The effect of sampling in histogramming and analytical reconstruction of 3d AX-PET data

Improvement in both sensitivity and resolution is achieved by the novel AX-PET concept. This design incorporates axial orientation of long crystal (for coincident detection radially) and orthogonally placed wave length shifter strips (for axial detection). Iterative reconstruction of AX-PET list-mode data was performed by the AX-PET collaboration. But this reconstruction takes long processing time due to large dataset and complexity of algorithm. On the contrary, 3D Reprojection (3DRP) is an analytical image reconstruction technique which can be used to reconstruct the 3D list-mode data of two modules AX-PET demonstrator in shorter time. In this study, 3DRP method is used for image reconstruction. This process requires histogramming and histogramming requires sampling of the coincident events. Obtaining optimum sampling for better resolution is one of the main goals in the image processing. PET scanner acquires data both in axial and radial direction. Hence, optimum sampling rates for axial, radial and angular directions are required. In this study, histogramming is done with different sampling rates to see their effect in the resolution of the reconstructed images. The construction of the scanner causes gaps and non-homogeneously sampled Filled of View (FOV). Gap filling method fill the gaps generated from inter crystal and inter module gaps. Coincident detection differs due to difference of the positions of crystals. Normalization is required to have the uniform response from all the detectors. In this study normalization and gap filling were used before 3DRP reconstruction. Preliminary result shows the ability of resolving the capillary of 1.4 mm. But for the complex phantoms the smallest resolvable inserts was 2 mm. The best results were obtained with the sampling rate of 1mm compared to other sampling rates for different phantoms due to better statistics. The list-mode data of the phantoms used in this study is a low statistics data. To exploit the novelty of AX-PET, high statistics data incorporating more counts is required. /Kir1

A unifying co-operative web caching architecture

Network caching of objects has become a standard way of reducing network traffic and latency in the web. However, web caches exhibit poor performance with a hit rate of about 30%. A solution to improve this hit rate is to have a group of proxies form co-operation where objects can be cached for later retrieval. A co-operative cache system includes protocols for hierarchical and transversal caching. The drawback of such a system lies in the resulting network load due to the number of messages that need to be exchanged to locate an object. This paper proposes a new co-operative web caching architecture, which unifies previous methods of web caching. Performance results shows that the architecture achieve up to 70% co-operative hit rate and accesses the cached object in at most two hops. Moreover, the architecture is scalable with low traffic and database overhead

Data on Growth, survivability, water quality and hemato-biochemical indices of Nile Tilapia (Oreochromis niloticus) fry fed with selected marine microalgae

Data of this article describes growth, survival rate, water quality and hemato-biochemical indices of Nile Tilapia (Oreochromis niloticus) fry. To collect the data, the Nile Tilapia fry was reared in 30 L glass aquarium (18 fish/ tank) for 56-days under controlled environmental condition. Feed was prepared with 25 and 50% replacement of commercial fish meal with Nannochloropsis sp. and Tetraselmis sp. microalgae, while no replacement was made for control feed. Initial and final body weight of fish was recorded to find the data of growth rate; survival rate was calculated from the initial and final live individuals recorded during the experiment; physico-chemical parameters were analyzed to collect water quality data; hemato-biochemical indices were collected using hematology analyzer and photometry. The data on growth, survival rate and hemato-biochemical indices were statistically significant (p < 0.05). Therefore, these data might contribute to the selection of marine microalgae to improve the water quality during fish farming which could enhance the growth and survivability of fish. In addition, the data of hemato-biochemical indices represent that feeding selected marine microalgae might result in the production of healthy and disease-free fish

Huruf: An Application for Arabic Handwritten Character Recognition Using Deep Learning

Handwriting Recognition has been a field of great interest in the Artificial Intelligence domain. Due to its broad use cases in real life, research has been conducted widely on it. Prominent work has been done in this field focusing mainly on Latin characters. However, the domain of Arabic handwritten character recognition is still relatively unexplored. The inherent cursive nature of the Arabic characters and variations in writing styles across individuals makes the task even more challenging. We identified some probable reasons behind this and proposed a lightweight Convolutional Neural Network-based architecture for recognizing Arabic characters and digits. The proposed pipeline consists of a total of 18 layers containing four layers each for convolution, pooling, batch normalization, dropout, and finally one Global average pooling and a Dense layer. Furthermore, we thoroughly investigated the different choices of hyperparameters such as the choice of the optimizer, kernel initializer, activation function, etc. Evaluating the proposed architecture on the publicly available 'Arabic Handwritten Character Dataset (AHCD)' and 'Modified Arabic handwritten digits Database (MadBase)' datasets, the proposed model respectively achieved an accuracy of 96.93% and 99.35% which is comparable to the state-of-the-art and makes it a suitable solution for real-life end-level applications.Comment: Accepted in 25th ICCIT (6 pages, 4 tables, 4 figures

Electrochemiluminescence nanoimmunosensor for CD63 protein using a carbon nanochips/iron oxide/nafion-nanocomposite modified mesoporous carbon interface

The detection of extracellular vesicles, or exosomes are important mediators in intercellular communication and often play a role in cancer progression. CD63 is a key exosomal protein due to its distinctive cellular functions and association with many cancers. This describes a label-free electrochemiluminescence (ECL) nanoimmunosensor for the detection of CD63 protein over mesoporous carbon screen-printed electrode (MC-SPE) modified with novel nanocomposite of carbon nanochips (CNCs), iron oxide (Fe3O4) and nafion (NAF) . Fourier-transform infrared spectroscopy and field emission scanning electron microscopy were used to analyse nanocomposite. All the analytical performance of fabricated CD63 immunosensor were conducted applying ECL. In spite of the simple fabrication strategies utilized, the fabricated immunosensor showcased a broad linear range to detect CD63 from 100 fg mL-1 to 10 ng mL-1, with a limit of detection of 100 fg mL-1, excellent selectivity, interference-resistance capability and potential to detect CD63 in real clinical samples

Recent advancement in sensitive detection of carcinoembryonic antigen using nanomaterials based immunosensors

Carcinoembryonic antigen (CEA) is a prominent cancer biomarker that allows for early diagnosis of various cancers. Present immunoassays techniques help quantify such target molecules in test samples via anti-antibody reaction. Despite their rapid usage, conventional immunoassay techniques demonstrate several limitations that can be easily overcome by employing nanomaterials in sensing assays. Thus, nanomaterial-based immunosensors have gained steady attention from the scientific community owing to their high specificity and low detection limit. Various nanomaterials like platinum, gold, silver and carbon exhibit exceptional properties have allowed promising results in the detection and diagnostics of CEA. Thus, the present review aims to explore the significance and the recent developments of nanomaterial-based biosensors for detecting CEA biomarkers with high sensitivity, selectivity, and specificity. After a brief introduction, we discussed the fundamentals of immunosensors immobilization strategies and common nanomaterials. In the next section, we highlighted the recent advances in the common immunosensors detection approaches for CEA alone and simultaneous detection of CEA with other biomarkers detection. Finally, we concluded the review by discussing the future perspectives of this promising field of biomarkers detection

Comparison of CMIP6 and CMIP5 model performance in simulating historical precipitation and temperature in Bangladesh: a preliminary study

The relative performance of global climate models (GCMs) of phases 5 and 6 of the coupled model intercomparison project (CMIP5 and CMIP6, respectively) was assessed in this study based on their ability to simulate annual and seasonal mean rainfall and temperature over Bangladesh for the period 1977–2005. Multiple statistical metrics were used to measure the performance of the GCMs at 30 meteorological observation stations. Two robust multi-criteria decision analysis methods were used to integrate the results obtained using different metrics for an unbiased ranking of the GCMs. The results revealed MIROC5 as the most skillful among CMIP5 GCMs and ACCESS-CM2 among CMIP6 GCMs. Overall, CMIP6 MME showed a significant improvement in simulating rainfall and temperature over Bangladesh compared to CMIP5 MME. The highest improvements were found in simulating cold season (winter and post-monsoon) rainfall and temperature in higher elevated areas. The improvement was relatively more for rainfall than for temperature. The models could capture the interannual variability of annual and seasonal rainfall and temperature reliably, except for the winter rainfall. However, systematic wet and cold/warm biases still exist in CMIP6 models for Bangladesh. CMIP6 GCMs showed higher spatial correlations with observed data, but the higher difference in standard deviations and centered root mean square errors compared to CMIP5 GCMs indicates better performance in simulating geographical distribution but lower performance in simulating spatial variability of most of the climate variables except for minimum temperature at different timescales. In terms of Taylor skill score, the CMIP6 MME showed higher performance in simulating rainfall but lower performance in simulating temperature than CMIP5 MME for most of the timeframes. The findings of this study suggest that the added value of rainfall and temperature simulations in CMIP6 models is not consistent among the climate models used in this research. However, it sets a precedent for future research on climate change risk assessment for the scientific community

The effect of sampling in histogramming and analytical reconstruction of 3d AX-PET data

Improvement in both sensitivity and resolution is achieved by the novel AX-PET concept. This design incorporates axial orientation of long crystal (for coincident detection radially) and orthogonally placed wave length shifter strips (for axial detection). Iterative reconstruction of AX-PET list-mode data was performed by the AX-PET collaboration. But this reconstruction takes long processing time due to large dataset and complexity of algorithm. On the contrary, 3D Reprojection (3DRP) is an analytical image reconstruction technique which can be used to reconstruct the 3D list-mode data of two modules AX-PET demonstrator in shorter time. In this study, 3DRP method is used for image reconstruction. This process requires histogramming and histogramming requires sampling of the coincident events. Obtaining optimum sampling for better resolution is one of the main goals in the image processing. PET scanner acquires data both in axial and radial direction. Hence, optimum sampling rates for axial, radial and angular directions are required. In this study, histogramming is done with different sampling rates to see their effect in the resolution of the reconstructed images. The construction of the scanner causes gaps and non-homogeneously sampled Filled of View (FOV). Gap filling method fill the gaps generated from inter crystal and inter module gaps. Coincident detection differs due to difference of the positions of crystals. Normalization is required to have the uniform response from all the detectors. In this study normalization and gap filling were used before 3DRP reconstruction. Preliminary result shows the ability of resolving the capillary of 1.4 mm. But for the complex phantoms the smallest resolvable inserts was 2 mm. The best results were obtained with the sampling rate of 1mm compared to other sampling rates for different phantoms due to better statistics. The list-mode data of the phantoms used in this study is a low statistics data. To exploit the novelty of AX-PET, high statistics data incorporating more counts is required. /Kir1

Enhancing Relaxation on the Go: Exploring the Impact of a Novel Mobile App-Guided Exercises during Commute

Relaxation plays a vital role in enhancing the commute experience. Incorporating exercise into commute routines has been suggested as an effective means to promote relaxation. This study explores the novel concept of utilizing mobile app-guided exercise during the commute to enhance relaxation and its potential impact on overall well-being. This area has yet to be investigated. The particular processes by which travel fosters relaxation have yet to be widely recognized, so there is a need for additional research better to comprehend the psychological and physical benefits of travel relaxation. In this study, we introduced a travel relaxation feature in the Peacify app to address the absence of such features in existing apps. Through a cross-sectional survey, 91 participants from Dhaka city were enlisted between September 2022 and October 2023. Using snowball sampling, participants were recruited via social media and completed an anonymous online questionnaire. The Satisfaction with Travel Scale (STS) measured travel satisfaction and a few demographic questions, while descriptive and chi-square tests analyzed relationships between variables. A Pearson correlation analysis explored the correlation between Travel Relaxation Techniques before and after the intervention. Descriptive statistics for the before and after the intervention indicate a potential positive impact on the participants' satisfaction during travel. Participants preferred mindful breathing (62.6%) and found shoulder rolls (48.4%) as the leading challenge. 71.4% of participants reported that the Peacify travel relaxation techniques were helpful. The results provide empirical support for the efficacy of the intervention in improving participants' overall travel experiences, resulting in a highly significant two-tailed p-value of p&lt;0.001. The Pearson correlation coefficient is 0.266, and the associated p-value is .011. This correlation is statistically significant at the 0.05 level (two-tailed). The study assessed the effectiveness of the mobile app in promoting travel relaxation through physical activities. The results indicated decreased stress levels, an enhanced emotional state, and heightened calmness while travelling. Most participants preferred mindful breathing, although some encountered challenges with shoulder roll exercises. Statistical analysis showed a significant positive correlation between before- and after-intervention responses. The results emphasize the practical utility of apps in enhancing travel relaxation and suggest their potential for promoting well-being in travel contexts