Search results for: wound rotor synchronous machines

Authors: Diwei Lin, Amanda Tan, Rajinder Singh-Rai

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We present the first reported case of a concomitant Leydig cell tumor (LCT) and paratesticular leiomyoma in an adult male with a known history of bilateral cryptorchidism. An 80-year-old male presented with a 2-month history of a left testicular lump associated with mild discomfort and a gradual increase in size on a background of bilateral cryptorchidism requiring multiple orchidopexy procedures as a child. Ultrasound confirmed a lesion suspicious for malignancy and he proceeded to a left radical orchidectomy. Histopathological assessment of the left testis revealed a concomitant testicular LCT with malignant features and paratesticular leiomyoma. Leydig cell tumors (LCTs) are the most common pure testicular sex cord-stromal tumors, accounting for up to 3% of all testicular tumors. They can occur at almost any age, but are noted to have a bi-modal distribution, with a peak incidence at 6 to 10 and at 20 to 50 years of age. LCT’s are often hormonally active and can lead to feminizing or virilizing syndromes. LCT’s are usually regarded as benign but can rarely exhibit malignant traits. Paratesticular tumours are uncommon and their reported prevalence varies between 3% and 16%. They occur in a complex anatomical area which includes the contents of the spermatic cord, testicular tunics, epididymis and vestigial remnants. Up to 90% of paratesticular tumours are believed to originate from the spermatic cord, though it is often difficult to definitively ascertain the exact site of origin. Although any type of soft-tissue neoplasm can be found in the paratesticular region, the most common benign tumors reported are lipomas of the spermatic cord, adenomatoid tumours of the epididymis and leiomyomas of the testis. Genetic studies have identified potential mutations that could potentially cause LCTs, but there are no known associations between concomitant LCTs and paratesticular tumors. The presence of cryptorchidism in adults with both LCTs and paratesticular neoplasms individually has been previously reported and it appears intuitive that cryptorchidism is likely to be associated with the concomitant presentation in this case report. This report represents the first documented case in the literature of a unilateral concomitant LCT and paratesticular leiomyoma on a background of bilateral cryptorchidism.

Keywords: testicular cancer, leydig cell tumour, leiomyoma, paratesticular neoplasms

Procedia PDF Downloads 342

Authors: Recep Keşli, Gülşah Aşık, Cengiz Demir, Onur Türkyılmaz

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Objective: Proteus mirabilis (P. mirabilis) is one of Gram-negative pathogens in human and it causes urinary tract and nosocomial infections. P. mirabilis is susceptible to β-lactams, aminoglycosides, fluoroquinolones, and trimethoprim/sulfamethoxazole. It was aimed to investigate the resistance status to antimicrobial agents of Proteus mirabilis strains produced from samples sent to Afyon Kocatepe University, ANS Research and Practice Hospital, Microbiology Laboratory from different clinics and polyclinics during the period of 24 months. Methods: Between October 2013 and September 2015, a total of 30 Proteus were isolated from clinical samples of patients were hospitalized in intensive care units and in various departments of Afyon Kocatepe University, ANS Research and Practice Hospital. Identification of the bacteria was determined by conventional methods and VITEK 2 system (bioMérieux, France) was used additionally. Antibacterial susceptibility tests were performed by Kirby Bauer disc (Oxoid, Hempshire, England) diffusion method following the recommendations of CLSI. Results: Of the total 30 Proteus strains isolated from clinical samples, 19 from urine, 7 from wound, 4 from tracheal aspiration materials were isolated. Antimicrobial resistant for these strains were determined to 24,3% for meropenem, 26.2% for imipenem, 20.2% for amikacin 10.5% for cefepim, 33.3% for ciprofloxacin and levofloxacine, 31.6% for ceftazidime, 20% for ceftriaxone, 15.2% for gentamicin and 26.6% for amoxicillin-clavulanate, 26.2% trimethoprim-sulfamethoxale. Conclusion: In the present study, the highest number of clinical isolates of P. mirabilis were isolated from urine (63,3%), followed by the others (36,6%). The distribution of samples P. mirabilis strains to the clinics were as fallows; 16,8% intensive care unit (ICU), 29,9% polyclinics, 53,3% hospital service units The most effective antibiotic on the total of strains were found to be cefepim, the least effective antibiotics on the total of strains were found to be trimethoprim-sulfamethoxale.

Keywords: proteus mirabilis, antibiotic resistance, intensive care unit, Proteus spp.

Procedia PDF Downloads 259

Authors: Chittapon Jantararussamee, Malai Taweechotipatr, Udomsri Showpittapornchai, Wisuit Pradidarcheep

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Hepatic fibrosis is characterized by collagen accumulation in hepatic lobules following wound healing process. If lefts untreated, it could progress into hepatic cirrhosis, portal hypertension, and liver failure. Probiotics comprise of lactic acid bacteria which are crucial components of the intestinal microflora and possess many beneficial properties. The objective of this study is to investigate the hepatoprotective effects of probiotic lactic acid bacteria (mixture of Lactobacillus paracasei, Lactobacillus casei, and Lactobacillus confusus at a ratio of 1: 1: 1) on thioacetamide-induced liver fibrotic rats in term of histomorphology study. Twenty-four male Wistar rats were randomly divided into four groups with 6 rats each: (A) control, (B) fibrotic, (C) fibrotic+probiotic, and (D) probiotic. Group (A) received daily oral administration of distilled water. Group (B and C) were induced by intraperitoneal injection of thioacetamide (TAA) (200 mg/kg BW) 3 times per week for consecutive 8 weeks. In probiotic-treated group (C and D), the number of a mixture of the viable microbial cells at 10⁹ CFU/ml was administered orally daily. After sacrifice, liver tissues were collected and processed for routine histological technique and stained with Sirius red. It was found that the fibrotic rats showed hepatic injury marked by area of inflammation, hydropic degeneration of hepatocytes, and accumulation of myofibroblast-like cells. The collagen fibers were substantially accumulated in the hepatic lobules. Moreover, probiotic-treated group significantly reduced the accumulation of collagen in rats treated by TAA. The liver damage was found to be lesser in the probiotic-treated group. It was noted that the liver tissues of control and probiotics groups were shown to be normal. Administration with probiotic lactic acid bacteria could improve the histomorphology in fibrotic liver and be useful for prevention of hepatic disorders.

Keywords: liver fibrosis, probiotics, lactic acid bacteria, thioacetamide

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Authors: Andres Portocarrero Bonifaz, Caterina Sandra Camarena Rodriguez, Ricardo Palma Esparza, Nicolas Antonio Romero Carlos

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Reference levels for common X-rays procedures have been set in many protocols. In Peru, during quality control tests, the dose tolerance is set by these international recommendations. Nevertheless, further studies can be made to assess the national reality and relate dose levels with different parameters such as kV, mA/mAs, exposure time, type of processing (digital, digitalized or conventional), etc. In this paper three radiologic procedures were taken into account for study, general X-rays (fixed and mobile), intraoral X-rays (fixed, mobile and portable) and mammography. For this purpose, an Unfors Xi detector was used; the dose was measured at a focus - detector distance which varied depending on the procedure, and was corrected afterward to find the surface entry dose. The data used in this paper was gathered over a period of over 3 years (2015-2018). In addition, each X-ray machine was taken into consideration only once. The results hope to achieve a new standard which reflects the local practice, and address the issues of the ‘Bonn Call for Action’ in Peru. For this purpose, the 75% percentile of the dose of each radiologic procedure was calculated. In future quality control services, those machines with dose values higher than the selected threshold should be informed that they surpass the reference dose levels established in comparison other radiological centers in the country.

Keywords: general X-rays, intraoral X-rays, mammography, reference dose levels

Procedia PDF Downloads 129

Authors: Abhimanyu Pati, Krishna Kumar Veluri

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The paper intends to bring out a real life experience encountered during actual implementation of a large scale Tier-1 Enterprise Resource Planning (ERP) system in a multi-location, discrete manufacturing organization in India, involved in manufacturing of auto components and aggregates. The business complexities, prior to the implementation of ERP, include multi-product with hierarchical product structures, geographically distributed multiple plant locations with disparate business practices, lack of inter-plant broadband connectivity, existence of disparate legacy applications for different business functions, and non-standardized codifications of products, machines, employees, and accounts apart from others. On the other hand, the manufacturing environment consisted of processes like Assemble-to-Order (ATO), Make-to-Stock (MTS), and Engineer-to-Order (ETO) with a mix of discrete and process operations. The paper has highlighted various business plan areas and concerns, prior to the implementation, with specific focus on strategic issues and objectives. Subsequently, it has dealt with the complete process of ERP implementation, starting from strategic planning, project planning, resource mobilization, and finally, the program execution. The step-by-step process provides a very good learning opportunity about the implementation methodology. At the end, various organizational challenges and lessons emerged, which will act as guidelines and checklist for organizations to successfully align and implement ERP and achieve their business objectives.

Keywords: ERP, ATO, MTS, ETO, discrete manufacturing, strategic planning

Procedia PDF Downloads 220

Authors: Tariq Aljuneidi, Akif Asil Bulgak

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Remanufacturing may be defined as the process of bringing used products to “like-new” functional state with warranty to match, and it is one of the most popular product end-of-life scenarios. An efficient remanufacturing network lead to an efficient design of sustainable manufacturing enterprise. In remanufacturing network, products are collected from the customer zone, disassembled and remanufactured at a suitable remanufacturing facility. In this respect, another issue to consider is how the returned product to be remanufactured, in other words, what is the best layout for such facility. In order to achieve a sustainable manufacturing system, Cellular Manufacturing System (CMS) designs are highly recommended, CMSs combine high throughput rates of line layouts with the flexibility offered by functional layouts (job shop). Introducing the CMS while designing a remanufacturing network will benefit the utilization of such a network. This paper presents and analyzes a comprehensive mathematical model for the design of Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper, the proposed model is the first one to date that consider CMS and remanufacturing system simultaneously. The proposed DCRS model considers several manufacturing attributes such as multi-period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, available time for workers, worker assignments, and machine procurement, where the demand is totally satisfied from a returned product. A numerical example is presented to illustrate the proposed model.

Keywords: cellular manufacturing system, remanufacturing, mathematical programming, sustainability

Procedia PDF Downloads 353

Authors: M. Azadi, M. Kalhor

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Excavation of shallow tunnels such as subways in urban areas plays a significant role as a life line and investigation of the soil behavior against tunnel construction is one of the vital subjects studied in the geotechnical scope. Nowadays, urban tunnels are mostly drilled by T.B.Ms and changing the applied forces to tunnel lining is one of the most risky matters while drilling tunnels by these machines. Variation of soil cementation can change the behavior of these forces in the tunnel lining. Therefore, this article is designed to assess the impact of tunnel excavation in different soils and several amounts of cementation on applied loads to tunnel lining under static and dynamic loads. According to the obtained results, changing the cementation of soil will affect the applied loadings to the tunnel envelope significantly. It can be determined that axial force in tunnel lining decreases considerably when soil cementation increases. Also, bending moment and shear force in tunnel lining decreases as the soil cementation increases and causes bending and shear behavior of the segments to improve. Based on the dynamic analyses, as cohesion factor in soil increases, bending moment, axial and shear forces of segments decrease but lining behavior of the tunnel is the same as static state. The results show that decreasing the overburden applied to lining caused by cementation is different in two static and dynamic states.

Keywords: seismic behavior, twin tunnels, tunnel positions, TBM, optimum distance

Procedia PDF Downloads 266

Authors: Anna Lierova, Jitka Kasparova, Marcela Jelicova, Lucie Korecka, Zuzana Bilkova, Zuzana Sinkorova

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Hyaluronic acid (HA) is a simple linear, unbranched polysaccharide with a lot of exceptional physiological and chemical properties such as high biocompatibility and biodegradability, strong hydration and viscoelasticity that depend on the size of the molecule. It plays the important role in a variety of molecular events as tissue hydration, mechanical protection of tissues and as well as during inflammation, leukocyte migration, and extracellular matrix remodeling. Also, HA-based biomaterials, including HA scaffolds, hydrogels, thin membranes, matrix grafts or nanoparticles are widely use in various biomedical applications. Our goal is to determine the radioprotective effect of hyaluronic acid nanoparticles (HA NPs). We are investigating effect of ionizing radiation on stability of HA NPs, in vitro relative toxicity of nanoscale as well as effect on cell lines and specific surface receptors and their response to ionizing radiation. An exposure to ionizing radiation (IR) can irreversibly damage various cell types and may thus have implications for the level of the whole tissue. Characteristic manifestations are formation of over-granulated tissue, remodeling of extracellular matrix (ECM) and abortive wound healing. Damages are caused by either direct interaction with DNA and IR proteins or indirectly by radicals formed during radiolysis of water Accumulation and turnover of ECM are a hallmark of radiation induces lung injury, characterized by inflammation, repair or remodeling health pulmonary tissue. HA is a major component of ECM in lung and plays an important role in regulating tissue injury, accelerating tissue repair, and controlling disease outcomes. Due to that, HA NPs were applied to in vivo model (C57Bl/6J mice) before total body or partial thorax irradiation. This part of our research is targeting on effect of exogenous HA on the development and/or mitigating acute radiation syndrome and radiation induced lung injuries.

Keywords: hyaluronic acid, ionizing radiation, nanoparticles, radiation induces lung damages

Procedia PDF Downloads 143

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

Procedia PDF Downloads 380

Authors: Mahmoud Meckawey

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This research is dealing with one of the most important aspects of maintenance fields, that is Maintenance Strategy. It's the branch which concerns the concepts and the schematic thoughts in how to manage maintenance and how to deal with the defects in the engineering products (buildings, machines, etc.) in general. Through the papers we will act with the followings: i) The Engineering Product & the Technical Systems: When we act with the maintenance process, in a strategic view, we act with an (engineering product) which consists of multi integrated systems. In fact, there is no engineering product with only one system. We will discuss and explain this topic, through which we will derivate a developed definition for the maintenance process. ii) The factors or basis of the functionality efficiency: That is the main factors affect the functional efficiency of the systems and the engineering products, then by this way we can give a technical definition of defects and how they occur. iii) The legality of occurrence of defects (Legal defects and Illegal defects): with which we assume that all the factors of the functionality efficiency been applied, and then we will discuss the results. iv) The Guarantee, the Functional Span Age and the Technical surplus concepts: In the complementation with the above topic, and associated with the Reliability theorems, where we act with the Probability of Failure state, with which we almost interest with the design stages, that is to check and adapt the design of the elements. But in Maintainability we act in a different way as we act with the actual state of the systems. So, we act with the rest of the story that means we have to act with the complementary part of the probability of failure term which refers to the actual surplus of the functionality for the systems.

Keywords: engineering product and technical systems, functional span age, legal and illegal defects, technical and functional surplus

Procedia PDF Downloads 453

Authors: Peter Križan, Juraj Beniak, Ľubomír Šooš, Miloš Matúš

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Biomass treatment through densification is very suitable and important technology before its effective energy recovery. Densification process of biomass is significantly influenced by various technological and also material parameters which are ultimately reflected on the final solid Biofuels quality. The paper deals with the experimental research of the relationship between technological and material parameters during densification of fast-growing trees, roundly fast-rowing willow. The main goal of presented experimental research is to determine the relationship between pressing pressure raw material fraction size from a final briquettes density point of view. Experimental research was realized by single-axis densification. The impact of fraction size with interaction of pressing pressure and stabilization time on the quality properties of briquettes was determined. These parameters interaction affects the final solid biofuels (briquettes) quality. From briquettes production point of view and also from densification machines constructions point of view is very important to know about mutual interaction of these parameters on final briquettes quality. The experimental findings presented here are showing the importance of mentioned parameters during the densification process.

Keywords: briquettes density, densification, fraction size, pressing pressure, stabilization time

Procedia PDF Downloads 339

Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 213

Authors: M. Etezadi, A. Fahimifar

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In many geotechnical designs in rocks and rock masses, tensile strength of rock and rock mass is needed. The difficulties associated with performing a direct uniaxial tensile test on a rock specimen have led to a number of indirect methods for assessing the tensile strength that in the meantime the Brazilian test is more popular. Brazilian test is widely applied in rock engineering because specimens are easy to prepare, the test is easy to conduct and uniaxial compression test machines are quite common. This study compares experimental results of direct and Brazilian tensile tests carried out on two rock types and three concrete types using 39 cylindrical and 28 disc specimens. The tests are performed using Servo-Control device. The relationship between direct and indirect tensile strength of specimens is extracted using linear regression. In the following, tensile strength of direct and indirect test is evaluated using finite element analysis. The results are analyzed and effective factors on results are studied. According to the experimental results Brazilian test is shown higher tensile strength than direct test. Because of decreasing the contact surface of grains and increasing the uniformity in concrete specimens with fine aggregate (largest grain size= 6mm), higher tensile strength in direct test is shown. The experimental and numerical results of tensile strength are compared and empirical relationship witch is obtained from experimental tests is validated.

Keywords: tensile strength, brittle materials, direct and indirect tensile test, numerical modeling

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Authors: A. Kampker, K. Kreisköther, C. Reinders

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Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.

Keywords: additive manufacturing, design of experiments, mold making, PolyJet, 3D-Printing

Procedia PDF Downloads 234

Authors: Pouyan Jahanbin, Mahmoud Houshmand, Omid Fatahi Valilai

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A flexible manufacturing system (FMS) is a manufacturing system having the capability of handling the variations of products features that is the result of ever-changing customer demands. The flexibility of the manufacturing systems help to utilize the resources in a more effective manner. However, the control of such systems would be complicated and challenging. FMS needs CNC machines and robots and other resources for establishing the flexibility and enhancing the efficiency of the whole system. Also it needs to integrate the resources to reach required efficiency and flexibility. In order to reach this goal, an integrator framework is proposed in which the machining data of CNC machine tools is received through a STEP-NC file. The interoperability of the system is achieved by the information system. This paper proposes an information system that its data model is designed based on object oriented approach and is implemented through a knowledge-based system. The framework is connected to a database which is filled with robot’s control commands. The framework programs the robots by rules embedded in its knowledge based system. It also controls the interactions of CNC machine tools for loading and unloading actions by robot. As a result, the proposed framework improves the integration of manufacturing resources in Flexible Manufacturing Systems.

Keywords: CNC machine tools, industrial robots, knowledge-based systems, manufacturing recourses integration, flexible manufacturing system (FMS), object-oriented data model

Procedia PDF Downloads 431

Authors: Michael G. Pantelyat

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Fundamental basics of pure and applied research in the area of magneto-thermo-mechanical numerical analysis and design of innovative electromagnetic devices (modern induction heaters, novel thermoelastic actuators, rotating electrical machines, induction cookers, electrophysical devices) are elaborated. Thus, mathematical models of magneto-thermo-mechanical processes in electromagnetic devices taking into account main interactions of interrelated phenomena are developed. In addition, graphical representation of coupled (multiphysics) phenomena under consideration is proposed. Besides, numerical techniques for nonlinear problems solution are developed. On this base, effective numerical algorithms for solution of actual problems of practical interest are proposed, validated and implemented in applied 2D and 3D computer codes developed. Many applied problems of practical interest regarding modern electrical engineering devices are numerically solved. Investigations of the influences of various interrelated physical phenomena (temperature dependences of material properties, thermal radiation, conditions of convective heat transfer, contact phenomena, etc.) on the accuracy of the electromagnetic, thermal and structural analyses are conducted. Important practical recommendations on the choice of rational structures, materials and operation modes of electromagnetic devices under consideration are proposed and implemented in industry.

Keywords: electromagnetic devices, multiphysics, numerical analysis, simulation and design

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Qi LI, Xu Lin, Nengming Lin

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Objective: The aim of this study was to investigate the role of desmocollin 2 (DSC2) protein in the proliferation, migration and drug resistance of lung cancer cells. Method: CCK-8 assays and colony formation assays were used to evaluate the effect of dsc2 regulation on cancer cell viability and colony formation. Transwell assays and wound healing assays were also performed. Cell flow double staining was used to detect the apoptosis rate of cells with DSC2, which was added cisplatin. Western blot assay was used to detect cell cycle, PI3k/Akt and apoptosis-related proteins. Results: Our data showed that dsc2 is upregulated in clinical lung cancer tissues compared with pericarcinomatous tissues, and it is differentially expressed in lung cancer cell lines. The down-regulation of dsc2 in A549 and H358 lung cancer cells significantly suppressed the cell proliferation, metastasis, and motility. In contrast, the opposite effects were observed in overexpression of dsc2 both in H23 and PC9 cell lines. In addition to lung adenocarcinoma cell lines, we also examined its expression in lung squamous cell lines, such as H226. Western blotting showed that dsc2 could reduce the level of phosphorylated Akt (Ser 473) and p-mTOR. Thus, it is speculated that dsc2 up-regulation promotes proliferation and invasiveness through activation of the PI3K/AKT pathway. Also, knockdown of dsc2 in A549 and H226 could significantly decreased in the levels of cyclinB and wee1 protein. Additionally, flow cytometry showed that dsc2 knockdown combined with cisplatin could significantly enhance cell apoptosis rate. Conclusion: These data suggest that dsc2 promotes the proliferation and migration of lung cancer cells in vitro. Also, the results suggested that dsc2 could affect the cell cycle and apoptosis of lung cells. Furthermore, knockdown of dsc2 could sensitize cisplatin in both lung adenocarcinoma and lung squamous cell lines. Thus we suggested that dsc2 can be used as a therapeutic target for lung cancer.

Keywords: desmocollin 2, cisplatin, lung cancer, PI3K/AKT, lung squamous cell

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Authors: P. S. Percin, O. Inanli, S. Karakaya

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Bitter melon (Momordica charantia) is a medicinal vegetable, which is used traditionally to remedy diabetes. Bitter melon contains several classes of primary and secondary metabolites. In traditional Turkish medicine bitter melon is used for wound healing and treatment of peptic ulcers. Nowadays, bitter melon is used for the treatment of diabetes and ulcerative colitis in many countries. The main constituents of bitter melon, which are responsible for the anti-diabetic effects, are triterpene, protein, steroid, alkaloid and phenolic compounds. In this study total phenolics, total carotenoids and β-carotene contents of mature and immature bitter melons were determined. In addition, in vitro α-amylase and α-glucosidase activities of mature and immature bitter melons were studied. Total phenolic contents of immature and mature bitter melon were 74 and 123 mg CE/g bitter melon respectively. Although total phenolics of mature bitter melon was higher than that of immature bitter melon, this difference was not found statistically significant (p > 0.05). Carotenoids, a diverse group of more than 600 naturally occurring red, orange and yellow pigments, play important roles in many physiological processes both in plants and humans. The total carotenoid content of mature bitter melon was 4.36 fold higher than the total carotenoid content of immature bitter melon. The compounds that have hypoglycaemic effect of bitter melon are steroidal saponins known as charantin, insulin-like peptides and alkaloids. α-Amylase is one of the main enzymes in human that is responsible for the breakdown of starch to more simple sugars. Therefore, the inhibitors of this enzyme can delay the carbohydrate digestion and reduce the rate of glucose absorption. The immature bitter melon extract showed α-amylase and α-glucosidase inhibitory activities in vitro. α-Amylase inhibitory activity was higher than that of α-glucosidase inhibitory activity when IC50 values were compared. In conclusion, the present results provide evidence that aqueous extract of bitter melon may have an inhibitory effect on carbohydrate breakdown enzymes.

Keywords: bitter melon, in vitro antidiabetic activity, total carotenoids, total phenols

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 51

Authors: Feiruz Ab'lah, Zarini Ismail, Mohamad Zaki Hassan, Siti Nadia Mohd Bakhori, Mohamad Azlan Suhot, Mohd Yusof Md. Daud, Shamsul Sarip

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The construction industry is one of the major sectors in Malaysia. Apart from providing facilities, services, and goods it also offers employment opportunities to local and foreign workers. In fact, the construction workers are exposed to a hazardous level of noises that generated from various sources including excavators, bulldozers, concrete mixer, and piling machines. Previous studies indicated that the piling and concrete work was recorded as the main source that contributed to the highest level of noise among the others. Therefore, the aim of this study is to obtain the noise exposure during piling process and to determine the awareness of workers against noise pollution at the construction site. Initially, the reading of noise was obtained at construction site by using a digital sound level meter (SLM), and noise exposure to the workers was mapped. Readings were taken from four different distances; 5, 10, 15 and 20 meters from the piling machine. Furthermore, a set of questionnaire was also distributed to assess the knowledge regarding noise pollution at the construction site. The result showed that the mean noise level at 5m distance was more than 90 dB which exceeded the recommended level. Although the level of awareness regarding the effect of noise pollution is satisfactory, majority of workers (90%) still did not wear ear protecting device during work period. Therefore, the safety module guidelines related to noise pollution controls should be implemented to provide a safe working environment and prevent initial occupational hearing loss.

Keywords: construction, noise awareness, noise pollution, piling machine

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

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The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: T. Vikneshvaran, A. Aminudin, U. Alyaa Hashim, Waziralilah N. Fathiah, D. Shakirah Shukor

Abstract:

This paper presents the experimental study conducted on a structure of three-floor height building model. Most vibrations are undesirable and can cause damages to the buildings, machines and people all around us. The vibration wave from earthquakes, construction and winds have high potential to bring damage to the buildings. Excessive vibrations can result in structural and machinery failures. This failure is related to the human life and environment around it. The effect of vibration which causes failure and damage to the high rise buildings can be controlled in real life by implementing tuned mass damper (TMD) into the structure of the buildings. This research aims to study the effect and performance improvement achieved by applying TMD into the building structure. A structure model of three degrees of freedom (3DOF) is designed to demonstrate the performance of TMD to the designed model. The model designed is the physical representation of actual building structure in real life. It is constructed at a reduced scale and will be used for the experiment. Thus, the result obtained will be more accurate to compared with the real life effect. Based on the result from experimental study, by applying TMD to the structure model, the forces of vibration and the displacement mode of the building reduced. Thus, the reduced in vibration of the building helps to maintain the good condition of the building.

Keywords: degrees-of-freedom, displacement mode, natural frequency, tuned mass damper

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

Abstract:

We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

Procedia PDF Downloads 345

Authors: Ziya Uddin

Abstract:

This paper deals with the theoretical and numerical investigation of magneto-hydrodynamic boundary layer flow of a nano fluid past a wedge shaped wick in heat pipe used for the cooling of electronic components and different type of machines. To incorporate the effect of nanoparticle diameter, concentration of nanoparticles in the pure fluid, nano thermal layer formed around the nanoparticle and Brownian motion of nano particles etc., appropriate models are used for the effective thermal and physical properties of nano fluids. To model the rotation of nano particles inside the base fluid, microfluidics theory is used. In this investigation ethylene glycol (EG) based nanofluids, are taken into account. The non-linear equations governing the flow and heat transfer are solved by using a very effective particle swarm optimization technique along with Runge-Kutta method. The values of heat transfer coefficient are found for different parameters involved in the formulation viz. nanoparticle concentration, nanoparticle size, magnetic field and wedge angle etc. It is found that the wedge angle, presence of magnetic field, nanoparticle size and nanoparticle concentration etc. have prominent effects on fluid flow and heat transfer characteristics for the considered configuration.

Keywords: nanofluids, wedge shaped wick, heat pipe, numerical modeling, particle swarm optimization, nanofluid applications, Heat transfer

Procedia PDF Downloads 360

Authors: Sara Mostowfi, Hassan Sadeghinaeini, Sana Behnamasl, Leila Ensaniat, Maryam Mostafaee

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Nowadays, most of product producers, e.g. home appliance, electronic machines and vehicles focus on quality and comfort, and promise consumers ease of use and pleasurable experiences during product using. Consumers make their purchase decisions according to two needs: functional and emotional needs. Functional needs are fulfilled by product functionality, besides emotional needs are related to psychologists’ aspects of production. Emotions are distinctive elements which should be added to products and services to lead them up. In this case, the authors’ survey conducted pleasurable and hedonomic aspects in products of a home appliance company in Iran. In this regard, three samples of home appliance were selected: mixer, rice cooker, iron. Fifteen women (20-60) participated in this study. Every user evaluated each product by questionnaire based on 7 point semantic differential scale. After analyzing the results with statistical methods, results showed that 90% of users aren’t satisfied with hedonic and pleasurable criteria in interaction with these products. They notified that regarding hedonomics and pleasurable criteria’s they will have better ease of use and functionality. Our findings show a significant association between products’ features and user satisfaction. It seems that industrial design has a significant impression on the company’s products and with regard the pleasurable criteria the company sales will be more successful.

Keywords: home appliance, interaction, pleasure, hedonomy, ergonomy

Procedia PDF Downloads 355

Authors: Jonas Colin

Abstract:

Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

Procedia PDF Downloads 35

Authors: Riaan Kleyn

Abstract:

Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

Procedia PDF Downloads 63

Authors: Lavrentiadou S. N., Angelou V., Chatzimisios K., Papazoglou L.

Abstract:

The aim of this study was the isolation and culture of keratinocytes and fibroblasts from feline skin to ultimately create an artificial engineered skin (including dermis and epidermis) useful for the effective treatment of large cutaneous deficits in cats. Epidermal keratinocytes and dermal fibroblasts were freshly isolated from skin biopsies using an 8 mm biopsy punch obtained from 8 healthy cats that had undergone ovariohysterectomy. The owner’s consent was obtained. All cats had a complete blood count and a serum biochemical analysis and were screened for feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) preoperatively. The samples were cut into small pieces and incubated with collagenase (2 mg/ml) for 5-6 hours. Following digestion, cutaneous cells were filtered through a 100 μm cell strainer, washed with DMEM, and grown in DMEM supplemented with 10% FBS. The undigested epidermis was washed with DMEM and incubated with 0.05% Trypsin/0.02% EDTA (TE) solution. Keratinocytes recovered in the TE solution were filtered through a 100 μm and a 40 μm cell strainer and, following washing, were grown on a collagen type I matrix in DMEM: F12 (3:1) medium supplemented with 10% FΒS, 1 μm hydrocortisone, 1 μm isoproterenol and 0.1 μm insulin. Both fibroblasts and keratinocytes were grown in a humidified atmosphere with 5% CO2 at 37oC. The medium was changed twice a week and cells were cultured up to passage 4. Cells were grown to 70-85% confluency, at which point they were trypsinized and subcultured in a 1:4 dilution. The majority of the cells in each passage were transferred to a freezing medium and stored at -80oC. Fibroblasts were frozen in DMEM supplemented with 30% FBS and 10% DMSO, whereas keratinocytes were frozen in a complete keratinocyte growth medium supplemented with 10% DMSO. Both cell types were thawed and successfully grown as described above. Therefore, we can create a bank of fibroblasts and keratinocytes, from which we can recover cells for further culture and use for the generation of skin equivalent in vitro. In conclusion, cutaneous cell isolation and cell culture and expansion were successfully developed. To the authors’ best knowledge, this is the first study reporting isolation and culture of keratinocytes and fibroblasts from feline skin. However, these are preliminary results and thus, the development of autologous-engineered feline skin is still in process.

Keywords: cat, fibroblasts, keratinocytes, skin equivalent, wound

Procedia PDF Downloads 84

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

Procedia PDF Downloads 74