Search results for: neutral vs. emotion classification

Authors: Zhe Li, Aihua Cai

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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

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Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

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Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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Authors: Sara Gallo, Margherita Pasini, Margherita Brondino, Daniela Raccanello, Roberto Burro, Elisa Menardo

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Most of the studies on the ability of environments to recover people’s cognitive resources have been conducted in laboratory using simulated environments (e.g., photographs, videos, or virtual reality), based on the implicit assumption that exposure to simulated environments has the same effects of exposure to real environments. However, the technical characteristics of simulated environments, such as the dynamic or static characteristics of the stimulus, critically affect their perception. Measuring perceived restorativeness in situ rather than in laboratory could increase the validity of the obtained measurements. Personal mobile devices could be useful because they allow accessing immediately online surveys when people are directly exposed to an environment. At the same time, it becomes important to develop short and reliable measuring instruments that allow a quick assessment of the restorative qualities of the environments. One of the frequently used self-report measures to assess perceived restorativeness is the “Perceived Restorativeness Scale” (PRS) based on Attention Restoration Theory. A lot of different versions have been proposed and used according to different research purposes and needs, without studying their validity. This longitudinal study reported some preliminary validation analyses on a short version of original scale, the PRS-6, developed to be quick and mobile-friendly. It is composed of 6 items assessing fascination and being-away. 102 Italian university students participated to the study, 84% female with age ranging from 18 to 47 (M = 20.7; SD = 2.9). Data were obtained through a survey online that asked them to report their perceived restorativeness of the environment they were in (and the kind of environment) and their positive emotion (Positive and Negative Affective Schedule, PANAS) once a day for seven days. Cronbach alpha and item-total correlations were used to assess reliability and internal consistency. Confirmatory Factor Analyses (CFA) models were run to study the factorial structure (construct validity). Correlation analyses between PRS and PANAS scores were used to check discriminant validity. In the end, multigroup CFA models were used to study measurement invariance (configural, metric, scalar, strict) between different mobile devices and between day of assessment. On the whole, the PRS-6 showed good psychometric proprieties, similar to those of the original scale, and invariance across devices and days. These results suggested that the PRS-6 could be a valid alternative to assess perceived restorativeness when researchers need a brief and immediate evaluation of the recovery quality of an environment.

Keywords: restorativeness, validation, short scale development, psychometrics proprieties

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Authors: Alvin Chun Man Kwok, Wai Sun Chan, Wei Yuan, Joseph Tin Yum Wong

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Cellulose, the most abundant biopolymer, is the major constituent of plant and dinoflagellate cell walls. Thecate dinoflagellates, in particular, are renowned for their remarkable capacity to synthesize intricate cellulosic thecal plates (CTPs). Unlike the extracellular two-dimensional structure of plant cell walls, these CTPs are three-dimensional and reside within the cellular structure itself. The deposition of CTPs occurs with remarkable precision, and their arrangement serves as crucial taxonomic markers. It is noteworthy that these plates possess the hardness of wood, despite the absence of lignin. Partial and prolonged hydrolysis of CTPs results in the formation of uniform long bundles and lowdimensional, modular crystalline whiskers. This observation aligns with the consistent nanomechanical properties, suggesting a CTPboard structure. The unique composition and structural characteristics of CTPs distinguish them from other cellulose-based materials in the natural world. Spectroscopic studies using Raman and FTIR methods indicate a clear low crystallinity index, with the OH shift becoming more distinct following SDS treatment. Birefringence imaging confirms the highly organized structure of CTPs, demonstrating varying degrees of anisotropy in different regions, including both seaward and cytosolic passages. The knockdown of a cellulose synthase enzyme in dinoflagellates resulted in severe malformation of CTPs and hindered the life-cycle transition. Unlike certain other microalgal groups, these unique circum-spherical depositions of CTPs were not pre-fabricated and transported "to site," but synthesized within alveolar sacs at the specific site. Our research is particularly focused on unraveling the mechanisms underlying the biodeposition of CTPs and exploring their potential biotechnological applications. Understanding the processes involved in CTP formation can pave the way for harnessing their unique properties for various practical applications. Dinoflagellates play a crucial role as major agents of algal blooms and are also known for producing anti-greenhouse sulfur compounds such as DMS/DMSP, highlighting the significance of CTPs as a carbon-neutral source of cellulose. Grant acknowledgement: Research in the laboratory are supported by GRF16104523 from Research Grant Council to JTYW.

Keywords: cellulosic thecal plates, dinoflagellates, cellulose, cell wall

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Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

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Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

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Authors: Benjawan Saengwichian, Alasdair E. Charles, Philip J. Hyde

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Magnetically controlled growing rods (MCGRs) have been used to stabilise and correct spinal curvature in children to support non-invasive scoliosis adjustment. Although the encapsulated driving components are intended to be isolated from body fluid contact, in vivo corrosion was observed on these components due to sealing mechanism damage. Consequently, a corrosion circuit is created with the body fluids, resulting in malfunction of the lengthening mechanism. Particularly, the chloride ions in blood plasma or cerebrospinal fluid (CSF) may corrode the MCGR alloys, possibly resulting in metal ion release in long-term use. However, there is no data available on the corrosion resistance of spinal implant alloys in CSF. In this study, an in vitro immersion configuration was designed to simulate in vivo corrosion of 440C SS-Ti6Al4V couples. The 440C stainless steel (SS) was heat-treated to investigate the effect of tempering temperature on intergranular corrosion (IGC), while crevice and galvanic corrosion were studied by limiting the clearance of dissimilar couples. Tests were carried out in a neutral artificial cerebrospinal fluid (ACSF) and phosphate-buffered saline (PBS) under aeration and deaeration for 2 months. The composition of the passive films and metal ion release were analysed. The effect of galvanic coupling, pH, dissolved oxygen and anion species on corrosion rates and corrosion mechanisms are discussed based on quantitative and qualitative measurements. The results suggest that ACSF is more aggressive than PBS due to the combination of aggressive chlorides and sulphate anions, while phosphate in PBS acts as an inhibitor to delay corrosion. The presence of Vivianite on the SS surface in PBS lowered the corrosion rate (CR) more than 5 times for aeration and nearly 2 times for deaeration, compared with ACSF. The CR of 440C is dependent on passive film properties varied by tempering temperature and anion species. Although the CR of Ti6Al4V is insignificant, it tends to release more Ti ions in deaerated ACSF than under aeration, about 6 µg/L. It seems the crevice-like design has more effect on macroscopic corrosion than combining the dissimilar couple, whereas IGC is dominantly observed on sensitized microstructure.

Keywords: cerebrospinal fluid, crevice corrosion, intergranular corrosion, magnetically controlled growing rods

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Authors: Imran Hanif, Amanda Persdotter, Sedigheh Bigdeli, Jesper Liske, Torbjorn Jonsson

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Renewable fuels such as biomass/waste for power production is an attractive alternative to fossil fuels in order to achieve a CO₂ -neutral power generation. However, the combustion results in the release of corrosive species. This puts high demands on the corrosion resistance of the alloys used in the boiler. Stainless steels containing nickel and/or nickel containing coatings are regarded as suitable corrosion resistance material especially in the superheater regions. However, the corrosive environment in the boiler caused by the presence of water vapour and reactive alkali very rapidly breaks down the primary protection, i.e., the Cr-rich oxide scale formed on stainless steels. The lifetime of the components, therefore, relies on the properties of the oxide scale formed after breakaway, i.e., the secondary protection. The aim of the current study is to investigate the role of varying nickel content (0–82%) on the high-temperature corrosion of model alloys with 18% Cr (Fe in balance) in the laboratory mimicking industrial conditions at 600°C. The influence of nickel is investigated on both the primary protection and especially the secondary protection, i.e., the scale formed after breakaway, during the oxidation/corrosion process in the dry O₂ (primary protection) and more aggressive environment such as H₂O, K₂CO₃ and KCl (secondary protection). All investigated alloys experience a very rapid loss of the primary protection, i.e., the Cr-rich (Cr, Fe)₂O₃, and the formation of secondary protection in the aggressive environments. The microstructural investigation showed that secondary protection of all alloys has a very similar microstructure in all more aggressive environments consisting of an outward growing iron oxide and inward growing spinel-oxide (Fe, Cr, Ni)₃O₄. The oxidation kinetics revealed that it is possible to influence the protectiveness of the scale formed after breakaway (secondary protection) through the amount of nickel in the alloy. The difference in oxidation kinetics of the secondary protection is linked to the microstructure and chemical composition of the complex spinel-oxide. The detailed microstructural investigations were carried out using the extensive analytical techniques such as electron back scattered diffraction (EBSD), energy dispersive X-rays spectroscopy (EDS) via the scanning and transmission electron microscopy techniques and results are compared with the thermodynamic calculations using the Thermo-Calc software.

Keywords: breakaway corrosion, EBSD, high-temperature oxidation, SEM, TEM

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely. It depends on subspace decomposition of the covariance matrix to separate signal subspace from noise subspace. The decomposition normally is done by either Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD) of the Auto-Correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. In this paper, the multipath channel estimation problem for a Slow Frequency Hopping (SFH) system using noise space based method is considered. An efficient method to estimate multipath the time delays basically is proposed, by applying MUltiple Signal Classification (MUSIC) algorithm which used the null space extracted by the Rank Revealing LU factorization (RRLU). The RRLU provides accurate information about the rank and the numerical null space which make it a valuable tool in numerical linear algebra. The proposed novel method decreases the computational complexity approximately to the half compared with RRQR methods keeping the same performance. Computer simulations are also included to demonstrate the effectiveness of the proposed scheme.

Keywords: frequency hopping, channel model, time delay estimation, RRLU, RRQR, MUSIC, LS-ESPRIT

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

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This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

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Authors: Wen Xu

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The expansion of Confucius institutes and Chinese as a Foreign Language (CFL) education is often considered as cultural invasion and part of much bigger, if not ambitious, Chinese central government agenda among Western public opinion. The CFL knowledge and teaching practice inherent in textbooks are also harshly critiqued as failing to align with Western educational principles. This paper takes up these concerns and attempts to articulate that Confucius’s idea of ‘education without discrimination’ appears to have become synonymous with social justice touted in contemporary Australian education and policy discourses. To do so, it capitalises on Bernstein's conceptualization of classification and pedagogic rights to articulate CFL curriculum's potential of drawing in and drawing out curriculum boundaries to achieve educational justice. In this way, the potential useful knowledge of CFL constitutes a worthwhile tool to engage in a peripheral Western country’s education issues, as well as to include disenfranchised students in the multicultural Australian society. It opens spaces for critically theorising CFL curricular justice in Australian educational contexts, and makes an original contribution to scholarly argumentation that CFL curriculum has the potential of including socially and economically disenfranchised students in schooling.

Keywords: curriculum justice, Chinese as a Foreign Language curriculum, Bernstein, equity

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Authors: Maria Ahmad, Michael Page, Danë Goodsman

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‘Educational’ debriefing – a construct distinct from clinical debriefing – is used following simulated scenarios and is central to learning and development in fields ranging from aviation to emergency medicine. However, little research into educational debriefing in prehospital medicine exists. This qualitative study explored the facilitation and effects of prehospital educational debriefing and identified obstacles to debriefing, using the London’s Air Ambulance Pre-Hospital Care Course (PHCC) as a model. Method: Ethnographic observations of moulages and debriefs were conducted over two consecutive days of the PHCC in October 2019. Detailed contemporaneous field notes were made and analysed thematically. Subsequently, seven one-to-one, semi-structured interviews were conducted with four PHCC debrief facilitators and three course participants to explore their experiences of prehospital educational debriefing. Interview data were manually transcribed and analysed thematically. Results: Four overarching themes were identified: the approach to the facilitation of debriefs, effects of debriefing, facilitator development, and obstacles to debriefing. The unpredictable debriefing environment was seen as both hindering and paradoxically benefitting educational debriefing. Despite using varied debriefing structures, facilitators emphasised similar key debriefing components, including exploring participants’ reasoning and sharing experiences to improve learning and prevent future errors. Debriefing was associated with three principal effects: releasing emotion; learning and improving, particularly participant compound learning as they progressed through scenarios; and the application of learning to clinical practice. Facilitator training and feedback were central to facilitator learning and development. Several obstacles to debriefing were identified, including mismatch of participant and facilitator agendas, performance pressure, and time. Interestingly, when used appropriately in the educational environment, these obstacles may paradoxically enhance learning. Conclusions: Educational debriefing in prehospital medicine is complex. It requires the establishment of a safe learning environment, an understanding of participant agendas, and facilitator experience to maximise participant learning. Aspects unique to prehospital educational debriefing were identified, notably the unpredictable debriefing environment, interdisciplinary working, and the paradoxical benefit of educational obstacles for learning. This research also highlights aspects of educational debriefing not extensively detailed in the literature, such as compound participant learning, display of ‘professional honesty’ by facilitators, and facilitator learning, which require further exploration. Future research should also explore educational debriefing in other prehospital services.

Keywords: debriefing, prehospital medicine, prehospital medical education, pre-hospital care course

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Authors: Hung-Yi Chen, Shih-Jye Wu

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The existing literature provides little discussion on why a public monopolist gives up its market dominant position and allows private firms entering the market. We argue that the privatization of a public monopolist under a vertically related market may induce the entry of private firms. We develop a model of a mixed oligopoly with vertically related markets to explain the change in the market from a public monopolist to a mixed oligopoly and examine issues on privatizing the downstream public enterprise both in the short run and long run in the vertically related markets. We first show that the welfare-maximizing public monopoly firm is suboptimal in the vertically related markets. This is due to the fact that the privatization will reduce the input price charged by the upstream foreign monopolist. Further, the privatization will induce the entry of private firms since input price will decrease after privatization. Third, we demonstrate that the complete privatizing the public firm becomes a possible solution if the entry cost of private firm is low. Finally, we indicate that the public firm should partially privatize if the free-entry of private firms is allowed. JEL classification: F12, F14, L32, L33

Keywords: free entry, mixed oligopoly, public monopoly, the initiation of privatization, vertically related markets, mixed oligopoly

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Authors: Iwona Misztalewska-Turkowicz, Agnieszka Z. Wilczewska, Karolina H. Markiewicz

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Carbenes - species which possess neutral carbon atom with two shared and two unshared valence electrons, are known for their high reactivity and instability. Nevertheless, it is also known, that some carbenes i.e. N-heterocyclic carbenes (NHCs), can form stable crystals. The usability of NHCs in organic synthesis was studied. Due to their exceptional properties (high nucleophilicity) NHCs are commonly used as organocatalysts and also as ligands in transition metal complexes. NHC ligands possess better electron-donating properties than phosphines. Moreover, they exhibit lower toxicity. Due to these features, phosphines are frequently replaced by NHC ligands. In this research is discussed the synthesis of five-membered NHCs which are mainly obtained by deprotonation of azolium salts, e.g., imidazolium or imidazolinium salts. Some of them are immobilized on a solid support what leads to formation of heterogeneous, recyclable catalysts. Magnetic nanoparticles (MNPs) are often used as a solid support for catalysts. MNPs can be easily separated from the reaction mixture using an external magnetic field. Due to their low size and high surface to volume ratio, they are a good choice for immobilization of catalysts. Herein is presented synthesis of N-heterocyclic carbene copper complexes directly on the surface of magnetic nanoparticles. Formation of four different catalysts is discussed. They vary in copper oxidation state (Cu(I) and Cu(II)) and structure of NHC ligand. Catalysts were tested in Huisgen reaction, a type of copper catalyzed azide-alkyne cycloaddition (CuAAC) reaction. Huisgen reaction represents one of the few universal and highly efficient reactions in which 1,2,3-triazoles can be obtained. The catalytic activity of all synthesized catalysts was compared with activity of commercially available ones. Different reaction conditions (solvent, temperature, the addition of reductant) and reusability of the obtained catalysts were investigated and are discussed. The project was financially supported by National Science Centre, Poland, grant no. 2016/21/N/ST5/01316. Analyses were performed in Centre of Synthesis and Analyses BioNanoTechno of University of Bialystok. The equipment in the Centre of Synthesis and Analysis BioNanoTechno of University of Bialystok was funded by EU, as a part of the Operational Program Development of Eastern Poland 2007-2013, project: POPW.01.03.00-20-034/09-00 and POPW.01.03.00-20-004/11.

Keywords: N-heterocyclic carbenes, click reaction, magnetic nanoparticles, copper catalysts

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Authors: Olga Mironiuk, Małgorzata Kossowska

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The aim of the present study was to investigate the influence of Situational Attribution Training on reducing automatic in-group stereotyping in females. The experiment was conducted with the control of age and level of prejudice. 90 female participants were randomly assigned to two conditions: experimental and control group (each group was also divided into younger- and older-aged condition). Participants from the experimental condition were subjected to more extensive training. In the first part of the experiment, the experimental group took part in the first session of Situational Attribution Training while the control group participated in the Grammatical Training Control. In the second part of the research both groups took part in the Situational Attribution Training (which was considered as the second training session for the experimental group and the first one for the control condition). The training procedure was based on the descriptions of ambiguous situations which could be explained using situational or dispositional attributions. The participant’s task was to choose the situational explanation from two alternatives, out of which the second one presented the explanation based on neutral or stereotypically associated with women traits. Moreover, the experimental group took part in the third training session after two- day time delay, in order to check the persistence of the training effect. The main hypothesis stated that among participants taking part in the more extensive training, the automatic in-group stereotyping would be less frequent after having finished training sessions. The effectiveness of the training was tested by measuring the response time and the correctness of answers: the longer response time for the examples where one of two possible answers was based on the stereotype trait and higher correctness of answers was considered to be a proof of the training effectiveness. As the participants’ level of prejudice was controlled (using the Ambivalent Sexism Inventory), it was also assumed that the training effect would be weaker for participants revealing a higher level of prejudice. The obtained results did not confirm the hypothesis based on the response time: participants from the experimental group responded faster in case of situations where one of the possible explanations was based on stereotype trait. However, an interesting observation was made during the analysis of the answers’ correctness: regardless the condition and age group affiliation, participants made more mistakes while choosing the situational explanations when the alternative was based on stereotypical trait associated with the dimension of warmth. What is more, the correctness of answers was higher in the third training session for the experimental group in case when the alternative of situational explanation was based on the stereotype trait associated with the dimension of competence. The obtained results partially confirm the effectiveness of the training.

Keywords: female, in-group stereotyping, prejudice, situational attribution training

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Authors: Kamrun Nahar Koly, Saimul Islam

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Overweight and obesity is increasing at an alarming rate and a leading risk factor for morbidity throughout the world. In a country like Bangladesh where under nutrition and overweight both co-exist at the same time, but this issue has been underexplored as expected. The aim of the present study was to assess the knowledge, attitudes and identify the barriers of the physicians regarding overweight and obesity management on an urban hospital of Dhaka city in Bangladesh. A simple cross sectional study was conducted at two selected government and two private hospital to assess the knowledge, attitude and common barriers regarding overweight and obesity management among healthcare professionals. One hundred and fifty five physicians were surveyed. A standard questionnaire was constructed in local language and interview was administrated. Among the 155 physicians, majority 53 (34.20%) were working on SMC, 36 (23.20%) from DMC, 33 (21.30%) were based on SSMC and the rest 33 (21.30%) were from HFRCMH. Mean age of the study physicians were 31.88±5.92. Majority of the physicians 80 (51.60%) were not able to answer the correct prevalence of obesity but also a substantial number of them 75(48.40%) could mark the right answer. Among the physicians 150 (96.77%) reported BMI as a diagnostic index for overweight and obesity, where as 43 (27.74%) waist circumference, 30 (19.35%) waist hip ratio and 26 (16.77%) marked mid-arm circumference. A substantial proportion 71 (46.70%) of the physicians thought that they do not have much to do controlling weight problem in Bangladesh context though it has been opposed by 42 (27.60%) of the physicians and 39(25.70%) was neutral to comment. The majority of them 147 (96.1%) thought that a family based education program would be beneficial followed by 145 (94.8%) physicians mentioned about raising awareness among mothers as she is the primary caregiver. The idea of a school based education program will also help to early intervene referred by 142 (92.8%) of the physicians. Community based education program was also appreciated by 136 (89.5%) of the physicians. About 74 (47.7%) of them think that the patients still lack in motivation to maintain their weight properly at the same time too many patients to deal with can be a barrier as well assumed by 73 (47.1%) of them. Lack of national policy or management guideline can act as an obstacle told by 60 (38.7%) of the physicians. The relationship of practicing as a part of the general examination and chronic disease management was statistically significant (p<0.05) with physician occupational status. As besides, perceived barriers like lack of parents support, lack of a national policy was statistically significant (p<0.05) with physician occupational status. For the young physician, more training programme will be needed to transform their knowledge and attitude into practice. However, several important barriers interface for the physician treatment efforts and need to address.

Keywords: obesity management, physician, awareness, barriers, Bangladesh

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: Alessandra Marcelletti, Giovanni Trovato

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Corruption in public offices is found to be the reflection of country-specific features, however, the exact magnitude and the statistical significance of its determinants effect has not yet been identified. The paper aims to propose an estimation method to measure the impact of country fundamentals on corruption, showing that covariates could differently affect the extent of corruption across countries. Thus, we exploit a model able to take into account different factors affecting the incentive to ask or to be asked for a bribe, coherently with the use of the Corruption Perception Index. We assume that discordant results achieved in literature may be explained by omitted hidden factors affecting the agents' decision process. Moreover, assuming homogeneous covariates effect may lead to unreliable conclusions since the country-specific environment is not accounted for. We apply a Finite Mixture Model with concomitant variables to 129 countries from 1995 to 2006, accounting for the impact of the initial conditions in the socio-economic structure on the corruption patterns. Our findings confirm the hypothesis of the decision process of accepting or asking for a bribe varies with specific country fundamental features.

Keywords: Corruption, Finite Mixture Models, Concomitant Variables, Countries Classification

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Authors: Fatima Ali Abbass, Hassan Ibrahim Rkein

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The number of entities worldwide that currently accept digital currency as payment is increasing; however, digital currency still is not widely accepted as a medium of exchange, nor they represent legal tender. At the same time, this makes accounting for cryptocurrency, as cash (Currency) is not possible under IAS 7 and IAS 32, Cryptocurrency also cannot be accounted for as Financial Assets at fair value through profit or loss under IFRS 9. Therefore, this paper studies the possible means to account for Cryptocurrency, since, as of today, there is not yet an accounting standard that deals with cryptocurrency. The request to have a specific accounting standard is increasing from top accounting firms and from professional accounting bodies. This study uses a mixture of qualitative and quantitative analysis in its quest to explore the best possible way to account for cryptocurrency. Interviews and surveys were conducted targeting accounting professionals. This study highlighted the deficiencies in the current way of accounting for Cryptocurrency as intangible Assets with an indefinite life. The deficiency becomes well highlighted, as the asset will then be subject to impairment, where under GAAP, only depreciation in the value of the intangible asset is recognized. On the other hand, appreciation in the value of the asset is ignored, and this prohibits the reporting entity from showing the true value of the cryptocurrency asset. This research highlights the gap that arises due to using accounting standards that are not specific for Cryptocurrency and this study confirmed that there is an urgent need to call upon the accounting standards setters (IASB and FASB) to issue accounting standards specifically for Cryptocurrency.

Keywords: cryptocurrency, accounting, IFRS, GAAP, classification, measurement

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Authors: Salam N. Abdo, Orien L. Tulp, George P. Einstein

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The purpose of this exploratory study was to gather the insights into psoriasis etiology, treatment, and patient experience, for developing psoriasis and psoriatic arthritis diagnostic test. Data collection methods consisted of a comprehensive meta-analysis of relevant studies and psoriasis patient survey. Established meta-analysis guidelines were used for the selection and qualitative comparative analysis of psoriasis and psoriatic arthritis research studies. Only studies that clearly discussed psoriasis etiology, treatment, and patient experience were reviewed and analyzed, to establish a qualitative data base for the study. Using the insights gained from meta-analysis, an existing psoriasis patient survey was modified and administered to collect additional data as well as triangulate the results. The hypothesis is that specific types of psoriatic disease have specific etiology and pathophysiologic pattern. The following etiology categories were identified: bacterial, environmental/microbial, genetic, immune, infectious, trauma/stress, and viral. Additional results, obtained from meta-analysis and confirmed by patient survey, were the common age of onset (early to mid-20s) and type of psoriasis (plaque; mild; symmetrical; scalp, chest, and extremities, specifically elbows and knees). Almost 70% of patients reported no prescription drug use due to severe side effects and prohibitive cost. These results will guide the development of psoriasis and psoriatic arthritis diagnostic test. The significant number of medical publications classified psoriatic arthritis disease as inflammatory of an unknown etiology. Thus numerous meta-analyses struggle to report any meaningful conclusions since no definitive results have been reported to date. Therefore, return to the basics is an essential step to any future meaningful results. To date, medical literature supports the fact that psoriatic disease in its current classification could be misidentifying subcategories, which in turn hinders the success of studies conducted to date. Moreover, there has been an enormous commercial support to pursue various immune-modulation therapies, thus following a narrow hypothesis/mechanism of action that is yet to yield resolution of disease state. Recurrence and complications may be considered unacceptable in a significant number of these studies. The aim of the ongoing study is to focus on a narrow subgroup of patient population, as identified by this exploratory study via meta-analysis and patient survey, and conduct an exhaustive work up, aiming at mechanism of action and causality before proposing a cure or therapeutic modality. Remission in psoriasis has been achieved and documented in medical literature, such as immune-modulation, phototherapy, various over-the-counter agents, including salts and tar. However, there is no psoriasis and psoriatic arthritis diagnostic test to date, to guide the diagnosis and treatment of this debilitating and, thus far, incurable disease. Because psoriasis affects approximately 2% of population, the results of this study may affect the treatment and improve the quality of life of a significant number of psoriasis patients, potentially millions of patients in the United States alone and many more millions worldwide.

Keywords: biologics, early diagnosis, etiology, immune disease, immune modulation therapy, inflammation skin disorder, phototherapy, plaque psoriasis, psoriasis, psoriasis classification, psoriasis disease marker, psoriasis diagnostic test, psoriasis marker, psoriasis mechanism of action, psoriasis treatment, psoriatic arthritis, psoriatic disease, psoriatic disease marker, psoriatic patient experience, psoriatic patient quality of life, remission, salt therapy, targeted immune therapy

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Authors: Miraji H. Mohamed

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The purpose of this study is to critique ‘radicalisation’ and more particularly ‘youth radicalisation’ by exploring its usage in online newspapers. ‘Radicalisation’ and ‘extremism’ have become the most common terms in terrorism studies since the 9/11 attacks. Regardless of the geographic location, when the word terrorism is used the terms ‘radicalisation’ and ‘extremism’ always follow to attempt to explore the journey of the perpetrators towards violence. These terms have come to represent a discourse of dominantly pejorative traits often used to describe spaces, groups, and processes identified as problematic. Even though ambiguously defined they feature widely in government documents, political statements, news articles, academic research, social media platforms, religious gatherings, and public discussions. Notably, ‘radicalisation’ and ‘extremism’ have been closely conflated with the term youth to form ‘youth radicalisation’ to refer to a discourse of ‘youth at risk’. The three terms largely continue to be used unquestioningly and interchangeably hence the reason why they are placed in single quotation marks to deliberately question their conventional usage. Albeit this comes timely in the Kenyan context where there has been a proliferation of academic and expert research on ‘youth radicalisation’ (used as a neutral label) without considering the political, cultural and socio-historical contexts that inform this label. This study seeks to draw these nuances by employing a genealogical approach that historicises and deconstructs ‘youth radicalisation’; and by applying a Discourse-Historical Approach (DHA) of Critical Discourse Analysis to analyse Kenyan online newspaper - The Daily Nation between 2015 and 2018. By applying the concept of representation to analyse written texts, the study reveals that the use of ‘youth radicalisation’ as a discursive strategy disproportionately affects young people especially those from cultural/ethnic/religious minority groups. Also, the ambiguous use of ‘radicalisation’ and ‘youth radicalisation’ by the media reinforces the discourse of ‘youth at risk’ which has become the major framework underpinning Countering Violent Extremism (CVE) interventions. Similarly, the findings indicate that the uncritical use of ‘youth radicalisation’ has been used to serve political interests; and has become an instrument of policing young people, thus contributing to their cultural shaping. From this, it is evident that the media could thwart rather than assist CVE efforts. By exposing the political nature of the three terms through evidence-based research, this study offers recommendations on how critical reflective reporting by the media could help to make CVE more nuanced.

Keywords: discourse, extremism, radicalisation, terrorism, youth

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Authors: Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Tomohiko Akahoshi

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The incidence of Disseminated intravascular coagulation (DIC) following gastrointestinal surgery has a poor prognosis. Therefore, it is important to determine the factors that can predict the prognosis of DIC. This study will investigate the factors that may influence the outcome of DIC in patients after gastrointestinal surgery. Eighty-one patients were admitted to the intensive care unit after gastrointestinal surgery in Kyushu University Hospital from 2003 to 2021. Acute DIC scores were estimated using the new Japanese Association for Acute Medicine (JAAM) score from before and after surgery from day 1, day 3, and day 7. Acute DIC scores will be compared with The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a variety of biochemical parameters. This study applied machine learning algorithms to predict the prognosis of DIC after gastrointestinal surgery. The results of this study are expected to be used as an indicator for evaluating patient prognosis so that it can increase life expectancy and reduce mortality from cases of DIC patients after gastrointestinal surgery.

Keywords: the survival rate, gastrointestinal surgery, JAAM score, neural network, machine learning, disseminated intravascular coagulation (DIC)

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Authors: Alvarez Barrantes, Robert Dorrell, Christopher Hackney, Anne Baar, Roberto Fernandez, Daniel Parsons

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Microplastic particles entering fluvial environments are deposited with natural sediments. Their settling properties can change by the absorption or adsorption of contaminants, organic matter, and organisms. These deposits include positively, neutrally, and negatively buoyant particles. This study aims to understand how plastic particles of different densities interact with natural sediments as they settle and how they are stored within the sediment deposit. The results of this study contribute to a better understanding of the deposition of microplastic particles and associated pollution in rivers. A set of 48 experiments was designed to investigate the settling process of microplastic particles in freshwater. The experimental work describes the vertical variation of cohesive and/or non-cohesive sediment versus microplastic densities in deposited sediment. The experiment consisted of adding microplastic particles, sediment, and water in a waterproof carton tube of a height of 24 cm and a diameter of 5 cm. The plastic selected is positively, neutrally, and negatively buoyant. The sediments consist of sand and clay with four different concentrations. The mixture of materials was shaken until is thoroughly mixed and left to settle for 24 hours. After the settlement, the tubes were frozen at -20 °C to be able to cut them and measure the thickness of the deposits and analyze the sediment and plastic distribution. The most representative experiments were repeated in a glass tube of the same size; to analyse the influences of current flows and depositional process. Finally, the glass tube experiments were used to study organic materials adsorption in plastic, settling the sample for four months. Defined microplastic layers were identified as the density of the plastic change. Preliminary results show that most of the positive buoyancy particles floated, neutral buoyancy particles form a layer above the sediment and negative buoyancy particles mixed with the sediment. The vertical grain size distribution of the deposits was analysed to determine deposition variation with and without plastic. It is expected that the positively buoyant particles are trapped in the sediment by the currents flows and sink due to organic material adsorption. Finally, the experiments will explain how microplastic particles, including positively buoyant ones, are stored in natural sediment deposits.

Keywords: microplastic adsorption process, microplastic deposition in natural sediment, microplastic pollution in rivers, storages of positive buoyancy microplastic particles

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Authors: Zixi You

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With the demand of multilingual speakers increasing in the job market, multi-language learning programs have become more and more popular among undergraduate students. A study on multi-language learning strategies is therefore highly demanded on both practical and theoretical levels. Based on previous classification of learning strategies in SLA, and an investigation of BA Modern Language program students (with post-A level L2 and ab initio L3 learning experience from year one), this study explores and compares different types of learning strategies used by multi-language speakers and learners, transferable learning strategies between L2 and L3, and factors affecting the transfer. The results indicate that all the 23 types of learning strategies of L2 are employed when learning L3 from ab initio level, yet with different tendencies. Learning strategy transfer from L2 to L3 (i.e., the learners attribute the applying of these L3 learning strategies to be a direct result of their L2 learning experience) are observed in all 23 types of learning strategies. Comparatively, six types of “cognitive strategies” have higher transfer tendency than others. With regard to the failure of the transfer of some particular L2 strategies and the development of independent L3 strategies of individual learners, factors such as language proficiency, language typology and learning environment have played important roles among others. The presentation of this study will provide audiences with detailed data, insightful analysis and discussion on both theoretical and practical aspects of multi-language learning that will benefit both students and educators.

Keywords: learning strategy, multi-language acquisition, second language acquisition, strategy transfer

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Authors: Raka Rahmatulloh, Mohammad Ilham Nugraha, Muhammad Ifan Fathurrahman

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The agricultural sector covers a wide area, one of them is livestock subsector that supply needs of the food source of animal protein. Animal protein is produced by the main livestock production such as meat, milk, eggs, etc. Besides the main production, livestock would produce metabolic residue, so called livestock wastes. Characteristics of livestock wastes can be either solid (feces), liquid (urine), and gas (methane) which turned out to be useful and has economical value when well-processed and well-controlled. Nowadays, this livestock wastes is considered as a source of pollutants, especially water pollution. If the source of pollutants used in an integrated way, it will have a positive impact on organic farming and a healthy environment. Management of livestock wastes can be integrated with the farming sector to the planting and caring that rely on fertilizers. Most Indonesian farmers still use chemical fertilizers, where the use of it in the long term will disturb the ecological balance of the environment. One of the main efforts is to use organic fertilizers instead of chemical fertilizer that conducted by the Faculty of Animal Husbandry, Padjadjaran University. The method is to use the solid waste of livestock and agricultural wastes into liquid organic fertilizer, feed additive, biogas and vermicompost through decomposition. The decomposition takes as long as 14 days including aeration and extraction process using water as a nutrients solvent media which contained in decomposes and disinfection media to release pathogenic microorganisms in decomposes. Liquid organic fertilizer has highly efficient for the farmers to have a ratio of carbon/nitrogen (C/N) 25/1 to 30/1 and neutral pH (6.5-7.5) which is good for plant growth. Feed additive may be given to improve the digestibility of feed so that substances can be easily absorbed by the body for production. Biogas contains methane (CH4), which has a high enough heat to produce electricity. Vermicompost is an overhaul of waste organic material that has excellent structure, porosity, aeration, drainage, and moisture holding capacity. Based on the case study above, an integrated livestock wastes management program strongly supports the Indonesian government in the achievement of sustainable livestock development.

Keywords: integrated, livestock wastes, organic fertilizer, sustainable livestock development

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Authors: S. Ayeko, J. Milton, C. Hughes, K. Anderson, R. G. Middleton

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Background: Periprosthetic femoral fractures (PFF) in association with hip hemiarthroplasty or total hip arthroplasty is a common and serious complication. In the Vancouver Classification system algorithm, B1 fractures should be treated with Open Reduction and Internal Fixation (ORIF) and preferentially revised in combination with ORIF if B2 or B3. This study aims to assess patient outcomes after plate osteosynthesis alone for Vancouver B1 and B2 fractures. The main outcome is the 1-year re-revision rate, and secondary outcomes are 30-day and 1-year mortality. Method: This is a retrospective single-centre case-series review from January 2016 to June 2021. Vancouver B1 and B2, non-malignancy fractures in adults over 18 years of age treated with polyaxial Non-Contact Bridging plate osteosynthesis, have been included. Outcomes were gathered from electronic notes and radiographs. Results: There were 50 B1 and 64 B2 fractures. 26 B2 fractures were managed with ORIF and revision, 39 ORIF alone. Of the revision group, one died within 30 days (3.8%), one at one year (3.8%), and two were revised within one year (7.7). Of the B2 ORIF group, three died within 30-day mortality (7.96%), eight at one year (21.1%), and 0 were revised in 1 year. Conclusion: This study has demonstrated that satisfactory outcomes can be achieved with ORIF, excluding revision in the management of B2 fractures.

Keywords: arthroplasty, bridging plate, periprosthetic fracture, revision surgery

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