Search results for: neural stem cells

Authors: Yusha'u Shu'aibu Baraya, Kah Keng Wong, Nik Soriani Yaacob

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Strobilanthes crispus (S. crispus), is a Malaysian herb locally known as ‘Pecah kaca’ or ‘Jin batu’ which have demonstrated potent anticancer effects in both in vitro and in vivo models. In particular, S. crispus subfraction (SCS) significantly reduced tumor growth in N-methyl-N-Nitrosourea-induced breast cancer rat model. However, there is paucity of information on the effects of SCS in breast cancer metastasis. Thus, in this study, the antimetastatic effects of SCS (100 mg/kg) was investigated following 30 days of treatment in 4T1-induced mammary tumor (n = 5) model. The response to treatment was assessed based on the outcome of the tumour growth, body weight and hematological parameters. The results demonstrated that tumor bearing mice treated with SCS (TM-S) had significant (p<0.05) reduction in the mean tumor number and tumor volume as well as tumor weight compared to the tumor bearing mice (TM), i.e. tumor untreated group. Also, there was no secondary tumor formation or tumor-associated lesions in the major organs of TM-S compared to the TM group. Similarly, comparable body weights were observed among the TM-S, normal (uninduced) mice treated with SCS and normal (untreated/control) mice (NM) groups compared to the TM group (p<0.05). Furthermore, SCS administration does not cause significant changes in the hematological parameters as compared to the NM group, which indicates no sign of anemia and toxicity related effects. In conclusion, SCS significantly inhibited the overall tumor growth and metastasis in 4T1-induced breast cancer mouse model suggesting its promising potentials as therapeutic agent for breast cancer treatment.

Keywords: 4T1-cells, breast cancer, metastasis, Strobilanthes crispus

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Authors: Sizhu Wang, Cuisong Tang, Lin Zhang, Guangyu Tang

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Objective: We aimed to detect the composition of bone marrow fatty acids early after ovariectomized (OVX) surgery and explore the potential mechanism. Methods: Thirty-two female Sprague-Dawley (SD) rats (12 weeks) were randomly divided into OVX group and Sham group (N=16/group), and received ovariectomy or sham surgery respectively. After 3 and 28 days, eight rats in each group were sacrificed to detect the composition of bone marrow fatty acids by gas chromatography–mass spectrometry (GC–MS) and evaluate the trabecular bone microarchitecture by micro-CT. Significant different fatty acids in the early stage of post-menopausal osteoporosis were selected by OPLS-DA and t test. Then selected fatty acids were further studied in the process of osteogenic differentiation through RT-PCR and Alizarin Red S staining. Results: An apparent sample clustering and group separation were observed between OVX group and sham group three days after surgery, which suggested the role of bone marrow fatty acids in the early stage of postmenopausal osteoporosis. Specifically, myristate, palmitoleate and arachidonate were found to play an important role in classification between OVX group and sham group. We further investigated the effect of palmitoleate and arachidonate on osteogenic differentiation and found that palmitoleate promoted the osteogenic differentiation of MC3T3-E1 cells while arachidonate inhibited this process. Conclusion: Profound bone marrow fatty acids changes have taken place in the early stage of post-menopausal osteoporosis. Bone marrow fatty acids may begin to affect osteogenic differentiation shortly after deficiency of estrogen.

Keywords: bone marrow fatty acids, GC-MS, osteoblast, osteoporosis, post-menopausal

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: B. Hekner, J. Myalski, P. Wrzesniowski

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This study presents aluminum matrix composites reinforced by glassy carbon (GC) and titanium (Ti). In the first step, the heterophase (GC+Ti), spatial form (similar to skeleton) of reinforcement was obtained via own method. The polyurethane foam (with spatial, open-cells structure) covered by suspension of Ti particles in phenolic resin was pyrolyzed. In the second step, the prepared heterogeneous foams were infiltrated by aluminium alloy. The manufactured composites are designated to industrial application, especially as a material used in tribological field. From this point of view, the glassy carbon was applied to stabilise a coefficient of friction on the required value 0.6 and reduce wear. Furthermore, the wear can be limited due to titanium phase application, which reveals high mechanical properties. Moreover, fabrication of thin titanium layer on the carbon skeleton leads to reduce contact between aluminium alloy and carbon and thus aluminium carbide phase creation. However, the main modification involves the manufacturing of reinforcement in the form of 3D, skeleton foam. This kind on reinforcement reveals a few important advantages compared to classical form of reinforcement-particles: possibility to control homogeneity of reinforcement phase in composite material; low-advanced technique of composite manufacturing- infiltration; possibility to application the reinforcement only in required places of material; strict control of phase composition; High quality of bonding between components of material. This research is founded by NCN in the UMO-2016/23/N/ST8/00994.

Keywords: metal matrix composites, MMC, glassy carbon, heterophase composites, tribological application

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Authors: Tabugbo B. Ifeyinwa, Josephat O. Ogbuagu, Okeke A. Princewill, Victor C. Eze

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The increasing amount of plastic pollution in maritime settings poses a substantial risk to the functioning of ecosystems and the preservation of biodiversity. This comprehensive analysis combines the most recent data on the environmental effects of pollution from macroplastics, microplastics, and nanoplastics within marine ecosystems. Our goal is to provide a comprehensive understanding of the cumulative impacts that plastic waste accumulates on marine life by outlining the origins, processes, and ecological repercussions connected with each size category of plastic debris. Microplastics and nanoplastics have more sneaky effects that are controlled by chemicals. These effects can get through biological barriers and affect the health of cells and the whole body. Compared to macroplastics, which primarily contribute to physical harm through entanglement and ingestion by marine fauna, microplastics, and nanoplastics are associated with non-physical effects. The review underlines a vital need for research that crosses disciplinary boundaries to untangle the intricate interactions that the various sizes of plastic pollution have with marine animals, evaluate the long-term ecological repercussions, and identify effective measures for mitigating the effects of plastic pollution. Additionally, we urge governmental interventions and worldwide cooperation to solve this pervasive environmental concern. Specifically, we identify significant knowledge gaps in the detection and effect assessment of nanoplastics. To protect marine biodiversity and preserve ecosystem services, this review highlights how urgent it is to address the broad spectrum of plastic pollution.

Keywords: macroplastic pollution, marine ecosystem, microplastic pollution, nanoplastic pollution

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Authors: Rajandeep Kaur, Rajeev Gupta

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Background: Chronic myeloid leukemia (CML) is the most common leukaemia in India. The annual incidence of chronic myeloid leukemia in India was originally reported to be 0.8 to 2.2 per 1,00,000 population. CML is a clonal disorder that is usually easily diagnosed because the leukemic cells of more than 95% of patients have a distinctive cytogenetic abnormality, the Philadelphia chromosome (Ph1). The approval of tyrosine kinase inhibitors (TKIs), which target BCR-ABL1 kinase activity, has significantly reduced the mortality rate associated with chronic myeloid leukemia (CML) and revolutionized treatment. Material and Methods: 80 diagnosed cases of CML were taken. Investigations were done. Bone marrow and molecular studies were also done and with EUTOS, patients were stratified into low and high-risk groups and then treatment with Imatinib was given to all patients and the molecular response was evaluated at 6 months and 12 months follow up with BCR-ABL by RT-PCR quantitative assay. Results: In the study population, out of 80 patients in the study population, 40 were females and 40 were males, with M: F is 1:1. Out of total 80 patients’ maximum patients (54) were in 31-60 years age group. Our study showed a most common symptom of presentation is abdominal discomfort followed by fever. Out of the total 80 patients, 25 (31.3%) patients had high EUTOS scores and 55 (68.8%) patients had low EUTOS scores. On 6 months follow up 36.3% of patients had Complete Molecular Response, 16.3% of patients had Major Molecular Response and 47.5% of patients had No Molecular Response but on 12 months follow up 71.3% of patients had Complete Molecular Response, 16.25% of patients had Major Molecular Response and 12.5% patients had No Molecular Response. Conclusion: In this study, we found a significant correlation between EUTOS score and Molecular response at 6 months and 12 months follow up after Imatinib therapy.

Keywords: chronic myeloid leukemia, European treatment and outcome study score, hematological response, molecular response, tyrosine kinase inhibitor

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Paulomi Polly Burey, Mark Lynch

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It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Saqib Ali

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Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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Authors: Yang Zhao, Feng Zhang, Xuanchu Duan

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Trans-differentiation of human Tenon fibroblasts (HTFs) to myo-fibroblasts and fibrosis of episcleral tissue are the most common reasons for the failure of glaucoma filtration surgery, with limited treatment options like antimetabolites which always have side-effects such as leakage of filter bulb, infection, hypotony, and endophthalmitis. Rosiglitazone, a specific thiazolidinedione is a synthetic high-affinity ligand for PPAR-r, which has been used in the treatment of type2 diabetes, and found to have pleiotropic functions against inflammatory response, cell proliferation and tissue fibrosis and to benefit to a variety of diseases in animal myocardium models, steatohepatitis models, etc. Here, in vitro we cultured primary HTFs and stimulated with TGF- β to induced myofibrogenic, then treated cells with Rosiglitazone to assess for fibrogenic response. In vivo, we used rabbit glaucoma model to establish the formation of post- trabeculectomy scarring. Then we administered subconjunctival injection with Rosiglitazone beside the filtering bleb, later protein, mRNA and immunofluorescence of fibrogenic markers are checked, and filtering bleb condition was measured. In vitro, we found Rosiglitazone could suppressed proliferation and migration of fibroblasts through macroautophagy via TGF- β /Smad signaling pathway. In vivo, on postoperative day 28, the mean number of fibroblasts in Rosiglitazone injection group was significantly the lowest and had the least collagen content and connective tissue growth factor. Rosiglitazone effectively controlled human and rabbit fibroblasts in vivo and in vitro. Its subconjunctiiva application may represent an effective, new avenue for the prevention of scarring after glaucoma surgery.

Keywords: fibrosis, glaucoma, macroautophagy, rosiglitazone

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Authors: Mostafa Mabrouk, Basma E. Abdel-Ghany, Mona Moaness, Bothaina M. Abdel-Hady, Hanan H. Beherei

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Tissue engineering became a promising field for bone repair and regenerative medicine in which cultured cells, scaffolds and osteogenic inductive signals are used to regenerate tissues. The annual cost of treating bone defects in Egypt has been estimated to be many billions, while enormous costs are spent on imported bone grafts for bone injuries, tumors, and other pathologies associated with defective fracture healing. The current study is aimed at developing a more strategic approach in order to speed-up recovery after bone damage. This will reduce the risk of fatal surgical complications and improve the quality of life of people affected with such fractures. 3D scaffolds loaded with cheap nano-particles that possess an osteogenic effect were prepared by nano-electrospinning. The Microstructure and morphology characterizations of the 3D scaffolds were monitored using scanning electron microscopy (SEM). The physicochemical characterization was investigated using X-ray diffractometry (XRD) and infrared spectroscopy (IR). The Physicomechanical properties of the 3D scaffold were determined by a universal testing machine. The in vitro bioactivity of the 3D scaffold was assessed in simulated body fluid (SBF). The bone-bonding ability of novel 3D scaffolds was also evaluated. The obtained nanofibrous scaffolds demonstrated promising microstructure, physicochemical and physicomechanical features appropriate for enhanced bone regeneration. Therefore, the utilized nanomaterials loaded with the drug are greatly recommended as cheap alternatives to growth factors.

Keywords: bone regeneration, cheap scaffolds, nanomaterials, active molecules

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Authors: Balakrishna Valluru, Ruth Suckling

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A 16 year old male was found collapsed on the road following stab injuries to the chest and abdomen and was transported to the emergency department by ambulance. On arrival in the emergency department the patient was breathless and appeared pale. He was maintaining his airway with spontaneous breathing and had a heart rate of 122 beats per minute with a blood pressure of 83/63 mmHg. He was resuscitated initially with three units of packed red cells. Clinical examination identified three incisional wounds each measuring 2 cm. These were in the left para-sternal region, right infra-scapular region and left upper quadrant of the abdomen. The chest wound over the left parasternal area at the level of 4tth intercostal space was bleeding intermittently on leaning forwards and was relieving his breathlessness intermittently. CT imaging was performed to characterize his injuries and determine his management. CT scan of chest and abdomen showed moderate size haemopericardium with left sided haemopneumothorax. The patient underwent urgent surgical repair of the left ventricle and left anterior descending artery. He recovered without complications and was discharged from the hospital. This case highlights the fact that the potential to develop a life threatening cardiac tamponade was mitigated by the left parasternal stab wound. This injury fortuitously provided a pericardial window through which the bleeding from the injured left ventricle and left anterior descending artery could drain into the left hemithorax providing an opportunity for timely surgical intervention to repair the cardiac injuries.

Keywords: stab, incisional, haemo-pericardium, haemo-pneumothorax

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: Moataz Medhat, Essam E. Khalil, Hatem Haridy

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In the present study, a numerical simulation study is used to 3-D model the steady-state combustion of a staged natural gas flame in a 300 kW swirl-stabilized burner, using ANSYS solver to find the highest combustion efficiency by changing the inlet air swirl number and burner quarl angle in a furnace and showing the effect of flue gas recirculation, type of fuel and staging. The combustion chamber of the gas turbine is a cylinder of diameter 1006.8 mm, and a height of 1651mm ending with a hood until the exhaust cylinder has been reached, where the exit of combustion products which have a diameter of 300 mm, with a height of 751mm. The model was studied by 15 degree of the circumference due to axisymmetric of the geometry and divided into a mesh of about 1.1 million cells. The numerical simulations were performed by solving the governing equations in a three-dimensional model using realizable K-epsilon equations to express the turbulence and non-premixed flamelet combustion model taking into consideration radiation effect. The validation of the results was done by comparing it with other experimental data to ensure the agreement of the results. The study showed two zones of recirculation. The primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. It is found that the increase in temperature in the external recirculation zone is a result of increasing the swirl number of the inlet air stream. Also it was found that recirculating part of the combustion products back to the combustion zone decreases pollutants formation especially nitrogen monoxide.

Keywords: burner selection, natural gas, analysis, recirculation

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Authors: Akan C. Offong, E. J. Anthony, Vasilije Manovic

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A modified steady-state numerical model is developed for the electrochemical reduction of CO₂ to formic acid. The numerical model achieves a CD (current density) (~60 mA/cm²), FE-faradaic efficiency (~98%) and conversion (~80%) for CO₂ electro-reduction to formic acid in a microfluidic cell. The model integrates charge and species transport, mass conservation, and momentum with electrochemistry. Specifically, the influences of Bi-Sn based nanoparticle catalyst (on the cathode surface) at different mole fractions and 1-ethyl-3-methyl imidazolium tetra-fluoroborate ([EMIM][BF₄]) electrolyte, on CD, FE and CO₂ conversion to formic acid is studied. The reaction is carried out at a constant concentration of electrolyte (85% v/v., [EMIM][BF₄]). Based on the mass transfer characteristics analysis (concentration contours), mole ratio 0.5:0.5 Bi-Sn catalyst displays the highest CO₂ mole consumption in the cathode gas channel. After validating with experimental data (polarisation curves) from literature, extensive simulations reveal performance measure: CD, FE and CO₂ conversion. Increasing the negative cathode potential increases the current densities for both formic acid and H₂ formations. However, H₂ formations are minimal as a result of insufficient hydrogen ions in the ionic liquid electrolyte. Moreover, the limited hydrogen ions have a negative effect on formic acid CD. As CO₂ flow rate increases, CD, FE and CO₂ conversion increases.

Keywords: carbon dioxide, electro-chemical reduction, ionic liquids, microfluidics, modelling

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Authors: M. Knezevic, V. Marecic, M. Ozanic, I. Kelava, M. Mihelcic, M. Santic

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Francisella tularensis is a highly infectious, gram-negative intracellular bacterium and the causative agent of tularemia. The bacterium has been isolated from more than 250 wild species, including protozoa cells. Since Francisella is very virulent and persists in the environment for years, the aim of this study was to investigate whether Acanthamoeba castellanii-grown F. novicida exhibits an alteration in the resistance to disinfectants. It has been shown by other intracellular pathogens, including Legionella pneumophila that bacteria grown in amoeba exhibit more resistance to disinfectants. However, there is no data showing Francisella viability behaviour after intracellular life cycle in A. castellani. In this study, the bacterial suspensions of A. castellanii-grown or in vitro-grown Francisella were treated with three different disinfectants, and the bacterial viability after disinfection treatment was determined by a colony-forming unit (CFU) counting method, transmission electron microscopy (TEM), fluorescence microscopy as well as the leakage of intracellular fluid. Our results have shown that didecyldimethylammonium chloride (DDAC) combined with isopropyl alcohol was the most effective in bacterial killing; all in vitro-grown and A. castellanii-grown F. novicida were killed after only 10s. Surprisingly, in comparison to in vitro-grown bacteria, A. castellanii-grown F. novicida was more sensitive to decontamination by the benzalkonium chloride combined with DDAC and formic acid and the polyhexamethylene biguanide (PHMB). We can conclude that the tested disinfectants exhibit antimicrobial activity by causing a loss of structural organization and integrity of the Francisella cell wall and membrane and the subsequent leakage of the intracellular contents. Finally, the results of this study clearly demonstrate that Francisella grown in A. castellanii had become more susceptible to many disinfectants.

Keywords: Acanthamoeba, disinfectant, Francisella, sensitivity

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Yassir Abdelrazig, Ren Moses

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Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: Bernard L. Middleton, Susan P. Cosgrove

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There is an immediate need for alternative anti-herpetic treatment options effective for both primary infections and reoccurring reactivations of herpes simplex virus types 1 (HSV-1) and 2 (HSV-2). Alternatives currently approved for the purposes of clinical administration includes antivirals and a reduced set of nucleoside analogues. The present article tests a treatment based on a systemic understanding of how the herpes virus affects cell inhibition and breakdown and targets different phases of the viral cycle, including the entry stage, reproductive cross mutation, and cell-to-cell infection. The treatment consisted of five immunotherapeutic core compounds (5CC), which were hypothesized to be capable of neutralizing human monoclonal antibodies. The tested 5CC were noted as being functional in the application of eliminating the DNA synthesis of herpes viral interferon (IFN) - induced cellular antiviral response. They were here found to neutralize antiviral reproduction by blocking cell-to-cell infection. The activity of the 5CC was tested on RC-37 in vitro using an assay plaque reduction and in vivo against HSV-1 and HSV-2. The 50% inhibitory concentration (IC50) of 5CC was 0.0009% for HSV-1 plaque formation and 0.0008% for HSV-2 plaque formation. Further tests were performed to evaluate the susceptibility of HSV-1 and HSV-2 to anti-herpetic drugs in Vero cells after virus entry. There were high-level markers of the 5CC virucidal activity in the viral suspension of HSV-1 and HSV-2. These concentrations of the 5CC are nontoxic and reduced plaque formation by 98.2% for HSV-1 and 93.0% for HSV-2. Virus HSV-1 and HSV-2 titers were reduced significantly by 5CC to the point of being negative, ranging 0.01–0.09 in 72%. The results concluded the 5CC as being an effective treatment option for the herpes simplex virus.

Keywords: synergy pharmaceuticals, herpes treatment, herpes cure, synergy pharmaceuticals treatment

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Francisco Pedroza-Montero, Jesús Naín Pedroza-Montero, Diego Soto-Puebla, Osiris Alvarez-Bajo, Beatriz Castaneda, Sofía Navarro-Espinoza, Martín Pedroza-Montero

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Nanodiamonds have been widely studied for their physical properties, including chemical inertness, biocompatibility, optical transparency from the ultraviolet to the infrared region, high thermal conductivity, and mechanical strength. In this work, we studied how the fluorescence spectrum of nanodiamonds quenches concerning the concentration in aqueous solutions systematically ranging from 0.1 to 10 mg/mL. Our results demonstrated a non-linear fluorescence quenching as the concentration increases for both of the NV zero-phonon lines; the 5 mg/mL concentration shows the maximum fluorescence emission. Furthermore, this behaviour is theoretically explained as an electronic recombination process that modulates the intensity in the NV centres. Finally, to gain more insight, the FRET methodology is used to determine the fluorescence efficiency in terms of the fluorophores' separation distance. Thus, the concentration level is simulated as follows, a small distance between nanodiamonds would be considered a highly concentrated system, whereas a large distance would mean a low concentrated one. Although the 5 mg/mL concentration shows the maximum intensity, our main interest is focused on the concentration of 0.5 mg/mL, which our studies demonstrate the optimal human cell viability (99%). In this respect, this concentration has the feature of being as biocompatible as water giving the possibility to internalize it in cells without harming the living media. To this end, not only can we track nanodiamonds on the surface or inside the cell with excellent precision due to their fluorescent intensity, but also, we can perform thermometry tests transforming a fluorescence contrast image into a temperature contrast image.

Keywords: nanodiamonds, fluorescence spectroscopy, concentration, bioimaging, thermometry

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Authors: Helmi Vent

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This four-year artistic research project has set the goal of exploring the adaptable transitions within the realms between the two genres. This paper will single out one research question from the entire project for its focus, namely on how and under what circumstances such transitions between a reinterpretation and a new creation can take place during the performative process. The film documentation that accompany the project were produced at the Mozarteum University in Salzburg, Austria, as well as on diverse everyday stages at various locations. The model institution that hosted the project is the LIA – Lab Inter Arts, under the direction of Helmi Vent. LIA combines artistic research with performative applications. The project participants are students from various artistic fields of study. The film documentation forms a central platform for the entire project. They function as audiovisual records of performative performative origins and development processes, while serving as the basis for analysis and evaluation, including the self-evaluation of the recorded material and they also serve as illustrative and discussion material in relation to the topic of this paper. Regarding the “interspaces” and variable 'transitions': The performing arts in the western cultures generally orient themselves toward existing original compositions – most often in the interconnected fields of music, dance and theater – with the goal of reinterpreting and rehearsing a pre-existing score, choreographed work, libretto or script and presenting that respective piece to an audience. The essential tool in this reinterpretation process is generally the artistic ‘language’ performers learn over the course of their main studies. Thus, speaking is combined with singing, playing an instrument is combined with dancing, or with pictorial or sculpturally formed works, in addition to many other variations. If the Performing Arts would rid themselves of their designations from time to time and initially follow the emerging, diffusely gliding transitions into the unknown, the artistic language the performer has learned then becomes a creative resource. The illustrative film excerpts depicting the realms between Performing Arts and Performance Art present insights into the ways the project participants embrace unknown and explorative processes, thus allowing the genesis of new performative designs or concepts to be invented between the participants’ acquired cultural and artistic skills and their own creations – according to their own ideas and issues, sometimes with their direct involvement, fragmentary, provisional, left as a rough draft or fully composed. All in all, it is an evolutionary process and its key parameters cannot be distilled down to their essence. Rather, they stem from a subtle inner perception, from deep-seated emotions, imaginations, and non-discursive decisions, which ultimately result in an artistic statement rising to the visible and audible surface. Within these realms between performing arts and performance art and their extremely flexible transitions, exceptional opportunities can be found to grasp and realise art itself as a research process.

Keywords: art as research method, Lab Inter Arts ( LIA ), performing arts, performance art

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Authors: Yamina Boukari, Nashiru Billa, Andrew Morris, Stephen Doughty, Kevin Shakesheff

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Poly (lactic-co-glycolic) acid (PLGA) is a synthetic polymer that can be used in bone tissue engineering with the aim of creating a scaffold in order to support the growth of cells. The formation of microspheres from this polymer is an attractive strategy that would allow for the development of an injectable system, hence avoiding invasive surgical procedures. The aim of this study was to develop a microsphere delivery system for use as an injectable scaffold in bone tissue engineering and evaluate various formulation parameters on its properties. Porous and lysozyme-containing PLGA microspheres were prepared using the double emulsion solvent evaporation method from various molecular weights (MW). Scaffolds were formed by sintering to contain 1 -3mg of lysozyme per gram of scaffold. The mechanical and physical properties of the scaffolds were assessed along with the release of lysozyme, which was used as a model protein. The MW of PLGA was found to have an influence on microsphere size during fabrication, with increased MW leading to an increased microsphere diameter. An inversely proportional relationship was displayed between PLGA MW and mechanical strength of formed scaffolds across loadings for low, intermediate and high MW respectively. Lysozyme release from both microspheres and formed scaffolds showed an initial burst release phase, with both microspheres and scaffolds fabricated using high MW PLGA showing the lowest protein release. Following the initial burst phase, the profiles for each MW followed a similar slow release over 30 days. Overall, the results of this study demonstrate that lysozyme can be successfully incorporated into porous PLGA scaffolds and released over 30 days in vitro, and that varying the MW of the PLGA can be used as a method of altering the physical properties of the resulting scaffolds.

Keywords: bone, microspheres, PLGA, tissue engineering

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Authors: Okpaneje Onyinye Theresa, Ugwu Laeticia Udodiri, Okereke Ngozi Agatha, Okoli Nonso Livinus

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This work is on the synthesis and study of the optical characterization of polyaniline/nickel sulphide nanocomposite. Polyaniline (PANI) and nickel sulphide (NiS) nanoparticles were synthesized by oxidative chemical polymerization and sol-gel method. The polyaniline nickel sulphide nanocomposites with various concentrations of NiS were synthesized by in-situ polymerization of aniline monomer. In each case, the nickel sulphide nanoparticles were uniformly dispersed in the aniline hydrochloride before the initiation of oxidative chemical polymerization using ammonium persulphate. The samples formed were subjected to optical characterization using an ultraviolet (UV)-visible light (VIS) spectrophotometer (model: 756S UV – VIS). Optical analysis of the synthesized nanoparticles and nanocomposites showed absorption of radiation within VIS regions. The Tauc model was used to obtain the optical band gap. Energy band gap values of PANI and NiS were found to be 2.50 eV and 1.95 eV, respectively. PANI/NiSnanocomposites has an energy band gap that decreased from 2.25 eV to 1.90 eV as the amount of NiS increased (from 0.5g to 2.0g). These optical results showed that these nanocomposites are potential materials to be considered in solar cells and optoelectronics devices. The structural analysis confirmed the formation of polyaniline and hexagonal nickel sulphide with an average crystallite size of 25.521 nm, while average crystallite sizes of PANI/NiSnanocomposites ranged from 19.458 nm to 25.108 nm. Average particle sizes obtained from the SEM images ranged from 23.24 nm to 51.88 nm. Compositional results confirmed the presence of desired elements that made up the nanoparticles and nanocomposites.

Keywords: polyaniline, nickel sulphide, polyaniline-nickel sulphide nanocomposite, optical characterization, structural analysis, morphological properties, compositional properties

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Authors: Saeed Asiri, Yousuf Z. AL-Zahrani

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A new class of support structures, called periodic structures, is introduced in this paper as a viable means for isolating the vibration transmitted from the sea waves to offshore platform structures through its legs. A passive approach to reduce transmitted vibration generated by waves is presented. The approach utilizes the property of periodic structural components that creates stop and pass bands. The stop band regions can be tailored to correspond to regions of the frequency spectra that contain harmonics of the wave frequency, attenuating the response in those regions. A periodic structural component is comprised of a repeating array of cells, which are themselves an assembly of elements. The elements may have differing material properties as well as geometric variations. For the purpose of this research, only geometric and material variations are considered and each cell is assumed to be identical. A periodic leg is designed in order to reduce transmitted vibration of sea waves. The effectiveness of the periodicity on the vibration levels of platform will be demonstrated theoretically. The theory governing the operation of this class of periodic structures is introduced using the transfer matrix method. The unique filtering characteristics of periodic structures are demonstrated as functions of their design parameters for structures with geometrical and material discontinuities; and determine the propagation factor by using the spectral finite element analysis and the effectiveness of design on the leg structure by changing the ratio of step length and area interface between the materials is demonstrated in order to find the propagation factor and frequency response.

Keywords: vibrations, periodic structures, offshore, platforms, transfer matrix method

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Authors: Cristina Busuioc, Georgeta Voicu, Sorin-Ion Jinga

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The human bone presents in its dry form piezoelectric properties, which means that a mechanical stress results in electric polarization and an applied electric field causes strain. The immediate consequence was the revealing of piezoelectricity role in bone remodelling, as well as the integration of ceramic materials with piezoelectric behaviour in the composition of unitary or composite biomaterials. Thus, we prepared hydroxyapatite - collagen hybrid materials with barium titanate addition in order to achieve a better osseointegration. Barium titanate powder synthesized by a combined sol-gel-hydrothermal method, commercial hydroxyapatite and laboratory extracted collagen gel were employed as starting materials. Before the composites, fabrication, the powder with piezoelectric features was characterized in detail from the compositional, structural, morphological and electrical point of view. The next step was to elucidate the influence of barium titanate presence especially on the biological properties of the final materials. The biocompatibility of the hybrid supports without or with piezoelectric addition was investigated on mouse osteoblast cells through LDH cytotoxicity assay, LIVE/DEAD cell viability assay, and MTT cell proliferation assay. All results indicated that the analysed materials do not exert cytotoxic effects and present the ability to sustain cell survival and to promote their proliferation. In conclusion, barium titanate nanoparticles exhibit a good biocompatibility and osteoinductive properties, while the derived composite materials based on hydroxyapatite as oxide phase and collagen as polymeric phase can be successfully used for tissue engineering applications.

Keywords: barium titanate, hybrid composites, piezoelectricity, tissue engineering

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Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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Authors: Thidathit Prachanukool, Chaiyaporn Yuksen, Welawat Tienpratarn, Sorravit Savatmongkorngul, Panvilai Tangkulpanich, Chetsadakon Jenpanitpong, Yuranan Phootothum, Malivan Phontabtim, Promphet Nuanprom

Abstract:

Background: Ruptured appendicitis has a high morbidity and mortality and requires immediate surgery. The Alvarado Score is used as a tool to predict the risk of acute appendicitis, but there is no such score for predicting rupture. This study aimed to developed the prediction score to determine the likelihood of ruptured appendicitis in an Asian population. Methods: This study was diagnostic, retrospectively cross-sectional and exploratory model at the Emergency Medicine Department in Ramathibodi Hospital between March 2016 and March 2018. The inclusion criteria were age >15 years and an available pathology report after appendectomy. Clinical factors included gender, age>60 years, right lower quadrant pain, migratory pain, nausea and/or vomiting, diarrhea, anorexia, fever>37.3°C, rebound tenderness, guarding, white blood cell count, polymorphonuclear white blood cells (PMN)>75%, and the pain duration before presentation. The predictive model and prediction score for ruptured appendicitis was developed by multivariable logistic regression analysis. Result: During the study period, 480 patients met the inclusion criteria; of these, 77 (16%) had ruptured appendicitis. Five independent factors were predictive of rupture, age>60 years, fever>37.3°C, guarding, PMN>75%, and duration of pain>24 hours to presentation. A score > 6 increased the likelihood ratio of ruptured appendicitis by 3.88 times. Conclusion: Using the Ramathibodi Welawat Ruptured Appendicitis Score. (RAMA WeRA Score) developed in this study, a score of > 6 was associated with ruptured appendicitis.

Keywords: predictive model, risk score, ruptured appendicitis, emergency room

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