students learned professional skills and also skills from different fields of study, international cooperation, and communication skills. Benefits and challenges: After three years, it is possible to consider what the changes mean in the everyday work of the teachers - and of course – what it means to students and the learning process. The perspective is HAMK’s electrical and automation study programme: At first, the change always means more work. The routines born after many years and the course material used for years may not be valid anymore. Teachers are teaching in modules simultaneously and often with some subjects overlapping. Finding the time to plan the modules together is often difficult. The essential benefit is that the learning outcomes have improved. This can be seen in the feedback given by both the teachers and the students. Conclusions: A new type of working environment is being born. A team of teachers designs a module that matches the objectives and ponders the answers to such questions as what are the knowledge-based targets of the module? Which pedagogical solutions will achieve the desired results? At what point do multiple teachers instruct the class together? How is the module evaluated? How can the module be developed further for the next execution? The team discusses openly and finds the solutions. Collegiate responsibility and support are always present. These are strengthening factors of the new communal university teaching culture. They are also strong sources of pleasure of work.

Keywords: pedagogical development, summer studies, team teaching, well-being at work

Procedia PDF Downloads 109

Authors: Nawras Kurzom, Avi Mendelsohn

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The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Justo Rodriguez, Daming Chen, Amador M. Guzman

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The detection, treatment, and control of rapidly propagating, deadly viruses such as COVID-19, require the development of inexpensive, fast, and accurate devices to address the urgent needs of the population. Microfluidics-based sensors are amongst the different methods and techniques for detection that are easy to use. A micro analyzer is defined as a microfluidics-based sensor, composed of a network of microchannels with varying functions. Given their size, portability, and accuracy, they are proving to be more effective and convenient than other solutions. A micro analyzer based on the concept of “Lab on a Chip” presents advantages concerning other non-micro devices due to its smaller size, and it is having a better ratio between useful area and volume. The integration of multiple processes in a single microdevice reduces both the number of necessary samples and the analysis time, leading the next generation of analyzers for the health-sciences. In some applications, the flow of solution within the microchannels is originated by a pressure gradient, which can produce adverse effects on biological samples. A more efficient and less dangerous way of controlling the flow in a microchannel-based analyzer is applying an electric field to induce the fluid motion and either enhance or suppress the mixing process. Electrokinetic flows are characterized by no less than two non-dimensional parameters: the electric Rayleigh number and its geometrical aspect ratio. In this research, stable and unstable flows have been studied numerically (and when possible, will be experimental) in a T-shaped microchannel. Additionally, unstable electrokinetic flows for Rayleigh numbers higher than critical have been characterized. The flow mixing enhancement was quantified in relation to the stretching and folding that fluid particles undergo when they are subjected to supercritical electrokinetic flows. Computational simulations were carried out using a finite element-based program while working with the flow mixing concepts developed by Gollub and collaborators. Hundreds of seeded massless particles were tracked along the microchannel from the entrance to exit for both stable and unstable flows. After post-processing, their trajectories, the folding and stretching values for the different flows were found. Numerical results show that for supercritical electrokinetic flows, the enhancement effects of the folding and stretching processes become more apparent. Consequently, there is an improvement in the mixing process, ultimately leading to a more homogenous mixture.

Keywords: microchannel, stretching and folding, electro kinetic flow mixing, micro-analyzer

Procedia PDF Downloads 126

Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Ertuğrul Yılmaz

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One of the most important occupational groups in the food chain from farm to fork is a veterinary medicine. This occupational group, which has important duties in the prevention of many zoonotic diseases and in public health, takes place in many critical control points from soil to our kitchen. It has important duties from mycotoxins transmitted from the soil to slaughterhouses or milk processing facilities. Starting from the soil, which constitutes 70% of mycotoxin contamination, up to the TMR made from raw materials obtained from the soil, there are all critical control points from feeding to slaughterhouses and milk production enterprises. We can take the precaution of mycotoxins such as Aflatoxin B1, Ochratoxin, Zearalenone, and Fumonisin, which we encounter on farms while in the field. It has been reported that aflatoxin B1 is a casenerogen and passes into milk in studies. It is likely that many mycotoxins pose significant threats to public health and will turn out to be even more dangerous over time. Even raw material storage and TMR preparation are very important for public health. The danger of fumonisin accumulating in the liver will be understood over time. Zoonotic diseases are also explained with examples. In this study, how important veterinarians are in terms of public health is explained with examples. In the two-year mycotoxin screenings, fumonisin mycotoxin was found to be very high in corn and corn by-products, and it was determined that it accumulated in the liver for a long time and remained cornic in animals. It has been determined that mycotoxins are present in all livestock feeds, poultry feeds, and raw materials, not alone, but in double-triple form. Starting from the end, mycotoxin scans should be carried out from feed to raw materials and from raw materials to soil. In this way, we prevent the transmission of mycotoxins to animals and from animals to humans. Liver protectors such as toxin binders, beta-glucan, mannan oligosaccharides, activated carbon, prebiotics, and silymarin were used in certain proportions in the total mixed ratio, and positive results were obtained. Humidity and temperature controls of raw material silos were made at certain intervals. Necropsy was performed on animals that died as a result of mycotoxicosis, and macroscopic photographs were taken of the organs. We have determined that the mycotoxin screening in experimental animals and the feeds made without detecting the presence and amount of bacterial factors affect the results of the project to be made. For this, a series of precautionary plans have been created, starting from the production processes.

Keywords: mycotoxins, feed safety, processes, public health

Procedia PDF Downloads 84

Authors: Amit Kumar, Archana Gupta, Poonam Tandon, E. D. D’Silva

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Nonlinear optical (NLO) materials are the key materials for the fast processing of information and optical data storage applications. In the last decade, materials showing nonlinear optical properties have been the object of increasing attention by both experimental and computational points of view. Chalcones are one of the most important classes of cross conjugated NLO chromophores that are reported to exhibit good SHG efficiency, ultra fast optical nonlinearities and are easily crystallizable. The basic structure of chalcones is based on the π-conjugated system in which two aromatic rings are connected by a three-carbon α, β-unsaturated carbonyl system. Due to the overlap of π orbitals, delocalization of electronic charge distribution leads to a high mobility of the electron density. On a molecular scale, the extent of charge transfer across the NLO chromophore determines the level of SHG output. Hence, the functionalization of both ends of the π-bond system with appropriate electron donor and acceptor groups can enhance the asymmetric electronic distribution in either or both ground and excited states, leading to an increased optical nonlinearity. In this research, the experimental and theoretical study on the structure and vibrations of (2E)-3-[4-(methylsulfanyl) phenyl]-1-(3-bromophenyl) prop-2-en-1-one (3Br4MSP) is presented. The FT-IR and FT-Raman spectra of the NLO material in the solid phase have been recorded. Density functional theory (DFT) calculations at B3LYP with 6-311++G(d,p) basis set were carried out to study the equilibrium geometry, vibrational wavenumbers, infrared absorbance and Raman scattering activities. The interpretation of vibrational features (normal mode assignments, for instance) has an invaluable aid from DFT calculations that provide a quantum-mechanical description of the electronic energies and forces involved. Perturbation theory allows one to obtain the vibrational normal modes by estimating the derivatives of the Kohn−Sham energy with respect to atomic displacements. The molecular hyperpolarizability β plays a chief role in the NLO properties, and a systematical study on β has been carried out. Furthermore, the first order hyperpolarizability (β) and the related properties such as dipole moment (μ) and polarizability (α) of the title molecule are evaluated by Finite Field (FF) approach. The electronic α and β of the studied molecule are 41.907×10-24 and 79.035×10-24 e.s.u. respectively, indicating that 3Br4MSP can be used as a good nonlinear optical material.

Keywords: DFT, MEP, NLO, vibrational spectra

Procedia PDF Downloads 221

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 73

Authors: Ngoc Thao Linh Dang

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Urban waterfront redevelopment is a global phenomenon, and thousands of schemes are being carried out in large metropoles, medium-sized cities, and even small towns all over the world. This opportunity brings the city back to the river and rediscovers waterfront revitalization as a unique opportunity for cities to reconnect with their unique historical and cultural image. The redevelopment can encourage economic investments, serve as a social platform for public interactions, and allow dwellers to express their rights to the city. Many coastal cities have effectively transformed the perception of their waterfront area through years of redevelopment initiatives, having been neglected for over a century. However, this process has never been easy due to the particular complexity of the space: local culture, history, and market-led development. Moreover, municipal governments work out the balance of diverse stakeholder interests, especially when repurposing high-profile and redundant spaces that form the core of urban economic investment while also accommodating the present and future generations in sustainable environments. Urban critics consistently grapple with the effectiveness of the planning process on the new waterfront, where public spaces are criticized for presenting a lack of opportunities for actual public participation due to privatization and authoritarian governance while no longer doing what they are ‘meant to’: all arise in reaction to the perceived failure of these places to meet expectations. The planning culture and the decision-making context determine the level of public involvement in the planning process; however, in the context of competing market forces and commercial interests dominating cities’ planning agendas, planning for public space in urban waterfronts tends to be for economic gain rather than supporting residents' social needs. These newly pleasing settings satisfied the cluster of middle-class individuals, new communities living along the waterfront, and tourists. A trend of public participatory exclusion is primarily determined by the nature of the planning being undertaken and the decision-making context in which it is embedded. Starting from this context, the research investigates the influence of planning on waterfront regeneration and the role of participation in this process. The research aims to look specifically at the characteristics of the planning process of the waterfront in Da Nang and its impact on the regeneration of the place to regain the city’s historical value and enhance local cultural identity and images. Vietnam runs a top-down planning system where municipal governments have control or power over what happens in their city following the approved planning from the national government. The community has never been excluded from development; however, their participation is still marginalized. In order to ensure social equality, a proposed approach called "bottom-up" should be considered and implemented alongside the traditional "top-down" process and provide a balance of perspectives, as it allows for the voices of the most underprivileged social group involved in a planning project to be heard, rather than ignored. The research provides new insights into the influence of the planning process on the waterfront regeneration in the context of Da Nang.

Keywords: planning process, public participation, top-down planning, waterfront regeneration

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Authors: Daramola Japheth, Tabiti S. Tabiti, Daramola Elizabeth Lara, Hussaini Yusuf Atulukwu

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Bida urban centre is faced with solid waste management problems which are evident in the processes of waste generation, onsite storage, collection, transfer and transport, processing and disposal of solid waste. As a result of this the urban centre is defaced with litters of garbage and offensive odours due to indiscriminate dumping of refuse within the neighborhood. The partial removal of the fuel subsidy by the Federal Government in January 2012 leads to the formation of Subsidy Reinvestment Programmes (SURE-P), the Federal Government’s share is 41 per cent of the savings while the States and Local Government shared the remaining 59 percent. The SURE-P Committee in carrying out the mandate entrusted upon it by the President by identifying few critical infrastructure and social Safety nets that will ameliorate the sufferings of Nigerians. Waste disposal programme as an aspect of Solid waste management is one of the areas of focus for Niger State SURE-programmes incorporated under Niger State Environmental Protection Agency. The emergence of this programme as related to waste management in Bida has left behind a huge refuse spots along major corridors leading to a serious state of mess. Major roads within the LGA is now turned to dumping site, thereby obstructing traffic movements, while the aesthetic nature of the town became something else with offensive odours all over. This paper however wishes to underscore the use of geographical Information System in identifying solid waste sports towards effective solid waste management in the Bida urban centre. The paper examined the spatial location of dumping points and its impact on the environment. Hand held Global Position System was use to pick the dumping points location; where a total number of 91 dumping points collected were uploaded to ArcGis 10.2 for analysis. Interview method was used to derive information from households living near the dumping site. It was discovered that the people now have to cope with offensive odours, rodents invasion, dog and cats coming around the house as a result of inadequate and in prompt collection of waste around the neighborhood. The researchers hereby recommend that more points needs to be created with prompt collections of waste within the neighborhood by the necessary SURE - P agencies.

Keywords: dumping site, neighborhood, refuse, waste

Procedia PDF Downloads 529

Authors: Nahush Modak, Meena Pangarkar, Anand Pathak, Ankita Tamhane

Abstract:

Background: Breast cancer is the prominent cause of cancer and mortality among women. This study was done to show the statistical analysis of a cohort of over 250 patients detected with breast cancer diagnosed by oncologists using Immunohistochemistry (IHC). IHC was performed by using ER; PR; HER2; Ki-67 antibodies. Materials and methods: Formalin fixed Paraffin embedded tissue samples were obtained by surgical manner and standard protocol was followed for fixation, grossing, tissue processing, embedding, cutting and IHC. The Ventana Benchmark XT machine was used for automated IHC of the samples. Antibodies used were supplied by F. Hoffmann-La Roche Ltd. Statistical analysis was performed by using SPSS for windows. Statistical tests performed were chi-squared test and Correlation tests with p<.01. The raw data was collected and provided by National Cancer Insitute, Jamtha, India. Result: Luminal B was the most prevailing molecular subtype of Breast cancer at our institute. Chi squared test of homogeneity was performed to find equality in distribution and Luminal B was the most prevalent molecular subtype. The worse prognostic indicator for breast cancer depends upon expression of Ki-67 and her2 protein in cancerous cells. Our study was done at p <.01 and significant dependence was observed. There exists no dependence of age on molecular subtype of breast cancer. Similarly, age is an independent variable while considering Ki-67 expression. Chi square test performed on Human epidermal growth factor receptor 2 (HER2) statuses of patients and strong dependence was observed in percentage of Ki-67 expression and Her2 (+/-) character which shows that, value of Ki depends upon Her2 expression in cancerous cells (p<.01). Surprisingly, dependence was observed in case of Ki-67 and Pr, at p <.01. This shows that Progesterone receptor proteins (PR) are over-expressed when there is an elevation in expression of Ki-67 protein. Conclusion: We conclude from that Luminal B is the most prevalent molecular subtype at National Cancer Institute, Jamtha, India. There was found no significant correlation between age and Ki-67 expression in any molecular subtype. And no dependence or correlation exists between patients’ age and molecular subtype. We also found that, when the diagnosis is Luminal A, out of the cohort of 257 patients, no patient shows >14% Ki-67 value. Statistically, extremely significant values were observed for dependence of PR+Her2- and PR-Her2+ scores on Ki-67 expression. (p<.01). Her2 is an important prognostic factor in breast cancer. Chi squared test for Her2 and Ki-67 shows that the expression of Ki depends upon Her2 statuses. Moreover, Ki-67 cannot be used as a standalone prognostic factor for determining breast cancer.

Keywords: breast cancer molecular subtypes , correlation, immunohistochemistry, Ki-67 and HR, statistical analysis

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

Abstract:

Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Ricardo Torcato, Helder Morais

Abstract:

The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

Procedia PDF Downloads 153