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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Amir Nourbakhsh Habibabadi, Alireza Ashori

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Context: The growing concern over the management of plastic waste and the high demand for wood-based products have led to the development of wood-plastic composites. Agricultural residues, which are abundantly available, can be used as a source of lignocellulosic fibers in the production of these composites. The use of recycled polymers and nanomaterials is also a promising approach to enhance the mechanical and physical properties of the composites. Research Aim: The aim of this study was to investigate the feasibility of using recycled high-density polyethylene (rHDPE), polypropylene (rPP), and agricultural residues fibers for manufacturing wood-plastic nano-composites. The effects of these materials on the mechanical properties of the composites, specifically tensile and flexural strength, were studied. Methodology: The study utilized an experimental approach where extruders and hot presses were used to fabricate the composites. Five types of cellulosic residues fibers (bagasse, corn stalk, rice straw, sunflower, and canola stem), three levels of nanomaterials (carbon nanotubes, nano silica, and nanoclay), and coupling agent were used to chemically bind the wood/polymer fibers, chemicals, and reinforcement. The mechanical properties of the composites were then analyzed. Findings: The study found that composites made with rHDPE provided moderately superior tensile and flexural properties compared to rPP samples. The addition of agricultural residues in several types of wood-plastic nano-composites significantly improved their bending and tensile properties, with bagasse having the most significant advantage over other lignocellulosic materials. The use of recycled polymers, agricultural residues, and nano-silica resulted in composites with the best strength properties. Theoretical Importance: The study's findings suggest that using agricultural fiber residues as reinforcement in wood/plastic nanocomposites is a viable approach to improve the mechanical properties of the composites. Additionally, the study highlights the potential of using recycled polymers in the development of value-added products without compromising the product's properties. Data Collection and Analysis Procedures: The study collected data on the mechanical properties of the composites using tensile and flexural tests. Statistical analyses were performed to determine the significant effects of the various materials used. Question addressed: Can agricultural residues and recycled polymers be used to manufacture wood-plastic nano-composites with enhanced mechanical properties? Conclusion: The study demonstrates the feasibility of using agricultural residues and recycled polymers in the production of wood-plastic nano-composites. The addition of these materials significantly improved the mechanical properties of the composites, with bagasse being the most effective agricultural residue. The study's findings suggest that composites made from recycled materials can offer value-added products without sacrificing performance.

Keywords: polymer, composites, wood, nano

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

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

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

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Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

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Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

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Authors: Khin Thandar Soe, Mark Stephen Pulham

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Ballistic building materials play a crucial role in ensuring the safety of the occupants within protective structures. Traditional options like Ordinary Portland Cement (OPC)-based walls, including reinforced concrete walls, precast concrete walls, masonry walls, and concrete blocks, are frequently employed for ballistic protection, but they have several drawbacks such as being thick, heavy, costly, and challenging to construct. On the other hand, glass and composite materials offer lightweight and easier construction alternatives, but they come with a high price tag. There has been no reported test data on magnesium-based ballistic wall panels or modular wall systems so far. This paper presents groundbreaking small arms test data related to the development of the world’s first magnesia cement ballistic wall panels and modular wall system. Non-hydraulic magnesia cement exhibits several superior properties, such as lighter weight, flexibility, acoustics, and fire performance, compared to the traditional Portland Cement. However, magnesia cement is hydrophilic and may degrade in prolonged contact with water. In this research, modified magnesia cement for water resistant and durability from UBIQ Technology is applied. The specimens are made of a modified magnesia cement formula and prepared in the Laboratory of UBIQ Technology Pty Ltd. The specimens vary in thickness, and the tests cover various small arms threats in compliance with standards AS/NZS2343 and UL752 and are performed up to the maximum threat level of Classification R2 (NATO) and UL-Level 8(NATO) by the Accredited Test Centre, BMT (Ballistic and Mechanical Testing, VIC, Australia). In addition, the results of the test conducted on the specimens subjected to the small 12mm diameter steel ball projectile impact generated by a gas gun are also presented and discussed in this paper. Gas gun tests were performed in UNSW@ADFA, Canberra, Australia. The tested results of the magnesia panels and wall systems are compared with one of concrete and other wall panels documented in the literature. The conclusion drawn is that magnesia panels and wall systems exhibit several advantages over traditional OPC-based wall systems, and they include being lighter, thinner, and easier to construct, all while providing equivalent protection against threats. This makes magnesia cement-based materials a compelling choice of application where efficiency and performance are critical to create a protective environment.

Keywords: ballistics, small arms, gas gun, projectile, impact, wall panels, modular, magnesia cement

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Authors: Hetvi Trivedi

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Technological escalation cannot be negated. The same is true for the benefits of technology. However, such escalation has interfered with the traditional theories of protection under Intellectual Property Rights. Out of the many trends that have disrupted the old-school understanding of Intellectual Property Rights, one is hashtags. What began modestly in the year 2007 has now earned a remarkable status, and coupled with the unprecedented rise in social media the hashtag culture has witnessed a monstrous growth. A tiny symbol on the keypad of phones or computers is now a major trend which also serves companies as a critical investment measure in establishing their brand in the market. Due to this a section of the Intellectual Property Rights- Trademarks is undergoing a humungous transformation with hashtags like #icebucket, #tbt or #smilewithacoke, getting trademark protection. So, as the traditional theories of IP take on the modern trends, it is necessary to understand the change and challenge at a theoretical and proportional level and where need be, question the change. Traditionally, Intellectual Property Rights serves the societal need for intellectual productions that ensure its holistic development as well as cultural, economic, social and technological progress. In a two-pronged effort at ensuring continuity of creativity, IPRs recognize the investment of individual efforts that go into creation by way of offering protection. Commonly placed under two major theories- Utilitarian and Natural, IPRs aim to accord protection and recognition to an individual’s creation or invention which serve as an incentive for further creations or inventions, thus fully protecting the creative, inventive or commercial labour invested in the same. In return, the creator by lending the public the access to the creation reaps various benefits. This way Intellectual Property Rights form a ‘social contract’ between the author and society. IPRs are similarly attached to a social function, whereby individual rights must be weighed against competing rights and to the farthest limit possible, both sets of rights must be treated in a balanced manner. To put it differently, both the society and the creator must be put on an equal footing with neither party’s rights subservient to the other. A close look through doctrinal research, at the recent trend of trademark protection, makes the social function of IPRs seem to be moving far from the basic philosophy. Thus, where technology interferes with the philosophies of law, it is important to check and allow such growth only in moderation, for none is superior than the other. The human expansionist nature may need everything under the sky that can be tweaked slightly to be counted and protected as Intellectual Property- like a common parlance word transformed into a hashtag, however IP in order to survive on its philosophies needs to strike a balance. A unanimous global decision on the judicious use of IPR recognition and protection is the need of the hour.

Keywords: hashtag trademarks, intellectual property, social function, technology

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Authors: Ahmad Kayvani Fard, Gordon Mckay, Muataz Hussien

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Adsorption/sorption is believed to be one of the optimal processes for the removal of heavy metals from water due to its low operational and capital cost as well as its high removal efficiency. Different materials have been reported in literature as adsorbent for heavy metal removal in waste water such as natural sorbents, organic polymers (synthetic) and mineral materials (inorganic). The selection of adsorbents and development of new functional materials that can achieve good removal of heavy metals from water is an important practice and depends on many factors, such as the availability of the material, cost of material, and material safety and etc. In this study we reported the synthesis of doped Activated carbon and Carbon nanotube (CNT) with different loading of metal oxide nanoparticles such as Fe2O3, Fe3O4, Al2O3, TiO2, SiO2 and Ag nanoparticles and their application in removal of heavy metals, hydrocarbon, and organics from waste water. Commercial AC and CNT with different loadings of mentioned nanoparticle were prepared and effect of pH, adsorbent dosage, sorption kinetic, and concentration effects are studied and optimum condition for removal of heavy metals from water is reported. The prepared composite sorbent is characterized using field emission scanning electron microscopy (FE-SEM), high transmission electron microscopy (HR-TEM), thermogravimetric analysis (TGA), X-ray diffractometer (XRD), the Brunauer, Emmett and Teller (BET) nitrogen adsorption technique, and Zeta potential. The composite materials showed higher removal efficiency and superior adsorption capacity compared to commercially available carbon based adsorbent. The specific surface area of AC increased by 50% reaching up to 2000 m2/g while the CNT specific surface area of CNT increased by more than 8 times reaching value of 890 m2/g. The increased surface area is one of the key parameters along with surface charge of the material determining the removal efficiency and removal efficiency. Moreover, the surface charge density of the impregnated CNT and AC have enhanced significantly where can benefit the adsorption process. The nanoparticles also enhance the catalytic activity of material and reduce the agglomeration and aggregation of material which provides more active site for adsorbing the contaminant from water. Some of the results for treating wastewater includes 100% removal of BTEX, arsenic, strontium, barium, phenolic compounds, and oil from water. The results obtained are promising for the use of AC and CNT loaded with metal oxide nanoparticle in treatment and pretreatment of waste water and produced water before desalination process. Adsorption can be very efficient with low energy consumption and economic feasibility.

Keywords: carbon nanotube, activated carbon, adsorption, heavy metal, water treatment

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Authors: Othman E. Othman, Amira M. Nowier, Medhat El-Denary

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Camels play an important socio-economic role within the pastoral and agricultural system in the dry and semidry zones of Asia and Africa. Camels are economically important animals in Egypt where they are dual purpose animals (meat and milk). The analysis of chemical composition of camel milk showed that the total protein contents ranged from 2.4% to 5.3% and it is divided into casein and whey proteins. The casein fraction constitutes 52% to 89% of total camel milk protein and it divided into 4 fractions namely αs1, αs2, β and κ-caseins which are encoded by four tightly genes. In spite of the important role of casein genes and the effects of their genetic polymorphisms on quantitative traits and technological properties of milk, the studies for the detection of genetic polymorphism of camel milk genes are still limited. Due to this fact, this work focused - using PCR-RFP and sequencing analysis - on the identification of genetic polymorphisms and SNPs of two casein genes in Maghrabi camel breed which is a dual purpose camel breed in Egypt. The amplified fragments at 488-bp of the camel κ-CN gene were digested with AluI endonuclease. The results showed the appearance of three different genotypes in the tested animals; CC with three digested fragments at 203-, 127- and 120-bp, TT with three digested fragments at 203-, 158- and 127-bp and CT with four digested fragments at 203-, 158-, 127- and 120-bp. The frequencies of three detected genotypes were 11.0% for CC, 48.0% for TT and 41.0% for CT genotypes. The sequencing analysis of the two different alleles declared the presence of a single nucleotide polymorphism (C→T) at position 121 in the amplified fragments which is responsible for the destruction of a restriction site (AG/CT) in allele T and resulted in the presence of two different alleles C and T in tested animals. The nucleotide sequences of κ-CN alleles C and T were submitted to GenBank with the accession numbers; KU055605 and KU055606, respectively. The primers used in this study amplified 942-bp fragments spanning from exon 4 to exon 6 of camel αS1-Casein gene. The amplified fragments were digested with two different restriction enzymes; SmlI and AluI. The results of SmlI digestion did not show any restriction site whereas the digestion with AluI endonuclease revealed the presence of two restriction sites AG^CT at positions 68^69 and 631^632 yielding the presence of three digested fragments with sizes 68-, 563- and 293-bp.The nucleotide sequences of this fragment from camel αS1-Casein gene were submitted to GenBank with the accession number KU145820. In conclusion, the genetic characterization of quantitative traits genes which are associated with the production traits like milk yield and composition is considered an important step towards the genetic improvement of livestock species through the selection of superior animals depending on the favorable alleles and genotypes; marker assisted selection (MAS).

Keywords: genetic polymorphism, SNP polymorphism, Maghrabi camels, κ-Casein gene, αS1-Casein gene

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: María Luisa Gonzalez-SanJose, Mihaela Mihnea, Vicente Gomez-Miguel

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The zoning methodology currently recommended by the OIVV as official methodology to carry out viticulture zoning studies and to define and delimit the ‘terroirs’ has been applied in this study. This methodology has been successfully applied on the most significant an important Spanish Oenological D.O. regions, such as Ribera de Duero, Rioja, Rueda and Toro, but also it have been applied around the world in Portugal, different countries of South America, and so on. This is a complex methodology that uses edaphoclimatic data but also other corresponding to vineyards and other soils’ uses The methodology is useful to determine Homogeneous Soil Units (HSU) to different scale depending on the interest of each study, and has been applied from viticulture regions to particular vineyards. It seems that this methodology is an appropriate method to delimit correctly the medium in order to enhance its uses and to obtain the best viticulture and oenological products. The present work is focused on the comparison of volatile composition of wines made from grapes grown in different HSU that coexist in a particular viticulture region of Castile-Lion cited near to Burgos. Three different HSU were selected for this study. They represented around of 50% of the global area of vineyards of the studied region. Five different vineyards on each HSU under study were chosen. To reduce variability factors, other criteria were also considered as grape variety, clone, rootstocks, vineyard’s age, training systems and cultural practices. This study was carried out during three consecutive years, then wine from three different vintage were made and analysed. Different red wines were made from grapes harvested in the different vineyards under study. Grapes were harvested to ‘Technological maturity’, which are correlated with adequate levels of sugar, acidity, phenolic content (nowadays named phenolic maturity), good sanitary stages and adequate levels of aroma precursors. Results of the volatile profile of the wines produced from grapes of each HSU showed significant differences among them pointing out a direct effect of the edaphoclimatic characteristic of each UHT on the composition of the grapes and then on the volatile composition of the wines. Variability induced by HSU co-existed with the well-known inter-annual variability correlated mainly with the specific climatic conditions of each vintage, however was most intense, so the wine of each HSU were perfectly differenced. A discriminant analysis allowed to define the volatiles with discriminant capacities which were 21 of the 74 volatiles analysed. Detected discriminant volatiles were chemical different, although .most of them were esters, followed by were superior alcohols and fatty acid of short chain. Only one lactone and two aldehydes were selected as discriminant variable, and no varietal aroma compounds were selected, which agree with the fact that all the wine were made from the same grape variety.

Keywords: viticulture zoning, terroir, wine, volatile profile

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 139

Authors: André Melo Franco Lorena De Barros, Elida Geralda Campos

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The bilingual education has just started in Brazils public schools. This paper is a didactic sequence of biology bilingual lessons about biologic control in the Brazilian Savana. This sequence has been applied in the first year of a bilingual education program in the only public English and Portuguese bilingual high school in Brazil. The aim of this work is to develop and apply a didactic sequence capable of developing the scientific literacy through the bilingual education associated with Problem Based Learning. This didactic sequence was applied in a class of 30 students. It was divided in three lessons. In the first lesson the students were divided in groups and received a fiction Letter from a mayor explaining the problem and asking students for help. The organic soy plantation of the mayor’s is been attacked by caterpillars. The students read the text then raised hypothesis of how they could solve the problem. In the second lesson the students searched online to verify if theirs hypothesis were correct and to find answers for the question proposed. In the third lesson the groups got together and discussed about their results and wrote a final essay with the answers for the problem proposed. The tools used to acquire information about the didactic sequence were: researcher’s diary, survey, interview and essay developed by the students. Most of the initial hypothesis couldn’t answer the problem properly. By the second lesson most of the students could answer properly. During the third lesson all the groups figured out suitable answers. The forms of biological control, birds habits and transgenic were deeply studied by the students. This methodology was successful for developing the scientific literacy with most of the students and also concluded that the quality of learning is directly associated with the effort of each student during the process. [ARAÚJO, Denise Lino de. O que é (e como se faz) sequência didática. Entrepalavras, Fortaleza, v. 3, n. 3, p.322-334, jul. 2013.] [FRANCO, Aline Aparecida et al. Preferência alimentar de Anticarsia gemmatalis Hübner (Lepidoptera: Noctuidae) por cultivares de soja. Científica: Revista de Ciências Agrárias, Jaboticabal, v. 1, n. 42, p.32-38, 29 jan. 2014.] [RIBEIRO, Luis Roberto de Camargo. Aprendizagem baseada em problemas (PBL): Uma experiência no ensino superior. São Carlos: Editora da Universidade Federal de São Carlos Ribeiro, 2008. 151 p.] [TRIVELATO, Sílvia L. Frateschi; TONIDANDEL, Sandra M. Rudella. Ensino Por Investigação: Eixos Organizadores Para Sequências De Ensino De Biologia. Ensaio Pesquisa em Educação em Ciências, Belo Horizonte, v. 17, n. especial, p.97-114, nov. 2015.].

Keywords: Bilingual Education, Environmental Education, Problem Based Learning, Science education

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Authors: A. J. Cobley, L. Krishnan

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The demand for multi-functional lightweight materials in sectors such as automotive, aerospace, electronics is growing, and for this reason fibre-reinforced, epoxy polymer composites are being widely utilized. The fibre reinforcing material is mainly responsible for the strength and stiffness of the composites whilst the main role of the epoxy polymer matrix is to enhance the load distribution applied on the fibres as well as to protect the fibres from the effect of harmful environmental conditions. The superior properties of the fibre-reinforced composites are achieved by the best properties of both of the constituents. Although factors such as the chemical nature of the epoxy and how it is cured will have a strong influence on the properties of the epoxy matrix, the method of mixing and degassing of the resin can also have a significant impact. The production of a fibre-reinforced epoxy polymer composite will usually begin with the mixing of the epoxy pre-polymer with a hardener and accelerator. Mechanical methods of mixing are often employed for this stage but such processes naturally introduce air into the mixture, which, if it becomes entrapped, will lead to voids in the subsequent cured polymer. Therefore, degassing is normally utilised after mixing and this is often achieved by placing the epoxy resin mixture in a vacuum chamber. Although this is reasonably effective, it is another process stage and if a method of mixing could be found that, at the same time, degassed the resin mixture this would lead to shorter production times, more effective degassing and less voids in the final polymer. In this study the effect of four different methods for mixing and degassing of the pre-polymer with hardener and accelerator were investigated. The first two methods were manual stirring and magnetic stirring which were both followed by vacuum degassing. The other two techniques were ultrasonic mixing/degassing using a 40 kHz ultrasonic bath and a 20 kHz ultrasonic probe. The cured cast resin samples were examined under scanning electron microscope (SEM), optical microscope, and Image J analysis software to study morphological changes, void content and void distribution. Three point bending test and differential scanning calorimetry (DSC) were also performed to determine the thermal and mechanical properties of the cured resin. It was found that the use of the 20 kHz ultrasonic probe for mixing/degassing gave the lowest percentage voids of all the mixing methods in the study. In addition, the percentage voids found when employing a 40 kHz ultrasonic bath to mix/degas the epoxy polymer mixture was only slightly higher than when magnetic stirrer mixing followed by vacuum degassing was utilized. The effect of ultrasonic mixing/degassing on the thermal and mechanical properties of the cured resin will also be reported. The results suggest that low frequency ultrasound is an effective means of mixing/degassing a pre-polymer mixture and could enable a significant reduction in production times.

Keywords: degassing, low frequency ultrasound, polymer composites, voids

Procedia PDF Downloads 277

Authors: N. Demertzis, J. L. Bowen

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Sepsis is a complex and rapidly evolving condition, resulting from uncontrolled prolonged activation of host immune system due to pathogenic insult. The aim of this study is the development of a multiplex electrochemical sensing platform, capable of detecting both pathogen associated and host immune markers to enable the rapid and definitive diagnosis of sepsis. A combination of aptamers and molecular imprinting approaches have been employed to generate sensing systems for lipopolysaccharide (LPS), c-reactive protein (CRP) and procalcitonin (PCT). Gold working electrodes were mechanically polished and electrochemically cleaned with 0.1 M sulphuric acid using cyclic voltammetry (CV). Following activation, a self-assembled monolayer (SAM) was generated, by incubating the electrodes with a thiolated anti-LPS aptamer / dithiodibutiric acid (DTBA) mixture (1:20). 3-aminophenylboronic acid (3-APBA) in combination with the anti-LPS aptamer was used for the development of the hybrid molecularly imprinted sensor (apta-MIP). Aptasensors, targeting PCT and CRP were also fabricated, following the same approach as in the case of LPS, with mercaptohexanol (MCH) replacing DTBA. In the case of the CRP aptasensor, the SAM was formed following incubation of a 1:1 aptamer: MCH mixture. However, in the case of PCT, the SAM was formed with the aptamer itself, with subsequent backfilling with 1 μM MCH. The binding performance of all systems has been evaluated using electrochemical impedance spectroscopy. The apta-MIP’s polymer thickness is controlled by varying the number of electropolymerisation cycles. In the ideal number of polymerisation cycles, the polymer must cover the electrode surface and create a binding pocket around LPS and its aptamer binding site. Less polymerisation cycles will create a hybrid system which resembles an aptasensor, while more cycles will be able to cover the complex and demonstrate a bulk polymer-like behaviour. Both aptasensor and apta-MIP were challenged with LPS and compared to conventional imprinted (absence of aptamer from the binding site, polymer formed in presence of LPS) and non-imprinted polymers (NIPS, absence of LPS whilst hybrid polymer is formed). A stable LPS aptasensor, capable of detecting down to 5 pg/ml of LPS was generated. The apparent Kd of the system was estimated at 17 pM, with a Bmax of approximately 50 pM. The aptasensor demonstrated high specificity to LPS. The apta-MIP demonstrated superior recognition properties with a limit of detection of 1 fg/ml and a Bmax of 100 pg/ml. The CRP and PCT aptasensors were both able to detect down to 5 pg/ml. Whilst full binding performance is currently being evaluated, there is none of the sensors demonstrate cross-reactivity towards LPS, CRP or PCT. In conclusion, stable aptasensors capable of detecting LPS, PCT and CRP at low concentrations have been generated. The realisation of a multiplex panel such as described herein, will effectively contribute to the rapid, personalised diagnosis of sepsis.

Keywords: aptamer, electrochemical impedance spectroscopy, molecularly imprinted polymers, sepsis

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Authors: Kumlachew Zelalem Walle, Chun-Chen Yang

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Solid-state lithium metal batteries (SSLMBs) are considered promising candidates for next-generation energy storage devices due to their superior energy density and excellent safety. However, recent findings have shown that the formation of lithium (Li) dendrites in SSLMBs still exhibits a terrible growth ability, which makes the development of SSLMBs have to face the challenges posed by the Li dendrite problem. In this work, an inorganic/organic mixture coating material (g-C3N4/ZIF-8/PVDF) was used to modify the surface of lithium metal anode (LMA). Then the modified LMA (denoted as g-C₃N₄@Li) was assembled with lithium nafion (LiNf) coated commercial NCM811 (LiNf@NCM811) using a bilayer hybrid solid electrolyte (Bi-HSE) that incorporated 20 wt.% (vs. polymer) LiNf coated Li6.05Ga0.25La3Zr2O11.8F0.2 ([email protected]) filler faced to the positive electrode and the other layer with 80 wt.% (vs. polymer) filler content faced to the g-C₃N₄@Li. The garnet-type Li6.05Ga0.25La3Zr2O11.8F0.2 (LG0.25LZOF) solid electrolyte was prepared via co-precipitation reaction process from Taylor flow reactor and modified using lithium nafion (LiNf), a Li-ion conducting polymer. The Bi-HSE exhibited high ionic conductivity of 6.8  10–4 S cm–1 at room temperature, and a wide electrochemical window (0–5.0 V vs. Li/Li+). The coin cell was charged between 2.8 to 4.5 V at 0.2C and delivered an initial specific discharge capacity of 194.3 mAh g–1 and after 100 cycles it maintained 81.8% of its initial capacity at room temperature. The presence of a nano-sheet g-C3N4/ZIF-8/PVDF as a composite coating material on the LMA surface suppress the dendrite growth and enhance the compatibility as well as the interfacial contact between anode/electrolyte membrane. The g-C3N4@Li symmetrical cells incorporating this hybrid electrolyte possessed excellent interfacial stability over 1000 h at 0.1 mA cm–2 and a high critical current density (1 mA cm–2). Moreover, the in-situ formation of Li3N on the solid electrolyte interface (SEI) layer as depicted from the XPS result also improves the ionic conductivity and interface contact during the charge/discharge process. Therefore, these novel multi-layered fabrication strategies of hybrid/composite solid electrolyte membranes and modification of the LMA surface using mixed coating materials have potential applications in the preparation of highly safe high-voltage cathodes for SSLMBs.

Keywords: high-voltage cathodes, hybrid solid electrolytes, garnet, graphitic-carbon nitride (g-C3N4), ZIF-8 MOF

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Authors: Luke Miller

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This paper develops an options pricing methodology to value strategic pricing strategies in the services sector. More specifically, this study provides a unifying taxonomy of current service sector pricing practices, frames these pricing decisions as strategic real options, demonstrates accepted option valuation techniques to assess service sector pricing decisions, and suggests future research areas where pricing decisions and real options overlap. Enhancing revenue in the service sector requires proactive decision making in a world of uncertainty. In an effort to strategically price service products, revenue enhancement necessitates a careful study of the service costs, customer base, competition, legalities, and shared economies with the market. Pricing decisions involve the quality of inputs, manpower, and best practices to maintain superior service. These decisions further hinge on identifying relevant pricing strategies and understanding how these strategies impact a firm’s value. A relatively new area of research applies option pricing theory to investments in real assets and is commonly known as real options. The real options approach is based on the premise that many corporate decisions to invest or divest in assets are simply an option wherein the firm has the right to make an investment without any obligation to act. The decision maker, therefore, has more flexibility and the value of this operating flexibility should be taken into consideration. The real options framework has already been applied to numerous areas including manufacturing, inventory, natural resources, research and development, strategic decisions, technology, and stock valuation. Additionally, numerous surveys have identified a growing need for the real options decision framework within all areas of corporate decision-making. Despite the wide applicability of real options, no study has been carried out linking service sector pricing decisions and real options. This is surprising given the service sector comprises 80% of the US employment and Gross Domestic Product (GDP). Identifying real options as a practical tool to value different service sector pricing strategies is believed to have a significant impact on firm decisions. This paper identifies and discusses four distinct pricing strategies available to the service sector from an options’ perspective: (1) Cost-based profit margin, (2) Increased customer base, (3) Platform pricing, and (4) Buffet pricing. Within each strategy lie several pricing tactics available to the service firm. These tactics can be viewed as options the decision maker has to best manage a strategic position in the market. To demonstrate the effectiveness of including flexibility in the pricing decision, a series of pricing strategies were developed and valued using a real options binomial lattice structure. The options pricing approach discussed in this study allows service firms to directly incorporate market-driven perspectives into the decision process and thus synchronizing service operations with organizational economic goals.

Keywords: option pricing theory, real options, service sector, valuation

Procedia PDF Downloads 331

Authors: Belgheis Ebrahimi, Jun Lu

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In recent years, there has been a growing recognition of the potential of marine-based functional foods and combination therapies in promoting a healthy lifestyle and exploring their effectiveness in preventing or treating diseases. The combination of marine bioactive compounds or extracts offers synergistic or enhancement effects through various mechanisms, including multi-target actions, improved bioavailability, enhanced bioactivity, and mitigation of potential adverse effects. Both the green-lipped mussel (GLM) and fucoidan derived from brown seaweed are rich in bioactivities. These two, mussel and fucoidan, have not been previously formulated together. This study aims to combine GLM oil from Perna canaliculus with low molecular weight fucoidan (LMWF) extracted from Undaria pinnatifida to investigate the unique mixture’s anti-inflammatory and antioxidant properties. The cytotoxicity of individual compounds and combinations was assessed using the MTT assay in (THP-1 and RAW264.7) cell lines. The anti-inflammatory activity of mussel-fucoidan was evaluated by treating LPS-stimulated human monocyte and macrophage (THP1-1) cells. Subsequently, the inflammatory cytokines released into the supernatant of these cell lines were quantified via ELISA. Antioxidant activity was determined by using the free radical scavenging assay (DPPH). DPPH assay demonstrated that the radical scavenging activity of the combinations, particularly at concentrations exceeding 1 mg/ml, showed a significantly higher percentage of inhibition when compared to the individual component. This suggests an enhancement effect when the two compounds are combined, leading to increased antioxidant activity. In terms of immunomodulatory activity, the individual compounds exhibited distinct behaviors. GLM oil displayed a higher ability to suppress the cytokine TNF- compared to LMWF. Interestingly, the LMWF fraction, when used individually, did not demonstrate TNF- suppression. However, when combined with GLM, the TNF- suppression (anti-inflammatory) activity of the combination was better than GLM or LWMF alone. This observation underscores the potential for enhancement interactions between the two components in terms of anti-inflammatory properties. This study revealed that each individual compound, LMWF, and GLM, possesses unique and notable bioactivity. The combination of these two individual compounds results in an enhancement effect, where the bioactivity of each is enhanced, creating a superior combination. This suggests that the combination of LMWF and GLM has the potential to offer a more potent and multifaceted therapeutic effect, particularly in the context of antioxidant and anti-inflammatory activities. These findings hold promise for the development of novel therapeutic interventions or supplements that harness the enhancement effects.

Keywords: combination, enhancement effect, perna canaliculus, undaria pinnatifida

Procedia PDF Downloads 55

Authors: Yuan Yue, Wen-Wei Wang

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The objective of this research is to comprehensively evaluate the impact of alkaline environments on the durability of Glass Fiber Reinforced Polymer (GFRP) reinforcements in concrete structures and further explore their potential value within the construction industry. Specifically, we investigate the effects of two widely used high-performance concrete (HPC) materials on the durability of GFRP bars when embedded within them under varying temperature conditions. A total of 279 GFRP bar specimens were manufactured for microcosmic and mechanical performance tests. Among them, 270 specimens were used to test the residual tensile strength after 120 days of immersion, while 9 specimens were utilized for microscopic testing to analyze degradation damage. SEM techniques were employed to examine the microstructure of GFRP and cover concrete. Unidirectional tensile strength experiments were conducted to determine the remaining tensile strength after corrosion. The experimental variables consisted of four types of concrete (engineering cementitious composite (ECC), ultra-high-performance concrete (UHPC), and two types of ordinary concrete with different compressive strengths) as well as three acceleration temperatures (20, 40, and 60℃). The experimental results demonstrate that high-performance concrete (HPC) offers superior protection for GFRP bars compared to ordinary concrete. Two types of HPC enhance durability through different mechanisms: one by reducing the pH of the concrete pore fluid and the other by decreasing permeability. For instance, ECC improves embedded GFRP's durability by lowering the pH of the pore fluid. After 120 days of immersion at 60°C under accelerated conditions, ECC (pH=11.5) retained 68.99% of its strength, while PC1 (pH=13.5) retained 54.88%. On the other hand, UHPC enhances FRP steel's durability by increasing porosity and compactness in its protective layer to reinforce FRP reinforcement's longevity. Due to fillers present in UHPC, it typically exhibits lower porosity, higher densities, and greater resistance to permeation compared to PC2 with similar pore fluid pH levels, resulting in varying degrees of durability for GFRP bars embedded in UHPC and PC2 after 120 days of immersion at a temperature of 60°C - with residual strengths being 66.32% and 60.89%, respectively. Furthermore, SEM analysis revealed no noticeable evidence indicating fiber deterioration in any examined specimens, thus suggesting that uneven stress distribution resulting from interface segregation and matrix damage emerges as a primary causative factor for tensile strength reduction in GFRP rather than fiber corrosion. Moreover, long-term prediction models were utilized to calculate residual strength values over time for reinforcement embedded in HPC under high temperature and high humidity conditions - demonstrating that approximately 75% of its initial strength was retained by reinforcement embedded in HPC after 100 years of service.

Keywords: GFRP bars, HPC, degeneration, durability, residual tensile strength.

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Authors: Min Han, Di Wu, Lin Yuan, Fei Liu

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Mechanical sensors have undergone a continuous evolution and have become an important part of many industries, ranging from manufacturing to process, chemicals, machinery, health-care, environmental monitoring, automotive, avionics, and household appliances. Concurrently, the microelectronics and microfabrication technology have provided us with the means of producing mechanical microsensors characterized by high sensitivity, small size, integrated electronics, on board calibration, and low cost. Here we report a new kind of mechanical sensors based on the quantum transport process of electrons in the closely spaced nanoparticle films covering a flexible polymer sheet. The nanoparticle films were fabricated by gas phase depositing of preformed metal nanoparticles with a controlled coverage on the electrodes. To amplify the conductance of the nanoparticle array, we fabricated silver interdigital electrodes on polyethylene terephthalate(PET) by mask evaporation deposition. The gaps of the electrodes ranged from 3 to 30μm. Metal nanoparticles were generated from a magnetron plasma gas aggregation cluster source and deposited on the interdigital electrodes. Closely spaced nanoparticle arrays with different coverage could be gained through real-time monitoring the conductance. In the film coulomb blockade and quantum, tunneling/hopping dominate the electronic conduction mechanism. The basic principle of the mechanical sensors relies on the mechanical deformation of the fabricated devices which are translated into electrical signals. Several kinds of sensing devices have been explored. As a strain sensor, the device showed a high sensitivity as well as a very wide dynamic range. A gauge factor as large as 100 or more was demonstrated, which can be at least one order of magnitude higher than that of the conventional metal foil gauges or even better than that of the semiconductor-based gauges with a workable maximum applied strain beyond 3%. And the strain sensors have a workable maximum applied strain larger than 3%. They provide the potential to be a new generation of strain sensors with performance superior to that of the currently existing strain sensors including metallic strain gauges and semiconductor strain gauges. When integrated into a pressure gauge, the devices demonstrated the ability to measure tiny pressure change as small as 20Pa near the atmospheric pressure. Quantitative vibration measurements were realized on a free-standing cantilever structure fabricated with closely-spaced nanoparticle array sensing element. What is more, the mechanical sensor elements can be easily scaled down, which is feasible for MEMS and NEMS applications.

Keywords: gas phase deposition, mechanical sensors, metallic nanoparticle arrays, quantum conductance

Procedia PDF Downloads 256

Authors: Zhuoran Li, Guan Qin

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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.

Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method

Procedia PDF Downloads 151

Authors: Adamu Usman, Grace Stanley Balami

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Pearl millet (Pennisetum glaucum L. R. Br.) is a cereal cultivated in arid and semi-arid areas of the world. It supports more than 100 million people around the world. Parasitic weed (Striga hermonthica Del. Benth) is a major constraint to its production. Estimated yield losses are put at 10 - 95% depending on variety, ecology and cultural practices. Potentials in selection of traits in pearl millets for grain yield have been reported and it depends on genotypic variability and heritability among landraces. Variability and heritability among cultivars could offer opportunities for improvement. The study was conducted to determine the genetic variability among cultivars and estimate broad sense heritability among grain yield and related traits. F1 breeding populations were generated with 9 parental cultivars, viz; Ex-Gubio, Ex-Monguno, Ex-Baga as males and PEO 5984, Super-SOSAT, SOSAT-C88, Ex-Borno and LCIC9702 as females through Line × Tester mating during 2017 dry season at Lushi Irrigation Station, Bauchi Metropolitan in Bauchi State, Nigeria. The F1 population and the parents were evaluated during cropping season of 2018 at Bauchi and Maiduguri. Data collected were subjected to analysis of variance. Results showed significant difference among cultivars and among traits indicating variability. Number of plants at emergence, days to 50% flowering, days to 100% flowering, plant height, panicle length, number of plants at harvest, Striga count at 90 days after sowing, panicle weight and grain yield were significantly different. Significant variability offer opportunity for improvement as superior individuals can be isolated. Genotypic variance estimates of traits were largely greater than environmental variances except in plant height and 1000 seed weight. Environmental variances were low and in some cases negligible. The phenotypic variances of all traits were higher than genotypic variances. Similarly phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV). High heritability was found in days to 50% flowering (90.27%), Striga count at 90 days after sowing (90.07%), number of plants at harvest (87.97%), days to 100% flowering (83.89%), number of plants at emergence (82.19%) and plant height (73.18%). Greater heritability estimates could be due to presence of additive gene. The result revealed wider variability among genotypes and traits. Traits having high heritability could easily respond to selection. High value of GCV, PCV and heritability estimates indicate that selection for these traits are possible and could be effective.

Keywords: variability, heritability, phenotypic, genotypic, striga

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Authors: Nejoud Alostad, Anup Bora, Prashant Dhote

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Kuwait Oil Company (KOC) has been producing from its major reservoirs that are well defined and highly productive and of superior reservoir quality. These reservoirs are maturing and priority is shifting towards difficult reservoir to meet future production requirements. This paper discusses the results of the detailed integrated study for one of the satellite complex field discovered in the early 1960s. Following acquisition of new 3D seismic data in 1998 and re-processing work in the year 2006, an integrated G&G study was undertaken to review Lower Cretaceous prospectivity of this reservoir. Nine wells have been drilled in the area, till date with only three wells showing hydrocarbons in two formations. The average oil density is around 300API (American Petroleum Institute), and average porosity and water saturation of the reservoir is about 23% and 26%, respectively. The area is dissected by a number of NW-SE trending faults. Structurally, the area consists of horsts and grabens bounded by these faults and hence compartmentalized. The Wara/Burgan formation consists of discrete, dirty sands with clean channel sand complexes. There is a dramatic change in Upper Wara distributary channel facies, and reservoir quality of Wara and Burgan section varies with change of facies over the area. So predicting reservoir facies and its quality out of sparse well data is a major challenge for delineating the prospective area. To characterize the reservoir of Wara/Burgan formation, an integrated workflow involving seismic, well, petro-physical, reservoir and production engineering data has been used. Porosity and water saturation models are prepared and analyzed to predict reservoir quality of Wara and Burgan 3rd sand upper reservoirs. Subsequently, boundary conditions are defined for reservoir and non-reservoir facies by integrating facies, porosity and water saturation. Based on the detailed analyses of volumetric parameters, potential volumes of stock-tank oil initially in place (STOIIP) and gas initially in place (GIIP) were documented after running several probablistic sensitivity analysis using Montecalro simulation method. Sensitivity analysis on probabilistic models of reservoir horizons, petro-physical properties, and oil-water contacts and their effect on reserve clearly shows some alteration in the reservoir geometry. All these parameters have significant effect on the oil in place. This study has helped to identify uncertainty and risks of this prospect particularly and company is planning to develop this area with drilling of new wells.

Keywords: original oil-in-place, sensitivity, uncertainty, sandstone, reservoir modeling, Monte-Carlo simulation

Procedia PDF Downloads 174

Authors: Tiffanie-Marie Borg, Yasmin Zeinolabediny, Nima Heidari, Ali Noorani, Mark Slevin, Angel Cullen, Stefano Olgiati, Alberto Zerbi, Alessandro Danovi, Adrian Wilson

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Knee Osteoarthritis (OA) is a critical cause of disability globally. In recent years, there has been growing interest in non-invasive treatments, such as intra-articular injection of micro-fragmented fat (MFAT), showing great potential in treating OA. Mesenchymal stem cells (MSCs), originating from pericytes of micro-vessels in MFAT, can differentiate into mesenchymal lineage cells such as cartilage, osteocytes, adipocytes, and osteoblasts. Secretion of growth factor and cytokines from MSCs have the capability to inhibit T cell growth, reduced pain and inflammation, and create a micro-environment that through paracrine signaling, can promote joint repair and cartilage regeneration. Here we have shown, for the first time, data supporting the hypothesis that women respond better in terms of improvements in pain and function to MFAT injection compared to men. Historically, women have been underrepresented in studies, and studies with both sexes regularly fail to analyse the results by sex. To mitigate this bias and quantify it, we describe a technique using reproducible statistical analysis and replicable results with Open Access statistical software R to calculate the magnitude of this difference. Genetic, hormonal, environmental, and age factors play a role in our observed difference between the sexes. This observational, intention-to-treat study included the complete sample of 456 patients who agreed to be scored for pain (visual analogue scale (VAS)) and function (Oxford knee score (OKS)) at baseline regardless of subsequent changes to adherence or status during follow-up. We report that a significantly larger number of women responded to treatment than men: [90% vs. 60% change in VAS scores with 87% vs. 65% change in OKS scores, respectively]. Women overall had a stronger positive response to treatment with reduced pain and improved mobility and function. Pre-injection, our cohort of women were in more pain with worse joint function which is quite common to see in orthopaedics. However, during the 2-year follow-up, they consistently maintained a lower incidence of discomfort with superior joint function. This data clearly identifies a clear need for further studies to identify the cell and molecular biological and other basis for these differences and be able to utilize this information for stratification in order to improve outcome for both women and men.

Keywords: gender differences, micro-fragmented adipose tissue, knee osteoarthritis, stem cells

Procedia PDF Downloads 169

Authors: Abid Hussain, Binay Kumar

Abstract:

Environment-friendly lead-free Na₀.₅₂K₀.₄₄Li₀.₀₄Nb₀.₈₄Ta₀.₁₀Sb₀.₀₆O₃ (NKLNTS) ceramic was synthesized by solid-state reaction method in search of a potential candidate to replace lead-based ceramics such as PbZrO₃-PbTiO₃ (PZT), Pb(Mg₁/₃Nb₂/₃)O₃-PbTiO₃ (PMN-PT) etc., for various applications. The ceramic was calcined at temperature 850 ᵒC and sintered at 1090 ᵒC. The powder X-Ray Diffraction (XRD) pattern revealed the formation of pure perovskite phase having tetragonal symmetry with space group P4mm of the synthesized ceramic. The surface morphology of the ceramic was studied using Field Emission Scanning Electron Microscopy (FESEM) technique. The well-defined grains with homogeneous microstructure were observed. The average grain size was found to be ~ 0.6 µm. A very large value of piezoelectric charge coefficient (d₃₃ ~ 754 pm/V) was obtained for the synthesized ceramic which indicated its potential for use in transducers and actuators. In dielectric measurements, a high value of ferroelectric to paraelectric phase transition temperature (Tm~305 ᵒC), a high value of maximum dielectric permittivity ~ 2110 (at 1 kHz) and a very small value of dielectric loss ( < 0.6) were obtained which suggested the utility of NKLNTS ceramic in high-temperature ferroelectric devices. Also, the degree of diffuseness (γ) was found to be 1.61 which confirmed a relaxor ferroelectric behavior in NKLNTS ceramic. P-E hysteresis loop was traced and the value of spontaneous polarization was found to be ~11μC/cm² at room temperature. The pyroelectric coefficient was obtained to be very high (p ∼ 1870 μCm⁻² ᵒC⁻¹) for the present case indicating its applicability in pyroelectric detector applications including fire and burglar alarms, infrared imaging, etc. NKLNTS ceramic showed fatigue free behavior over 107 switching cycles. Remanent hysteresis task was performed to determine the true-remanent (or intrinsic) polarization of NKLNTS ceramic by eliminating non-switchable components which showed that a major portion (83.10 %) of the remanent polarization (Pr) is switchable in the sample which makes NKLNTS ceramic a suitable material for memory switching devices applications. Time-Dependent Compensated (TDC) hysteresis task was carried out which revealed resistive leakage free nature of the ceramic. The performance of NKLNTS ceramic was found to be superior to many lead based piezoceramics and hence can effectively replace them for use in piezoelectric, pyroelectric and long duration ferroelectric applications.

Keywords: dielectric properties, ferroelectric properties , lead free ceramic, piezoelectric property, solid state reaction, true-remanent polarization

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Authors: Andrea Dragu, Solen Kinayyigit, Valerie Colliere, Karin Karin Philippot, Camelia Bala, Vasile I. Parvulescu

Abstract:

The production of transportation fuels from biomass has gained a growing attention due to diminishing fossil fuel reserves, rising petroleum prices and increasing concern about global warming. In recent years, renewable hydrocarbons that are completely fungible with fossil fuels have been suggested to be efficiently produced by catalytic deoxygenation of fatty acids and their derivatives viadecarboxylation / decarbonylation. Several triglycerides (tall oil fatty acids) and saturated/unsaturated fatty acids and their corresponding esters were used as feedstocks. Their impact together with the influence of the reaction conditions and the catalyst composition on the nature of the reaction pathways of the deoxygenation of vegetable oils and their derivatives were recently reviewed. Following this state of the art the aim of the present study was the investigation of Pd NPs deposited onto mesoporous carbon supports as active and stable catalysts for the deoxygenation of oleic acid. The catalysts were prepared by the deposition of Pd NPs synthesised following an organometallic route on mesoporous carbons with different characteristics. Experiments were carried out under both batch and flow conditions. They demonstrated that under batch conditions (200 atm; 573K), the extent of the reaction depended, firstly, on the Pd loading and then on the metal dispersion and the oxidation state of palladium, both influenced by the way the support has been treated before the NPs deposition and by the preparation/stabilization methodology of Pd NPs. No aromatic compounds were detected in the reaction products but octadecanol and octadecane were observed in large extents. Under flow conditions (4 atm; 573 K), the conversion of stearic acid was superior to that observed in batch conditions. The product mixture contained over 20% heptadecane. No octadecanol, octadecane, and aromatic compounds were detected. The maxima in performances are obtained after only 0.5 h. After that, the yields in heptadecane suffer from a severe decrease until 3h reaction time. However, at that time, stopping feeding the reactor with oleic acid and flushing the catalyst only with mesitylene recovered the activity and the selectivity of the catalysts. With the complete removal of H2, the analysis revealed the presence of heptadecene in high excess compared to heptadecane (almost 7 to 1), thus suggesting decarbonylation as the main route. ICP-OES measurements indicated no leaching of palladium and simple washing of catalysts with mesitylene allowed recycling without any change in conversion or product distribution. Noteworthy, mesitylene as solvent exhibited no effect in this reaction. In conclusion, this study demonstrates the feasibility of such catalysts for the green production of fuels from biomass.

Keywords: fuels from biomass, green catalyst, Pd nano-particles , recycble catalyst

Procedia PDF Downloads 286

Authors: Natalie A. Sterk, Bernard van Vuuren, Petrie Marais, Bongani Mthombeni

Abstract:

Injuries to the internal structures of the thorax and abdomen remain a leading cause of death among soldiers. Body armour is a standard issue piece of military equipment designed to protect the vital organs against ballistic and stab threats. When configured for maximum protection, the excessive weight and size of the armour may limit soldier mobility and increase physical fatigue and discomfort. Providing soldiers with more armour than necessary may, therefore, hinder their ability to react rapidly in life-threatening situations. The capability to determine the optimal trade-off between the amount of essential anatomical coverage and hindrance on soldier performance may significantly enhance the design of armour systems. The current study aimed to develop and pilot a methodology for relating internal anatomical structures with actual armour plate coverage in real-time using low-dose diagnostic X-ray scanning. Several pilot scanning sessions were held at Lodox Systems (Pty) Ltd head-office in South Africa. Testing involved using the Lodox eXero-dr to scan dummy trunk rigs at various degrees and heights of measurement; as well as human participants, wearing correctly fitted body armour while positioned in supine, prone shooting, seated and kneeling shooting postures. The verification of sizing and metrics obtained from the Lodox eXero-dr were then confirmed through a verification board with known dimensions. Results indicated that the low-dose diagnostic X-ray has the capability to clearly identify the vital internal structures of the aortic arch, heart, and lungs in relation to the position of the external armour plates. Further testing is still required in order to fully and accurately identify the inferior liver boundary, inferior vena cava, and spleen. The scans produced in the supine, prone, and seated postures provided superior image quality over the kneeling posture. The X-ray-source and-detector distance from the object must be standardised to control for possible magnification changes and for comparison purposes. To account for this, specific scanning heights and angles were identified to allow for parallel scanning of relevant areas. The low-dose diagnostic X-ray provides a non-invasive, safe, and rapid technique for relating vital internal structures with external structures. This capability can be used for the re-evaluation of anatomical coverage required for essential protection while optimising armour design and fit for soldier performance.

Keywords: body armour, low-dose diagnostic X-ray, scanning, vital organ coverage

Procedia PDF Downloads 101

Authors: Peter J. Fusco, Dave M. Mathew, Chris Mathew, Kenneth H. Levy, Kathryn S. Varghese, Stephanie Salazar-Restrepo, Serena M. Mathew, Sofia Khaja, Eamon Vega, Mia Polizzi, Alyssa Mullane, Adham Ahmed

Abstract:

Background: Laparoscopic (LS) removal of neuroblastomas in children has been reported to offer favorable outcomes compared to the conventional open thoracotomy (OT) procedure. Critical perioperative measures such as blood loss, operative time, length of stay, and time to postoperative chemotherapy have all supported laparoscopic use rather than its more invasive counterpart. Herein, a pairwise meta-analysis was performed comparing perioperative outcomes between LS and OT in thoracoabdominal neuroblastoma cases. Methods: A comprehensive literature search was performed on PubMed, Ovid EMBASE, and Scopus databases to identify studies comparing the outcomes of pediatric patients with thoracoabdominal neuroblastomas undergoing resection via OT or LS. After deduplication, 4,227 studies were identified and subjected to initial title screening with exclusion and inclusion criteria to ensure relevance. When studies contained overlapping cohorts, only the larger series were included. Primary outcomes include estimated blood loss (EBL), hospital length of stay (LOS), and mortality, while secondary outcomes were tumor recurrence, post-operative complications, and operation length. The “meta” and “metafor” packages were used in R, version 4.0.2, to pool risk ratios (RR) or standardized mean differences (SMD) in addition to their 95% confidence intervals in the random effects model via the Mantel-Haenszel method. Heterogeneity between studies was assessed using the I² test, while publication bias was assessed via funnel plot. Results: The pooled analysis included 209 patients from 5 studies (141 OT, 68 LS). Of the included studies, 2 originated from the United States, 1 from Toronto, 1 from China, and 1was from a Japanese center. Mean age between study cohorts ranged from 2.4 to 5.3 years old, with female patients occupying between 30.8% to 50% of the study populations. No statistically significant difference was found between the two groups for LOS (SMD -1.02; p=0.083), mortality (RR 0.30; p=0.251), recurrence(RR 0.31; p=0.162), post-operative complications (RR 0.73; p=0.732), or operation length (SMD -0.07; p=0.648). Of note, LS appeared to be protective in the analysis for EBL, although it did not reach statistical significance (SMD -0.4174; p= 0.051). Conclusion: Despite promising literature assessing LS removal of pediatric neuroblastomas, results showed it was non-superior to OT for any explored perioperative outcomes. Given the limited comparative data on the subject, it is evident that randomized trials are necessary to further the efficacy of the conclusions reached.

Keywords: laparoscopy, neuroblastoma, thoracoabdominal, thoracotomy

Procedia PDF Downloads 108