Search results for: sensor monitoring

Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Deinzel R. Uezono, Vivien Fe F. Fadrilan-Camacho, Bianca Margarita L. Medina, Antonio Domingo R. Reario, Trisha M. Salcedo, Luke Wesley P. Borromeo

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The environment of health care workers is considered one of the most hazardous settings due to the nature of their work. In developing countries especially, the Philippines, this continues to be overlooked in terms of programs and services on occupational health and safety (OHS). One possible reason for this is the existing information gap on OHS which limits data comparability and impairs effective monitoring and assessment of interventions. To address this gap, there is a need to determine the current conditions of Filipino health care workers in their workplace. This descriptive cross-sectional study assessed the occupational health and safety conditions of health care workers in barangay health centers in a selected city in Metro Manila, Philippines by: (1) determining the hazards present in the workplace; (2) determining the most common self-reported medical problems; and (3) describing the elements of an OHS system based on the six building blocks of health system. Assessment was done through walkthrough survey, self-administered questionnaire, and key informant interview. Data analysis was done using Epi Info 7 and NVivo 11. Results revealed different health hazards present in the workplace particularly biological hazards (exposure to sick patients and infectious specimens), physical hazards (inadequate space and/or lighting), chemical hazards (toxic reagents and flammable chemicals), and ergonomic hazards (activities requiring repetitive motion and awkward posture). Additionally, safety hazards (improper capping of syringe and lack of fire safety provisions) were also observed. Meanwhile, the most commonly self-reported chronic diseases among health care workers (N=336) were hypertension (20.24%, n=68) and diabetes (12.50%, n=42). Top commonly self-reported symptoms were colds (66.07%, n=222), coughs (63.10%, n=212), headache (55.65%, n=187), and muscle pain (50.60%, n=170) while other diseases were influenza (16.96%, n=57) and UTI (15.48%, n=52). In terms of the elements of the OHS system, a general policy on occupational health and safety was found to be lacking and in effect, an absence of health and safety committee overseeing the implementing and monitoring of the policy. No separate budget specific for OHS programs and services was also found to be a limitation. As a result, no OHS personnel and trainings/seminar were identified. No established information system for OHS was in place. In conclusion, health and safety hazards were observed to be present across the barangay health centers visited in a selected city in Metro Manila. Medical conditions identified as most commonly self-reported were hypertension and diabetes for chronic diseases; colds, coughs, headache, and muscle pain for medical symptoms; and influenza and UTI for other diseases. As for the elements of the occupational health and safety system, there was a lack in the general components of the six building blocks of the health system.

Keywords: health hazards, occupational health and safety, occupational health and safety system, safety hazards

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Authors: Nasser Al-Rawahi

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The study aims at determining self-regulated learning strategies used by Omani physical education candidates to learn sport skills. The data were collected by a self-regulated learning theory questionnaire. The sample of the study comprised of 145 undergraduate physical education students enrolled in the department of physical education at the College of Education, Sultan Qaboos University. The findings of the study revealed that the most commonly used strategies for learning sport skills by Omani physical education candidate are ‘the effort learning strategies, planning learning strategies and evaluation learning strategies’. However, the reflection learning strategies, self-monitoring and self-efficacy learning strategies were revealed as the least used strategies by the PE candidates in learning and acquiring sport skills. Based on these findings, suggestions and recommendations for future research were provided.

Keywords: learning strategies, physical education candidates, self-regulated learning theory, Oman

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Authors: Claudio Clemente, Valentina Gargiulo, Alessio Occhicone, Giovanni Piero Pepe, Giovanni Ausanio, Michela Alfè

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Volatile organic compound (VOC) emissions represent a serious risk to human health and the integrity of the ecosystems, especially at high concentrations. For this reason, it is very important to continuously monitor environmental quality and develop fast and reliable portable sensors to allow analysis on site. Chemiresistors have become promising candidates for VOC sensing as their ease of fabrication, variety of suitable sensitive materials, and simple sensing data. A chemoresistive gas sensor is a transducer that allows to measure the concentration of an analyte in the gas phase because the changes in resistance are proportional to the amount of the analyte present. The selection of the sensitive material, which interacts with the target analyte, is very important for the sensor performance. The most used VOC detection materials are metal oxides (MOx) for their rapid recovery, high sensitivity to various gas molecules, easy fabrication. Their sensing performance can be improved in terms of operating temperature, selectivity, and detection limit. Metal-organic frameworks (MOFs) have attracted a lot of attention also in the field of gas sensing due to their high porosity, high surface area, tunable morphologies, structural variety. MOFs are generated by the self-assembly of multidentate organic ligands connecting with adjacent multivalent metal nodes via strong coordination interactions, producing stable and highly ordered crystalline porous materials with well-designed structures. However, most MOFs intrinsically exhibit low electrical conductivity. To improve this property, MOFs can be combined with organic and inorganic materials in a hybrid fashion to produce composite materials or can be transformed into more stable structures. MOFs, indeed, can be employed as the precursors of metal oxides with well-designed architectures via the calcination method. The MOF-derived MOx partially preserved the original structure with high surface area and intrinsic open pores, which act as trapping centers for gas molecules, and showed a higher electrical conductivity. Core-shell heterostructures, in which the surface of a metal oxide core is completely coated by a MOF shell, forming a junction at the core-shell heterointerface, can also be synthesized. Also, nanocomposite in which MOF structures are intercalated with graphene related materials can also be produced, and the conductivity increases thanks to the high mobility of electrons of carbon materials. As MOF structures, zinc-based MOFs belonging to the ZIF family were selected in this work. Several Zn-based materials based and/or derived from MOFs were produced, structurally characterized, and arranged in a chemo resistive architecture, also exploring the potentiality of different approaches of sensing layer deposition based on PLD (pulsed laser deposition) and, in case of thermally labile materials, MAPLE (Matrix Assisted Pulsed Laser Evaporation) to enhance the adhesion to the support. The sensors were tested in a controlled humidity chamber, allowing for the possibility of varying the concentration of ethanol, a typical analyte chosen among the VOCs for a first survey. The effect of heating the chemiresistor to improve sensing performances was also explored. Future research will focus on exploring new manufacturing processes for MOF-based gas sensors with the aim to improve sensitivity, selectivity and reduce operating temperatures.

Keywords: chemiresistors, gas sensors, graphene related materials, laser deposition, MAPLE, metal-organic frameworks, metal oxides, nanocomposites, sensing performance, transduction mechanism, volatile organic compounds

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Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

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In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

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Authors: A. Kudrev

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The duplex Poly(A)-Poly(U) denaturation in an aqueous solutions in mixtures with the tetracationic MeTMPyP4 (Me = 2H, Zn(II); TMPyP4 is 5,10,15,20-tetrakis(N-methylpyridinium-4-yl)porphyrin), was investigated by monitoring the changes in the UV-Vis absorbance spectrum with increasing temperatures from 20°С to 70°С (рН 7.0, I=0.15M). The absorbance data matrices were analyzed with a versatile chemometric procedure that provides the melting profile (distribution of species) and the pure spectrum for each chemical species present along the heating experiment. As revealed by the increase of Tm, the duplex structure was stabilized by these porphyrins. The values of stabilization temperature ΔTm in the presence of these porphyrins are relatively large, 1.2-8.4 °C, indicating that the porphyrins contribute differently in stabilizing the duplex Poly(A)-Poly(U) structure. Remarkable is the fact that the porphyrin TMPyP4 was less effective in the stabilization of the duplex structure than the metalloporphyrin Zn(X)TMPyP4 which suggests that metallization play an important role in porphyrin-RNA binding. Molecular Dynamics Simulations has been used to illustrate melting of the duplex dsRNA bound with a porphyrin molecule.

Keywords: melting, Poly(A)-Poly(U), TMPyP4, Zn(X)TMPyP4

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Authors: Temesgen Geremew

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The excessive emission of heavy metal ions from industrial processes poses a serious threat to both the environment and human health. This study presents a distinct approach utilizing (PTh-MnS/CoS NPs) for the highly selective and sensitive detection of Hg²⁺ ions in water. Such detection is crucial for safeguarding human health, protecting the environment, and accurately assessing toxicity. The fabrication method employs a simple and efficient chemical precipitation technique, harmoniously combining polythiophene, MnS, and CoS NPs to create highly active substrates for SERS. The MnS@Hg²⁺ exhibits a distinct Raman shift at 1666 cm⁻¹, enabling specific identification and demonstrating the highest responsiveness among the studied semiconductor substrates with a detection limit of only 1 nM. This investigation demonstrates reliable and practical SERS detection for Hg²⁺ ions. Relative standard deviation (RSD) ranged from 0.49% to 9.8%, and recovery rates varied from 96% to 102%, indicating selective adsorption of Hg²⁺ ions on the synthesized substrate. Furthermore, this research led to the development of a remarkable set of substrates, including (MnS, CoS, MnS/CoS, and PTh-MnS/CoS) nanoparticles were created right there on SiO₂/Si substrate, all exhibiting sensitive, robust, and selective SERS for Hg²⁺ ion detection. These platforms effectively monitor Hg²⁺ concentrations in real environmental samples.

Keywords: surface-enhanced raman spectroscopy (SERS), sensor, mercury ions, nanoparticles, and polythiophene.

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

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A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml^-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 10³ l mol^-1cm^-1 and 0.0125 μg cm^-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: solvent extraction, PMPT, Palladium (II), spectrophotometry

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Authors: Saeeda Nadir Ali, Najma Sultana, Muhammad Saeed Arayne, Amtul Qayoom

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Present study describes a simple and a fast liquid chromatographic method using ultraviolet detector for simultaneous determination of anxiety relief medicine alprazolam with ACE inhibitors i.e; lisinopril, captopril and enalapril employing purospher star C18 (25 cm, 0.46 cm, 5 µm). Separation was achieved within 5 min at ambient temperature via methanol: water (8:2 v/v) with pH adjusted to 2.9, monitoring the detector response at 220 nm. Optimum parameters were set up as per ICH (2006) guidelines. Calibration range was found out to be 0.312-10 µg mL-1 for alprazolam and 0.625-20 µg mL-1 for all the ACE inhibitors with correlation coefficients > 0.998 and detection limits 85, 37, 68 and 32 ng mL-1 for lisinopril, captopril, enalapril and alprazolam respectively. Intra-day, inter-day precision and accuracy of the assay were in acceptable range of 0.05-1.62% RSD and 98.85-100.76% recovery. Method was determined to be robust and effectively useful for the estimation of studied drugs in dosage formulations and human serum without obstruction of excipients or serum components.

Keywords: alprazolam, ACE inhibitors, RP HPLC, serum

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Authors: H. Boucheloukh, N. Aoun, S. Rouissa, T. Sehili, F. Parrino, V. Loddo

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Photocatalysis has made a revolution in wastewater treatment and the elimination of persistent organic pollutants. This process is based on the use of semiconductors as photocatalysts. In this study, nickel ferrite spinel (NiFe2O4) nanoparticles were successfully synthesized by the sol-gel route. The structural, morphological, elemental composition, chemical state, particle size, optical and electrochemical characterizations using powder X-ray diffraction (P-XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDAX ). We tested the prepared NiFe2O4(NPS)by monitoring the degradation of Rose Bengal (RB) dye in an aqueous solution under direct sunlight irradiation. The effects of catalyst dosage and dye concentration were also considered for the effective degradation of RB dye. The optimum catalyst dosage and concentration of dye were found to be 1 g/L and 10 μM, respectively. A maximum of 80% photocatalytic degradation efficiency (DE%) was achieved at 120 min of direct sunlight irradiation.

Keywords: Rose Bengal, Nickelate, photocatalysis, irradiation

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

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The goal of this experiment is to develop a sensor that can quickly check the concentration by using the nanoparticles made by chitosan and gold. Using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) is the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. As for the GABA, what is the primary inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability pass through the nervous system. A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). When the system is formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: mercaptopropionic acid, chitosan-gold nanoshell, γ-aminobutyric acid, surface-enhanced raman scattering

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: Paola Millare, Nelinda Catherine Pangilinan

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Background and Aim: Cervical cancer is the most commonly diagnosed gynecological malignancy during pregnancy. Owing to the rarity of the disease, and the complexity of all factors that have to be taken into consideration, standardization of treatment is very difficult. Cervical cancer is the second most common malignancy among women. The treatment of cancer during pregnancy is most challenging in the case of cervical cancer, since the pregnant uterus itself is affected. This report aims to present a case of cervical cancer in a pregnant woman and how to manage this case and several issues accompanied with it. Methods: This is a case of a 28 year-old, Gravida 4 Para 2 (1111), who presented with watery to mucoid, whitish, non-foul smelling and increasing in amount. Internal examination revealed normal external genitalia, parous outlet, cervix was transformed into a fungating mass measuring 5x4 cm, with left parametrial involvement, body of uterus was enlarged to 24 weeks size, no adnexal mass or tenderness. She had cervical punch biopsy, which revealed, adenocarcinoma, well-differentiated cervical tissue. Standard management for cases with stage 2B cervical carcinoma was to start radiation or radical hysterectomy. In the case of patients diagnosed with cervical cancer and currently pregnant, these kind of management will result to fetal loss. The patient still declined the said management and opted to delay the treatment and wait for her baby to reach at least term and proceed to cesarean section as route of delivery. Results: The patient underwent an elective cesarean section at 37th weeks age of gestation, with an outcome of a term, live baby boy APGAR score 7,9 birthweight 2600 grams. One month postpartum, the patient followed up and completed radiotherapy, chemotherapy and brachytherapy. She was advised to go back after 6 months for monitoring. On her last check up, an internal examination was done which revealed normal external genitalia, vagina admits 2 fingers with ease, there is a palpable fungating mass at the cervix measuring 2x2 cm. A repeat gynecologic oncologic ultrasound was done revealing cervical mass, endophytic, grade 1 color score with stromal invasion 35% post radiation reactive lymph nodes with intact paracolpium, pericervical, and parametrial involvement. The patient was then advised to undergo pelvic boost and for close monitoring of the cervical mass. Conclusion: Cervical cancer in pregnancy is rare but is a dilemma for women and their physicians. Treatment should be multidisciplinary and individualized following careful counseling. In this case, the treatment was clearly on the side of preventing the progression of cervical cancer while she is pregnant, however due to ethical reasons, the management deviates on the right of the patient to decide for her own health and her unborn child. The collaborative collection of data relating to treatment and outcome is strongly encouraged.

Keywords: cancer, cervical, ethical, pregnancy

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Anisa Suraya Ab Razak, Izza Hayat

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Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

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Authors: Minakshi Goswami, M. V. Khire

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The urban land use is an outcome of geographical and socio economic factors over the decades. Hence, spatial information on land use and possibilities of alternate use is essential for the selection, planning and implementation to meet the increasing demands of human needs and welfare of the urban area. This information assists in monitoring the land use resulting out of charging demands of increasing urban population over the decades. So in this paper, a detailed work on urban land use pattern, with a special reference to build up land in Bangalore city is analyzed in view of the various master plans from 1975to 2011. An attempt has been made to study the status of urban land use of Bangalore city during this period to detect the changes on land utilization rate that has taken place in each master plan period, particularly in the built-up land. The set of measures taken by the city corporation to contain the problems regarding the extremely bothering existing land use in Bangalore city is analyzed.

Keywords: built up land, land use changes, master plan, population

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Ali Afaghi, Sehraneh Ghaemi

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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

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Authors: Joshefina Bengoechea Fernandez, Alex Bell

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In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

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Authors: Pawel Twardowski, Maciej Tabaszewski, Jakub Czyżycki

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The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process.

Keywords: milling of hardened steel, tool wear, vibrations, machine learning

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Authors: Elisabetta Ceretti, Silvia Bonizzoni, Alberto Bonetti, Milena Villarini, Marco Verani, Maria Antonella De Donno, Sara Bonetta, Umberto Gelatti

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Introduction: Air pollution is a global problem. In 2013, the International Agency for Research on Cancer (IARC) classified air pollution and particulate matter as carcinogenic to human. The study of the health effects of air pollution in children is very important because they are a high-risk group in terms of the health effects of air pollution and early exposure during childhood can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE (Monitoring Air Pollution Effects on Children for supporting public health policy) is a project founded by EU Life+ Programme which intends to evaluate the associations between air pollution and early biological effects in children and to propose a model for estimating the global risk of early biological effects due to air pollutants and other factors in children. Methods: The study was carried out on 6-8-year-old children living in five Italian towns in two different seasons. Two biomarkers of early biological effects, primary DNA damage detected with the comet assay and frequency of micronuclei, were investigated in buccal cells of children. Details of children diseases, socio-economic status, exposures to other pollutants and life-style were collected using a questionnaire administered to children’s parents. Child exposure to urban air pollution was assessed by analysing PM0.5 samples collected in the school areas for PAHs and nitro-PAHs concentration, lung toxicity and in vitro genotoxicity on bacterial and human cells. Data on the chemical features of the urban air during the study period were obtained from the Regional Agency for Environmental Protection. The project created also the opportunity to approach the issue of air pollution with the children, trying to raise their awareness on air quality, its health effects and some healthy behaviors by means of an educational intervention in the schools. Results: 1315 children were recruited for the study and participate in the first sampling campaign in the five towns. The second campaign, on the same children, is still ongoing. The preliminary results of the tests on buccal mucosa cells of children will be presented during the conference as well as the preliminary data about the chemical composition and the toxicity and genotoxicity features of PM0.5 samples. The educational package was tested on 250 children of the primary school and showed to be very useful, improving children knowledge about air pollution and its effects and stimulating their interest. Conclusions: The associations between levels of air pollutants, air mutagenicity and biomarkers of early effects will be investigated. A tentative model to calculate the global absolute risk of having early biological effects for air pollution and other variables together will be proposed and may be useful to support policy-making and community interventions to protect children from possible health effects of air pollutants.

Keywords: air pollution exposure, biomarkers of early effects, children, public health policy

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Authors: Gilbert Omorodion Osayemwenre, Edson Meyer, R. T. Taziwa

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The electrical analysis of single junction amorphous silicon solar modules is carried out using outdoor monitoring technique. Like crystalline silicon PV modules, the electrical characterisation and performance of single junction amorphous silicon modules are best described by its current-voltage (IV) characteristic. However, IV curve has a direct dependence on the type of PV technology and material properties used. The analysis reveals discrepancies in the modules performance parameter even though they are of similar technology. The aim of this work is to compare the electrical performance output of each module, using electrical parameters with the aid of PVPM 100040C IV tracer. These results demonstrated the relevance of standardising the performance parameter for effective degradation analysis of a-Si:H.

Keywords: PVPM 100040C IV tracer, SolarWatt part, single junction amorphous silicon module (a-Si:H), Staebler-Wronski (S-W) degradation effect

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Authors: Chiung-Hui Chen

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With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity

Procedia PDF Downloads 287

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Arlinda Memetaj

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A sound system of administrative justice represents a vital element of democratic governance. The proper control of public administration consists not only of a sound civil service framework and legislative oversight, but empowerment of the public and courts to hold public officials accountable for their decision-making through the application of fair administrative procedural rules and the use of appropriate administrative appeals processes and judicial review. The establishment of both effective public administration and administrative justice system has been for a long period of time among the most ‘important and urgent’ final strategic objectives of almost any country in the Balkans region, including Macedonia, Albania and Kosovo. Closely related to this is their common strategic goal to enter the membership in the European Union, which requires fulfilling of many criteria and standards as incorporated in EU acquis communautaire. The latter is presently done with the framework of the Stabilization and Association Agreement which each of these countries has concluded with the EU accordingly. To above aims, each of the three countries has so far adopted a huge series of legislative and strategic documents related to any aspects of their individual administrative justice system. ‘Changes and reforms’ in this field have been thus the most frequent terms being used in any of these countries. The three countries have already established their own national administrative judiciary, while permanently amending their laws on the general administrative procedure introducing thereby considerable innovations concerned. National administrative courts are expected to have crucial important role within the broader judiciary systems-related reforms of these countries; they are designed to check the legality of decisions of the state administration with the aim to guarantee an effective protection of human rights and legitimate interests of private persons through a regular, conform, fast and reasonable judicial administrative process. Further improvements in this field are presently an integral crucial part of all the relevant national strategic documents including the ones on judiciary reform and public administration reform, as adopted by each of the three countries; those strategic documents are designed among others to provide effective protection of their citizens` rights` of administrative justice. On the basis of the later, the paper finally is aimed at highlighting selective common challenges and problems of the three countries on their European road, while claiming (among others) that the current status quo situation in each of them may be overcome only if there is a proper implementation of the administrative courts decisions and a far stricter international monitoring process thereof. A new approach and strong political commitment from the highest political leadership is thus absolutely needed to ensure the principles of transparency, accountability and merit in public administration. The main methods used in this paper include the analytical and comparative ones due to the very character of the paper itself.

Keywords: administrative courts , administrative justice, administrative procedure, benefit, effective administrative justice, human rights, implementation, monitoring, reform

Procedia PDF Downloads 152

Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Andrew Hwang

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The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion

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Authors: Sunpetch Angkititrakul, Seree Klaengair, Dusadee Phongaran, Arunee Ritthipanun

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The objective of this study is to determine the prevalence and antimicrobial resistance pattern of Salmonella spp. isolated from pigs at slaughterhouses in the northeast of Thailand. During 2015-2016, all samples were isolated and identified by ISO 6579:2002. A total of 699 samples of rectal swab were collected and isolated for the presence of Salmonella. Salmonella was detected in 275 of 699 (39.34%) samples. 24 serovars were identified in the 275 isolates. The most prevalent serovars were rissen (36.97%), S. enterica ser.4,5,12:i: (25.35%) and typhimurium (21.33%). In this study, 76.30% of the isolates were resistant to at least one antimicrobial drug and 38.39% were multidrug resistant. The highest resistances were found in ampicillin (69.20%), tetracycline (66.35%), sulfamethoxazole/trimethoprim (35.55%) and chloramphenicol (9.00%) The results showed high prevalence of Salmonella spp. in pigs and high antimicrobial resistance among the isolates, and indicated the need for monitoring program to control Salmonella contamination and reduce the dissemination of antimicrobial resistance in pig supply chain.

Keywords: prevalence, antimicrobial resistance, Salmonella spp., pig

Procedia PDF Downloads 144