Search results for: features comparison

Authors: Majid Yazdandoust

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This study, tries to suggest a design method based on displacement using finite difference numerical modeling in reinforcing soil retaining wall with steel strip. In this case, dynamic loading characteristics such as duration, frequency, peak ground acceleration, geometrical characteristics of reinforced soil structure and type of the site are considered to correct the pseudo static method and finally introduce the pseudo static coefficient as a function of seismic performance level and peak ground acceleration. For this purpose, the influence of dynamic loading characteristics, reinforcement length, height of reinforced system and type of the site are investigated on seismic behavior of reinforcing soil retaining wall with steel strip. Numerical results illustrate that the seismic response of this type of wall is highly dependent to cumulative absolute velocity, maximum acceleration, and height and reinforcement length so that the reinforcement length can be introduced as the main factor in shape of failure. Considering the loading parameters, mechanically stabilized earth wall parameters and type of the site showed that the used method in this study leads to most efficient designs in comparison with other methods which are generally suggested in cods that are usually based on limit-equilibrium concept. The outputs show the over-estimation of equilibrium design methods in comparison with proposed displacement based methods here.

Keywords: pseudo static coefficient, seismic performance design, numerical modeling, steel strip reinforcement, retaining walls, cumulative absolute velocity, failure shape

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Authors: Akbar Nawaz Khan, Abdul Ghaffar, Abdur Rehman, Muhammad Naeem Riaz, Sayed Muhammad Hassan Andrabi

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The present study was conducted to compare sheep rearing in nomadic with transhumance system in term of production parameters. The following parameters which studied for comparison were household size, landholding area, flock size, body condition score, fecal egg count and live weight change in sheep under nomadic and transhumance systems of management in Malakand since October 2010 to March 2011. Further the effects of Body Condition Score (BCS) and Fecal Egg Count (FEC) on production were also examined. Two systems were checked for the purpose to check the efficiency of production. A total of eight flocks, four each from nomadic and transhumance system were selected for the study; each flock was divided into treatment and controlled groups to check the effect of treatment or de-wormers. A total of 160 animals were selected randomly (80 treated, 80 controlled). The adult ram average weight transhumance system was 55.58 kg while in nomadic that was 54.16 kg, weight change was positive, and the highest change was recorded in transhumance treated which was 13%. Fecal egg count was record low (75 EPG) in transhumance treated group while high (330 EPG) in nomadic controlled. Body condition score was recorded 3.6 for transhumance treated and 3.32 for nomadic treated. It is concluded from the present study that transhumance system performed significantly (p < 0.05) better in respect of live weight, BCS, FEC, family size, Landholding area, number of animals in a flock, offspring record, culling, and mortality. Mean values are 7.367 ± 0221, 0.900 ± 0.071, 63.167 ± 1.559, 55.600 ± 1.480, 8.300 ± 0.321 and 2.500 ± 0.158 respectively. De-wormer effect on FEC showed a significant reduction in egg load in mature sheep on both systems.

Keywords: small ruminant, sheep, nomadic, transhumance, Malakand, production efficiency

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Authors: Bindu I. Somarajan, Viney Gupta, Gagandeep Kaur Walia, Jasbir Kaur, Sunil Kumar, Shikha Gupta, Abadh K. Chaurasia, Dinesh Gupa, Abhinav Kaushik, Aditi Mehta, Vipin Gupta, Arundhati Sharma

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Background: Juvenile onset primary open angle glaucoma (JOAG), affects individuals under the age of 40 years. Studies on a few families of JOAG, that led to the discovery of the Myocilin gene, reported the disease to have an autosomal dominant pattern of inheritance. However, sporadic forms of JOAG been seen to be more common in some populations. Most pathological homozygous mutations in the CYP1B1 gene associated with JOAG have been seen among sporadic cases. Given the higher prevalence of sporadic JOAG cases in our population, we aimed to look for common mutations E229K and R368H, the two most common variants in the CYP1B1 gene associated with glaucoma. Objective: To determine the frequency and evaluate genotype phenotype correlation of CYP1B1 E229K and R368H mutations in a cohort of 120 sporadic Juvenile open angle glaucoma patients.Methods: Unrelated JOAG patients whose first degree relatives had been examined and found to be unaffected were included in the study. The patients and their parents were screened for E229K and R368H mutations. The phenotypic characteristics were compared between probands with and with out these mutations by SPSS v16. Results: Out of 120 JOAG patients included in the study, the E229K mutation was seen in 9 probands (7.5%) and R368H in 7 (5.8%). The average age of onset of the disease (p=0.3) and the highest untreated IOP (p=0.4) among those carrying mutations was not significantly different from those who did not have these mutations. The proportion of probands with angle dysgenesis among those with E229K and R368H mutations was 70% (11 out of 16) in comparison to 65% (67 out of 104) of those who did not harbour these mutations (p=0.56). Similarly the probands with moderate to high myopia among those with E229K and R368H mutations was 20% (3 out of 16) in comparison to 18% (18 out of 104) of those who did not harbour these mutations(p=0.59). Conclusion: The frequency of E229K and R368H mutations of the CYP1B1 gene is low even among sporadic JOAG patients. Moreover there is no clinical correlation between the presence of these mutations and disease severity

Keywords: CYP1B1, gene, IOP, JOAG, mutation

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Authors: Vernie C. Convicto, Henry P. Aringa, Wilson I. Barredo

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This study presents a conformational model of the helical structures of globular protein particularly ferritin in the framework of white noise path integral formulation by using Associated Legendre functions, Bessel and convolution of Bessel and trigonometric functions as modulating functions. The model incorporates chirality features of proteins and their helix-turn-helix sequence structural motif.

Keywords: globular protein, modulating function, white noise, winding probability

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Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

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Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

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Authors: Ali Bagherinia

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Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment. Cloud computing has new features, such as flexibility, virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization, that simulation results in CloudSim simulator prove this.

Keywords: cloud computing, task scheduling, virtualization, SLA

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Authors: Anne R. Fernandez, Mohammad Akmal Adnan, Tanes Prasat, Indu Bala Jaganath, Brian Kirby, Kamalan Jeevaratnam

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Introduction: Plants from the Phyllantus genus have been used indigenously for the treatment of a variety of ailments for generations. A cocktail of phytonutrients prepared from a plant of the genus Phyllanthus has demonstrated the potential to alleviate ailments which include cardiovascular disorders. In this study, we investigated the cholesterol modulating properties of a highly purified proprietary extract of a Phyllanthus species in hypercholesteraemic mice. Methods: Hypercholesteraemia was induced in ICR mice by ad-libitum feeding of high fat diet daily for six weeks. The mice were then divided into 3 groups and force fed with 10mg/kg of atorvastatin, 200mg/kg of the proprietary Phyllanthus extract and water respectively. Blood samples were taken at the end of fourth week of treatment by a tail prick. At the end of the eighth week of treatment, mice were sacrificed and serum levels of total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides were measured. Results: The mean cholesterol levels in the mice fed with high fat diet were 44% (p < 0.05) higher than the mice on normal diet thus validating the model developed. The plasma HDL was significantly elevated in mice treated with the formulation (p ˂ 0.05) in comparison to the statin-treated and control mice. The total cholesterol levels in the mice treated with the proprietary extract were reduced significantly (p < 0.05) at the end of 4 weeks of treatment in comparison to the mice treated with atorvastatin. By the end of 8 weeks of treatment, there was no significant difference in the cholesterol levels of the mice in all groups. Conclusion: These results demonstrate that this proprietary extract from Phyllanthus species has the beneficial effect of reducing total cholesterol level more rapidly than atorvastatin and increasing HDL levels. Since an increase in the HDL cholesterol can reduce the risk of heart disease, this proprietary extract is a useful and safe therapeutic option compared to atorvastatin.

Keywords: high-density lipoprotein, hypercholesteraemic mice model, ICR mice, Phyllanthus spp.

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Authors: Ülle Parm, Kata Pedamäe, Jaak Jürimäe, Evelin Lätt, Aivar Orav, Anna-Liisa Tamm

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Vegetarianism has gained popularity across the world. It`s being chosen for multiple reasons, but among Estonians, these have remained unknown. Previously, attention to bone health and probable nutrient deficiency of vegetarians has been paid and in vegetarians lower body mass index (BMI) and blood cholesterol level has been found but the results are inconclusive. The goal was to explain reasons for choosing vegetarian diet in Estonia and impact of vegetarianism to body composition – BMI, fat percentage (fat%), fat mass (FM), and fat free mass (FFM). The study group comprised of 68 vegetarians and 103 omnivorous. The determining body composition with DXA (Hologic) was concluded in 2013. Body mass (medical electronic scale, A&D Instruments, Abingdon, UK) and height (Martin metal anthropometer to the nearest 0.1 cm) were measured and BMI calculated (kg/m2). General data (physical activity level included) was collected with questionnaires. The main reasons why vegetarianism was chosen were the healthiness of the vegetarian diet (59%) and the wish to fight for animal rights (72%) Food additives were consumed by less than half of vegetarians, more often by men. Vegetarians had lower BMI than omnivores, especially amongst men. Based on BMI classification, vegetarians were less obese than omnivores. However, there were no differences in the FM, FFM and fat percentage figures of the two groups. Higher BMI might be the cause of higher physical activity level among omnivores compared with vegetarians. For classifying people as underweight, normal weight, overweight and obese both BMI and fat% criteria were used. By BMI classification in comparison with fat%, more people in the normal weight group were considered; by using fat% in comparison with BMI classification, however, more people categorized as overweight. It can be concluded that the main reasons for vegetarianism chosen in Estonia are healthiness of the vegetarian diet and the wish to fight for animal rights and vegetarian diet has no effect on body fat percentage, FM and FFM.

Keywords: body composition, body fat percentage, body mass index, vegetarianism

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Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Mohammed S. Aly, Abou-Zeid N. El-Shahat, Nabila Y. Naguib, Huussie A. Said-Al Ahl, Atef M. Zakaria, Mohamed A. Abou Dahab

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This study was conducted during two successive seasons of 2000/2001 and 2001/2002 to evaluate the response of Anethum graveolens L. plants to nitrogen fertilizer with or without bio-fertilizer on fruits yield, total flavonoids and carbohydrates content, essential oil yield and constituents. Results cleared that the treatment of 60 Kg N/feddan without and with bio-fertilizer gave the highest umbels number per plant through the two seasons and these increments were significant in comparison with control plants. Meanwhile, fruits weight (g/plant) showed significant increase with the treatments of nitrogen fertilizers alone and combined with bio-fertilizers compared with control plants in the first and second season. Maximum increments were resulted with the previous treatment (60 Kg N/fed). Fruits yield (Kg/fed) revealed the same trend of fruits weight (g/plant). Total flavonoids contents were significantly increased with all of used treatments. Maximum increase was noticed with bio-fertilizers combined with 60 Kg N/fed during two seasons. Total carbohydrate contents showed significant increase with applied nitrogen fertilizers treatments as alone, meanwhile total carbohydrate contents were increased non-significantly with the other used treatments during the two seasons in comparison with control plants content. The treatment of bio-fertilizer and in most of nitrogen fertilizer levels significantly increased essential oil percentage, content and yield. The treatment of 60 Kg N/fed with or without bio-fertilizer gave the best values. All identified compounds were observed in the essential oil of all treatments. The major compounds were limonene, carvone and dillapiole. The most effective fertilization on limonene content was 40 Kg N/fed and/or bio-fertilizers. Meanwhile 20 Kg N/fed with or without bio-fertilizers increased carvone, but most of fertilization treatments except those of bio-fertlizers and 40 Kg N/fed increased dillapiole content.

Keywords: carbohydrates, dill, essential oil, fertilizer, flavonoids

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Authors: Mateusz Wielopolski, Asia Guerreschi

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Circular Economy, as the counterargument to the ‘make-take-dispose’ linear model, is an approach that includes a variety of schools of thought looking at environmental, economic, and social sustainability. This, in turn, leads to a variety of strategies and often confusion when it comes to choosing the right one to make a circular transition as effective as possible. Due to the close interplay of circular product design, business model and social responsibility, companies often struggle to develop strategies that comply with all three triple-bottom-line criteria. Hence, to transition to circularity effectively, product design approaches must become more inclusive. In a case study conducted with the University of Bayreuth and the ISPO, we correlated aspects of material choice in product design, labeling and technological innovation with customer preferences and education about specific material and technology features. The study revealed those attributes of the consumers’ environmental awareness that directly translate into an increase of purchase power - primarily connected with individual preferences regarding sports activity and technical knowledge. Based on this outcome, we constituted a product development approach that incorporates the consumers’ individual preferences towards sustainable product features as well as their awareness about materials and technology. It allows deploying targeted customer education campaigns to raise the willingness to pay for sustainability. Next, we implemented the customer preference and education analysis into a circularity assessment tool that takes into account inherent company assets as well as subjective parameters like customer awareness. The outcome is a detailed but not cumbersome scoring system, which provides guidance for material and technology choices for circular product design while considering business model and communication strategy to the attentive customers. By including customer knowledge and complying with corresponding labels, companies develop more effective circular design strategies, while simultaneously increasing customers’ trust and loyalty.

Keywords: circularity, sustainability, product design, material choice, education, awareness, willingness to pay

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Authors: Fernando Martín-Espejo, Christophe Crombez

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This paper presents a political-economic analysis of the reforms introduced during the coronavirus crisis at the EU level with a special emphasis on the recovery fund Next Generation EU (NGEU). It also introduces a spatial model to evaluate whether the governmental features of the recovery fund can be framed inside the community method. Particularly, by evaluating the brake clause in the NGEU legislation, this paper analyses theoretically the political and legislative implications of the introduction of flexibility clauses in the EU decision-making process.

Keywords: EU, legislative procedures, spatial model, coronavirus

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Authors: Andrew C. Eloka Eboka, Freddie L. Inambao

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Comparative investigation and assessment of microalgal technology as a biodiesel production option was studied alongside other second generation feedstocks. This was carried out by comparing the fuel properties of species of Chlorella vulgaris, Duneliella spp, Synechococus spp and Senedesmus spp with the feedstock of Jatropha (ex-basirika variety), Hura crepitans, rubber and Natal mahogany seed oils. The micro-algae were cultivated in an open pond using a photobioreactor (New Brunsink set-up model BF-115 Bioflo/CelliGen made in the US) with operating parameters: 14L capacity, working volume of 7.5L media, including 10% inoculum, at optical density of 3.144 @540nm and light intensity of 200 lux, for 23 and 16 days respectively. Various produced/accumulated biomasses were harvested by draining, flocculation, centrifugation, drying and then subjected to lipid extraction processes. The oils extracted from the algae and feedstocks were characterised and used to produce biodiesel fuels, by the transesterification method, using modified optimization protocol. Fuel properties of the final biodiesel products were evaluated for chemo-physical and fuel properties. Results revealed Chlorella vulgaris as the best strain for biomass cultivation, having the highest lipid productivity (5.2mgL-1h-1), the highest rate of CO2 absorption (17.85mgL-1min-1) and the average carbon sequestration in the form of CO2 was 76.6%. The highest biomass productivity was 35.1mgL-1h-1 (Chlorella), while Senedesmus had the least output (3.75mgL-1h-1, 11.73mgL-1min-1). All species had good pH value adaptation, ranging from 6.5 to 8.5. The fuel properties of the micro-algal biodiesel in comparison with Jatropha, rubber, Hura and Natal mahogany were within ASTM specification and AGO used as the control. Fuel cultivation from microalgae is feasible and will revolutionise the biodiesel industry.

Keywords: biodiesel, fuel properties, microalgae, second generation, seed oils, feedstock, photo-bioreactor, open pond

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Attef Kouadria, Yehya Bouteghrine, Amar Manaa, Tarek Mouats, Djalel Eddine Tria, Hamid Abdelhafid Ghouti

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Personal protection systems have been used in several forms for centuries. The need for light-weight composite structures has been in great demand due to their weight and high mechanical properties ratios in comparison to heavy and cumbersome steel plates. In this regard, lighter ceramic plates with a backing plate made of high strength polymeric fibers, mostly aramids, are widely used for protection against ballistic threats. This study aims to improve the ballistic performance of ceramic/composite plates subjected to ballistic impact by reducing the back face deformation (BFD) measured after each test. A new hybridization technique was developed in this investigation to increase the energy absorption capabilities of the backing plates. The hybridization consists of combining different types of aramid fabrics with different linear densities of aramid fibers (Dtex) and areal densities with an epoxy resin to form the backing plate. Therefore, several composite structures architectures were prepared and tested. For better understanding the effect of the hybridization, a serial of tensile, compression, and shear tests were conducted to determine the mechanical properties of the homogeneous composite materials prepared from different fabrics. It was found that the hybridization allows the backing plate to combine between the mechanical properties of the used fabrics. Aramid fabrics with higher Dtex were found to increase the mechanical strength of the backing plate, while those with lower Dtex found to enhance the lateral wave dispersion ratio due to their lower areal density. Therefore, the back face deformation was significantly reduced in comparison to a homogeneous composite plate.

Keywords: aramid fabric, ballistic impact, back face deformation, body armor, composite, mechanical testing

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Prakash Chandra Dhara, Rupa Maity, Mousumi Chatterjee

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Crowbars are used for the gardening purpose. The same tools are used by both male and female gardeners. The existing crowbars are suitable for the female gardeners. The present study was aimed to design a crowbar, which was required to use by the women for the gardening purpose, from the viewpoints of ergonomics. The study was carried out on 50 women in different villages of Howrah districts in West Bengal state. Different models of existing crowbars which were commonly used by the women were collected and evaluated by examining their shape and size. The problems of using existing crowbar were assessed by direct observation during its operation. The musculoskeletal disorder of the subjects for using the crowbar was evaluated by modified Nordic questionnaire method. The anthropometric dimensions, especially hand dimension, of the subjects were taken in standardized static conditions. Considering the problems of using the existing crowbars some design concepts were developed and accordingly three prototypes models (P1, P2, P3) of crowbar were prepared for designing of a modified crowbar for women. Psychophysical analysis of those prototypes was made by paired comparison tests. In the above test subjective preference for different characteristics of the crowbar, e.g., length, weight, length and breadth of the blade, handle diameter, position of the handle, were determined. From the results of the paired comparison test and percentile values of hand dimensions, a modified design of crowbar was suggested. The prototype model P1 possessed more preferred characteristics of the tool than that of other prototype models. In the final design, the weight of the tool and length of the blade was reduced from that of the existing crowbar. Other dimensions were also changed. Two handles were suggested in the redesigned tool for better gripping and operation. The modified crowbar was evaluated by studying the body joint angles, viz., wrist, shoulder and elbow, for assessing the suitability of the design. It was concluded that the redesigned crowbar was suitable for women’s use.

Keywords: body dimension, crowbar, ergo-design, women, hand anthropometry

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Authors: Claudia L. Bianchi, Giuseppina Cerrato, Federico Galli, Federica Minozzi, Valentino Capucci

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At the beginning of the industrial productions, porcelain gres tiles were considered as just a technical material, aesthetically not very beautiful. Today thanks to new industrial production methods, both properties, and beauty of these materials completely fit the market requests. In particular, the possibility to prepare slabs of large sizes is the new frontier of building materials. Beside these noteworthy architectural features, new surface properties have been introduced in the last generation of these materials. In particular, deposition of TiO₂ transforms the traditional ceramic into a photocatalytic eco-active material able to reduce polluting molecules present in air and water, to eliminate bacteria and to reduce the surface dirt thanks to the self-cleaning property. The problem of photocatalytic materials resides in the fact that it is necessary a UV light source to activate the oxidation processes on the surface of the material, processes that are turned off inexorably when the material is illuminated by LED lights and, even more so, when we are in darkness. First, it was necessary a thorough study change the existing plants to deposit the photocatalyst very evenly and this has been done thanks to the advent of digital printing and the development of an ink custom-made that stabilizes the powdered TiO₂ in its formulation. In addition, the commercial TiO₂, which is used for the traditional photocatalytic coating, has been doped with metals in order to activate it even in the visible region and thus in the presence of sunlight or LED. Thanks to this active coating, ceramic slabs are able to purify air eliminating odors and VOCs, and also can be cleaned with very soft detergents due to the self-cleaning properties given by the TiO₂ present at the ceramic surface. Moreover, the presence of dopant metals (patent WO2016157155) also allows the material to work as well as antibacterial in the dark, by eliminating one of the negative features of photocatalytic building materials that have so far limited its use on a large scale. Considering that we are constantly in contact with bacteria, some of which are dangerous for health. Active tiles are 99,99% efficient on all bacteria, from the most common such as Escherichia coli to the most dangerous such as Staphilococcus aureus Methicillin-resistant (MRSA). DIGITALIFE project LIFE13 ENV/IT/000140 – award for best project of October 2017.

Keywords: Ag-doped microsized TiO₂, eco-active ceramic, photocatalysis, digital coating

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: Çiğdem Avcı Karataş

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Mitigation of structural damage caused by earthquake and reduction of fatality is one of the main concerns of engineers in seismic prone zones of the world. To achieve this aim many technologies have been developed in the last decades and applied in construction and retrofit of structures. On the one hand Turkey is well-known a country of high level of seismicity; on the other hand steel-composite structures appear competitive today in this country by comparison with other types of structures, for example only-steel or concrete structures. Composite construction is the dominant form of construction for the multi-storey building sector. The reason why composite construction is often so good can be expressed in one simple way - concrete is good in compression and steel is good in tension. By joining the two materials together structurally these strengths can be exploited to result in a highly efficient design. The reduced self-weight of composite elements has a knock-on effect by reducing the forces in those elements supporting them, including the foundations. The floor depth reductions that can be achieved using composite construction can also provide significant benefits in terms of the costs of services and the building envelope. The scope of this paper covers analysis, materials take-off, cost analysis and economic comparisons of a multi-storey building with composite and steel frames. The aim of this work is to show that designing load carrying systems as composite is more economical than designing as steel. Design of the nine stories building which is under consideration is done according to the regulation of the 2007, Turkish Earthquake Code and by using static and dynamic analysis methods. For the analyses of the steel and composite systems, plastic analysis methods have been used and whereas steel system analyses have been checked in compliance with EC3 and composite system analyses have been checked in compliance with EC4. At the end of the comparisons, it is revealed that composite load carrying systems analysis is more economical than the steel load carrying systems analysis considering the materials to be used in the load carrying system and the workmanship to be spent for this job.

Keywords: composite analysis, earthquake, steel, multi-storey building

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Authors: Andrey Angorsky

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In the article an issue about the possible number of fundamental physical interactions is studied. The theory of similarity on the dimensionless quantity as the damping ratio serves as the instrument of analysis. The structure with the features of Higgs field comes out from non-commutative expression for this ratio. The experimentally checked up supposition about the nature of dark energy is spoken out.

Keywords: damping ratio, dark energy, dimensionless quantity, fundamental physical interactions, Higgs field, non-commutative expression

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Authors: Shaima Almalhan, Lubna Shukri, Miriam Talal, Safaa Teskieh

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Since artificial intelligence is a rapidly evolving topic that has had a significant impact on technical growth and innovation, this paper examines people's awareness, use, and engagement with the Google Translate application. To see how familiar aware users are with the app and its features, quantitative and qualitative research was conducted. The findings revealed that consumers have a high level of confidence in the application and how far people they benefit from this sort of innovation and how convenient it makes communication.

Keywords: artificial intelligence, google translate, speech recognition, language translation, camera translation, speech to text, text to speech

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Authors: A. M. El-Akhdar, A. M. El-Tager, H. M. El-Hennawy

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This paper presents a broadband power divider with equal power division ratio. Two sections of transmission line transformers based on coupled microstrip lines are applied to obtain broadband performance. In addition, design methodology is proposed for the novel structure. A prototype is designed, simulated to operate in the band from 2.1 to 3.8 GHz to fulfill the requirements of 3G and 4G applications. The proposed structure features reduced size and less resistors than other conventional techniques. Simulation verifies the proposed idea and design methodology.

Keywords: power dividers, coupled lines, microstrip, 4G applications

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Authors: Tobias Strübing, Fatemeh Ziaeetabar

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Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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Authors: Driss Kettani

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ICT4D actors are naturally attempted to include AI in the range of enabling technologies and tools that could support and boost the Development process, and to refer to these as AI4D. But, doing so, assumes that AI complies with the very specific features of ICT4D context, including, among others, affordability, relevance, openness, and ownership. Clearly, none of these is fulfilled, and the enthusiastic posture that AI4D is a natural part of ICT4D is not grounded and, to certain extent, does not serve the purpose of Technology for Development at all. In the context of Development, it is important to emphasize and prioritize ICT4D, in the national digital transformation strategies, instead of borrowing "trendy" waves of the IT Industry that are motivated by business considerations, with no specific care/consideration to Development.

Keywords: AI, ICT4D, technology for development, position paper

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Authors: Nora Mohammed Al-Kehayez

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This present investigation was performed to study the effect of low fat yogurt on serum and liver lipids profile of male albino rats (weighing 100 g+or- 5 gram) when fed balanced or high fat high cholesterol diets and given yogurt ad libitum compared with control groups. Rats were divided into 4 groups, each group contains 6 rats. The groups of rats were fed as follows: Group(1) was fed balanced diet + water(control). Group(2) was fed balanced diet + low fat yogurt. Group(3) was fed high fat high cholesterol diet + water(Control). Group(4) was fed high fat high cholesterol diet + low fat yogurt. The obtained results could be summarized as follows: When rats were given low fat yogurt and fed balanced or high fat high cholesterol diets a significantly greater weight gains resulted in comparison with the control groups given water instead of yogurt. The data on the weights of liver and heart expressed' as percentage increased the body weight in case of rats which were fed balanced diet with low fat yogurt while in case of rats which were fed high fat high cholesterol diet with low fat yogurt the increment scenes to be less. Results of serum cholesterol levels in serum of rats were given balanced or high fat high cholesterol diets and consuming low fat yogurt was showed a significant reduction values. However the low fat yogurt produced the highest significant decrease values. The values of serum cholesterol go hand in hand with serum lipoprotein fractions in rats given low fat yogurt with both balanced or high fat high cholesterol diets. An increase of high density lipoprotein HDL-C and a decrease of low density lipoprotein LDL-C values were obtained. When rats ingested low fat yogurt a significant decrease in serum and liver triglycerides content was obtained wether with balanced or high fat high cholesterol diets. Rats consuming high fat high cholesterol diets with water showed a significant increase in liver total lipids, total cholesterol and phospholipides levels in comparison with the same liver parameters in rats given balanced diet with water. Supplement with low fat yogurt significantly suppressed these effects.

Keywords: yogurt, lipids profile, albino, rats

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Authors: Zhengming Wu

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NanoFrazor lithography systems were developed as a first true alternative or extension to standard mask-less nanolithography methods like electron beam lithography (EBL). In contrast to EBL they are based on thermal scanning probe lithography (t-SPL). Here a heatable ultra-sharp probe tip with an apex of a few nm is used for patterning and simultaneously inspecting complex nanostructures. The heat impact from the probe on a thermal responsive resist generates those high-resolution nanostructures. The patterning depth of each individual pixel can be controlled with better than 1 nm precision using an integrated in-situ metrology method. Furthermore, the inherent imaging capability of the Nanofrazor technology allows for markerless overlay, which has been achieved with sub-5 nm accuracy as well as it supports stitching layout sections together with < 10 nm error. Pattern transfer from such resist features below 10 nm resolution were demonstrated. The technology has proven its value as an enabler of new kinds of ultra-high resolution nanodevices as well as for improving the performance of existing device concepts. The application range for this new nanolithography technique is very broad spanning from ultra-high resolution 2D and 3D patterning to chemical and physical modification of matter at the nanoscale. Nanometer-precise markerless overlay and non-invasiveness to sensitive materials are among the key strengths of the technology. However, while patterning at below 10 nm resolution is achieved, significantly increasing the patterning speed at the expense of resolution is not feasible by using the heated tip alone. Towards this end, an integrated laser write head for direct laser sublimation (DLS) of the thermal resist has been introduced for significantly faster patterning of micrometer to millimeter-scale features. Remarkably, the areas patterned by the tip and the laser are seamlessly stitched together and both processes work on the very same resist material enabling a true mix-and-match process with no developing or any other processing steps in between. The presentation will include examples for (i) high-quality metal contacting of 2D materials, (ii) tuning photonic molecules, (iii) generating nanofluidic devices and (iv) generating spintronic circuits. Some of these applications have been enabled only due to the various unique capabilities of NanoFrazor lithography like the absence of damage from a charged particle beam.

Keywords: nanofabrication, grayscale lithography, 2D materials device, nano-optics, photonics, spintronic circuits

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Paolo Boscaro, Vasile Hulea, François Fajula, Francis Luck, Anne Galarneau

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TiO2 based monoliths with hierarchical macropores and mesopores have been synthesized following a novel one pot sol-gel synthesis method. Taking advantage of spinodal separation that occurs between titanium isopropoxide and an acidic solution in presence of polyethylene oxide polymer, monoliths with homogeneous interconnected macropres of 3 μm in diameter and mesopores of ca. 6 nm (surface area 150 m2/g) are obtained. Furthermore, these monoliths present some carbon and nitrogen (as shown by XPS and elemental analysis), which considerably reduce titanium oxide energy gap and enable light to be absorbed up to 700 nm wavelength. XRD shows that anatase is the dominant phase with a small amount of brookite. Enhanced light absorption and high porosity of the monoliths are responsible for a remarkable photocatalytic activity. Wastewater treatment has been performed in closed reactor under sunlight using orange G dye as target molecule. Glass reactors guarantee that most of UV radiations (to almost 300 nm) of solar spectrum are excluded. TiO2 nanoparticles P25 (usually used in photocatalysis under UV) and un-doped TiO2 monoliths with similar porosity were used as comparison. C,N-doped TiO2 monolith allowed a complete colorant degradation in less than 1 hour, whereas 10 h are necessary for 40% colorant degradation with P25 and un-doped monolith. Experiment performed in the dark shows that only 3% of molecules have been adsorbed in the C,N-doped TiO2 monolith within 1 hour. The much higher efficiency of C,N-doped TiO2 monolith in comparison to P25 and un-doped monolith, proves that doping TiO2 is an essential issue and that nitrogen and carbon are effective dopants. Monoliths offer multiples advantages in respect to nanometric powders: sample can be easily removed from batch (no needs to filter or to centrifuge). Moreover flow reactions can be set up with cylindrical or flat monoliths by simple sheathing or by locking them with O-rings.

Keywords: C-N doped, sunlight photocatalytic activity, TiO2 monolith, visible absorbance

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