Search results for: thermal cycling machine

Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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Authors: Arjun Prakash, Vinutha H., Karthik N.

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BACKGROUND: Carpal tunnel syndrome (CTS) is a common entrapment neuropathy with an estimated prevalence of 0.6 - 5.8% in the general adult population. It is caused by compression of the Median Nerve (MN) at the wrist as it passes through a narrow osteofibrous canal. Presently, the diagnosis is established by the clinical symptoms and physical examination and Nerve conduction study (NCS) is used to assess its severity. However, it is considered to be painful, time consuming and expensive, with a false-negative rate between 16 - 34%. Ultrasonography (USG) is now increasingly used as a diagnostic tool in CTS due to its non-invasive nature, increased accessibility and relatively low cost. Elastography is a newer modality in USG which helps to assess stiffness of tissues. However, there is limited available literature about its applications in peripheral nerves. OBJECTIVES: Our objectives were to measure the Cross-Sectional Area (CSA) and elasticity of MN at the carpal tunnel using Grey scale Ultrasonography (USG), Strain Elastography (SE) and Shear Wave Elastography (SWE). We also made an attempt to independently evaluate the role of Gray scale USG, SE and SWE in grading the severity of CTS, keeping NCS as the gold standard. MATERIALS AND METHODS: After approval from the Institutional Ethics Review Board, we conducted a comparative cross sectional study for a period of 18 months. The participants were divided into two groups. Group A consisted of 54 patients with clinically diagnosed CTS who underwent NCS, and Group B consisted of 50 controls without any clinical symptoms of CTS. All Ultrasound examinations were performed on SAMSUNG RS 80 EVO Ultrasound machine with 2 - 9 Mega Hertz linear probe. In both groups, CSA of the MN was measured on Grey scale USG, and its elasticity was measured at the carpal tunnel (in terms of Strain ratio and Shear Modulus). The variables were compared between both groups by using ‘Independent t test’, and subgroup analyses were performed using one-way analysis of variance. Receiver operating characteristic curves were used to evaluate the diagnostic performance of each variable. RESULTS: The mean CSA of the MN was 13.60 + 3.201 mm2 and 9.17 + 1.665 mm2 in Group A and Group B, respectively (p < 0.001). The mean SWE was 30.65 + 12.996 kPa and 17.33 + 2.919 kPa in Group A and Group B, respectively (p < 0.001), and the mean Strain ratio was 7.545 + 2.017 and 5.802 + 1.153 in Group A and Group B respectively (p < 0.001). CONCLUSION: The combined use of Gray scale USG, SE and SWE is extremely useful in grading the severity of CTS and can be used as a painless and cost-effective alternative to NCS. Early diagnosis and grading of CTS and effective treatment is essential to avoid permanent nerve damage and functional disability.

Keywords: carpal tunnel, ultrasound, elastography, nerve conduction study

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Authors: Ahmed Gonnah, Omar Masoud, Mohamed Abdel-Wahab, Ahmed ElMosalamy, Abdulrahman Al-Naseem

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Introduction: Fibroadenomas are solid, mobile, and non-tender benign breast lumps, with the highest prevalence amongst young women aged between 15 and 35. Symptoms can include discomfort, and they can become problematic, particularly when they enlarge, resulting in many referrals for biopsies, with fibroadenomas accounting for 30-75% of the cases. Diagnosis is based on triple assessment that involves a clinical examination, ultrasound imaging and mammography, as well as core needle biopsies. Current management includes observation for 6-12 months, with the indication of definitive surgery, in cases that are older than 35 years or with fibroadenoma persistence. Serious adverse effects of surgery might include nipple-areolar distortion, scarring and damage to the breast tissue, as well as the risks associated with surgery and anesthesia, making it a non-feasible option. Methods: A literature search was performed on the databases EMBASE. MEDLINE/PubMed, Google scholar and Ovid, for English language papers published between 1st of January 2000 and 17th of March 2021. A structured protocol was employed to devise a comprehensive search strategy with keywords and Boolean operators defined by the research question. The keywords used for the search were ‘HIFU’, ‘High-Intensity Focused Ultrasound’, ‘Fibroadenoma’, ‘Breast’, ‘Lesion’. This review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Recently, a thermal ablative technique, High Intensity Focused Ultrasound (HIFU), was found to be a safe, non-invasive, and technically successful alternative, having displayed promising outcomes in reducing the volume of fibroadenomas, pain experienced by patients, and the length of hospitalization. Quality of life improvement was also evidenced, exhibited by the disappearance of symptoms, and enhanced physical activity post-intervention, in addition to patients’ satisfaction with the cosmetic results and future recommendation of the procedure to other patients. Conclusion: Overall, HIFU is a well-tolerated treatment associated with a low risk of complications that can potentially include erythema, skin discoloration and bruising, with the majority of this self-resolving shortly after the procedure.

Keywords: ultrasound, HIFU, breast, efficacy, side effects, fibroadenoma

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Melkamu A. Zeru, Yamral M. Warkaw, Aweke A. Mitku, Muluwerk Ayele

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Introduction: Malaria is a severe health threat in the World, mainly in Africa. It is the major cause of health problems in which the risk of morbidity and mortality associated with malaria cases are characterized by spatial variations across the county. This study aimed to investigate the spatial patterns and predictors of malaria distribution in Ethiopia. Methods: A weighted sample of 15,239 individuals with rapid diagnosis tests was obtained from the Central Statistical Agency and Ethiopia malaria indicator survey of 2015. Global Moran's I and Moran scatter plots were used in determining the distribution of malaria cases, whereas the local Moran's I statistic was used in identifying exposed areas. In data manipulation, machine learning was used for variable reduction and statistical software R, Stata, and Python were used for data management and analysis. The auto logistics spatial binary regression model was used to investigate the predictors of malaria. Results: The final auto logistics regression model reported that male clients had a positive significant effect on malaria cases as compared to female clients [AOR=2.401, 95 % CI: (2.125 - 2.713)]. The distribution of malaria across the regions was different. The highest incidence of malaria was found in Gambela [AOR=52.55, 95%CI: (40.54-68.12)] followed by Beneshangul [AOR=34.95, 95%CI: (27.159 - 44.963)]. Similarly, individuals in Amhara [AOR=0.243, 95% CI:(0.1950.303],Oromiya[AOR=0.197,95%CI:(0.1580.244)],DireDawa[AOR=0.064,95%CI(0.049-0.082)],AddisAbaba[AOR=0.057,95%CI:(0.044-0.075)], Somali[AOR=0.077,95%CI:(0.059-0.097)], SNNPR[OR=0.329, 95%CI: (0.261- 0.413)] and Harari [AOR=0.256, 95%CI:(0.201 - 0.325)] were less likely to had low incidence of malaria as compared with Tigray. Furthermore, for a one-meter increase in altitude, the odds of a positive rapid diagnostic test (RDT) decrease by 1.6% [AOR = 0.984, 95% CI :( 0.984 - 0.984)]. The use of a shared toilet facility was found as a protective factor for malaria in Ethiopia [AOR=1.671, 95% CI: (1.504 - 1.854)]. The spatial autocorrelation variable changes the constant from AOR = 0.471 for logistic regression to AOR = 0.164 for auto logistics regression. Conclusions: This study found that the incidence of malaria in Ethiopia had a spatial pattern that is associated with socio-economic, demographic, and geographic risk factors. Spatial clustering of malaria cases had occurred in all regions, and the risk of clustering was different across the regions. The risk of malaria was found to be higher for those who live in soil floor-type houses as compared to those who live in cement or ceramics floor type. Similarly, households with thatched, metal and thin, and other roof-type houses have a higher risk of malaria than ceramic tiles roof houses. Moreover, using a protected anti-mosquito net reduced the risk of malaria incidence.

Keywords: malaria, Ethiopia, auto logistics, spatial model, spatial clustering

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Authors: Ali Azam Talukder, Jamsheda Ferdous Tuli, Tanzina Islam Reba, Shuvra Kanti Dey, Mamoru Yamada

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Recent global warming created by various pollutants prompted us to find new energy sources instead of fossil fuels. Fossil fuels are one of the key factors to emit various toxic gases in this planet. To solve this problem, along with the scarcity of the worldwide energy crisis, scientists are looking for various alternative options to mitigate the necessity of required future fuels. In this context, bioethanol can be one of the most suitable alternative energy sources. Bioethanol is a renewable, environment-friendly and carbon-neutral sustainable energy. In our previous study, we identified several bioethanol-producing microbes from the natural fermented sources of Bangladesh. Among them, the strain 4C encoded Saccharomyces cerevisiae produced maximum bioethanol when the fermentation temperature was 25˚C. In this study, we have established high-temperature simultaneous saccharification and fermentation process (HTSSF) by co-culturing of thermally adapted thermosensitive 4C as a fermenting agent and Bacillus amyloliquefaciens (C7), as a saccharifying agent under various physiological conditions or treatments. Conventional methods were applied for cell culture, media preparation and other experimental purposes. High-temperature adaptation of strain 4C was made from 30-42ᵒC, using either YPD or YPS media. In brief, for thermal adaptation, the temperature was periodically increased by 2ᵒC, 1ᵒC and 0.5ᵒC when medium growth temperatures were 30-36ᵒC, 36-40ᵒC, and 40-42ᵒC, respectively, where applicable. Amylase activity and bioethanol content were measured by DNS (3, 5-dinitrosalicylic acid) and solvent extraction and dichromate oxidation method, respectively. Among the various growth parameters like temperatures (30˚C, 37˚C and 42˚C), pHs (5.0, 6.0 and 7.0), carbon sources (5.0-10.0%) and ethanol stress tolerance (0.0-12.0%) etc. were tested, maximum Amylase activity (4.0 IU/ml/min) was recorded for Bacillus amyloliquefaciens (C7) at 42˚C, pH 6.0 and 10% starch. On the other hand, 4.10% bioethanol content was recorded when the thermally adapted strain 4C was co-cultured with C7 at 37ᵒC, pH 6.0 and 10.0% starch for 72 hours at HTSSF process. On the other hand, thermally non-adapted strains gave only 0.5-2.0% bioethanol content under the same physiological conditions. The thermally adapted strain 4C and strain C7, both can tolerate ethanol stress up to 12%. Altogether, a comparative study revealed that our established HTSSF process may be suitable for pilot scale and subsequently at industrial level bioethanol production.

Keywords: bioethanol, co-culture, fermentation, saccharification

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: G .D. B. N. Kulasaooriya, H. B. S. Ariyarathne, I. Abeygunawardene, A. A. J. Rafarathne, B. V. Perera

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Elephant is the largest resident of the wild and has small surface to volume ratio as well as less number of sweat glands which cause challenges to the thermoregulation of this mammal. However, this megaherbivore has adopted specialised meachanisms to maintain its thermal balance through behavioral adaptations, ear flapping and well anastomosed arterioles and venules of the ear. Nevertheless, little is known on the involvement of the skin in the process of thermoregulation. The present study was undertaken to monitor the water evaporation rate from the skin of unrestrained wild elephant calves throughout the day and to understand its importance in the thermoregulation. Seven baby elephants housed in the elephant transit home, Udawalawe were used. Ambient temparature, relative humidity (RH) and radiation heat load was monitored throughout the day of the study period. Similarly, surface temparature of the skin was taken at six points including lateral ear pinna, lateral body and the rump during the same period. The skin water evaporation was also measured from the same sites using cobolt chloride method. The surface are of the skin was determined by assigning geometrical shapes to each body part. The results showed that the ambient temperature gradually increased with the day reaching maximum around 3.00 pm. The relative humidity was lowest early in the morning. The radiation heat load did not show any significant change in the study period. The skin temperature was different among lateral ear pinna, lateral body and the rump where the highest temperature was on the rump and the lowest on the lateral ear pinna. The skin temperature gradually increase with increasing ambient temperature but there was not a strong correlation (R2 =53.53) between these two. The skin temperature had strong correlation with RH (p<0.05 R2 =70.84% ) but a significant relationship was not considered since the radiation heat load was not varying in large scale. The skin evaporative water loss had a weak negative correlation with ambient temperature (correlation coefficient= -0.01) whereas strong positive correlation with RH (correlation coefficient= 25.275 ) and no corelation with radiation heat load. It also appeared that skin water loss increases as the skin temperature increased. In the present study, it was observed that on average, skin of the baby elephant looses 403 g/m2/h of water. Based on these observations it can be concluded that a large volume of water is evaporated from the skin of baby elephants and evaporative heat loss may be contributing significantly to the thermoregulation. However, further investigation on the influence of environmental factors on evaporative heat loss has to be conducted to understand the thermoregulatory mechanisms of the baby elephant.

Keywords: thermoregulation, behavioral adaptations, evaporation, elephant

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Authors: Xue Ma, Yang Fu, Dangyuan Lei

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Passive daytime radiative cooling is an emerging technology which has attracted worldwide attention in recent years due to its huge potential in cooling buildings without the use of electricity. Various coating materials with different optical properties have been developed to improve the daytime radiative cooling performance. However, commercial cooling coatings comprising functional fillers with optical bandgaps within the solar spectral range suffers from severe intrinsic absorption, limiting their cooling performance. Fortunately, it has recently been demonstrated that introducing fluorescent materials into polymeric coatings can covert the absorbed sunlight to fluorescent emissions and hence increase the effective solar reflectance and cooling performance. In this paper, we experimentally investigate the key factors for fluorescence-assisted radiative cooling with TiO2-based white coatings. The surrounding TiO2 nanoparticles, which enable spatial and temporal light confinement through multiple Mie scattering, lead to Purcell enhancement of phosphors in the coating. Photoluminescence lifetimes of two phosphors (BaMgAl10O17:Eu2+ and (Sr, Ba)SiO4:Eu2+) exhibit significant reduction of ~61% and ~23%, indicating Purcell factors of 2.6 and 1.3, respectively. Moreover, smaller Stokes shifts of the phosphors are preferred to further diminish solar absorption. Field test of fluorescent cooling coatings demonstrate an improvement of ~4% solar reflectance for the BaMgAl10O17:Eu2+-based fluorescent cooling coating. However, to maximize solar reflectance, a white appearance is introduced based on multiple Mie scattering by the broad size distribution of fillers, which is visually pressurized and aesthetically bored. Besides, most colored pigments absorb visible light significantly and convert it to non-radiative thermal energy, offsetting the cooling effect. Therefore, current colored cooling coatings are facing the compromise between color saturation and cooling effect. To solve this problem, we introduced colored fluorescent materials into white coating based on SiO2 microspheres as a top layer, covering a white cooling coating based on TiO2. Compared with the colored pigments, fluorescent materials could re-emit the absorbed light, reducing the solar absorption introduced by coloration. Our work investigated the scattering properties of SiO2 dielectric spheres with different diameters and detailly discussed their impact on the PL properties of phosphors, paving the way for colored fluorescent-assisted cooling coting to application and industrialization.

Keywords: solar reflection, infrared emissivity, mie scattering, photoluminescent emission, radiative cooling

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Authors: Jing Nan

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The air breakdown voltage in compact circuit breakers is a critical factor in the design and reliability of electrical distribution systems. This voltage determines the threshold at which the air insulation between conductors will fail or 'break down,' leading to an arc. This phenomenon is highly sensitive to the conditions within the breaker, such as the temperature and the distance between electrodes. Typically, air breakdown voltage models have been reliable for predicting failure under standard operational temperatures. However, in conditions post-arcing, where temperatures can soar above 2000K, these models face challenges due to the complex physics of ionization and electron behaviour at such high-energy states. Building upon the foundational understanding that the breakdown mechanism is initiated by free electrons and propelled by electric fields, which lead to ionization and, potentially, to avalanche or streamer formation, we acknowledge the complexity introduced by high-temperature environments. Recognizing the limitations of existing experimental data, a notable research gap exists in the accurate prediction of breakdown voltage at elevated temperatures, typically observed post-arcing, where temperatures exceed 2000K.To bridge this knowledge gap, we present a method that integrates gap distance and high-temperature effects into air breakdown voltage assessment. The proposed model is grounded in the physics of ionization, accounting for the dynamic behaviour of free electrons which, under intense electric fields at elevated temperatures, lead to thermal ionization and potentially reach the threshold for streamer formation as Meek's criterion. Employing the Saha equation, our model calculates equilibrium electron densities, adapting to the atmospheric pressure and the hot temperature regions indicative of post-arc temperature conditions. Our model is rigorously validated against established experimental data, demonstrating substantial improvements in predicting air breakdown voltage in the high-temperature regime. This work significantly improves the predictive power for air breakdown voltage under conditions that closely mimic operational stressors in compact circuit breakers. Looking ahead, the proposed methods are poised for further exploration in alternative insulating media, like SF6, enhancing the model's utility for a broader range of insulation technologies and contributing to the future of high-temperature electrical insulation research.

Keywords: air breakdown voltage, high-temperature insulation, compact circuit breakers, electrical discharge, saha equation

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Authors: Shin-Pin Tseng

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Nowadays, numerous spectral amplitude coding (SAC) fiber-optic code-division-multiple-access (FO-CDMA) techniques were appealing due to their capable of providing moderate security and relieving the effects of multiuser interference (MUI). Nonetheless, the performance of the previous network is degraded due to fixed in-phase cross-correlation (IPCC) value. Based on the above problems, a new SAC FO-CDMA network using partial M-sequence (PMS) code is presented in this study. Because the proposed PMS code is originated from M-sequence code, the system using the PMS code could effectively suppress the effects of MUI. In addition, two-code keying (TCK) scheme can applied in the proposed SAC FO-CDMA network and enhance the whole network performance. According to the consideration of system flexibility, simple optical encoders/decoders (codecs) using fiber Bragg gratings (FBGs) were also developed. First, we constructed a diagram of the SAC FO-CDMA network, including (N/2-1) optical transmitters, (N/2-1) optical receivers, and one N×N star coupler for broadcasting transmitted optical signals to arrive at the input port of each optical receiver. Note that the parameter N for the PMS code was the code length. In addition, the proposed SAC network was using superluminescent diodes (SLDs) as light sources, which then can save a lot of system cost compared with the other FO-CDMA methods. For the design of each optical transmitter, it is composed of an SLD, one optical switch, and two optical encoders according to assigned PMS codewords. On the other hand, each optical receivers includes a 1 × 2 splitter, two optical decoders, and one balanced photodiode for mitigating the effect of MUI. In order to simplify the next analysis, the some assumptions were used. First, the unipolarized SLD has flat power spectral density (PSD). Second, the received optical power at the input port of each optical receiver is the same. Third, all photodiodes in the proposed network have the same electrical properties. Fourth, transmitting '1' and '0' has an equal probability. Subsequently, by taking the factors of phase‐induced intensity noise (PIIN) and thermal noise, the corresponding performance was displayed and compared with the performance of the previous SAC FO-CDMA networks. From the numerical result, it shows that the proposed network improved about 25% performance than that using other codes at BER=10-9. This is because the effect of PIIN was effectively mitigated and the received power was enhanced by two times. As a result, the SAC FO-CDMA network using PMS codes has an opportunity to apply in applications of the next-generation optical network.

Keywords: spectral amplitude coding, SAC, fiber-optic code-division multiple-access, FO-CDMA, partial M-sequence, PMS code, fiber Bragg grating, FBG

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Authors: Temitayo Abayomi Ewemoje, Oluwamayowa Oluwafemi Oluwaniyi

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Agriculture and food processing, industry are among the largest industrial sectors that uses large amount of energy. Thus, a larger amount of gases from their fuel combustion technologies is being released into the environment. The choice of input energy supply not only directly having affects the environment, but also poses a threat to human health. The study was therefore designed to assess each unit production processes in order to identify hotspots using life cycle assessments (LCA) approach in South-western Nigeria. Data such as machine power rating, operation duration, inputs and outputs of shea butter materials for unit processes obtained at site were used to modelled Life Cycle Impact Analysis on GaBi6 (Holistic Balancing) software. Four scenarios were drawn for the impact assessments. Material sourcing from Kaiama, Scenarios 1, 3 and Minna Scenarios 2, 4 but different heat supply sources (Liquefied Petroleum Gas ‘LPG’ Scenarios 1, 2 and 10.8 kW Diesel Heater, scenarios 3, 4). Modelling of shea butter production on GaBi6 was for 1kg functional unit of shea butter produced and the Tool for the Reduction and Assessment of Chemical and other Environmental Impacts (TRACI) midpoint assessment was tool used to was analyse the life cycle inventories of the four scenarios. Eight categories in all four Scenarios were observed out of which three impact categories; Global Warming Potential (GWP) (0.613, 0.751, 0.661, 0.799) kg CO2¬-Equiv., Acidification Potential (AP) (0.112, 0.132, 0.129, 0.149) kg H+ moles-Equiv., and Smog (0.044, 0.059, 0.049, 0.063) kg O3-Equiv., categories had the greater impacts on the environment in Scenarios 1-4 respectively. Impacts from transportation activities was also seen to contribute more to these environmental impact categories due to large volume of petrol combusted leading to releases of gases such as CO2, CH4, N2O, SO2, and NOx into the environment during the transportation of raw shea kernel purchased. The ratio of transportation distance from Minna and Kaiama to production site was approximately 3.5. Shea butter unit processes with greater impacts in all categories was the packaging, milling and with the churning processes in ascending order of magnitude was identified as hotspots that may require attention. From the 1kg shea butter functional unit, it was inferred that locating production site at the shortest travelling distance to raw material sourcing and combustion of LPG for heating would reduce all the impact categories assessed on the environment.

Keywords: GaBi6, Life cycle assessment, shea butter production, TRACI

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Authors: Jignasha Derasari, Patel Krishna M, Modi Jignasa G.

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Chemical stability of pharmaceutical molecules is a matter of great concern as it affects the safety and efficacy of the drug product.Stability testing data provides the basis to understand how the quality of a drug substance and drug product changes with time under the influence of various environmental factors. Besides this, it also helps in selecting proper formulation and package as well as providing proper storage conditions and shelf life, which is essential for regulatory documentation. The ICH guideline states that stress testing is intended to identify the likely degradation products which further help in determination of the intrinsic stability of the molecule and establishing degradation pathways, and to validate the stability indicating procedures. A simple, accurate and precise stability indicating RP- HPLC method was developed and validated for simultaneous estimation of Amiloride Hydrochloride and Furosemide in tablet dosage form. Separation was achieved on an Phenomenexluna ODS C18 (250 mm × 4.6 mm i.d., 5 µm particle size) by using a mobile phase consisting of Ortho phosphoric acid: Acetonitrile (50:50 %v/v) at a flow rate of 1.0 ml/min (pH 3.5 adjusted with 0.1 % TEA in Water) isocratic pump mode, Injection volume 20 µl and wavelength of detection was kept at 283 nm. Retention time for Amiloride Hydrochloride and Furosemide was 1.810 min and 4.269 min respectively. Linearity of the proposed method was obtained in the range of 40-60 µg/ml and 320-480 µg/ml and Correlation coefficient was 0.999 and 0.998 for Amiloride hydrochloride and Furosemide, respectively. Forced degradation study was carried out on combined dosage form with various stress conditions like hydrolysis (acid and base hydrolysis), oxidative and thermal conditions as per ICH guideline Q2 (R1). The RP- HPLC method has shown an adequate separation for Amiloride hydrochloride and Furosemide from its degradation products. Proposed method was validated as per ICH guidelines for specificity, linearity, accuracy; precision and robustness for estimation of Amiloride hydrochloride and Furosemide in commercially available tablet dosage form and results were found to be satisfactory and significant. The developed and validated stability indicating RP-HPLC method can be used successfully for marketed formulations. Forced degradation studies help in generating degradants in much shorter span of time, mostly a few weeks can be used to develop the stability indicating method which can be applied later for the analysis of samples generated from accelerated and long term stability studies. Further, kinetic study was also performed for different forced degradation parameters of the same combination, which help in determining order of reaction.

Keywords: amiloride hydrochloride, furosemide, kinetic study, stability indicating RP-HPLC method validation

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Authors: Vladimir Messerle, Alexandr Ustimenko, Oleg Lavrichshev

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To enhance the efficiency of solid fuels’ use, to decrease the fuel oil rate in the thermal power plants fuel balance and to minimize harmful emissions, a plasma technology of coal ignition, gasification and incineration is successfully applied. This technology is plasma thermochemical preparation of fuel for burning (PTCPF). In the framework of this concept, some portion of pulverized solid fuel (PF) is separated from the main PF flow and undergone the activation by arc plasma in a specific chamber with plasma torch – PFS. The air plasma flame is a source of heat and additional oxidation, it provides a high-temperature medium enriched with radicals, where the fuel mixture is heated, volatile components of coal are extracted, and carbon is partially gasified. This active blended fuel can ignite the main PF flow supplied into the furnace. This technology provides the boiler start-up and stabilization of PF flame and eliminates the necessity for addition of highly reactive fuel. In the report, a model of PTCPF, implemented as a program PlasmaKinTherm for the PFS calculation is described. The model combines thermodynamic and kinetic methods for describing the process of PTCPF in PFS. The numerical investigation of operational parameters of PFS depending on the electric power of the plasma generator and steam coal ash content revealed the temperature and velocity of gas and coal particles, and concentrations of PTCPF products dependences on the PFS length. Main mechanisms of PTCPF were disclosed. It was found that in the range of electric power of plasma generator from 40 to 100 kW high ash bituminous coal, having consumption 1667 kg/h is ignited stably. High level of temperature (1740 K) and concentration of combustible components (44%) at the PFS exit is a confirmation of it. Augmentation in power of plasma generator results displacement maxima temperatures and speeds of PTCPF products upstream (in the direction of the plasma source). The maximum temperature and velocity vary in a narrow range of values and practically do not depend on the power of the plasma torch. The numerical study of indicators of the process of PTCPF depending on the ash content in the range of its values 20-70% demonstrated that at the exit of PFS concentration of combustible components decreases with an increase in coal ash, the temperature of the gaseous products is increasing, and coal carbon conversion rate is increased to a maximum value when the ash content of 60%, dramatically decreasing with further increase in the ash content.

Keywords: coal, efficiency, ignition, numerical modeling, plasma generator, plasma-fuel system

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Authors: K. Graniczkowska, N. Beloglazova, S. De Saeger

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The threat of synthetic drugs is one of the most significant current drug problems worldwide. The use of drugs of abuse has increased dramatically during the past three decades. Among others, Amphetamine-Type Stimulants (ATS) are globally the second most widely used drugs after cannabis, exceeding the use of cocaine and heroin. ATS are potent central nervous system (CNS) stimulants, capable of inducing euphoric static similar to cocaine. Recreational use of ATS is widespread, even though warnings of irreversible damage of the CNS were reported. ATS pose a big problem and their production contributes to the pollution of the environment by discharging big volumes of liquid waste to sewage system. Therefore, there is a demand to develop robust and sensitive sensors that can detect ATS and their intermediates in environmental water samples. A rapid and simple test is required. Analysis of environmental water samples (which sometimes can be a harsh environment) using antibody-based tests cannot be applied. Therefore, molecular imprinted polymers (MIPs), which are known as synthetic antibodies, have been chosen for that approach. MIPs are characterized with a high mechanical and thermal stability, show chemical resistance in a broad pH range and various organic or aqueous solvents. These properties make them the preferred type of receptors for application in the harsh conditions imposed by environmental samples. To the best of our knowledge, there are no existing MIPs-based sensors toward amphetamine and its intermediates. Also not many commercial MIPs for this application are available. Therefore, the aim of this study was to compare different techniques to obtain MIPs with high specificity towards ATS and characterize them for following use in a sensing unit. MIPs against amphetamine and its intermediates were synthesized using a few different techniques, such as electro-, thermo- and UV-initiated polymerization. Different monomers, cross linkers and initiators, in various ratios, were tested to obtain the best sensitivity and polymers properties. Subsequently, specificity and selectivity were compared with commercially available MIPs against amphetamine. Different linkers, such as lipoic acid, 3-mercaptopioponic acid and tyramine were examined, in combination with several immobilization techniques, to select the best procedure for attaching particles on sensor surface. Performed experiments allowed choosing an optimal method for the intended sensor application. Stability of MIPs in extreme conditions, such as highly acidic or basic was determined. Obtained results led to the conclusion about MIPs based sensor applicability in sewage system testing.

Keywords: amphetamine type stimulants, environment, molecular imprinted polymers, MIPs, sensor

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Authors: Jan Schmitt, Sophie Fischer

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After the Corona pandemic, climate change is a further, long-lasting challenge the society must deal with. An ongoing climate change need to be prevented. Nevertheless, the adoption tothe already changed climate conditionshas to be focused in many sectors. Recently, the decisive role of the economic sector with high value added can be seen in the Corona crisis. Hence, manufacturing industry as such a sector, needs to be prepared for climate change and adaption. Several examples from the manufacturing industry show the importance of a strategic effort in this field: The outsourcing of a major parts of the value chain to suppliers in other countries and optimizing procurement logistics in a time-, storage- and cost-efficient manner within a network of global value creation, can lead vulnerable impacts due to climate-related disruptions. E.g. the total damage costs after the 2011 flood disaster in Thailand, including costs for delivery failures, were estimated at 45 billion US dollars worldwide. German car manufacturers were also affected by supply bottlenecks andhave close its plant in Thailand for a short time. Another OEM must reduce the production output. In this contribution, a game-based learning approach is presented, which should enable manufacturing companies to derive their own strategies for climate adaption out of a mix of different actions. Based on data from a regional study of small, medium and large manufacturing companies in Mainfranken, a strongly industrialized region of northern Bavaria (Germany) the game-based learning approach is designed. Out of this, the actual state of efforts due to climate adaption is evaluated. First, the results are used to collect single actions for manufacturing companies and second, further actions can be identified. Then, a variety of climate adaption activities can be clustered according to the scope of activity of the company. The combination of different actions e.g. the renewal of the building envelope with regard to thermal insulation, its benefits and drawbacks leads to a specific strategy for climate adaption for each company. Within the game-based approach, the players take on different roles in a fictionalcompany and discuss the order and the characteristics of each action taken into their climate adaption strategy. Different indicators such as economic, ecologic and stakeholder satisfaction compare the success of the respective measures in a competitive format with other virtual companies deriving their own strategy. A "play through" climate change scenarios with targeted adaptation actions illustrate the impact of different actions and their combination onthefictional company.

Keywords: business strategy, climate change, climate adaption, game-based learning

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Authors: Michael T. Lobmann, Camilla Wellstein, Stefan Zerbe

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Vegetation plays an important role for the stabilization of slopes against erosion processes, such as shallow erosion and landslides. Plant roots reinforce the soil, increase soil cohesion and often cross possible shear planes. Hence, plant roots reduce the risk of slope failure. Generally, shrub and tree roots penetrate deeper into the soil vertically, while roots of forbs and grasses are concentrated horizontally in the topsoil and organic layer. Therefore, shrubs and trees have a higher potential for stabilization of slopes with deep soil layers than forbs and grasses. Consequently, research mainly focused on the vertical root effects of shrubs and trees. Nevertheless, a better understanding of the stabilizing effects of grasses and forbs is needed for better evaluation of the stability of natural and artificial slopes with herbaceous vegetation. Despite the importance of vertical root effects, field observations indicate that horizontal root effects also play an important role for slope stabilization. Not only forbs and grasses, but also some shrubs and trees form tight horizontal networks of fine and coarse roots and rhizomes in the topsoil. These root networks increase soil cohesion and horizontal tensile strength. Available methods for physical measurements, such as shear-box tests, pullout tests and singular root tensile strength measurement can only provide a detailed picture of vertical effects of roots on slope stabilization. However, the assessment of horizontal root effects is largely limited to computer modeling. Here, a method for measurement of in-situ cumulative horizontal root tensile strength is presented. A traction machine was developed that allows fixation of rectangular grass sods (max. 30x60cm) on the short ends with a 30x30cm measurement zone in the middle. On two alpine grass slopes in South Tyrol (northern Italy), 30x60cm grass sods were cut out (max. depth 20cm). Grass sods were pulled apart measuring the horizontal tensile strength over 30cm width over the time. The horizontal tensile strength of the sods was measured and compared for different soil depths, hydrological conditions, and root physiological properties. The results improve our understanding of horizontal root effects on slope stabilization and can be used for improved evaluation of grass slope stability.

Keywords: grassland, horizontal root effect, landslide, mountain, pasture, shallow erosion

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Authors: Bessy Thuranira

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Buildings, as they are designed and used, may contribute to serious environmental problems because of excessive consumption of energy and other natural resources. Buildings in the informal settlements particularly, due to their unplanned physical structure and design, have significantly contributed the global energy problematic scenario typified by high-level inefficiencies. Energy used in buildings in Africa is estimated to be the highest of the total national electricity consumption. Over the last decade, assessments of energy consumption and efficiency/inefficiency has focused on formal and modern buildings. This study seeks to go off the beaten path, by focusing on energy use in informal settlements. Operationally, it sought to establish the contribution of informal buildings in the overall energy consumption in the city and the country at large. This study was carried out in Mukuru kwa Reuben informal settlement where there is distinct manifestation of different settlement morphologies within a small locality. The research narrowed down to three villages (Mombasa, Kosovo and Railway villages) within the settlement, that were representative of the different slum housing typologies. Due to the unpredictability nature and informality in slums, this study takes a multi-methodology approach. Detailed energy audits and measurements are carried out to predict total building consumption, and document building design and envelope, typology, materials and occupancy levels. Moreover, the study uses semi-structured interviews and to access energy supply, cost, access and consumption patterns. Observations and photographs are also used to shed more light on these parameters. The study reveals the high energy inefficiencies in slum buildings mainly related to sub-standard equipment and appliances, building design and settlement layout, poor access and utilization/consumption patterns of energy. The impacts of this inefficiency are high economic burden to the poor, high levels of pollution, lack of thermal comfort and emissions to the environment. The study highlights a set of urban planning and building design principles that can be used to retrofit slums into more energy efficient settlements. The study explores principles of responsive settlement layouts/plans and appropriate building designs that use the beneficial elements of nature to achieve natural lighting, natural ventilation, and solar control to create thermally comfortable, energy efficient, and environmentally responsive buildings/settlements. As energy efficiency in informal settlements is a relatively less explored area of efficiency, it requires further research and policy recommendations, for which this paper will set a background.

Keywords: energy efficiency, informal settlements, renewable energy, settlement layout

Procedia PDF Downloads 110

Authors: Angelo Garofalo, Laura Donato, Maria Concetta Carnevale, Enrico Drioli, Omar Alharbi, Saad Aljlil, Alessandra Criscuoli, Catia Algieri

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Nowadays, water scarcity may be considered one of the most important and serious questions concerning our community: in fact, there is a remarkable mismatch between water supply and water demand. Exploitation of natural fresh water resources combined with higher water demand has led to an increased requirement for alternative water resources. In this context, desalination provides such an alternative source, offering water otherwise not accessible for irrigational, industrial and municipal use. Considering the various drawbacks of the polymeric membranes, zeolite membranes represent a potential device for water desalination owing to their high thermal and chemical stability. In this area wide attention was focused on the MFI (silicalite, ZSM-5) membranes, having a pore size lower (about 5.5 Å) than the major kinetic diameters of hydrated ions. In the present work, a scale-up for the preparation of supported silicalite membranes was performed. Therefore, tubular membranes 30 cm long were synthesized by using the secondary growth method coupled with the cross flow seeding procedure. The secondary growth presents two steps: seeding and growth of zeolite crystals on the support. This process, decoupling zeolite nucleation from crystals growth, permits to control the conditions of each step separately. The seeding procedure consists of a cross-flow filtration through a porous support coupled with the support rotation and tilting. The combination of these three different aspects allows a homogeneous and uniform coverage of the support with the zeolite seeds. After characterization by scanning electron microscope (SEM), X-ray diffractometry (XRD) and Energy-dispersive X-ray (EDX) analysis, the prepared membranes were tested by means of single gas permeation and then by Vacuum Membrane Distillation (VMD) using both deionized water and NaCl solutions. The experimental results evidenced the possibility to perform the scale up for the preparation of almost defect free silicalite membranes. VMD tests indicated the possibility to prepare membranes that exhibit interesting performance in terms of fluxes and salt rejections for concentrations from 0.2 M to 0.9 M. Furthermore, it was possible to restore the original performance of the membrane after an identified cleaning procedure. Acknowledgements: The authors gratefully acknowledge the support of the King Abdulaziz City for Science and Technology (KACST) for funding the research Project 895/33 entitled ‘Preparation and Characterization of Zeolite Membranes for Water Treatment’.

Keywords: desalination, MFI membranes, secondary growth, vacuum membrane distillation

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Authors: Lisa Monteiro, Jacqueline Saliba, Nadia Saiyouri, Humberto Y. Godoy

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Theevolution of the global environmental context incites companies to reduce their impact by reusing local materials and promoting circular economy. Dredged sediments represent a potential source of materials due to their large volume. Indeed, the dredging operations carried out in Gironde alone generated an annual volume of sediment of approximately 9 million m³. Moreover, on the eve of the evolution of laws concerning dredging practices, the recovery of sediments is necessary to create a viable economy for their management. This thesis work is oriented towards the development of an ecological binder from the fine fraction of untreated dredged sediments. In fact, their physico-chemical properties make them favorable for the synthesis of geopolymer, current competitor of cement, thanks to its lower carbon footprint and environmental impact. However, several obstacles must be overcome before implementing this new family of materials: the use of sediments without thermal or chemical treatment, the absence of a formulation approach, ignorance of the reactions produced, etc. During the first year of the thesis, a physico-chemical characterization of the sediments made it possible to validate their use as precursors forgeopolymerization according to three criteria: their fineness, their mineralogical composition, and the percentage of amorphous phase. Following these results, several formulations have been defined, taking into account the environmental impact. The sediments were activated with an alkaline solution of sodium hydroxide and sodium silicate. Two other formulations with cement and blast furnace slag have been defined for comparison. The results highlighted the possibility of forming geopolymers from untreated and still wet dredged sediments. The development of structural bonds through the formation of hydrated sodium aluminosilicate thus leads to higher strengths at 90 days (4.78 MPa) than a mixture with cement (0.75 MPa). A 30% gain in CO₂ emissions has also been obtained compared to cement. In order to reduce the uncertainties linked to the absence of a formulation approach, to optimize the number of experiments to be carried out in the laboratory, and to obtain an optimal formulation, an analysis by mixing plan was conducted in order to frame the responses according to the proportions of the constituents. Following the obtaining of an optimal binder, the work will focus on the study of the durability and the interspecific variability of the sediments on the mechanical properties by testing the binder developed with different sediments dredged from the Bordeaux estuary. , the Grand Port Maritime of Bayonne, La Rochelle, and the Bassinsd'Arcachon.

Keywords: compressive strength, dredged sediments, ecological binder, geopolymers

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Condition monitoring is used to increase machinery availability and machinery performance, whilst reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring system provides early warning of faults by predicting them at an early stage. When a localized fault occurs in gears, the vibration signals always exhibit non-stationary behavior. The periodic impulsive feature of the vibration signal appears in the time domain and the corresponding gear mesh frequency (GMF) emerges in the frequency domain. However, one limitation of frequency-domain analysis is its inability to handle non-stationary waveform signals, which are very common when machinery faults occur. Particularly at the early stage of gear failure, the GMF contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are selected or optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers induce a load on the output joint shaft flanges. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. The gearbox used for experimental measurements is of the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive: a five-speed gearbox with final drive gear and front wheel differential. The results obtained from practical experiments prove that the proposed method is very effective for gear fault diagnosis.

Keywords: wavelet analysis, pitted gear, autocorrelation, gear fault diagnosis

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Authors: Hellen L. De Castro e Silva, Ana A. Robles Aguilar, Erik Meers

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Digestates are residual by-products, rich in nutrients and trace elements, which can be used as organic fertilisers on soils. However, due to the non-digestibility of these elements and reduced dry matter during the anaerobic digestion process, metal concentrations are higher in digestates than in feedstocks, which might hamper their use as fertilisers according to the threshold values of some country policies. Furthermore, there is uncertainty regarding the required assimilated amount of these elements by some crops, which might result in their bioaccumulation. Therefore, further processing of the digestate to obtain safe fertilizing products has been recommended. This research aims to analyze the effect of applying the hydrothermal carbonization process to manure-derived digestates as a thermal treatment to reduce the bioavailability of heavy metals in mono and co-digestates derived from pig manure and maize from contaminated land in France. This study examined pig manure collected from a novel stable system (VeDoWs, province of East Flanders, Belgium) that separates the collection of pig urine and feces, resulting in a solid fraction of manure with high up-concentration of heavy metals and nutrients. Mono-digestion and co-digestion processes were conducted in semi-continuous reactors for 45 days at mesophilic conditions, in which the digestates were dried at 105 °C for 24 hours. Then, hydrothermal carbonization was applied to a 1:10 solid/water ratio to guarantee controlled experimental conditions in different temperatures (180, 200, and 220 °C) and residence times (2 h and 4 h). During the process, the pressure was generated autogenously, and the reactor was cooled down after completing the treatments. The solid and liquid phases were separated through vacuum filtration, in which the solid phase of each treatment -hydrochar- was dried and ground for chemical characterization. Different fractions (exchangeable / adsorbed fraction - F1, carbonates-bound fraction - F2, organic matter-bound fraction - F3, and residual fraction – F4) of some heavy metals (Cd, Cr, Ni, and Cr) have been determined in digestates and derived hydrochars using the modified Community Bureau of Reference (BCR) sequential extraction procedure. The main results indicated a difference in the heavy metals fractionation between digestates and their derived hydrochars; however, the hydrothermal carbonization operating conditions didn’t have remarkable effects on heavy metals partitioning between the hydrochars of the proposed treatments. Based on the estimated potential ecological risk assessment, there was one level decrease (considerate to moderate) when comparing the HMs partitioning in digestates and derived hydrochars.

Keywords: heavy metals, bioavailability, hydrothermal treatment, bio-based fertilisers, agriculture

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Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: Feng Wang, Vladislav Vasilyev

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Ferrocene (Fe(C5H5)2, i.e., di-cyclopentadienyle iron (FeCp2) or Fc) is a unique example of ‘wrong but seminal’ in chemistry history. It has significant applications in a number of areas such as homogeneous catalysis, polymer chemistry, molecular sensing, and nonlinear optical materials. However, the ‘molecular carousel’ has been a ‘notoriously difficult example’ and subject to long debate for its conformation and properties. Ferrocene is a dynamic molecule. As a result, understanding of the dynamical properties of ferrocene is very important to understand the conformational properties of Fc. In the present study, molecular dynamic (MD) simulations are performed. In the simulation, we use 5 geometrical parameters to define the overall conformation of Fc and all the rest is a thermal noise. The five parameters are defined as: three parameters d---the distance between two Cp planes, α and δ to define the relative positions of the Cp planes, in which α is the angle of the Cp tilt and δ the angle the two Cp plane rotation like a carousel. Two parameters to position the Fe atom between two Cps, i.e., d1 for Fe-Cp1 and d2 for Fe-Cp2 distances. Our preliminary MD simulation discovered the five parameters behave differently. Distances of Fe to the Cp planes show that they are independent, practically identical without correlation. The relative position of two Cp rings, α, indicates that the two Cp planes are most likely not in a parallel position, rather, they tilt in a small angle α≠ 0°. The mean plane dihedral angle δ ≠ 0°. Moreover, δ is neither 0° nor 36°, indicating under those conditions, Fc is neither in a perfect eclipsed structure nor a perfect staggered structure. The simulations show that when the temperature is above 80K, the conformers are virtually in free rotations, A very interesting result from the MD simulation is the five C-Fe bond distances from the same Cp ring. They are surprisingly not identical but in three groups of 2, 2 and 1. We describe the pentagon formed by five carbon atoms as ‘turtle swimming’ for the motion of the Cp rings of Fc as shown in their dynamical animation video. The Fe- C(1) and Fe-C(2) which are identical as ‘the turtle back legs’, Fe-C(3) and Fe-C(4) which are also identical as turtle front paws’, and Fe-C(5) ---’the turtle head’. Such as ‘turtle swimming’ analog may be able to explain the single substituted derivatives of Fc. Again, the mean Fe-C distance obtained from MD simulation is larger than the quantum mechanically calculated Fe-C distances for eclipsed and staggered Fc, with larger deviation with respect to the eclipsed Fc than the staggered Fc. The same trend is obtained for the five Fe-C-H angles from same Cp ring of Fc. The simulated mean IR spectrum at 7K shows split spectral peaks at approximately 470 cm-1 and 488 cm-1, in excellent agreement with quantum mechanically calculated gas phase IR spectrum for eclipsed Fc. As the temperature increases over 80K, the clearly splitting IR spectrum become a very board single peak. Preliminary MD results will be presented.

Keywords: ferrocene conformation, molecular dynamics simulation, conformer orientation, eclipsed and staggered ferrocene

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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Authors: Rasha Al-Saedi, Anthony Meijer

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The progress of new porous materials has increased rapidly over the past decade for use in applications such as catalysis, gas storage and removal of environmentally unfriendly species due to their high surface area and high thermal stability. In this work, a theoretical study of the zirconium-based metal organic framework (MOFs) were examined in order to determine their potential for gas adsorption of various guest molecules: CO2, N2, CH4 and H2. The zirconium cluster consists of an inner Zr6O4(OH)4 core in which the triangular faces of the Zr6- octahedron are alternatively capped by O and OH groups which bound to nine formate groups and three benzoate groups linkers. General formula is [Zr(μ-O)4(μ-OH)4(HCOO)9((phyO2C)3X))] where X= CH2OH, CH2NH2, CH2CONH2, n(NH2); (n = 1-3). Three types of adsorption sites on the Zr metal center have been studied, named according to capped chemical groups as the ‘−O site’; the H of (μ-OH) site removed and added to (μ-O) site, ‘–OH site’; (μ-OH) site removed, the ‘void site’ where H2O molecule removed; (μ-OH) from one site and H from other (μ-OH) site, in addition to no defect versions. A series of investigations have been performed aiming to address this important issue. First, density functional theory DFT-B3LYP method with 6-311G(d,p) basis set was employed using Gaussian 09 package in order to evaluate the gas adsorption performance of missing-linker defects in zirconium cluster. Next, study the gas adsorption behaviour on different functionalised zirconium clusters. Those functional groups as mentioned above include: amines, alcohol, amide, in comparison with non-substitution clusters. Then, dispersion-corrected density functional theory (DFT-D) calculations were performed to further understand the enhanced gas binding on zirconium clusters. Finally, study the water effect on CO2 and N2 adsorption. The small functionalized Zr clusters were found to result in good CO2 adsorption over N2, CH4, and H2 due to the quadrupole moment of CO2 while N2, CH4 and H2 weakly polar or non-polar. The adsorption efficiency was determined using the dispersion method where the adsorption binding improved as most of the interactions, for example, van der Waals interactions are missing with the conventional DFT method. The calculated gas binding strengths on the no defect site are higher than those on the −O site, −OH site and the void site, this difference is especially notable for CO2. It has been stated that the enhanced affinity of CO2 of no defect versions is most likely due to the electrostatic interactions between the negatively charged O of CO2 and the positively charged H of (μ-OH) metal site. The uptake of the gas molecule does not enhance in presence of water as the latter binds to Zr clusters more strongly than gas species which attributed to the competition on adsorption sites.

Keywords: density functional theory, gas adsorption, metal- organic frameworks, molecular simulation, porous materials, theoretical chemistry

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Authors: Clement Yeboah, Eva Laryea

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A pretest-posttest within subjects experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant, indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant, indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop an interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, computer game-based learning, statistics achievement, statistics anxiety

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Authors: Lesley Northrop, Justin DeGrazia, Jessica Greenwood

Abstract:

ASPIRA Labs now offers an en-suit and ready-to-implement technology transfer solution to enable labs and hospitals that lack the resources to build it themselves to offer in-house genetic testing. This unique platform employs a patented Molecular Inversion Probe (MIP) technology that combines the specificity of a hybrid capture protocol with the ease of an amplicon-based protocol and utilizes an advanced bioinformatics analysis pipeline based on machine learning. To demonstrate its efficacy, two independent genetic tests were validated on this technology transfer platform: expanded carrier screening (ECS) and hereditary cancer testing (HC). The analytical performance of ECS and HC was validated separately in a blinded manner for calling three different types of variants: SNVs, short indels (typically, <50 bp), and large indels/CNVs defined as multi-exonic del/dup events. The reference set was constructed using samples from Coriell Institute, an external clinical genetic testing laboratory, Maine Molecular Quality Controls Inc. (MMQCI), SeraCare and GIAB Consortium. Overall, the analytical performance showed a sensitivity and specificity of >99.4% for both ECS and HC in detecting SNVs. For indels, both tests reported specificity of 100%, and ECS demonstrated a sensitivity of 100%, whereas HC exhibited a sensitivity of 96.5%. The bioinformatics pipeline also correctly called all reference CNV events resulting in a sensitivity of 100% for both tests. No additional calls were made in the HC panel, leading to a perfect performance (specificity and F-measure of 100%). In the carrier panel, however, three additional positive calls were made outside the reference set. Two of these calls were confirmed using an orthogonal method and were re-classified as true positives leaving only one false positive. The pipeline also correctly identified all challenging carrier statuses, such as positive cases for spinal muscular atrophy and alpha-thalassemia, resulting in 100% sensitivity. After confirmation of additional positive calls via long-range PCR and MLPA, specificity for such cases was estimated at 99%. These performance metrics demonstrate that this tech-transfer solution can be confidently internalized by clinical labs and hospitals to offer mainstream ECS and HC as part of their test catalog, substantially increasing access to quality germline genetic testing for labs of all sizes and resources levels.

Keywords: clinical genetics, genetic testing, molecular genetics, technology transfer

Procedia PDF Downloads 163

Authors: Luixa Reizabal, Inaki Garcia, Eneko Sansinenea, Ainize Sarrionandia, Karmele Lopez De Ipina, Elsa Fernandez

Abstract:

Although the effects of incarceration in prisons close to prisoners’ and their families’ residences have been studied, little is known about the effects of remote incarceration. The present study shows the impact of secondary prisonization on mental health of elderly parents of Basque prisoners who are incarcerated in prisons located far away from prisoners’ and their families’ residences. Secondary prisonization refers to the effects that imprisonment of a family member has on relatives. In the study, psychological effects are analyzed by means of comparative methodology. Specifically, levels of psychopathology (depression, anxiety, and stress) and positive mental health (psychological, social, and emotional well-being) are studied in a sample of parents over 65 years old of prisoners incarcerated in prisons located a long distance away (concretely, some of them in a distance of less than 400 km, while others farther than 400 km) from the Basque Country. The dataset consists of data collected through a questionnaire and from a spontaneous speech recording. The statistical and automatic analyses show that levels of psychopathology and positive mental health of elderly parents of prisoners incarcerated in remote jails are affected by the incarceration of their sons or daughters. Concretely, these parents show higher levels of depression, anxiety, and stress and lower levels of emotional (but not psychological or social) wellbeing than parents with no imprisoned daughters or sons. These findings suggest that parents with imprisoned sons or daughters suffer the impact of secondary prisonization on their mental health. When comparing parents with sons or daughters incarcerated within 400 kilometers from home and parents whose sons or daughters are incarcerated farther than 400 kilometers from home, the latter present higher levels of psychopathology, but also higher levels of positive mental health (although the difference between the two groups is not statistically significant). These findings might be explained by resilience. In fact, in traumatic situations, people can develop a force to cope with the situation, and even present a posttraumatic growth. Bearing in mind all these findings, it could be concluded that secondary prisonization implies for elderly parents with sons or daughters incarcerated in remote jails suffering and, in consequence, that changes in the penitentiary policy applied to Basque prisoners are required in order to finish this suffering.

Keywords: automatic spontaneous speech analysis, elderly parents, machine learning, positive mental health, psychopathology, remote incarceration, secondary prisonization

Procedia PDF Downloads 263