Search results for: imaging and signal processing

Authors: Larisa Gheber

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Mitosis is an essential process by which duplicated genetic information is transmitted from mother to daughter cells. Incorrect chromosome segregation during mitosis can lead to genetic diseases, chromosome instability and cancer. This process is mediated by a dynamic microtubule-based intracellular structure, the mitotic spindle. One of the major factors that govern the mitotic spindle dynamics are the kinesin-5 biological nano motors that were believed to move unidirectionally on the microtubule filaments, using ATP hydrolysis, thus performing essential functions in mitotic spindle dynamics. Surprisingly, several reports from our and other laboratories have demonstrated that some kinesin-5 motors are bi-directional: they move in minus-end direction on the microtubules as single-molecules and can switch directionality under a number of conditions. These findings broke a twenty-five-years old dogma regarding kinesin directionality (1, 2). The mechanism of this bi-directional motility and its physiological significance remain unclear. To address this unresolved problem, we apply an interdisciplinary approach combining live cell imaging, biophysical single molecule, and structural experiments to examine the activity of these motors and their mutated variants in vivo and in vitro. Our data shows that factors such as protein phosphorylation (3, 4), motor clustering on the microtubules (5, 6) and structural elements (7, 8) regulate the bi-directional motility of kinesin motors. We also show, using Cryo-EM, that bi-directional kinesin motors obtain non-canonical microtubule binding, which is essential to their special motile properties and intracellular functions. We will discuss the implication of these findings to mechanism bi-directional motility and physiological roles in mitosis.

Keywords: mitosis, cancer, kinesin, microtubules, biochemistry, biophysics

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Authors: Nicholas Bayfield, Mark Newman

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Case Presentation: A 48-year-old male was brought in by ambulance after an out-of-hospital cardiac arrest, with 20 minutes of good-quality cardiopulmonary resuscitation in the community. Return of spontaneous circulation was achieved with defibrillation, revealing an inferior ST-elevation myocardial infarction. He was revascularized emergently in the cath lab and stabilised. Following the procedure, he was noted to have paradoxical respiratory movements of the sternum and high oxygen requirements. CT imaging demonstrated a flail chest with bilateral anterior rib 1-7 fractures as well as a large left-sided extra-pleural haematoma and small haemopneumothorax, secondary to CPR. The patient’s ventilation was stabilised with oxygen via a high-flow humidifier. Pain relief was provided. The anatomy of his rib fractures was not easily amenable to operative fixation. In addition, he was considered to be a high-risk operative candidate due to his recent arrest. He was managed thus non-operatively with an external vacuum dressing applied to the anterior chest wall to minimise respiratory compromise and minimise pain from the motion around the rib fracture sites. Non-operative management was successful, and the patient was reviewed one month later. The paradoxical sternal movement had abated. Discussion: External vacuum dressing has been trialled for non-operative management of rib fractures with varying success. It provides an external brace to minimise fracture site movement during respiration and coughing, thus minimising pain. This modality should be considered a low-cost, high-reward adjunct to non-operative management of bony thoracic trauma.

Keywords: thoracic surgery, thoracic trauma, rib fractures, negative pressure dressing

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Authors: Noori Shafiqullah

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Millions of people reside downstream of river basins that heavily rely on snowmelt originating from the Hindu Kush (HK) region. Snowmelt plays a critical role as a primary water source in these areas. This study aimed to evaluate snowfall and snowmelt characteristics in the HK region across altitudes ranging from 2019m to 4533m. To achieve this, the study employed a combination of remote sensing techniques and the Snow Model (SM) to analyze the spatial and temporal distribution of Snow Water Equivalent (SWE). By integrating the simulated Snow-cover Area (SCA) with data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the study optimized the Precipitation Gradient (PG), snowfall assessment, and the degree-day factor (DDF) for snowmelt distribution. Ground observed data from various elevations were used to calculate a temperature lapse rate of -7.0 (°C km-1). Consequently, the DDF value was determined as 3 (mm °C-1 d-1) for altitudes below 3000m and 3 to 4 (mm °C-1 d-1) for higher altitudes above 3000m. Moreover, the distribution of precipitation varies with elevation, with the PG being 0.001 (m-1) at lower elevations below 4000m and 0 (m-1) at higher elevations above 4000m. This study successfully utilized the SM to assess SCA and SWE by incorporating the two optimized parameters. The analysis of simulated SCA and MODIS data yielded coefficient determinations of R2, resulting in values of 0.95 and 0.97 for the years 2014-2015, 2015-2016, and 2016-2017, respectively. These results demonstrate that the SM is a valuable tool for managing water resources in mountainous watersheds such as the HK, where data scarcity poses a challenge."

Keywords: improved MODIS, experiment, snow water equivalent, snowmelt

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

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Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

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The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

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Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

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Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

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Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

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This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

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Authors: Ch. Sandeep Kumar Subudhi, S. Sivanandam

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Our system is to monitor the human body temperature, blood pressure (BP), Pulse Rate and ECG and tracking the patient location. In our system the body temperature is detected by using LM35 temperature sensor, blood pressure is detected by the BP sensor, pulse rate is detected by the ear plug pulse sensor and the ECG is detected by the three lead ECG sensor in the working environment of the patient. The sensed information is sent to the PIC16F877 microcontroller through signal conditioning circuit. A desired amount of sensor value is set and if it is exceeded preliminary steps should be taken by indication by buzzer. The sensor information will be transmitted from the patient unit to the main controller unit with the help of Zigbee communication medium which is connected with the microcontrollers in the both units. The main controller unit will send those sensor data as well as the location of that patient by the help of GPS module to the observer/doctor. The observer/doctor can receive the SMS sent by GSM module and further decision can be taken. The message is sent to a cell phone using global system mobile (GSM) Modem. MAX232 acts as a driver between microcontroller and modem.

Keywords: LM35, heart beat sensor, ECG Sensor, BP Sensor, Zigbee module, GSM module, GPS module, PIC16F877A microcontroller

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Authors: M. N. Hanina, M. Hairul Shahril, I. Ismatul Nurul Asyikin, A. K. Abdul Jalil, M. R. Salina, M. R. Maryam, M. Rosfarizan

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The extracellular proteins secreted by bacteria may be increased in stressful surroundings, such as in the presence of antibiotics. It appears that many antibiotics, when used at low concentrations, have in common the ability to activate or repress gene transcription, which is distinct from their inhibitory effect. There have been comparatively few studies on the potential of antibiotics as a specific chemical signal that can trigger a variety of biological functions. Therefore, this study was carried out to determine the effect of Streptomycin Sulfate in regulating extracellular proteins secreted by Bacillus subtilis ATCC21332. Results of Microdilution assay showed that the Minimum Inhibition Concentration (MIC) of Streptomycin Sulfate on B. subtilis ATCC21332 was 2.5 mg/ml. The bacteria cells were then exposed to Streptomycin Sulfate at concentration of 0.01 MIC before being further incubated for 48h to 72 h. The extracellular proteins secreted were then isolated and analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Proteins profile revealed that three additional bands with approximate sizes of 30 kDa, 22 kDa and 23 kDa were appeared for the treated bacteria with Streptomycin Sulfate. Thus, B. subtilis ATCC21332 in stressful condition with the presence of Streptomycin Sulfate at low concentration could induce the extracellular proteins secretion.

Keywords: Bacillus subtilis ATCC21332, streptomycin sulfate, extracellular proteins, antibiotics

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Authors: Avigail Moor, Michal Otmazgin, Hagar Tsiddon, Avivit Mahazri

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The goal of the present study was to refine sexual assault therapy through the examination of the level of agreement between survivor and therapist assessments of key recovery-promoting therapeutic interventions. This is the first study to explore the level of agreement between those who partake in the treatment process from either position. Semi structured interviews were conducted in this qualitative study with 10 survivors and 10 experienced therapists. The results document considerable concurrence between them regarding relational and trauma processing treatment components alike. Together, these reports outline key effective interventions, both common and specific in nature, concomitantly supported by both groups.

Keywords: sexual assault, rape treatment, therapist training, psychotherapy

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Authors: Faizan Asghar, Mohammad Jamal Khattak

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Aging, in general, refers to changes in rheological characteristics of asphalt mixture due to changes in chemical composition over the course of construction and service life of the pavement. The main goal of this study was to investigate the impact of oxidation on fatigue characteristics of a novel HMA composite fabricated with a combination of crumb rubber (CRM) and polyvinyl alcohol (PVA) fiber subject to aging of 7 and 14 days. A flexural beam fatigue test was performed to evaluate several characteristics of control, CRM modified, PVA reinforced, and novel rubber-fiber HMA composite. Experimental results revealed that aging had a significant impact on the fatigue performance of novel HMA composite. It was found that a suitable proportion of CRM and PVA radically affected the performance of novel rubber-fiber HMA in resistance to fracture and fatigue cracking when subjected to long-term aging. The developed novel HMA composite containing 2% CRM and 0.2% PVA presented around 29 times higher resistance to fatigue cracking for a period of 7 days of aging. To develop a cumulative plastic deformation level of 250 micros, such a mixture required over 50 times higher cycles than control HMA. Moreover, the crack propagation rate was reduced by over 90%, with over 12 times higher energy required to propagate a unit crack length in such a mixture compared to conventional HMA. Further, digital imaging correlation analyses revealed a more twisted and convoluted fracture path and higher strain distribution in rubber-fiber HMA composite. The fatigue performance after long-term aging of such novel HMA composite explicitly validates the ability to withstand load repetition that could lead to an extension in the service life of pavement infrastructure and reduce taxpayers’ dollars spent.

Keywords: crumb rubber, PVA fibers, dry process, aging, performance testing, fatigue life

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

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The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Zhenyu Du, Ed Collings, James Meredith

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The high cost of composite materials versus conventional materials remains a major barrier to uptake in the transport sector. This is exacerbated by a shortage of skilled labour which makes the labour content of a hand laid composite component (~40 % of total cost) an obvious target for reduction. Automation is a method to remove labour cost and improve quality. This work focuses on the challenges and benefits to automating the manufacturing process from raw fibre to trimmed component. It will detail the experimental work required to complete an automation cell, the control strategy used to integrate all machines and the final benefits in terms of throughput and cost.

Keywords: automation, low cost technologies, processing and manufacturing technologies, resin transfer moulding

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Jiahua Zhang, Qing Chang, Fengmei Yao

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Studying on the response of vegetation phenology to climate change at different temporal and spatial scales is important for understanding and predicting future terrestrial ecosystem dynamics andthe adaptation of ecosystems to global change. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset and climate data were used to analyze the dynamics of grassland phenology as well as their correlation with climatic factors in different eco-geographic regions and elevation units across the Tibetan Plateau. The results showed that during 2003–2012, the start of the grassland greening season (SOS) appeared later while the end of the growing season (EOS) appeared earlier following the plateau’s precipitation and heat gradients from southeast to northwest. The multi-year mean value of SOS showed differences between various eco-geographic regions and was significantly impacted by average elevation and regional average precipitation during spring. Regional mean differences for EOS were mainly regulated by mean temperature during autumn. Changes in trends of SOS in the central and eastern eco-geographic regions were coupled to the mean temperature during spring, advancing by about 7d/°C. However, in the two southwestern eco-geographic regions, SOS was delayed significantly due to the impact of spring precipitation. The results also showed that the SOS occurred later with increasing elevation, as expected, with a delay rate of 0.66 d/100m. For 2003–2012, SOS showed an advancing trend in low-elevation areas, but a delayed trend in high-elevation areas, while EOS was delayed in low-elevation areas, but advanced in high-elevation areas. Grassland SOS and EOS changes may be influenced by a variety of other environmental factors in each eco-geographic region.

Keywords: grassland, phenology, MODIS, eco-geographic regions, elevation, climatic factors, Tibetan Plateau

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Authors: Krasimir I. Ivanov, Penka S. Zapryanova, Stefan V. Krustev, Violina R. Angelova

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Three commonly used digestion methods (dry ashing, acid digestion, and microwave digestion) in different variants were compared for digestion of tobacco leaves. Three main macroelements (K, Ca and Mg) were analysed using AAS Spectrometer Spectra АА 220, Varian, Australia. The accuracy and precision of the measurements were evaluated by using Polish reference material CTR-VTL-2 (Virginia tobacco leaves). To elucidate the problems with elemental recovery X-Ray and SEM–EDS analysis of all residues after digestion were performed. The X-ray investigation showed a formation of KClO₄ when HClO4 was used as a part of the acids mixture. The use of HF at Ca and Mg determination led to the formation of CaF₂ and MgF₂. The results were confirmed by energy dispersive X-ray microanalysis. SPSS program for Windows was used for statistical data processing.

Keywords: digestion methods, plant tissue, determination of macroelements, K, Ca, Mg

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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This paper evaluates the bit error rate (BER) performance of MIMO-OFDM communication system. MIMO system uses multiple transmitting and receiving antennas with different coding techniques to either enhance the transmission diversity or spatial multiplexing gain. Utilizing alamouti algorithm were the same information transmitted over multiple antennas at different time intervals and then collected again at the receivers to minimize the probability of error, combat fading and thus improve the received signal to noise ratio. While utilizing V-BLAST algorithm, the transmitted signals are divided into different transmitting channels and transferred over the channel to be received by different receiving antennas to increase the transmitted data rate and achieve higher throughput. The paper provides a study of different diversity gain coding schemes and spatial multiplexing coding for MIMO systems. A comparison of various channels' estimation and equalization techniques are given. The simulation is implemented using MATLAB, and the results had shown the performance of transmission models under different channel environments.

Keywords: MIMO communication, BER, space codes, channels, alamouti, V-BLAST

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Authors: Qiaoyun Yang

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Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

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Authors: Dev Pratap Singh, Harshika Hasija, Ashwini S.

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The project aims to provide a touchless, intuitive interface for human-computer interaction, enabling users to control their computers using hand gestures and voice commands. The system leverages advanced computer vision techniques using the Media Pipe framework and OpenCV to detect and interpret real-time hand gestures, transforming them into mouse actions such as clicking, dragging, and scrolling. Additionally, the integration of a voice assistant powered by the speech recognition library allows for seamless execution of tasks like web searches, location navigation, and gesture control in the system through voice commands.

Keywords: gesture recognition, hand tracking, machine learning, convolutional neural networks, natural language processing, voice assistant

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Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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Authors: John Hawkins, Graham Burton

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Contextual targeting is a common strategy for advertising that places marketing messages in media locations that are expected to be aligned with the target audience. There are multiple major challenges to contextual targeting: the ideal categorisation scheme needs to be known, as well as the most appropriate subsections of that scheme for a given campaign or creative. In addition, the campaign reach is typically limited when targeting becomes narrow, so a balance must be struck between requirements. Finally, refinement of the process is limited by the use of evaluation methods that are either rapid but non-specific (click through rates), or reliable but slow and costly (conversions or brand recall studies). In this study we evaluate the use of attention measurement as a technique for understanding the performance of targeting on the basis of specific contextual topics. We perform the analysis using a large scale dataset of impressions categorised using the iAB V2.0 taxonomy. We evaluate multiple levels of the categorisation hierarchy, using categories at different positions within an initial creative specific ranking. The results illustrate that measuring attention time is an affective signal for the performance of a specific creative within a specific context. Performance is sustained across a ranking of categories from one period to another.

Keywords: contextual targeting, digital advertising, attention measurement, marketing performance

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Authors: Singh Deepeshwar, Suhas Vinchurkar

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Similar to neuroimaging findings through functional magnetic resonance imaging (fMRI) assessing regional cerebral blood oxygenation, the functional near infrared spectroscopy (fNIRS) has also been used to assess hemodynamic responses in the imaged region of the brain. The present study assessed hemodynamic responses in terms of changes in oxygenation (HbO), deoxygenation (HbR) and total hemoglobin (THb) on the prefrontal cortex (PFC), bilaterally, using fNIRS in 10 participants who performed three voluntary regulated breathing (pranayama) practices viz. (i) Left nostril breathing (LNB), (ii) Right nostril breathing (RNB); and (iii) Alternating nostril breathing (ANB) and compared with normal breathing as baseline (BS). For this, we used 64 channel NIRS system covering left and the right prefrontal cortex. The normal breathing kept as baseline (BS) measures as regressors in the investigation of hemodynamic responses when compared with LNB, RNB and ANB. In the results, we found greater oxygenation in contralateral side i.e., higher activation on the left prefrontal cortex (lPFC) during RNB, and right prefrontal cortex (rPFC) during LNB, whereas ANB showed greater deoxygenation responses on both sides of PFC. Interestingly, LNB showed increased oxygenation on ipsilateral side i.e., lPFC but not during RNB. This suggests that voluntary regulated breathing produced an immediate effect not only on contralateral but ipsilateral sides of the brain as well. In conclusion, breathing practices are tightly coupled to cerebral rhythms of alternating cerebral hemispheric activity during particular nostril breathing. These results of the specific nostril breathing do not support previous findings of contralateral hemispheric improvement while left or right nostril breathing only.

Keywords: hemodynamic responses, brain, pranayama, voluntary regulated breathing practices, prefrontal cortex

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Authors: Tamara Romero, Manuel Romero-Huelva, Jose V. Segarra, Jose Castro, Carlos Fernandez

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Many foods resulting from processing and manufacturing end up as waste, most of which is burned, dumped into landfills or used as compost, which leads to wasted resources, and environmental problems due to unsuitable disposal. Using residues of the crop and food processing industries to feed livestock has the advantage to obviating the need for costly waste management programs. The main residue generated in citrus cultivations and rice crop are pruning waste and rice straw, respectively. Within Spain, the Valencian Community is one of the world's oldest citrus and rice production areas. The objective of this experiment found out the effects of including orange leaves and rice straw as ingredients in the concentrate diets of goats, on milk production and methane (CH₄) emissions. Ten Murciano-Granadina dairy goats (45 kg of body weight, on average) in mid-lactation were selected in a crossover design experiment, where each goat received two treatments in 2 periods. Both groups were fed with 1.7 kg pelleted mixed ration; one group (n= 5) was a control (C) and the other group (n= 5) used orange leaves and rice straw (OR). The forage was alfalfa hay, and it was the same for the two groups (1 kg of alfalfa was offered by goat and day). The diets employed to achieve the requirements during lactation period for caprine livestock. The goats were allocated to individual metabolism cages. After 14 days of adaptation, feed intake and milk yield were recorded daily over a 5 days period. Physico-chemical parameters and somatic cell count in milk samples were determined. Then, gas exchange measurements were recorded individually by an open-circuit indirect calorimetry system using a head box. The data were analyzed by mixed model with diet and digestibility as fixed effect and goat as random effect. No differences were found for dry matter intake (2.23 kg/d, on average). Higher milk yield was found for C diet than OR (2.3 vs. 2.1 kg/goat and day, respectively) and, greater milk fat content was observed for OR than C (6.5 vs. 5.5%, respectively). The cheese extract was also greater in OR than C (10.7 vs. 9.6%). Goats fed OR diet produced significantly fewer CH₄ emissions than C diet (27 vs. 30 g/d, respectively). These preliminary results (LIFE Project LOWCARBON FEED LIFE/CCM/ES/000088) suggested that the use of these waste by-products was effective in reducing CH₄ emission without detrimental effect on milk yield.

Keywords: agricultural waste, goat, milk production, methane emission

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Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

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Authors: Surabhi Agrawal Kohli, Sunita Gupta, Esha Khanuja, Parul Garg, P. Gupta

Abstract:

Background: Adenomyosis is a common gynaecological condition that affects the menstruating women. Uterine enlargement, dysmenorrhoea, and menorrhagia are regarded as the cardinal clinical symptoms of adenomyosis. Classically it was thought, compared with ultrasonography, when adenomyosis is suspected, MRI enables more accurate diagnosis of the disease. Materials and Methods: 172 subjects were enrolled after an informed consent that had complaints of HMB, dyspareunia, dysmenorrhea, and chronic pelvic pain. Detailed history of the enrolled subjects was taken, followed by a clinical examination. These patients were then subjected to TVS where myometrial echo texture, presence of myometrial cysts, blurring of endomyometrial junction was noted. MRI was followed which noted the presence of junctional zone thickness and myometrial cysts. After hysterectomy, histopathological diagnosis was obtained. Results: 78 participants were analysed. The mean age was 44.2 years. 43.5% had parity of 4 or more. heavy menstrual bleeding (HMB) was present in 97.8% and dysmenorrhea in 93.48 % of HPE positive patient. Transvaginal sonography (TVS) and MRI had a sensitivity of 89.13% and 80.43%, specificity of 90.62% and 84.37%, positive likelihood ratio of 9.51 and 5.15, negative likelihood ratio of 0.12 and 0.23, positive predictive value of 93.18% and 88.1%, negative predictive value of 85.29% and 75% and a diagnostic accuracy of 89.74% and 82.5%. Comparison of sensitivity (p=0.289) and specificity (p=0.625) showed no statistically significant difference between TVS and MRI. Conclusion: Prevalence of 30.23%. HMB with dysmenorrhoea and chronic pelvic pain helps in diagnosis. TVS (Endomyometrial junction blurring) is both sensitive and specific in diagnosing adenomyosis without need for additional diagnostic tool. Both TVS and MRI are equally efficient, however because of certain additional advantages of TVS over MRI, it may be used as the first choice of imaging. MRI may be used additionally in difficult cases as well as in patients with existing co-pathologies.

Keywords: adenomyosis, heavy menstrual bleeding, MRI, TVS

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Authors: Tayab D. Memon, Shahji Farooque, Marvi Deshi, Imtiaz Hussain Kalwar, B. S. Chowdhry

Abstract:

Recently single-bit ternary FIR-like filter (SBTFF) hardware synthesize in FPGA is reported and compared with multi-bit FIR filter on similar spectral characteristics. Results shows that SBTFF dominates upon multi-bit filter overall. In this paper, an optimized adder module for ternary quantized sigma-delta modulated signal is presented. The adder is simulated using ModelSim for functional verification the area-performance of the proposed adder were obtained through synthesis in Xilinx and compared to conventional adder trees. The synthesis results show that the proposed adder tree achieves higher clock rates and lower chip area at higher inputs to the adder block; whereas conventional adder tree achieves better performance and lower chip area at lower number of inputs to the same adder block. These results enhance the usefulness of existing short word length DSP algorithms for fast and efficient mobile communication.

Keywords: short word length (SWL), DSP algorithms, FPGA, SBTFF, VHDL

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Authors: Punnoose A. K.

Abstract:

This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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Authors: Amel M. A. Osman, Roy Mahony, Lisa Dann, McKenna S.

Abstract:

Background: Computed Tomography (CT) is a significant source of radiation in the pediatric population. A new head injury (HI) pathway was introduced in 2021, which altered the previous process of HI being jointly admitted with general pediatrics and surgery to admit these patients under the Emergency Medicine Team. Admitted patients included those with positive CT findings not requiring immediate neurosurgical intervention and those who did not meet current criteria for urgent CT brain as per NICE guidelines but were still symptomatic for prolonged observations. This approach aims to decrease the number of CT scans performed. The main aim is to assess the variation in CT scanning rates since the change in the admitting process. A retrospective review of patients presenting to CHI PECU with HI over 6-month period (01/01/19-31/05/19) compared to a 6-month period post introduction of the new pathway (01/06/2022-31/12/2022). Data was collected from the electronic record databases, symphony, and PACS. Results: In 2019, there were 869 presentations of HI, among which 32 (3.68%) had CT scans performed. 2 (6.25%) of those scanned had positive findings. In 2022, there were 1122 HI presentations, with 47 (4.19%) CT scans performed and positive findings in 5 (10.6%) cases. 57 patients were admitted under the new pathway for observation, with 1 having a CT scan following admission. Conclusion: Quantitative lifetime radiation risks for children are not negligible. While there was no statistically significant reduction in CTs performed amongst HIs presenting to our department, a significant group met the criteria for admission under the PECU consultant for prolonged monitoring. There was also a greater proportion of abnormalities on CT scans performed in 2022, demonstrating improved patient selection for imaging. Further data analysis is ongoing to determine if those who were admitted would have previously been scanned under the old pathway.

Keywords: head injury, CT, admission, guidline

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