Search results for: neural signal recording

Authors: Seyran Naghdi

Abstract:

Background: Orphan drug development is limited by very high costs attributed to the research and development and small size market. How health policymakers address this challenge to consider both supply and demand sides need to be explored for directing the policies and plans in the right way. The price is an important signal for pharmaceutical companies’ profitability and the patients’ accessibility as well. Objective: This study aims to find out the orphan drugs' price-setting patterns and approaches in health systems through a systematic review of the available evidence. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach was used. MedLine, Embase, and Web of Sciences were searched via appropriate search strategies. Through Medical Subject Headings (MeSH), the appropriate terms for pricing were 'cost and cost analysis', and it was 'orphan drug production', and 'orphan drug', for orphan drugs. The critical appraisal was performed by the Joanna-Briggs tool. A Cochrane data extraction form was used to obtain the data about the studies' characteristics, results, and conclusions. Results: Totally, 1,197 records were found. It included 640 hits from Embase, 327 from Web of Sciences, and 230 MedLine. After removing the duplicates, 1,056 studies remained. Of them, 924 studies were removed in the primary screening phase. Of them, 26 studies were included for data extraction. The majority of the studies (>75%) are from developed countries, among them, approximately 80% of the studies are from European countries. Approximately 85% of evidence has been produced in the recent decade. Conclusions: There is a huge variation of price-setting among countries, and this is related to the specific pharmacological market structure and the thresholds that governments want to intervene in the process of pricing. On the other hand, there is some evidence on the availability of spaces to reduce the very high costs of orphan drugs development through an early agreement between pharmacological firms and governments. Further studies need to focus on how the governments could incentivize the companies to agree on providing the drugs at lower prices.

Keywords: orphan drugs, orphan drug production, pricing, costs, cost analysis

Procedia PDF Downloads 146

Authors: Li Yang, Yang Song, Martin Y. M. Chiang

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Objective: To experimentally substantiate the micromechanical compatibility between cell and scaffold, in the regenerative medicine approach for restoring bone volume, is essential for phenotypic transitions Methods: Through nanotechnology and electrospinning process, nanofibrous scaffolds were fabricated to host dental follicle stem cells (DFSCs). Blends (50:50) of polycaprolactone (PCL) and silk fibroin (SF), mixed with various content of cellulose nanocrystals (CNC, up to 5% in weight), were electrospun to prepare nanofibrous scaffolds with heterogeneous microstructure in terms of fiber size. Colloidal probe atomic force microscopy (AFM) and conventional uniaxial tensile tests measured the scaffold stiffness at the micro-and macro-scale, respectively. The cell elastic modulus and cell-scaffold adhesive interaction (i.e., a chemical function) were examined through single-cell force spectroscopy using AFM. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to determine if the mechanotransduction signal (i.e., Yap1, Wwr2, Rac1, MAPK8, Ptk2 and Wnt5a) is upregulated by the scaffold stiffness at the micro-scale (cellular scale). Results: The presence of CNC produces fibrous scaffolds with a bimodal distribution of fiber diameter. This structural heterogeneity, which is CNC-composition dependent, remarkably modulates the mechanical functionality of scaffolds at microscale and macroscale simultaneously, but not the chemical functionality (i.e., only a single material property is varied). In in vitro tests, the osteogenic differentiation and gene expression associated with mechano-sensitive cell markers correlate to the degree of micromechanical compatibility between DFSCs and the scaffold. Conclusion: Cells require compliant scaffolds to encourage energetically favorable interactions for mechanotransduction, which are converted into changes in cellular biochemistry to direct the phenotypic evolution. The micromechanical compatibility is indeed important to the efficacy of regenerative medicine.

Keywords: phenotype transition, scaffold stiffness, electrospinning, cellulose nanocrystals, single-cell force spectroscopy

Procedia PDF Downloads 153

Authors: Heeba A. Gurku

Abstract:

Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

Procedia PDF Downloads 57

Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

Procedia PDF Downloads 258

Authors: Muhammad Arif Rahman, Gamma Abdul Jabbar, Enggar Handra Pangestu, Alfi Syahrin Qadri, Iryan Anugrah Putra, Rizqi Ramadhandi.

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Indonesia lies above three major tectonic plates, Indo-Australia plate, Eurasia plate, and Pacific plate. Interactions between those plates resulted in high tectonic and volcanic activities that corelates into high risk of geological hazards in adjacent areas, one of the areas is in North of Sulawesi’s Islands. This case raises a problem in terms of infrastructure in order to mitigate existing infrastructure and various future infrastructures plan. One of the infrastructures that is essentials to enhance telecommunication aspect is submarine fiber optic cable, that has risk to geological hazard. This cable is essential that act as backbone in telecommunication. Damaged fiber optic cables can pose serious problem that make existing signal to be loss and have negative impact to people’s social and economic factor with also decreasing various governmental services performance. Submarine cables are facing challenges in terms of geological hazards, for instance are seamounts activity. Previous studies show that until 2023, five seamounts are identified in North of Sulawesi. Seamounts itself can damage and trigger many activities that can risks submarine cables, one of the examples is submarine landslide. Main focuses of this study are to identify new possible seamounts and submarine landslide path in area North of Sulawesi Islands to help minimize risks pose by those hazards, either to existing or future plan submarine cables. Using bathymetry data, this study conduct slope analysis and use distinctive morphological features to interpret possible seamounts. Then we mapped out valleys in between seamounts and determine where sediments might flow in case of landslide, and to finally, know how it affect submarine cables in the area.

Keywords: bathymetry, geological hazard, mitigation, seamount, submarine cable, submarine landslide, volcanic activity

Procedia PDF Downloads 46

Authors: Shubhita Mathur, Ritika Kar Bahal, Priyanka Chauhan, Anil K. Tyagi

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Mycobacterium tuberculosis, the causative agent of human tuberculosis, is a major cause of mortality. Bacillus Calmette-Guérin (BCG), the only licensed vaccine available for protection against tuberculosis confers highly variable protection ranging from 0%-80%. Thus, novel vaccine strains need to be evaluated for their potential as a vaccine against tuberculosis. We had previously constructed a triple gene mutant of M. tuberculosis (MtbΔmms), having deletions in genes encoding for phosphatases mptpA, mptpB, and sapM that are involved in host-pathogen interaction. Though vaccination with Mtb∆mms strain induced protection in the lungs of guinea pigs, the mutant strain was not able to control the hematogenous spread of the challenge strain to the spleens. Additionally, inoculation with Mtb∆mms resulted in some pathological damage to the spleens in the early phase of infection. In order to overcome the pathology caused by MtbΔmms in the spleens of guinea pigs and also to control the dissemination of the challenge strain, MtbΔmms was genetically modified by disrupting bioA gene to generate MtbΔmmsb strain. Further, in vivo attenuation of MtbΔmmsb was evaluated, and its protective efficacy was assessed against virulent M. tuberculosis challenge in guinea pigs. Our study demonstrates that Mtb∆mmsb mutant was highly attenuated for growth and virulence in guinea pigs. Vaccination with Mtb∆mmsb mutant generated significant protection in comparison to sham-immunized animals at 4 and 12 weeks post-infection in lungs and spleens of the infected animals. Our findings provide evidence that deletion of genes involved in signal transduction and biotin biosynthesis severely attenuates the pathogen and the single immunization with the auxotroph was able to provide significant protection as compared to sham-immunized animals. The protection imparted by Mtb∆mmsb fell short in comparison to the protection observed in BCG-immunized animals. This study nevertheless indicates the importance of attenuated multiple gene deletion mutants of M. tuberculosis in generating protection against tuberculosis.

Keywords: Mycobacterium tuberculosis, BCG, MtbΔmmsb, bioA, guinea pigs

Procedia PDF Downloads 106

Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: laser scribing, lightscribe DVD, graphene oxide, scanning electron microscopy

Procedia PDF Downloads 92

Authors: Şenay Güngör, Emre Elbaşi, Beyda Sadikoğlu, Utku Eren Bağci, Ömer Uzunel

Abstract:

One of the first places that comes to mind when it comes to tourism in Turkey is the Cappadocia Region. Due to its rich geological and geomorphological heritage, Cappadocia is one of the most visited destinations in the world. In fact, in the first half of 2023, the number of international tourists visiting Cappadocia exceeded 2 million. Considering that the economy of the Cappadocia region is largely based on tourism, it is understood that the quality and technology integration levels of the touristic services offered in the region are of great importance. In this context; as a result of the observations made in Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys, where the important hiking routes of the Cappadocia Region are located, it has been observed that the digital level of the routes is insufficient. It has been observed that the telephone networks in the area are very low or have completely lost their signal strength. In addition, it was determined that the materials such as maps and brochures used by tourism agencies to introduce the valleys are simple and incomplete. It is thought that this situation negatively affects the tourists' orientation and touristic experience in the field. Eliminating these deficiencies identified in the field, improving the digital level of the above-mentioned hiking routes and increasing the added value in destinations are among the main objectives of our study. Within the scope of the study, a mobile application that can work both online and offline on hiking routes has been prepared. 3D modeling of Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys were made using Geographical Information Systems (GIS). In addition, a website has been created to enable tourists to easily access all the above-mentioned information, visuals and technological applications related to the routes. As it is known, the effective use of information and communication technologies in touristic regions not only increases the satisfaction levels of tourists, but also positively affects the attraction of qualified tourists to the region. When the tangible and intangible outputs of this study are evaluated, it is thought that it will serve the social and economic development of the region and set an example for the digital transformation of other routes in the region.

Keywords: nevşehir, cappadocia, cappadocia valleys, trekking route

Procedia PDF Downloads 38

Authors: M. Yaqoob, C. S. O’Neill, S. Faraj, C. L. O’Neill

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This paper presents the preliminary findings from a study exploring nurse’s contributions to end of life decisions and to the care of dying patients in ICU units in the Kingdom of Bahrain. The process of dying is complex as medical clinicians are frequently unable to say with certainty when death will occur. It is generally accepted that end of life care begins when it is possible to know that death is imminent. Nurses do not make medical treatment decisions when caring for a dying patient. There are, however, many other types of decisions made when a patient is approaching the end of life and nurses are either formally or informally part of these decision making processes. This study explored nurses care practices at the end of life, in two ICU units in large hospitals in the Kingdom of Bahrain. The research design was a grounded theory approach. Ten nurses participated, six of whom were Bahraini nationals and four were Indian. A core category death avoidance talk was supported by three major subcategories, degrees of involvement in decision making; signalling and creating an awareness of death; care shifting from dying patients to family. Despite nurses asserting that they carried out the orders of doctors and had no role in decision making processes at end of life this study showed that there were degrees of nurse involvement. Doctors frequently discussed the patient’s clinical condition with nurses and also sought information regarding the family. Information about the family was of particular relevance if the doctor was considering a DNR order, which the nurses equated with dying. Families were not always informed when a DNR decision was made. When families were not informed the nurses engaged in sophisticated rituals signalling and creating awareness to family members that the death of their loved one was near. This process also involved a subtle shifting of care from the dying patient to the family. This seminar paper will focus particularly on how nurses signal and create an awareness of death in an ICU setting. The findings suggest that despite the avoidance of death talk in the ICU nurses indirectly convey and create an awareness that death is near to family members.

Keywords: decision making, dying patients, end of life, intensive care unit

Procedia PDF Downloads 363

Authors: Shengnan Chen, Shuhua Wang

Abstract:

Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 262

Authors: Şenay Güngör, Emre Elbaşi, Beyda Sadikğlu, Utku Eren Bağci, Ömer Uzunel

Abstract:

One of the first places that comes to mind when it comes to tourism in Turkey is the Cappadocia Region. Due to its rich geological and geomorphological heritage, Cappadocia is one of the most visited destinations in the world. In fact, in the first half of 2023, the number of international tourists visiting Cappadocia exceeded 2 million. Considering that the economy of the Cappadocia region is largely based on tourism, it is understood that the quality and technology integration levels of the touristic services offered in the region are of great importance. In this context; as a result of the observations made in Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys, where the important hiking routes of the Cappadocia Region are located, it has been observed that the digital level of the routes is insufficient. It has been observed that the telephone networks in the area are very low or have completely lost their signal strength. In addition, it was determined that the materials such as maps and brochures used by tourism agencies to introduce the valleys are simple and incomplete. It is thought that this situation negatively affects the tourists' orientation and touristic experience in the field. Eliminating these deficiencies identified in the field, improving the digital level of the above-mentioned hiking routes and increasing the added value in destinations are among the main objectives of our study. Within the scope of the study, a mobile application that can work both online and offline on hiking routes has been prepared. 3D modeling of Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys were made using Geographical Information Systems (GIS). In addition, a website has been created to enable tourists to easily access all the above-mentioned information, visuals and technological applications related to the routes. As it is known, the effective use of information and communication technologies in touristic regions not only increases the satisfaction levels of tourists, but also positively affects the attraction of qualified tourists to the region. When the tangible and intangible outputs of this study are evaluated, it is thought that it will serve the social and economic development of the region and set an example for the digital transformation of other routes in the region.

Keywords: nevşehir, cappadocia, cappadocia valleys, tourism route

Procedia PDF Downloads 31

Authors: Fang Liu, JunShuai Xue, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun

Abstract:

Terahertz spectra is in great demand since last two decades for many photonic and electronic applications. III-Nitride resonant tunneling diode is one of the promising candidates for portable and compact THz sources. Room temperature microwave oscillator based on GaN/AlN resonant tunneling diode was reported in this work. The devices, grown by plasma-assisted molecular-beam epitaxy on free-standing c-plane GaN substrates, exhibit highly repeatable and robust negative differential resistance (NDR) characteristics at room temperature. To improve the interface quality at the active region in RTD, indium surfactant assisted growth is adopted to enhance the surface mobility of metal atoms on growing film front. Thanks to the lowered valley current associated with the suppression of threading dislocation scattering on low dislocation GaN substrate, a positive peak current density of record-high 2.1 MA/cm2 in conjunction with a peak-to-valley current ratio (PVCR) of 1.2 are obtained, which is the best results reported in nitride-based RTDs up to now considering the peak current density and PVCR values simultaneously. When biased within the NDR region, microwave oscillations are measured with a fundamental frequency of 0.31 GHz, yielding an output power of 5.37 µW. Impedance mismatch results in the limited output power and oscillation frequency described above. The actual measured intrinsic capacitance is only 30fF. Using a small-signal equivalent circuit model, the maximum intrinsic frequency of oscillation for these diodes is estimated to be ~260GHz. This work demonstrates a microwave oscillator based on resonant tunneling effect, which can meet the demands of terahertz spectral devices, more importantly providing guidance for the fabrication of the complex nitride terahertz and quantum effect devices.

Keywords: GaN resonant tunneling diode, peak current density, microwave oscillation, intrinsic capacitance

Procedia PDF Downloads 106

Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

Procedia PDF Downloads 91

Authors: Braden M. Li, Inhwan Kim, Jesse S. Jur

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One of the fundamental challenges in the electronic textile (e-textile) industry is the mismatch in compliance between the rigid electronic components integrated onto soft textile platforms. To address these problems, various printing technologies using conductive inks have been explored in an effort to improve the electromechanical performance without sacrificing the innate properties of the printed textile. However, current printing methods deposit densely layered coatings onto textile surfaces with low through-plane wetting resulting in poor electromechanical properties. This work presents an inkjet printing technique in conjunction with unique Kirigami cut designs to address these issues for printed smart textiles. By utilizing particle free reactive silver inks, our inkjet process produces conformal and micron thick silver coatings that surround individual fibers of the printed smart textile. This results in a highly conductive (0.63 Ω sq-1) printed e-textile while also maintaining the innate properties of the textile material including stretchability, flexibility, breathability and fabric hand. Kirigami is the Japanese art of paper cutting. By utilizing periodic cut designs, Kirigami imparts enhanced flexibility and delocalization of stress concentrations. Kirigami cut design parameters (i.e., cut spacing and length) were correlated to both the mechanical and electromechanical properties of the printed textiles. We demonstrate that designs using a higher cut-out ratio exponentially softens the textile substrate. Thus, our designs achieve a 30x improvement in the overall stretchability, 1000x decrease in elastic modulus, and minimal resistance change over strain regimes of 100-200% when compared to uncut designs. We also show minimal resistance change of our Kirigami inspired printed devices after being stretched to 100% for 1000 cycles. Lastly, we demonstrate a Kirigami-inspired electrocardiogram (ECG) monitoring system that improves stretchability without sacrificing signal acquisition performance. Overall this study suggests fundamental parameters affecting the performance of e-textiles and their scalability in the wearable technology industry

Keywords: kirigami, inkjet printing, flexible electronics, reactive silver ink

Procedia PDF Downloads 112

Authors: Misty Attwood, Helgi Schioth

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Transmembrane proteins are important components in many essential cell processes such as signal transduction, cell-cell signalling, transport of solutes, structural adhesion activities, and protein trafficking. Due to their involvement in diverse critical activities, transmembrane proteins are implicated in different disease pathways and hence are the focus of intense interest in understanding functional activities, their pathogenesis in disease, and their potential as pharmaceutical targets. Further, as the structure and function of proteins are correlated, investigating a group of proteins with the same tertiary structure, i.e., the same number of transmembrane regions, may give understanding about their functional roles and potential as therapeutic targets. In this in silico bioinformatics analysis, we identify and comprehensively characterize the previously unstudied group of proteins with five transmembrane-spanning regions (5TM). We classify nearly 60 5TM proteins in which 31 are members of ten families that contain two or more family members and all members are predicted to contain the 5TM architecture. Furthermore, nine singlet proteins that contain the 5TM architecture without paralogues detected in humans were also identifying, indicating the evolution of single unique proteins with the 5TM structure. Interestingly, more than half of these proteins function in localization activities through movement or tethering of cell components and more than one-third are involved in transport activities, particularly in the mitochondria. Surprisingly, no receptor activity was identified within this family in sharp contrast with other TM families. Three major 5TM families were identified and include the Tweety family, which are pore-forming subunits of the swelling-dependent volume regulated anion channel in astrocytes; the sidoreflexin family that acts as mitochondrial amino acid transporters; and the Yip1 domain family engaged in vesicle budding and intra-Golgi transport. About 30% of the proteins have enhanced expression in the brain, liver, or testis. Importantly, 60% of these proteins are identified as cancer prognostic markers, where they are associated with clinical outcomes of various tumour types, indicating further investigation into the function and expression of these proteins is important. This study provides the first comprehensive analysis of proteins with 5TM regions and provides details of the unique characteristics and application in pharmaceutical development.

Keywords: 5TM, cancer prognostic marker, drug targets, transmembrane protein

Procedia PDF Downloads 86

Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 208

Authors: Niloofar Zebarjad

Abstract:

This research aims at finding a tool to provide basketball players with real-time audio feedback on their shooting form in free throw shots. Free throws played a pivotal role in taking the lead in fierce competitions. The major problem in performing an accurate free throw seems to be improper training. Since the arm movement during the free throw shot is complex, the coach or the athlete might miss the movement details during practice. Hence, there is a necessity to create a system that measures arm movements' critical characteristics and control for improper kinematics. The proposed setup in this study quantifies arm kinematics and provides real-time feedback as an audio signal consisting of a gyroscope sensor. Spatial shoulder angle data are transmitted in a mobile application in real-time and can be saved and processed for statistical and analysis purposes. The proposed system is easy to use, inexpensive, portable, and real-time applicable. Objectives: This research aims to modify and control the free throw using audio feedback and determine if and to what extent the new setup reduces errors in arm formations during throws and finally assesses the successful throw rate. Methods: One group of elite basketball athletes and two novice athletes (control and study group) participated in this study. Each group contains 5 participants being studied in three separate sessions over a week. Results: Empirical results showed enhancements in the free throw shooting style, shot pocket (SP), and locked position (LP). The mean values of shoulder angle were controlled on 25° and 45° for SP and LP, respectively, recommended by valid FIBA references. Conclusion: Throughout the experiments, the system helped correct and control the shoulder angles toward the targeted pattern of shot pocket (SP) and locked position (LP). According to the desired results for arm motion, adding another sensor to measure and control the elbow angle is recommended.

Keywords: audio-feedback, basketball, free-throw, locked-position, motor-control, shot-pocket

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Authors: Fei Ye, Åsa Barrefelt, Manuchehr Abedi-Valugerdi, Khalid M. Abu-Salah, Salman A. Alrokayan, Mamoun Muhammed, Moustapha Hassan

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With appropriate encapsulation in functional nanoparticles drugs are more stable in physiological environment and the kinetics of the drug can be more carefully controlled and monitored. Furthermore, targeted drug delivery can be developed to improve chemotherapy in cancer treatment, not only by enhancing intracellular uptake by target cells but also by reducing the adverse effects in non-target organs. Inorganic imaging agents, delivered together with anti-cancer drugs, enhance the local imaging contrast and provide precise diagnosis as well as evaluation of therapy efficacy. We have developed biodegradable polymeric vesicles as a nanocarrier system for multimodal bio-imaging and anticancer drug delivery. The poly (lactic-co-glycolic acid) PLGA) vesicles were fabricated by encapsulating inorganic imaging agents of superparamagnetic iron oxide nanoparticles (SPION), manganese-doped zinc sulfide (MN:ZnS) quantum dots (QDs) and the anticancer drug busulfan into PLGA nanoparticles via an emulsion-evaporation method. T2-weighted magnetic resonance imaging (MRI) of PLGA-SPION-Mn:ZnS phantoms exhibited enhanced negative contrast with r2 relaxivity of approximately 523 s-1 mM-1 Fe. Murine macrophage (J774A) cellular uptake of PLGA vesicles started fluorescence imaging at 2 h and reached maximum intensity at 24 h incubation. The drug delivery ability PLGA vesicles was demonstrated in vitro by release of busulfan. PLGA vesicles degradation was studied in vitro, showing that approximately 32% was degraded into lactic and glycolic acid over a period of 5 weeks. The biodistribution of PLGA vesicles was investigated in vivo by MRI in a rat model. Change of contrast in the liver could be visualized by MRI after 7 min and maximal signal loss detected after 4 h post-injection of PLGA vesicles. Histological studies showed that the presence of PLGA vesicles in organs was shifted from the lungs to the liver and spleen over time.

Keywords: biodegradable polymers, multifunctional nanoparticles, quantum dots, anticancer drugs

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Authors: Pascale Brasseur, Binu Gurung, Nicholas Halfpenny, James Eaton

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Development of minimally invasive treatments in recent years provides a potential alternative to invasive surgical interventions which are of limited value to patients with spinal metastases due to short life expectancy. A systematic review was conducted to explore the efficacy and safety of radiofrequency ablation (RFA), a minimally invasive treatment in patients with spinal metastases. EMBASE, Medline and CENTRAL were searched from database inception to March 2017 for randomised controlled trials (RCTs) and non-randomised studies. Conference proceedings for ASCO and ESMO published in 2015 and 2016 were also searched. Fourteen studies were included: three prospective interventional studies, four prospective case series and seven retrospective case series. No RCTs or studies comparing RFA with another treatment were identified. RFA was followed by cement augmentation in all patients in seven studies and some patients (40-96%) in the remaining seven studies. Efficacy was assessed as pain relief in 13/14 studies with the use of a numerical rating scale (NRS) or a visual analogue scale (VAS) at various time points. Ten of the 13 studies reported a significant decrease in pain outcome, post-RFA compared to baseline. NRS scores improved significantly at 1 week (5.9 to 3.5, p < 0.0001; 8 to 4.3, p < 0.02 and 8 to 3.9, p < 0.0001) and this improvement was maintained at 1 month post-RFA compared to baseline (5.9 to 2.6, p < 0.0001; 8 to 2.9, p < 0.0003; 8 to 2.9, p < 0.0001). Similarly, VAS scores decreased significantly at 1 week (7.5 to 2.7, p=0.00005; 7.51 to 1.73, p < 0.0001; 7.82 to 2.82, p < 0.001) and this pattern was maintained at 1 month post-RFA compared to baseline (7.51 to 2.25, p < 0.0001; 7.82 to 3.3; p < 0.001). A significant pain relief was achieved regardless of whether patients had cement augmentation in two studies assessing the impact of RFA with or without cement augmentation on VAS pain scores. In these two studies, a significant decrease in pain scores was reported for patients receiving RFA alone and RFA+cement at 1 week (4.3 to 1.7. p=0.0004 and 6.6 to 1.7, p=0.003 respectively) and 15-36 months (7.9 to 4, p=0.008 and 7.6 to 3.5, p=0.005 respectively) after therapy. Few minor complications were reported and these included neural damage, radicular pain, vertebroplasty leakage and lower limb pain/numbness. In conclusion, the efficacy and safety of RFA were consistently positive between prospective and retrospective studies with reductions in pain and few procedural complications. However, the lack of control groups in the identified studies indicates the possibility of selection bias inherent in single arm studies. Controlled trials exploring efficacy and safety of RFA in patients with spinal metastases are warranted to provide robust evidence. The identified studies provide an initial foundation for such future trials.

Keywords: pain relief, radiofrequency ablation, spinal metastases, systematic review

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Authors: Franca De Sarno, Alfonso Maria Ponsiglione, Enza Torino

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Recent advances in diagnostic imaging technology have significantly contributed to a better understanding of specific changes associated with diseases progression. Among different imaging modalities, Magnetic Resonance Imaging (MRI) represents a noninvasive medical diagnostic technique, which shows low sensitivity and long acquisition time and it can discriminate between healthy and diseased tissues by providing 3D data. In order to improve the enhancement of MRI signals, some imaging exams require intravenous administration of contrast agents (CAs). Recently, emerging research reports a progressive deposition of these drugs, in particular, gadolinium-based contrast agents (GBCAs), in the body many years after multiple MRI scans. These discoveries confirm the need to have a biocompatible system able to boost a clinical relevant Gd-chelate. To this aim, several approaches based on engineered nanostructures have been proposed to overcome the common limitations of conventional CAs, such as the insufficient signal-to-noise ratios due to relaxivity and poor safety profile. In particular, nanocarriers, labeling or loading with CAs, capable of carrying high payloads of CAs have been developed. Currently, there’s no a comprehensive understanding of the thermodynamic contributions enable of boosting the efficacy of conventional CAs by using biopolymers matrix. Thus, considering the importance of MRI in diagnosing diseases, here it is reported a successful example of the next generation of these drugs where the commercial gadolinium chelate is incorporate into a biopolymer nanostructure, formed by cross-linked hyaluronic acid (HA), with improved relaxation properties. In addition, they are highlighted the basic principles ruling biopolymer-CA interactions in the perspective of their influence on the relaxometric properties of the CA by adopting a multidisciplinary experimental approach. On the basis of these discoveries, it is clear that the main point consists in increasing the rigidification of readily-available Gd-CAs within the biopolymer matrix by controlling the water dynamics, the physicochemical interactions, and the polymer conformations. In the end, the acquired knowledge about polymer-CA systems has been applied to develop of Gd-based HA nanoparticles with enhanced relaxometric properties.

Keywords: biopolymers, MRI, nanoparticles, contrast agent

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Authors: Periklis Brakatsoulas

Abstract:

Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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Authors: Uliana N. Tumanova, Viacheslav M. Lyapin, Vladimir G. Bychenko, Alexandr I. Shchegolev, Gennady T. Sukhikh

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All cases of stillbirth undoubtedly subject to postmortem examination, since it is necessary to find out the cause of the stillbirths, as well as a forecast of future pregnancies and their outcomes. Determination of the time of death is an important issue which is addressed during the examination of the body of a stillborn. It is mean the period from the time of death until the birth of the fetus. The time for fetal deaths determination is based on the assessment of the severity of the processes of maceration. To study the possibilities of postmortem magnetic resonance imaging (MRI) for determining the time of intrauterine fetal death based on the evaluation of maceration in the kidney. We have conducted MRI morphological comparisons of 7 dead fetuses (18-21 gestational weeks) and 26 stillbirths (22-39 gestational weeks), and 15 bodies of died newborns at the age of 2 hours – 36 days. Postmortem MRI 3T was performed before the autopsy. The signal intensity of the kidney tissue (SIK), pleural fluid (SIF), external air (SIA) was determined on T1-WI and T2-WI. Macroscopic and histological signs of maceration severity and time of death were evaluated in the autopsy. Based on the results of the morphological study, the degree of maceration varied from 0 to 4. In 13 cases, the time of intrauterine death was up to 6 hours, in 2 cases - 6-12 hours, in 4 -12-24 hours, in 9 -2-3 days, in 3 -1 week, in 2 -1,5-2 weeks. At 15 dead newborns, signs of maceration were absent, naturally. Based on the data from SIK, SIF, SIA on MR-tomograms, we calculated the coefficient of MR-maceration (M). The calculation of the time of intrauterine death (MP-t) (hours) was performed by our formula: МR-t = 16,87+95,38×М²-75,32×М. A direct positive correlation of MR-t and autopsy data from the dead at the gestational ages 22-40 weeks, with a dead time, not more than 1 week, was received. The maceration at the antenatal fetal death is characterized by changes in T1-WI and T2-WI signals at postmortem MRI. The calculation of MP-t allows defining accurately the time of intrauterine death within one week at the stillbirths who died on 22-40 gestational weeks. Thus, our study convincingly demonstrates that radiological methods can be used for postmortem study of the bodies, in particular, the bodies of stillborn to determine the time of intrauterine death. Postmortem MRI allows for an objective and sufficiently accurate analysis of pathological processes with the possibility of their documentation, storage, and analysis after the burial of the body.

Keywords: intrauterine death, maceration, postmortem MRI, stillborn

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: E. Nakamachi, K. Matsumoto, K. Yamamoto, Y. Morita, H. Sakamoto

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In recently, electromagnetic and mechanical stimulations have been recognized as the effective extracellular environment stimulation technique to enhance the defected peripheral nerve tissue regeneration. In this study, we developed a new hybrid bioreactor by adopting 50 Hz uniform alternative current (AC) magnetic stimulation and 4% strain mechanical stimulation. The guide tube for nerve regeneration is mesh structured tube made of biodegradable polymer, such as polylatic acid (PLA). However, when neural damage is large, there is a possibility that peripheral nerve undergoes necrosis. So it is quite important to accelerate the nerve tissue regeneration by achieving enhancement of nerve axonal extension rate. Therefore, we try to design and fabricate the system that can simultaneously load the uniform AC magnetic field stimulation and the stretch stimulation to cells for enhancement of nerve axonal extension. Next, we evaluated systems performance and the effectiveness of each stimulation for rat adrenal pheochromocytoma cells (PC12). First, we designed and fabricated the uniform AC magnetic field system and the stretch stimulation system. For the AC magnetic stimulation system, we focused on the use of pole piece structure to carry out in-situ microscopic observation. We designed an optimum pole piece structure using the magnetic field finite element analyses and the response surface methodology. We fabricated the uniform AC magnetic field stimulation system as a bio-reactor by adopting analytically determined design specifications. We measured magnetic flux density that is generated by the uniform AC magnetic field stimulation system. We confirmed that measurement values show good agreement with analytical results, where the uniform magnetic field was observed. Second, we fabricated the cyclic stretch stimulation device under the conditions of particular strains, where the chamber was made of polyoxymethylene (POM). We measured strains in the PC12 cell culture region to confirm the uniform strain. We found slightly different values from the target strain. Finally, we concluded that these differences were allowable in this mechanical stimulation system. We evaluated the effectiveness of each stimulation to enhance the nerve axonal extension using PC12. We confirmed that the average axonal extension length of PC12 under the uniform AC magnetic stimulation was increased by 16 % at 96 h in our bio-reactor. We could not confirm that the axonal extension enhancement under the stretch stimulation condition, where we found the exfoliating of cells. Further, the hybrid stimulation enhanced the axonal extension. Because the magnetic stimulation inhibits the exfoliating of cells. Finally, we concluded that the enhancement of PC12 axonal extension is due to the magnetic stimulation rather than the mechanical stimulation. Finally, we confirmed that the effectiveness of the uniform AC magnetic field stimulation for the nerve axonal extension using PC12 cells.

Keywords: nerve cell PC12, axonal extension, nerve regeneration, electromagnetic-mechanical stimulation, bioreactor

Procedia PDF Downloads 233

Authors: Menna Ewida, Dalal Abou El-Ella, Dina Lasheen, Huessin El-Subbagh

Abstract:

Introduction: Vascular Endothelial Growth Factor receptor (VEGF) is a signal protein produced by cells that stimulates vasculogenesis to create new blood vessels. VEGF family binds to three trans-membrane tyrosine kinase receptors,Dihydrofolate reductase (DHFR) is an enzyme of crucial importance in medicinal chemistry. DHFR catalyzes the reduction 7,8 dihydro-folate to tetrahydrofolate and intimately couples with thymidylate synthase which is a pivotal enzyme that catalysis the reductive methylation of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP) utilizing N5,N10-methylene tetrahydrofolate as a cofactor which functions as the source of the methyl group. Purpose: Novel substituted Thiazole agents were designed as DHFR and VEGF-TK inhibitors with increased synergistic activity and decreased side effects. Methods: Five series of compounds were designed with a rational that mimic the pharmacophoric features present in the reported active compounds that target DHFR & VEGFR. These molecules were docked against Methotrexate & Sorafenib as controls. An in silico ADMET study was also performed to validate the bioavailability of the newly designed compounds. The in silico molecular docking & ADMET study were also applied to the non-classical antifolates for comparison. The interaction energy comparable to that of MTX for DHFRI and Sorafenib for VEGF-TKI activity were recorded. Results: Compound 5 exhibited the highest interaction energy when docked against Sorafenib, While Compound 9 showed the highest interaction energy when docked against MTX with the perfect binding mode. Comparable results were also obtained for the ADMET study. Most of the compounds showed absorption within (95-99) zone which varies according to the type of substituents. Conclusions: The Substituted Thiazole Analogues could be a suitable template for antitumor drugs that possess enhanced bioavailability and act as DHFR and VEGF-TK inhibitors.

Keywords: anti-tumor agents, DHFR, drug design, molecular modeling, VEGFR-TKIs

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Authors: C. Yin, B. Zhang, Y. Liu, J. Cai

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Airborne EM (AEM) is an effective geophysical exploration tool, especially suitable for ridged mountain areas. In these areas, topography will have serious effects on AEM system responses. However, until now little study has been reported on topographic effect on airborne EM systems. In this paper, an edge-based unstructured finite-element (FE) method is developed for 3D topographic modeling for both frequency and time-domain airborne EM systems. Starting from the frequency-domain Maxwell equations, a vector Helmholtz equation is derived to obtain a stable and accurate solution. Considering that the AEM transmitter and receiver are both located in the air, the scattered field method is used in our modeling. The Galerkin method is applied to discretize the Helmholtz equation for the final FE equations. Solving the FE equations, the frequency-domain AEM responses are obtained. To accelerate the calculation speed, the response of source in free-space is used as the primary field and the PARDISO direct solver is used to deal with the problem with multiple transmitting sources. After calculating the frequency-domain AEM responses, a Hankel’s transform is applied to obtain the time-domain AEM responses. To check the accuracy of present algorithm and to analyze the characteristic of topographic effect on airborne EM systems, both the frequency- and time-domain AEM responses for 3 model groups are simulated: 1) a flat half-space model that has a semi-analytical solution of EM response; 2) a valley or hill earth model; 3) a valley or hill earth with an abnormal body embedded. Numerical experiments show that close to the node points of the topography, AEM responses demonstrate sharp changes. Special attentions need to be paid to the topographic effects when interpreting AEM survey data over rugged topographic areas. Besides, the profile of the AEM responses presents a mirror relation with the topographic earth surface. In comparison to the topographic effect that mainly occurs at the high-frequency end and early time channels, the EM responses of underground conductors mainly occur at low frequencies and later time channels. For the signal of the same time channel, the dB/dt field reflects the change of conductivity better than the B-field. The research of this paper will serve airborne EM in the identification and correction of the topographic effects.

Keywords: 3D, Airborne EM, forward modeling, topographic effect

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Authors: Hager Elsheikh, Juliane Glaubitz, Frank Ulrich Weiss, Matthias Sendler

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Aim: Acute pancreatitis (AP) and chronic pancreatitis (CP) are both accompanied by a prominent immune response which influences the course of disease. Whereas during AP the pro-inflammatory immune response dominates, during CP a fibroinflammatory response regulates organ remodeling. The transcription factor signal transducer and activator of transcription 6 (STAT6) is a crucial part of the Type 2 immune response. Here we investigate the role of STAT6 in a mouse model of AP and CP. Material and Methods: AP was induced by hourly repetitive i.p. injections of caerulein (50µg/kg/bodyweight) in C57Bl/6 J and STAT6-/- mice. CP was induced by repetitive caerulein injections 6 times a day, 3 days a week over 4 weeks. Disease severity was evaluated by serum amylase/lipase measurement, H&E staining of pancreas. Pancreatic infiltrate was characterized by immunofluorescent labeling of CD68, CD206, CCR2, CD4 and CD8. Pancreas fibrosis was evaluated by Azan blue staining. qRT-PCR was performed of Arg1, Nos2, Il6, Il1b, Col3a, Socs3 and Ym1. Affymetrix chip array analyses were done to illustrate the IL4/IL13/STAT6 signaling in bone marrow derived macrophages. Results: AP severity is mitigated in STAT6-/- mice, as shown by decreased serum amylase and lipase, as well as histological damage. CP mice surprisingly showed only slightly reduced fibrosis of the pancreas. Also staining of CD206 a classical marker of alternatively activated macrophages showed no decrease of M2-like polarization in the absence of STAT6. In contrast, transcription profile analysis in BMDM showed complete blockade of the IL4/IL13 pathway in STAT6-/- animals. Conclusion: STAT6 signaling pathway is protective during AP and mitigates the pancreatic damage. During chronic pancreatitis the IL4/IL13 – STAT6 axisis involved in organ fibrogenesis. Notably, fibrosis is not dependent on a single signaling pathway, and alternative macrophage activation is also complex and involves different subclasses (M2a, M2b, M2c and M2d) which could be independent of the IL4/IL13 STAT6 axis.

Keywords: chronic pancreatitis, macrophages, IL4/IL13, Type immune response

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Authors: J. Ritonja

Abstract:

Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

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Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

Abstract:

Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 381