Search results for: network screening

Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Roberta Mugellesi Dow

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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Po-Chun Wang, Yan-Ru Lai, Sophia I. C. Lin, Alvin W. Y. Su

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The Generative Theory of Tonal Music (GTTM) provides systematic approaches to recognizing local boundaries of music. The rules have been implemented in some automated melody segmentation algorithms. Besides, there are also deep learning methods with GTTM features applied to boundary detection tasks. However, these studies might face constraints such as a lack of or inconsistent label data. The GTTM database is currently the most widely used GTTM database, which includes manually labeled GTTM rules and local boundaries. Even so, we found some problems with these labels. They are sometimes discrepancies with GTTM rules. In addition, since it is labeled at different times by multiple musicians, they are not within the same scope in some cases. Therefore, in this paper, we examine this database with musicians from the aspect of classical music and relabel the scores. The relabeled database - GTTM Database v2.0 - will be released for academic research usage. Despite the experimental and statistical results showing that the relabeled database is more consistent, the improvement in boundary detection is not substantial. It seems that we need more clues than GTTM rules for boundary detection in the future.

Keywords: dataset, GTTM, local boundary, neural network

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Authors: Hermann Kuehnle

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Developments in ICT totally reshape manufacturing as machines, objects and equipment on the shop floors will be smart and online. Interactions with virtualizations and models of a manufacturing unit will appear exactly as interactions with the unit itself. These virtualizations may be driven by providers with novel ICT services on demand that might jeopardize even well established business models. Context aware equipment, autonomous orders, scalable machine capacity or networkable manufacturing unit will be the terminology to get familiar with in manufacturing and manufacturing management. Such newly appearing smart abilities with impact on network behavior, collaboration procedures and human resource development will make distributed manufacturing a preferred model to produce. Computing miniaturization and smart devices revolutionize manufacturing set ups, as virtualizations and atomization of resources unwrap novel manufacturing principles. Processes and resources obey novel specific laws and have strategic impact on manufacturing and major operational implications. Mechanisms from distributed manufacturing engaging interacting smart manufacturing units and decentralized planning and decision procedures already demonstrate important effects from this shift of focus towards collaboration and interoperability.

Keywords: autonomous unit, networkability, smart manufacturing unit, virtualization

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Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based net-work simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, cloud computing, constellation, satellite, network simulation, netfilter

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Authors: Yuliya Huseva

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To investigate the contents of tears to determine latent blood. Methods: Tear samples from 72 women were studied with the microscopy of tears aspirated with a capillary and stained by Nocht and with a chemical method of test strips with chromogen. Statistical data processing was carried out using statistical packages Statistica 10.0 for Windows, calculation of Pearson's chi-square test, Yule association coefficient, the method of determining sensitivity and specificity. Results:, In 30.6% (22) of tear samples erythrocytes were revealed microscopically. Correlations between the presence of erythrocytes in the tear and the phase of the menstrual cycle has been discovered. In the follicular phase of the cycle, erythrocytes were found in 59.1% (13) people, which is significantly more (x2=4.2, p=0.041) compared to the luteal phase - in 40.9% (9) women. In the first seven days of the follicular phase of the menstrual cycle the erythrocytes were predominanted of in the tears of women examined testifies in favour of the vicarious bleeding from the mucous membranes of extragenital organs in sync with menstruation. Of the other cellular elements in tear samples with latent haemolacria, neutrophils prevailed - in 45.5% (10), while lymphocytes were less common - in 27.3% (6), because neutrophil exudation is accompanied by vasodilatation of the conjunctiva and the release of erythrocytes into the conjunctival cavity. It was found that the prognostic significance of the chemical method was 0.53 of the microscopic method. In contrast to microscopy, which detected blood in tear samples from 30.6% (22) of women, blood was detected chemically in tears of 16.7% (12). An association between latent haemolacria and endometriosis was found (k=0.75, p≤0.05). Microscopically, in the tears of patients with endometriosis, erythrocytes were detected in 70% of cases, while in healthy women without endometriosis - in 25% of cases. The proportion of women with erythrocytes in tears, determined by a chemical method, was 41.7% among patients with endometriosis, which is significantly more (x2=6.5, p=0.011) than 11.7% among women without endometriosis. The data obtained can be explained by the etiopathogenesis of the extragenital endometriosis which is caused by hematogenous spread of endometrial tissue into the orbit. In endometriosis, erythrocytes are found against the background of accumulations of epithelial cells. In the tear samples of 4 women with endometriosis, glandular cuboidal epithelial cells, morphologically similar to endometrial cells, were found, which may indicate a generalization of the disease. Conclusions: Single erythrocytes can normally be found in the tears, their number depends on the phase of the menstrual cycle, increasing in the follicular phase. Erythrocytes found in tears against the background of accumulations of epitheliocytes and their glandular atypia may indicate a manifestation of extragenital endometriosis. Both used methods (microscopic and chemical) are informative in revealing latent haemolacria. The microscopic method is more sensitive, reveals intact erythrocytes, and besides, it provides information about other cells. At the same time, the chemical method is faster and technically simpler, it determines the presence of haemoglobin and its metabolic products, and can be used as a screening.

Keywords: tear, blood, microscopy, epitheliocytes

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Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Wojciech Kulesza

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The north-western part of the Poland, specifically West Pomerania and Lubuskie provinces, from several years are the subject of research of the Department of Archaeology of Early Middle Ages of Institute of Archaeology of Nicolaus Copernicus University in Toruń. This area has a dense network of rivers and numerous lakes, where many of them are connected to the southern part of the Baltic Sea. During the many years of research in this area, archaeologists discovered the remains of the early Middle Ages settlement located on several islands and in most cases were encountered relics of early Middle Ages bridges linking those islands with the mainland. During the excavation, work was carried out both under water and on land for the accurate identification of islands and adjacent to them underwater areas. The result of this work is a graphic documentation, made in a three-dimensional technique, not only for the underwater trenches but also relics of bridges and objects discovered during exploration, which as the main theme will be presented in the full presentation.

Keywords: Poland, underwater archaeology, Nicolaus Copernicus University, early middle ages

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Authors: Jungho Moon, Myunggon Yoon

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This paper presents an implementation of a configurable UART-to-Ethernet converter using an ARM-based 32-bit microcontroller as well as a dedicated configuration program running on a PC for configuring the operating parameters of the converter. The program was written in Python. Various parameters pertaining to the operation of the converter can be modified by the configuration program through the Ethernet interface of the converter. The converter supports 3 representative asynchronous serial communication protocols, RS-232, RS-422, and RS-485 and supports 3 network modes, TCP/IP server, TCP/IP client, and UDP client. The TCP/IP and UDP protocols were implemented on the microcontroller using an open source TCP/IP protocol stack called lwIP (A lightweight TCP/IP) and FreeRTOS, a free real-time operating system for embedded systems. Due to the use of a real-time operating system, the firmware of the converter was implemented as a multi-thread application and as a result becomes more modular and easier to develop. The converter can provide a seamless bridge between a serial port and an Ethernet port, thereby allowing existing legacy apparatuses with no Ethernet connectivity to communicate using the Ethernet protocol.

Keywords: converter, embedded systems, ethernet, lwIP, UART

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

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Authors: Sophie Oakes-Rogers, Di Bailey, Karen Slade

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Female offenders are a uniquely vulnerable group, who are at high risk of suicide. Whilst the prevention of self-harm and suicide remains a key global priority, we need to better understand the relationship between these challenging behaviours that constitute a pressing problem, particularly in environments designed to prioritise safety and security. Method choice is unlikely to be random, and is instead influenced by a range of cultural, social, psychological and environmental factors, which change over time and between countries. A key aspect of self-harm and suicide in women receiving forensic care is the lack of free access to methods. At a time where self-harm and suicide rates continue to rise internationally, understanding the role of these influencing factors and the impact of current suicide prevention strategies on the use of near-lethal methods is crucial. This poster presentation will present findings from 25 interviews and 3 focus groups, which enlisted a Participatory Action Research approach to explore the differences between self-harming and suicidal behavior. A key element of this research was using the lived experiences of women receiving forensic care from one forensic pathway in the UK, and the staffs who care for them, to discuss the role of near-lethal self-harm (NLSH). The findings and suggestions from the lived accounts of the women and staff will inform a draft assessment tool, which better assesses the risk of suicide based on the lethality of methods. This tool will be the first of its kind, which specifically captures the needs of women receiving forensic services. Preliminary findings indicate women engage in NLSH for two key reasons and is determined by their history of self-harm. Women who have a history of superficial non-life threatening self-harm appear to engage in NLSH in response to a significant life event such as family bereavement or sentencing. For these women, suicide appears to be a realistic option to overcome their distress. This, however, differs from women who appear to have a lifetime history of NLSH, who engage in such behavior in a bid to overcome the grief and shame associated with historical abuse. NLSH in these women reflects a lifetime of suicidality and indicates they pose the greatest risk of completed suicide. Findings also indicate differences in method selection between forensic provisions. Restriction of means appears to play a role in method selection, and findings suggest it causes method substitution. Implications will be discussed relating to the screening of female forensic patients and improvements to the current suicide prevention strategies.

Keywords: forensic mental health, method substitution, restriction of means, suicide

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Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: terrestrial-satellite networks, latency, on-orbit satellite payload, simulation

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Authors: Jung-Hsuan Hsu

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Due to intense competition within the industry, companies have increasingly recognized partnerships with other companies. In addition, with outsourcing and globalization of the supply chain, it leads to companies' increasing reliance on external resources. Consequently, supply chain network becomes complex, so that it reduces the visibility of the manufacturing process. Therefore, this study is going to focus on the impact of supply chain relationship quality (SCRQ) on cooperative strategy and visibility. Questionnaire survey is going to be conducted as research method, using the organic food industry as the research subject, and the sampling method is random sampling. Finally, the data analysis will use SPSS statistical software and AMOS software to analyze and verify the hypothesis. The expected results in this study is to evaluate the supply chain relationship quality between Taiwan's food manufacturing and their suppliers regarding whether it has a positive impact for the persistence, frequency and diversity of cooperative strategy, as well as the dimensions of supply chain relationship quality on visibility regarding whether it has a positive effect.

Keywords: supply chain relationship quality (SCRQ), cooperative strategy, visibility, competition

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Authors: Ying Li, Rui Hu, Shizhen Chen, Xin Zhou, Yunhuang Yang

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Prostate cancer is one of the leading causes of cancer-related death among men. Prostate-specific antigen (PSA), a specific product of prostatic epithelial cells, is an important indicator of prostate cancer. Though PSA is not a specific serum biomarker for the screening of prostate cancer, it is recognized as an indicator for prostate cancer recurrence and response to therapy for patient’s post-prostatectomy. Since radical prostatectomy eliminates the source of PSA production, serum PSA levels fall below 50 pg/mL, and may be below the detection limit of clinical immunoassays (current clinical immunoassay lower limit of detection is around 10 pg/mL). Many clinical studies have shown that intervention at low PSA levels was able to improve patient outcomes significantly. Therefore, ultra-sensitive and precise assays that can accurately quantify extremely low levels of PSA (below 1-10 pg/mL) will facilitate the assessment of patients for the possibility of early adjuvant or salvage treatment. Currently, the commercially available ultra-sensitive ELISA kit (not used clinically) can only reach a detection limit of 3-10 pg/mL. Other platforms developed by different research groups could achieve a detection limit as low as 0.33 pg/mL, but they relied on sophisticated instruments to get the final readout. Herein we report a microfluidic platform for point-of-care (POC) detection of PSA with a detection limit of 0.5 pg/mL and without the assistance of any equipment. This platform is based on a previously reported volumetric-bar-chart chip (V-Chip), which applies platinum nanoparticles (PtNPs) as the ELISA probe to convert the biomarker concentration to the volume of oxygen gas that further pushes the red ink to form a visualized bar-chart. The length of each bar is used to quantify the biomarker concentration of each sample. We devised a long reading channel V-Chip (LV-Chip) in this work to achieve a wide detection window. In addition, LV-Chip employed a unique enzyme-free ELISA probe that enriched PtNPs significantly and owned 500-fold enhanced catalytic ability over that of previous V-Chip, resulting in a significantly improved detection limit. LV-Chip is able to complete a PSA assay for five samples in 20 min. The device was applied to detect PSA in 50 patient serum samples, and the on-chip results demonstrated good correlation with conventional immunoassay. In addition, the PSA levels in finger-prick whole blood samples from healthy volunteers were successfully measured on the device. This completely stand-alone LV-Chip platform enables convenient POC testing for patient follow-up in the physician’s office and is also useful in resource-constrained settings.

Keywords: point-of-care detection, microfluidics, PSA, ultra-sensitive

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Authors: Morteza Ghourchi, Meraj Jafari, Atena Soheilazizi

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Today, with the globalization of communications and the connection of countries within the framework of the global economy, free zones play the most important role as the engine of global economic development and globalization of countries. In this regard, corridors have a fundamental role in linking countries and free zones physically with each other. One of these corridors is the New Silk Road corridor (One Belt, One Road initiative), which is being built by China to connect with European countries. In connecting this corridor to European countries, Iran and Turkey are among the countries that play an important role in linking China to European countries through this corridor. The New Silk Road corridor, by connecting Iran’s free zones (Sarakhs and Maku) and Turkey’s free zones (Anatolia and Europe), can provide the best opportunity for expanding economic cooperation and regional development between Iran and Turkey. It can also provide economic links between Iran and Turkey with Central Asian countries and especially the port of Khorgos. On the other hand, it can expand Iran-Turkey economic relations more than ever before with Europe in a vast economic network. The research method was descriptive-analytical, using library resources, documents of Iranian free zones, and the Internet. In an interview with Fars News Agency, Mohammad Reza Kalaei, CEO of Sarakhs Free Zone, said that the main goal of Sarakhs Special Economic Zone is to connect Iran with the Middle East and create a transit corridor towards East Asian countries, including Turkey. Also, according to an interview with Hussein Gharousi, CEO of Maku Free Zone, the importance of this region is due to the fact that Maku Free Zone, due to its geographical location and its position on the China-Europe trade route, the East-West corridor, which is the closest point to the European Union through railway and transit routes, and also due to its proximity to Eurasian countries, is an ideal opportunity for industrial and technological companies. Creating a transit corridor towards East Asian countries, including Turkey, is one of the goals of this project Free zones between Iran and Turkey can sign an agreement within the framework of the New Silk Road to expand joint investments and economic cooperation towards regional convergence. The purpose of this research is to develop economic links between Iranian and Turkish free zones along the New Silk Road, which will lead to the expansion and development of regional cooperation between the two countries within the framework of neighboring policies. The findings of this research include the development of economic diplomacy between the Secretariat of the Supreme Council of Free Zones of Iran and the General Directorate of Free Zones of Turkey, the agreement to expand cooperation between the free zones of Sarakhs, Maku, Anatolia, and Europe, holding biennial conferences between Iranian free zones along the New Silk Road with Turkish free zones, creating a joint investment fund between Iran and Turkey in the field of developing free zones along the Silk Road, helping to attract tourism between Iranian and Turkish free zones located along the New Silk Road, improving transit infrastructure and transportation to better connect Iranian free zones to Turkish free zones, communicating with China, and creating joint collaborations between China’s dry ports and its free zones with Iranian and Turkish free zones.

Keywords: network economy, new silk road (one belt, one road initiative), free zones (Sarakhs, Maku, Anatolia, Europe), regional development, neighborhood policies

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Authors: G. Erkomaishvili, M. Kobalava, T. Lazariashvili, M. Saghareishvili

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The article discusses the consumer market of agricultural products and agricultural policy in Georgia. It is noted that development of the strategic areas of the agricultural sector needs a special support. These strategic areas should create the country's major export potential. It is important to develop strategies to access to the international markets, form extensive marketing network etc., which will become the basis for the promotion and revenue growth of the country. The Georgian agricultural sector, with the right state policy and support, can achieve success and gain access to the world market with competitive agricultural products. The paper discusses the current condition of agriculture, export and import of agricultural products and agricultural policy in Georgia. The conducted research concludes the information that there is an increasing demand on the green goods in the world market. Natural and climatic conditions of Georgia give a serious possibility of implementing it. The research presents an agricultural development strategy in Georgia and the findings and based on them recommendations are proposed.

Keywords: agriculture, export-import of agricultural products, agricultural cooperative society, agricultural policy, agricultural insurance

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Authors: Akanle Florence Foluso

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This paper examined briefly the patriarchy nature of gendered power system: a network of social, political and economic relationships through which men dominate and control female labour, as well as define women’s status, privileges and rights in the society. The paper discusses the historical perspective of “the academic experience of women. It takes a look at the plight of women in a academia in some Nigeria. Universities in at present to see if both men and women have equal opportunities. This paper focuses on women in Academics today, it examines the overall gender proportions of men and women by universities, women/men ratios by lecturers, women and men ratio of associate professors, women and men ratio of professors by universities. It also examines women and men ratio by Dean also executive heads (Vice Chancellors) Expofactor design was be used. The study population comprised of three selected universities from Ondo, Ekiti and Zanfara respectively. Involuntary and indept interview was used to collect data for the study data for the study was also collected from so purposively selected academic staff in the categories of Dean and senior staff who are familiar with gender issues. Findings souls that there is gender inequality academia.

Keywords: women, gender, inequality, academia

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Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

Abstract:

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Mikkel Snorre Wilms Boysen

Abstract:

From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

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Authors: Davi Marinho de Araujo Falcão, Ronaldo Moreira Salles, Paulo Henrique Maranhão

Abstract:

Disruption Tolerant Networks (DTN) are an evolution of Mobile Adhoc Networks (MANET) and work good in scenarioswhere nodes are sparsely distributed, with low density, intermittent connections and an end-to-end infrastructure is not possible to guarantee. Therefore, DTNs are recommended for high latency applications that can last from hours to days. The maritime scenario has mobility characteristics that contribute to a DTN network approach, but the concern with data security is also a relevant aspect in such scenarios. Continuing the previous work, which evaluated the performance of some DTN protocols (Epidemic, Spray and Wait, and Direct Delivery) in three warship scenarios and proposed the application of discriminant analysis, as a classification technique for secure connections, in the Epidemic protocol, thus, the current article proposes a new analysis of the directional discriminant function with opening angles smaller than 90 degrees, demonstrating that the increase in directivity influences the selection of a greater number of secure connections by the directional discriminant Epidemic protocol.

Keywords: DTN, discriminant function, epidemic protocol, security, tactical messages, warship scenario

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Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

Abstract:

UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Daniel Todorov, Anton Hinkov, Petya Angelova, Kalina Shishkova, Venelin Tsvetkov, Stoyan Shishkov

Abstract:

Human herpes viruses (HHV) are ubiquitous pathogens with a pandemic spread across the globe. HHV type 1 is the main causative agent of cold sores and fever blisters around the mouth and on the face, whereas HHV type 2 is generally responsible for genital herpes outbreaks. The treatment of both viruses is more or less successful with antivirals from the nucleoside analogues group. Their wide application increasingly leads to the emergence of resistant mutants In the past, medicinal plants have been used to treat a number of infectious and non-infectious diseases. Their diversity and ability to produce the vast variety of secondary metabolites according to the characteristics of the environment give them the potential to help us in our warfare with viral infections. The variable chemical characteristics and complex composition is an advantage in the treatment of herpes since the emergence of resistant mutants is significantly complicated. The screening process is difficult due to the lack of standardization. That is why it is especially important to follow the mechanism of antiviral action of plants. On the one hand, it may be expected to interact with its compounds, resulting in enhanced antiviral effects, and the most appropriate environmental conditions can be chosen to maximize the amount of active secondary metabolites. During our study, we followed the activity of various plant extracts on the viral replication cycle as well as their effect on the extracellular virion. We obtained our results following the logical sequence of the experimental settings - determining the cytotoxicity of the extracts, evaluating the overall effect on viral replication and extracellular virion.During our research, we have screened a variety of plant extracts for their antiviral activity against both virus replication and the virion itself. We investigated the effect of the extracts on the individual stages of the viral replication cycle - viral adsorption, penetration and the effect on replication depending on the time of addition. If there are positive results in the later experiments, we had studied the activity over viral adsorption, penetration and the effect of replication according to the time of addition. Our results indicate that some of the extracts from the Lamium album have several targets. The first stages of the viral life cycle are most affected. Several of our active antiviral agents have shown an effect on extracellular virion and adsorption and penetration processes. Our research over the last decade has shown several curative antiviral plants - some of which are from the Lamiacea family. The rich set of active ingredients of the plants in this family makes them a good source of antiviral preparation.

Keywords: human herpes virus, antiviral activity, Lamium album, Nepeta nuda

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Authors: Adam Aboalkaz, Rana Shamoon, Duncan Meikle, James Lewis

Abstract:

Background and aims: In orthopaedic theatres, radiological screening during operations is a commonly used and useful technique to visualise and guide the operating surgeon. Within any theatre using ionising radiation, it is imperative that the use of protective equipment and the wearing of a dosimeter at all times. 1. To assess compliance with use of protective equipment during orthopaedic procedures involving ionising radiation. 2. To assess the radiation risk knowledge of staff members regularly present in an orthopaedic theatre of a national major trauma centre, in accordance to the ionising radiation regulation (2000) guidelines. Method: We conducted an Observational study of 21 operations at the University Hospital of Wales, which is a major trauma centre, recording the compliance with use of protective equipment (lead aprons and thyroid shields) and dosimeters. The observations were performed sporadically over a two week period to ensure that all staff in monitored operating theatres were not aware of the ongoing study, as to avoid bias. A questionnaire testing the knowledge of trainees and staff within the orthopaedic department was given following completion of the initial phase of the study, with 19 responses. The questions were based on knowledge of ionising radiation exposure and monitoring. The questions also tested the general staff knowledge of what equipment should be worn and where to locate such equipment. Results: This study found that only 25% of staff members were wearing thyroid protectors when less than 1 meter from the radiation source and only 50% were wearing appropriate lead aprons whilst in this same vicinity. The study also showed that 0% of all staff members used a dosimeter whilst in an area of radiation exposure. From the distributed questionnaires, only 40% of staff understood where to stand whilst radiation was being used, and only 25% of staff knew where to find protective equipment. Conclusion: Overall our audit showed poor compliance with regards to the National and local policies, due to lack of awareness of the policy and lack of basic ionising radiation exposure knowledge. It was evident from the observational study and questionnaire that staff were not fully aware of what equipment should be worn, where to find such equipment and did not appreciate that the distance from the ionising radiation source altered its exposure effect. This lack of knowledge may affect the staff health and safety after long term exposure. Changes to clinical practice: From the outcome of this study, we managed to drastically increase awareness of ionising radiation within the orthopaedic department. A mandatory teaching session on the safety of ionising radiation has been incorporated into the orthopaedic induction week for all staff. The dosimeters have been moved to a visible location within the trauma operating theatre and all staff made aware of where to find protective equipment.

Keywords: audit, ionising radiation, observational study, protection

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

Abstract:

Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: M. Naimi, M. B. Khaled

Abstract:

The aim of the present work was to test in vitro inhibition of food pathogens and spoilage bacteria by crude bacteriocins from autochthonous lactic acid bacteria. Thirty autochthonous lactic acid bacteria isolated previously, belonging to the genera: Lactobacillus, Carnobacterium, Lactococcus, Vagococcus, Streptococcus, and Pediococcus, have been screened by an agar spot test and a well diffusion assay against Gram-positive and Gram-negative harmful bacteria: Bacillus cereus, Bacillus subtilis ATCC 6633, Escherichia coli ATCC 8739, Salmonella typhimurium ATCC 14028, Staphylococcus aureus ATCC 6538, and Pseudomonas aeruginosa under conditions means to reduce lactic acid and hydrogen peroxide effect to select bacteria with high bacteriocinogenic potential. Furthermore, crude bacteriocins semiquantification and heat sensitivity to different temperatures (80, 95, 110°C, and 121°C) were performed. Another exploratory test concerning the response of St. aureus ATCC 6538 to the presence of crude bacteriocins was realized. It has been observed by the agar spot test that fifteen candidates were active toward Gram-positive targets strains. The secondary screening demonstrated an antagonistic activity oriented only against St. aureus ATCC 6538, leading to the selection of five isolates: Lm14, Lm21, Lm23, Lm24, and Lm25 with a larger inhibition zone compared to the others. The ANOVA statistical analysis reveals a small variation of repeatability: Lm21: 0.56%, Lm23: 0%, Lm25: 1.67%, Lm14: 1.88%, Lm24: 2.14%. Conversely, slight variation was reported in terms of inhibition diameters: 9.58± 0.40, 9.83± 0.46, and 10.16± 0.24 8.5 ± 0.40 10 mm for, Lm21, Lm23, Lm25, Lm14and Lm24, indicating that the observed potential showed a heterogeneous distribution (BMS = 0.383, WMS = 0.117). The repeatability coefficient calculated displayed 7.35%. As for the bacteriocins semiquantification, the five samples exhibited production amounts about 4.16 for Lm21, Lm23, Lm25 and 2.08 AU/ml for Lm14, Lm24. Concerning the sensitivity the crude bacteriocins were fully insensitive to heat inactivation, until 121°C, they preserved the same inhibition diameter. As to, kinetic of growth , the µmax showed reductions in pathogens load for Lm21, Lm23, Lm25, Lm14, Lm24 of about 42.92%, 84.12%, 88.55%, 54.95%, 29.97% in the second trails. Inversely, this pathogen growth after five hours displayed differences of 79.45%, 12.64%, 11.82%, 87.88%, 85.66% in the second trails, compared to the control. This study showed potential inhibition to the growth of this food pathogen, suggesting the possibility to improve the hygienic food quality.

Keywords: exploratory test, lactic acid bacteria, crude bacteriocins, spoilage, pathogens

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