Search results for: feed processing

Authors: Maciej Życki, Anna Kowalik-klimczak, Monika Łożyńska, Wioletta Barszcz, Jolanta Drabik Anna Kowalik-klimczak

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The rapidly changing fashion trends generate huge amounts of leather and textile waste globally. The complexity of these types of waste makes recycling difficult in economic terms. Pyrolysis is suggested for this purpose, which transforms heterogeneous and complex waste into added-value products e.g. active carbons and soil fertilizer. The possibility of using pyrolysis for the valorization of leather and textile waste has been analyzed in this paper. In the first stage, leather and textile waste were subjected to TG/DTG thermogravimetric and DSC calorimetric analysis. These analyses provided basic information about thermochemical transformations and degradation rates during the pyrolysis of these types of waste and enabled the selection of the pyrolysis temperature. In the next stage, the effect of gas type using pyrolysis was investigated on the physicochemical properties, composition, structure, and formation of the specific surfaces of carbonized materials produced by means of a thermal treatment without oxygen access to the reaction chamber. These studies contribute some data about the thermal management and pyrolytic processing of leather and textile waste into useful carbonized materials, according to the circular economy model.

Keywords: pyrolysis, leather and textiles waste, composition and structure of carbonized materials, valorisation of waste, circular economy model

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Authors: Franklin Thambi Jose.S

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Computational Linguistics is a branch of linguistics, which deals with the computer and linguistic levels. It is also said, as a branch of language studies which applies computer techniques to linguistics field. In Computational Linguistics, Natural Language Processing plays an important role. This came to exist because of the invention of Information Technology. In computational syntax, the syntactic analyser breaks a sentence into phrases and clauses and identifies the sentence with the syntactic information. Tamil is one of the major Dravidian languages, which has a very long written history of more than 2000 years. It is mainly spoken in Tamilnadu (in India), Srilanka, Malaysia and Singapore. It is an official language in Tamilnadu (in India), Srilanka, Malaysia and Singapore. In Malaysia Tamil speaking people are considered as an ethnic group. In Tamil syntax, the sentences in Tamil are classified into four for this research, namely: 1. Main Sentence 2. Interrogative Sentence 3. Equational Sentence 4. Elliptical Sentence. In computational syntax, the first step is to provide required information regarding the head and its constituent of each sentence. This information will be incorporated to the system using programming languages. Now the system can easily analyse a given sentence with the criteria or mechanisms given to it. Providing needful criteria or mechanisms to the computer to identify the basic types of sentences using Syntactic parser in Tamil language is the major objective of this paper.

Keywords: tamil, syntax, criteria, sentences, parser

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Authors: Mehmet Nefes, Selman Demirel, Hasan H. Ertok, Cenk Sen

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A typical reliability engineering problem regarding communication satellites has been considered to determine redundancy allocation scheme of power amplifiers within payload transponder module, whose dominant function is to amplify power levels of the received signals from the Earth, through maximizing reliability against mass, power, and other technical limitations. Adding each redundant power amplifier component increases not only reliability but also hardware, testing, and launch cost of a satellite. This study investigates a multi-objective approach used in order to solve Redundancy Allocation Problem (RAP) for a communication satellite payload transponder, focusing on design cost due to redundancy and reliability factors. The main purpose is to find the optimum power amplifier redundancy configuration satisfying reliability and capacity thresholds simultaneously instead of analyzing respectively or independently. A mathematical model and calculation approach are instituted including objective function definitions, and then, the problem is solved analytically with different input parameters in MATLAB environment. Example results showed that payload capacity and failure rate of power amplifiers have remarkable effects on the solution and also processing time.

Keywords: communication satellite payload, multi-objective optimization, redundancy allocation problem, reliability, transponder

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Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

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Authors: Abir Soltani, Moez Amri, Jouda Mediouni Ben Jemâa

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In North Africa, the chickpea leafminer Liriomyza cicerina (Rondani) (Diptera: Agromizidae) is one of the major damaging pests affecting both spring and winter-planted chickpea. Damage is caused by the larvae which feed in the leaf mesophyll tissue, resulting in desiccation and premature leaf fall that can cause severe yield losses. In the present work, the distribution and the seasonal phenology of L. cicerina were studied on two chickpea varieties; a winter variety Beja 1 which is the most cultivated variety in Tunisia and a spring-sown variety Amdoun 1. The experiment was conducted during the cropping season 2015-2016. In the experimental research station Oued Beja, in the Beja region (36°44’N; 9°13’E). To determine the distribution and seasonal phenology of L. cicerina in both studied varieties Beja 1 and Amdoun 1, respectively 100 leave samples (50 from the top and 50 from the base) were collected from 10 chickpea plants randomly chosen from each field. The sampling was done during three development stages (i) 20-25 days before flowering (BFL), (ii) at flowering (FL) and (ii) at pod setting stage (PS). For each plant, leaves were checked from the base till the upper ones for the insect infestation progress into the plant in correlation with chickpea growth Stages. Fly adult populations were monitored using 8 yellow sticky traps together with weekly leaves sampling in each field. The traps were placed 70 cm above ground. Trap catches were collected once a week over the cropping season period. Results showed that L. cicerina distribution varied among both studied chickpea varieties and crop development stage all with seasonal phenology. For the winter chickpea variety Beja 1, infestation levels of 2%, 10.3% and 20.3% were recorded on the bases plant part for BFL, FL and PS stages respectively against 0%, 8.1% and 45.8% recorded for the upper plant part leaves for the same stages respectively. For the spring-sown variety Amdoun 1 the infestation level reached 71.5% during flowering stage. Population dynamic study revealed that for Beja 1 variety, L. cicerina accomplished three annual generations over the cropping season period with the third one being the most important with a capture level of 85 adult/trap by mid-May against a capture level of 139 adult/trap at the end May recorded for cv. Amdoun 1. Also, results showed that L. cicerina field infestation dispersal depends on the field part and on the crop growth stage. The border areas plants were more infested than the plants placed inside the plots. For cv. Beja 1, border areas infestations were 11%, 28% and 91.2% for BFL, FL and PS stages respectively, against 2%, 10.73% and 69.2% recorded on the on the inside plot plants during the for the same growth stages respectively. For the cv. Amdoun1 infestation level of 90% was observed on the border plants at FL and PS stages against an infestation level less than 65% recorded inside the plot.

Keywords: leaf miner, liriomyza cicerina, chickpea, distribution, seasonal phenology, Tunisia

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Authors: Darsh N. Patel, Eric Olson

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Fractals can be found everywhere, whether it be the shape of a leaf or a system of blood vessels. Fractals are used to help study and understand different physical and mathematical processes; however, their artistic nature is also beautiful to simply explore. This project explores fractals generated by a cubically convergent extension to Newton's method. With this iteration as a starting point, a complex plane spanning from -2 to 2 is created with a color wheel mapped onto it. Next, the polynomial whose roots the fractal will generate from is established. From the Fundamental Theorem of Algebra, it is known that any polynomial has as many roots (counted by multiplicity) as its degree. When generating the fractals, each root will receive its own color. The complex plane can then be colored to indicate the basins of attraction that converge to each root. From a computational point of view, this project’s code identifies which points converge to which roots and then obtains fractal images. A zoom path into the fractal was implemented to easily visualize the self-similar structure. This path was obtained by selecting keyframes at different magnifications through which a path is then interpolated. Using parallel processing, many images were generated and condensed into a video. This project illustrates how practical techniques used for scientific visualization can also have an artistic side.

Keywords: fractals, cubic method, Julia programming language, basin of attraction

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Authors: G. Kermarrec, J. Hartmann

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Spline surfaces are a major representation of freeform surfaces in the computer-aided graphic industry and were recently introduced in the field of geodesy for processing point clouds from terrestrial laser scanner (TLS). The surface fitting consists of approximating a trustworthy mathematical surface to a large numbered 3D point cloud. The standard B-spline surfaces lack of local refinement due to the tensor-product construction. The consequences are oscillating geometry, particularly in the transition from low-to-high curvature parts for scattered point clouds with missing data. More economic alternatives in terms of parameters on how to handle point clouds with a huge amount of observations are the recently introduced T-splines. As long as the partition of unity is guaranteed, their computational complexity is low, and they are flexible. T-splines are implemented in a commercial package called Rhino, a 3D modeler which is widely used in computer aided design to create and animate NURBS objects. We have applied T-splines surface fitting to terrestrial laser scanner point clouds from a bridge under load and a sheet pile wall with noisy observations. We will highlight their potential for modelling details with high trustworthiness, paving the way for further applications in terms of deformation analysis.

Keywords: deformation analysis, surface modelling, terrestrial laser scanner, T-splines

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Authors: Raj Kishore Swain, Kamdev Sethy, Sumanta Kumar Mishra

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Selenium is an essential trace element for the chicken with a variety of biological functions like growth, fertility, immune system, hormone metabolism, and antioxidant defense systems. Selenium deficiency in chicken causes exudative diathesis, pancreatic dystrophy and nutritional muscle dystrophy of the gizzard, heart and skeletal muscle. Additionally, insufficient immunity, lowering of production ability, decreased feathering of chickens and increased embryo mortality may occur due to selenium deficiency. Nano elemental selenium, which is bright red, highly stable, soluble and of nano meter size in the redox state of zero, has high bioavailability and low toxicity due to the greater surface area, high surface activity, high catalytic efficiency and strong adsorbing ability. To assess the effect of dietary nano-Se on performance and expression of gene in Vencobb broiler birds in comparison to its inorganic form (sodium selenite), four hundred fifty day-old Vencobb broiler chicks were randomly distributed into 9 dietary treatment groups with two replicates with 25 chicks per replicate. The dietary treatments were: T1 (Control group): Basal diet; T2: Basal diet with 0.3 ppm of inorganic Se; T3: Basal diet with 0.01875 ppm of nano-Se; T4: Basal diet with 0.0375 ppm of nano-Se; T5: Basal diet with 0.075 ppm of nano-Se, T6: Basal diet with 0.15 ppm of nano-Se, T7: Basal diet with 0.3 ppm of nano-Se, T8: Basal diet with 0.60 ppm of nano-Se, T9: Basal diet with 1.20 ppm of nano-Se. Nano selenium was synthesized by mixing sodium selenite with reduced glutathione and bovine serum albumin. The experiment was carried out in two phases: starter phase (0-3 wks), finisher phase (4-5 wk) in deep litter system. The body weight at the 5th week was best observed in T4. The best feed conversion ratio at the end of 5th week was observed in T4. Erythrocytic catalase, glutathione peroxidase and superoxide dismutase activity were significantly (P < 0.05) higher in all the nano selenium treated groups at 5th week. The antibody titers (log2) against Ranikhet diseases vaccine immunization of 5th-week broiler birds were significantly higher (P < 0.05) in the treatments T4 to T7. The selenium levels in liver, breast, kidney, brain, and gizzard were significantly (P < 0.05) increased with increasing dietary nano-Se indicating higher bioavailability of nano-Se compared to inorganic Se. The real time polymer chain reaction analysis showed an increase in the expression of antioxidative gene in T4 and T7 group. Therefore, it is concluded that supplementation of nano-selenium at 0.0375 ppm over and above the basal level can improve the body weight, antioxidant enzyme activity, Se bioavailability and expression of the antioxidative gene in broiler birds.

Keywords: chicken, growth, immunity, nano selenium

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Authors: Ergun Sakalar, Kubra Bilgic

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Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Blanca A. Pichardo, Victor H. Lopez, Melchor Salazar, Rafael Garcia, Alberto Ruiz

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Clad pipes in comparison to plain carbon steel pipes offer the oil and gas industry high corrosion resistance, reduction in economic losses due to pipeline failures and maintenance, lower labor risk, prevent pollution and environmental damage due to hydrocarbons spills caused by deteriorated pipelines. In this context, it is paramount to establish reliable welding procedures to join bimetallic plates or pipes. Thus, the aim of this work is to study the microstructure and mechanical behavior of clad plates welded by the gas metal arc welding (GMAW) process. A clad of 316L stainless steel was deposited onto API 5L X-60 plates by overlay welding with the GMAW process. Welding parameters were, 22.5 V, 271 A, heat input 1,25 kJ/mm, shielding gas 98% Ar + 2% O₂, reverse polarity, torch displacement speed 3.6 mm/s, feed rate 120 mm/s, electrode diameter 1.2 mm and application of an electromagnetic field of 3.5 mT. The overlay welds were subjected to macro-structural and microstructural characterization. After manufacturing the clad plates, a single V groove joint was machined with a 60° bevel and 1 mm root face. GMA welding of the bimetallic plates was performed in four passes with ER316L-Si filler for the root pass and an ER70s-6 electrode for the subsequent welding passes. For joining the clad plates, an electromagnetic field was applied with 2 purposes; to improve the microstructural characteristics and to assist the stability of the electric arc during welding in order to avoid magnetic arc blow. The welds were macro and microstructurally characterized and the mechanical properties were also evaluated. Vickers microhardness (100 g load for 10 s) measurements were made across the welded joints at three levels. The first profile, at the 316L stainless steel cladding, was quite even with a value of approximately 230 HV. The second microhardness profile showed high values in the weld metal, ~400 HV, this was due to the formation of a martensitic microstructure by dilution of the first welding pass with the second. The third profile crossed the third and fourth welding passes and an average value of 240 HV was measured. In the tensile tests, yield strength was between 400 to 450 MPa with a tensile strength of ~512 MPa. In the Charpy impact tests, the results were 86 and 96 J for specimens with the notch in the face and in the root of the weld bead, respectively. The results of the mechanical properties were in the range of the API 5L X-60 base material. The overlap welding process used for cladding is not suitable for large components, however, it guarantees a metallurgical bond, unlike the most commonly used processes such as thermal expansion. For welding bimetallic plates, control of the temperature gradients is key to avoid distortions. Besides, the dissimilar nature of the bimetallic plates gives rise to the formation of a martensitic microstructure during welding.

Keywords: clad pipe, dissimilar welding, gas metal arc welding, magnetic fields

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Abbas Mohamed Abbas, Raafat El-Shafie Fat-Helbary, Karrar Omar El Fergawy, Ahmed Hamed Sayed

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The exploration in archaeological area requires non-invasive methods, and hence the Ground Penetrating Radar (GPR) technique is a proper candidate for this task. GPR investigation is widely applied for searching for hidden ancient targets. So, in this paper GPR technique has been used in archaeological investigation. The aim of this study was to obtain information about the subsurface and associated structures beneath two selected sites at the western bank of the River Nile at Aswan city. These sites have archaeological structures of different ages starting from 6thand 12th Dynasties to the Greco-Roman period. The first site is called Nag’ El Gulab, the study area was 30 x 16 m with separating distance 2m between each profile, while the second site is Nag’ El Qoba, the survey method was not in grid but in lines pattern with different lengths. All of these sites were surveyed by GPR model SIR-3000 with antenna 200 MHz. Beside the processing of each profile individually, the time-slice maps have been conducted Nag’ El Gulab site, to view the amplitude changes in a series of horizontal time slices within the ground. The obtained results show anomalies may interpret as presence of associated tombs structures. The probable tombs structures similar in their depth level to the opened tombs in the studied areas.

Keywords: ground penetrating radar, archeology, Nag’ El Gulab, Nag’ El Qoba

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Authors: Maiss Razem

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The construction sector is considered a major consumer of materials that undergoes processes of extraction, processing, transportation, and maintaining when used in buildings. Several metrics have been devised to capture the environmental impact of the materials consumed during construction using lifecycle thinking. Rarely has the materiality of this sector been explored qualitatively and systemically. This paper aims to explore socio-cultural forces that drive the use of certain materials in the Jordanian construction industry, using practice theory as a heuristic method of analysis, more specifically Shove et al. three-element model. By conducting semi-structured interviews with architects, the results unravel contextually embedded routines when determining qualities of three materialities highlighted herein; stone, glass and spatial openness. The study highlights the inadequacy of only using efficiency as a quantitative metric of sustainable materials and argues for the need to link material consumption with socio-economic, cultural, and aesthetic driving forces. The operationalization of practice theory by tracing materials’ lifetimes as they integrate with competencies and meanings captures dynamic engagements through the analyzed routines of actors in the construction practice. This study can offer policymakers better-nuanced representation to green this sector beyond efficiency rhetoric and quantitative metrics.

Keywords: architects' practices, construction materials, Jordan, practice theory

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Authors: C. P. Mallapur, U. K. Hulihalli, D. N. Kambrekar

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Maize (Zea mays L.) an important cereal crop in the world has diversified uses including human consumption, animal feed, and industrial uses. A major constraint in low productivity of maize in India is undoubtedly insect pests particularly two species of stem borers, Chilo partellus (Swinhoe) and Sesamia inferens (Walker). The stem borers cause varying level of yield losses in different agro-climate regions (25.7 to 80.4%) resulting in a huge economic loss to the farmers. Although these pests are rather difficult to manage, efforts have been made to combat the menace by using effective insecticides. However, efforts have been made in the present study to integrate various possible approaches for sustainable management of these borers. Two field experiments were conducted separately during 2016-17 at Main Agricultural Research Station, University of Agricultural Sciences, Dharwad, Karnataka, India. In the first experiment, six treatments were randomized in RBD. The insect eggs at pinhead stage (@ 40 eggs/plant) were stapled to the under surface of leaves covering 15-20 % of plants in each plot after 15 days of sowing. The second experiment was planned with nine treatments replicated thrice. The border crop with NB -21 grass was planted all around the plots in the specific treatments while, cowpea intercrop (@6:1-row proportion) was sown along with the main crop and later, the insecticidal spray with chlorantraniliprole and nimbecidine was taken upon need basis in the specific treatments. The results indicated that the leaf injury and dead heart incidence were relatively more in the treatments T₂ and T₄ wherein, no insect control measures were made after the insect release (58.30 & 40.0 % leaf injury and 33.42 and 25.74% dead heart). On the contrary, these treatments recorded higher stem tunneling (32.4 and 24.8%) and resulted in lower grain yield (17.49 and 26.79 q/ha) compared to 29.04, 32.68, 40.93 and 46.38 q/ha recorded in T₁, T₃, T₅ and T₆ treatments, respectively. A maximum yield loss of 28.89 percent was noticed in T₂ followed by 19.59 percent in T₄ where no sprays were imposed. The data on integrated management trial revealed the lowest stem borer damage (19.28% leaf injury and 1.21% dead heart) in T₅ (seed treatment with thiamethoxam 70FS @ 8ml/kg seed + cow intercrop along with nimbecidine 0.03EC @ 5.0 ml/l and chlorantraniliprole 18.5SC spray @ 0.2 ml/l). The next best treatment was T₆ (ST+ NB-21 borer with nimbecidine and chlorantraniliprole spray) with 21.3 and 1.99 percent leaf injury and dead heart incidence, respectively. These treatments resulted in highest grain yield (77.71 and 75.53 q/ha in T₅ and T₆, respectively) compared to the standard check, T₁ (ST+ chlorantraniliprole spray) wherein, 27.63 percent leaf injury and 3.68 percent dead heart were noticed with 60.14 q/ha grain yield. The stem borers can cause yield loss up to 25-30 percent in maize which can be well tackled by seed treatment with thiamethoxam 70FS @ 8ml/kg seed and sowing the crop along with cowpea as intercrop (6:1 row proportion) or NB-21 grass as border crop followed by application of nimbecidine 0.03EC @ 5.0 ml/l and chlorantraniliprole 18.5SC @ 0.2 ml/l on need basis.

Keywords: Maize stem borers, Chilo partellus, Sesamia inferens, crop loss, integrated management

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Authors: Safa Gharbi, Hayfa Zgaya, Nesrine Zoghlami, Slim Hammadi, Cyril De Barbarin, Laurent Vinatier, Christiane Coupier

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Increasing productivity and quality of service, improving the working comfort and ensuring the efficiency of all processes are important challenges for every warehouse. The order picking is recognized to be the most important and costly activity of all the process in warehouses. This paper presents a new approach using Augmented Reality (AR) in the field of logistics. It aims to create a Head-Up Display (HUD) interface with a Warehouse Management System (WMS), using AR glasses. Integrating AR technology allows the optimization of order picking by reducing time of picking process, increasing the efficiency and delivering quickly. The picker will be able to access immediately to all the information needed for his tasks. All the information is displayed when needed in the field of vision (FOV) of the operator, without any action requested from him. These research works are part of the industrial project RASL (Réalité Augmentée au Service de la Logistique) which gathers two major partners: the LAGIS (Laboratory of Automatics, Computer Engineering and Signal Processing in Lille-France) and Genrix Group, European leader in warehouses logistics, who provided his software for implementation, and his logistics expertise.

Keywords: Augmented Reality (AR), logistics and optimization, Warehouse Management System (WMS), Head-Up Display (HUD)

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Authors: Stanley Dula, Oluwatosini A. Ijabadeniyi

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Biofilm formation is a major source of materials and foodstuffs contamination, contributing to occurrence of pathogenic and spoilage microbes in food processing resulting in food spoilage, transmission of diseases and significant food hygiene and safety issues. This study elucidates biofilm formation of E. coli O157:H7 and L. monocytogenes ATCC 7644 grown under food related environmental stress conditions of varying pH (5.0;7.0; and 8.5) and temperature (15, 25 and 37 ℃). Both strains showed confluent biofilm formation at 25 ℃ and 37 ℃, at pH 8.5 after 5 days. E. coli showed curli fimbriae production at various temperatures, while L. monocytogenes did not show pronounced expression. Swarm, swimming and twitching plate assays were used to determine strain motilities. Characterization of cell hydrophobicity was done using the microbial adhesion to hydrocarbons (MATH) assay using n-hexadecane. Both strains showed hydrophilic characteristics as they fell within a < 20 % interval. FT-IR revealed COOH at 1622 cm-1, and a strong absorption band at 3650 cm-1 – 3200 cm-1 indicating the presence of both -OH and -NH groups. Both strains were hydrophilic and could form biofilm at different combinations of temperature and pH. EPS produced in both species proved to be an acidic hetero-polysaccharide.

Keywords: biofilm, pathogens, hydrophobicity, motility

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

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Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Yousif Mohamed Y. Abdallah

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This is an experimental study deals with detection, measurement and analysis of the periodic physiological organ motion during external beam radiotherapy; to improve the accuracy of the radiation field placement, and to reduce the exposure of healthy tissue during radiation treatments. The importance of this study is to detect the maximum path of the mobile structures during radiotherapy delivery, to define the planning target volume (PTV) and irradiated volume during both inspiration and expiration period and to verify the target volume. In addition to its role to highlight the importance of the application of Intense Guided Radiotherapy (IGRT) methods in the field of radiotherapy. The results showed (body contour was equally (3.17 + 0.23 mm), for left lung displacement reading (2.56 + 0.99 mm) and right lung is (2.42 + 0.77 mm) which the radiation oncologist to take suitable countermeasures in case of significant errors. In addition, the use of the image registration technique for automatic position control is predicted potential motion. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, individualized assessment of tumor mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a single CT scan with a margin of 10 mm is clearly inappropriate.

Keywords: respiratory motion, external beam radiotherapy, image processing, lung

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Authors: Aoqi Zhang, Changgil Lee Lee, Seunghee Park

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A non-contact nondestructive technique using laser-induced ultrasonic wave generation method was applied to visualize corrosion damage at aluminum alloy plate structures. The ultrasonic waves were generated by a Nd:YAG pulse laser, and a galvanometer-based laser scanner was used to scan specific area at a target structure. At the same time, wave responses were measured at a piezoelectric sensor which was attached on the target structure. The visualization of structural damage was achieved by calculating logarithmic values of root mean square (RMS). Damage-sensitive feature was defined as the scattering characteristics of the waves that encounter corrosion damage. The corroded damage was artificially formed by hydrochloric acid. To observe the effect of the location where the corrosion was formed, the both sides of the plate were scanned with same scanning area. Also, the effect on the depth of the corrosion was considered as well as the effect on the size of the corrosion. The results indicated that the damages were successfully visualized for almost cases, whether the damages were formed at the front or back side. However, the damage could not be clearly detected because the depth of the corrosion was shallow. In the future works, it needs to develop signal processing algorithm to more clearly visualize the damage by improving signal-to-noise ratio.

Keywords: non-destructive testing, corrosion, pulsed laser scanning, ultrasonic waves, plate structure

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Authors: Youval Aberman, Jason E. Plaks

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This research provides initial evidence that self-efficacy of mitigation behavior – the belief that one’s action can make a difference on the environment – can be implicitly inferred from the way numerical information is presented in environmental messages. The scientific community sees climate change as a pressing issue, but the general public tends to construe climate change as an abstract phenomenon that is psychologically distant. As such, a main barrier to pro-environmental behavior is that individuals often believe that their own behavior makes little to no difference on the environment. When it comes to communicating how the behavior of billions of individuals affects global climate change, it might appear valuable to aggregate those billions and present the shocking enormity of the resources individuals consume. This research provides initial evidence that, in fact, this strategy is ineffective; presenting large-scale aggregate data dilutes the contribution of the individual and impedes individuals’ motivation to act pro-environmentally. The high-impact, underrepresented behavior of eating a sustainable diet was chosen for the present studies. US Participants (total N = 668) were recruited online for a study on ‘meat and the environment’ and received information about some of resources used in meat production – water, CO2e, and feed – with numerical information that varied in its frame of reference. A ‘Nation’ frame of reference discussed the resources used in the beef industry, such as the billions of CO2e released daily by the industry, while a ‘Meal’ frame of reference presented the resources used in the production of a single beef dish. Participants completed measures of pro-environmental attitudes and behavioral intentions, either immediately (Study 1) or two days (Study 2) after reading the information. In Study 2 (n = 520) participants also indicated whether they consumed less or more meat than usual. Study 2 included an additional control condition that contained no environmental data. In Study 1, participants who read about meat production at a national level, compared to at a meal level, reported lower motivation to make ecologically conscious dietary choices and reported lower behavioral intention to change their diet. In Study 2, a similar pattern emerged, with the added insight that the Nation condition, but not the Meal condition, deviated from the control condition. Participants across conditions, on average, reduced their meat consumption in the duration of Study 2, except those in the Nation condition who remained unchanged. Presenting nation-wide consequences of human behavior is a double-edged sword: Framing in a large scale might reveal the relationship between collective actions and environmental issues, but it hinders the belief that individual actions make a difference.

Keywords: climate change communication, environmental concern, meat consumption, motivation

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Authors: T. Vijay Bhasker, N. K. S Gowda, P. Krishnamoorthy, D. T. Pal, A. K. Pattanaik, A. K. Verma

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Boron (B) is a newer trace element and its biological importance and dietary essentiality is unclear in animals. The available literature suggests its putative role in bone mineralization, antioxidant status and steroid hormone synthesis. A feeding trial was conducted in Wister strain (Rattus norvegicus) albino rats for duration of 90 days. A total of 84 healthy weaned (3-4 weeks) experimental rats were randomly divided into 7 dietary groups (4 replicates of three each) viz., A (Basal diet/ Control), B (Basal diet + 5 ppm B), C (Basal diet + 10 ppm B), D (Basal diet + 20 ppm B), E (Basal diet + 40 ppm B), F (Basal diet-Ca 50%), G (Basal diet-Ca 50% + 40 ppm B). Dietary level of calcium (Ca) was maintained at two levels, 100% and 50% of requirement. Sodium borate was used as source of boron along with other ingredients of basal diet while preparing the pelletized diets. All the rats were kept in proper ventilated laboratory animal house maintained at temperature (23±2º C) and humidity (50 to 70%). At the end of experiment digestibility trial was conducted for 5 days to estimate nutrient digestibility and gut absorption of minerals. Eight rats from each group were sacrificed to collect the vital organs (liver, kidney and spleen) to study histopathology. Blood sample was drawn by heart puncture to determine biochemical profile. The average daily feed intake (g/rat/day), water intake (ml/rat/day) and body weight gain (g/rat/day) were similar among the dietary groups. The digestibility (%) of organic matter and crude fat were significantly improved (P < 0.05) was by B supplementation. The gut absorption (%) Ca was significantly increased (P < 0.01) in B supplemented groups compared to control. However, digestibility of dry matter and crude protein, gut absorption of magnesium and phosphorus showed a non-significant increasing trend with B supplementation. The gut absorption (%) of B (P < 0.01) was significantly lowered (P<0.05) in supplemented groups compared to un-supplemented ones. The serum level of triglycerides (mg/dL), HDL-cholesterol (mg/dL) and alanine transaminase (IU/L) were significantly lowered (P < 0.05) in B supplemented groups. While serum level of glucose (mg/dL) and alkaline phosphatase (KA units) showed a non-significant decreasing trend with B supplementation. However the serum levels of total cholesterol (mg/dL) and aspartate transaminase (IU/L) were similar among dietary groups. The histology sections of kidney and spleen revealed no significant changes among the dietary groups and were observed to be normal in anatomical architecture. However, the liver histology revealed cell degenerative changes with vacuolar degeneration and nuclear condensation in Ca deficient groups. But the comparative degenerative changes were mild in 40 ppm B supplemented Ca deficient group. In conclusion, dietary supplementation of graded levels of boron in rats had a positive effect on metabolism and health by improving nutrient digestibility and gut absorption of Ca. This indicates the beneficial role of dietary boron supplementation.

Keywords: boron, calcium, nutrient utilization, histopathology

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Heba Al-Kelesh

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Day after day, high-grade iron ores are consumed. Because of the strong global demand for iron and steel, it has necessitated the utilization of various low-grade iron ores, which are not suitable for direct exploitation in the iron industry. The low-grade ores cannot be dressed using traditional mineral processing methods because of complicated mineral compositions. The present work is aimed to investigate the reducibility of some Egyptian iron ores and concentrates by conditions emulate different blast furnace areas. Representative specimens are collected from El-Gedida–Baharia oasis, Eastern South Aswan, and Eastern desert-wadi Kareem (EDC). Some mineralogical and morphological characterizations are executed. The reactivity arrangement of green samples is Baharia>Aswan>EDC. The presence of magnetite decreased reactivity of EDC. The reducibility of the Aswan sample is lower than Baharia due to the presence of agglomerated metallic grain surrounded by semi-melted phases. Specimens are annealed at 1000ᵒC for 3 hours. After firing, the reducibility of Aswan becomes the lowest due to the formation of fayalite and calcium phosphate phases. The relative attitude for green and fired samples reduced at different conditions are studied. For thermal and top areas, the reactivity of fired samples is greater than green ones, which were confirmed by morphological examinations.

Keywords: reducibility, low grade, iron industry, blast furnace

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Authors: S. V. Vasilenkov, O. N. Demina

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Chernobyl NPP accident is the biggest in history of nuclear energetic. Bryansk region of Russia was exposed by the most intensive radiation pollution. For that, we made some researches in order to find the methods of soil rehabilitation on territories, polluted by radionuclides with the means of Cesium 137 leaching by watering. For experiments we took the soil from the upper more polluted 10 cm layer of different species. Cesium 137 leaching was made by different methods in washing columns. Washout of Cesium was made by periodical cycles in terms of 4-6 days. In experiments with easy argillaceous soil with start specific radioactivity 4158 bk/kg through 17 cycles the effective reducing was achieved and contained 1512 bk/kg. Besides, results of researches showed, that in the first 6-10 cycles we can see reducing of washing rate but after application of intensificators: ultrasound water processing, aerification, application of fertilizers (KCl), lime, freezing, we can see increasing of Cesium 137 leaching. The experimental investigations in washout of Cesium (Cs) – 137 from the soil were carried out in the field and laboratorial conditions during its freezing and melting. The experiments showed, that washout of Cesium (Cs) – 137 from the soil is rather high after freezing, than non-frozen soil is. And it conforms to washout of Cesium, made under the influence of the intensificaters. This fact allows to recommend chip and easy to construct technically arrangement for regulation of the snow-melt runoff for rehabilitation of the radioactive impoundment.

Keywords: pollution, radiation, Cesium 137 leaching, agriculture

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Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks

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