Only in the earth

In only a few short years, multimedia has become powerful and accepted enough to begin taking its rightful place in the changing the way we communicate. Communication in the \u2790s must accomplish two fundamental tasks: satiating the demanding aesthetic tastes and expectations of today\u27s sophisticated viewing audiences, and navigating the vast amount of knowledge, facts, and statistics that comprise the Information Age. Multimedia allows us to use the best combination of media to present com pelling information suited to specific situations. It allows user-control over how and when that information is accessed. Only In The Earth is the ultimate multimedia reference source for students, teachers, researchers, journalists... anyone who want instant information on recent social problems such as wars, drugs, crimes, AIDS, starvation, racism. I hope to show various images and information of contemporary society which comes alive in multimedia reference form available anywhere. My thesis is about harnessing the technology of the present and building toward the future. We now stand at an incredible time in the history of information and human communication. This interactive product will be controlled by Macromedia Director. All video images will be converted into Adobe Premiere. Any retouching will be done in Adobe photoshop

Potential role and mechanism of IFN-gamma inducible protein-10 on receptor activator of nuclear factor kappa-B ligand (RANKL) expression in rheumatoid arthritis

Introduction IFN-gamma inducible protein-10 (CXCL10), a member of the CXC chemokine family, and its receptor CXCR3 contribute to the recruitment of T cells from the blood stream into the inflamed joints and have a crucial role in perpetuating inflammation in rheumatoid arthritis (RA) synovial joints. Recently we showed the role of CXCL10 on receptor activator of nuclear factor kappa-B ligand (RANKL) expression in an animal model of RA and suggested the contribution to osteoclastogenesis. We tested the effects of CXCL10 on the expression of RANKL in RA synoviocytes and T cells, and we investigated which subunit of CXCR3 contributes to RANKL expression by CXCL10. Methods Synoviocytes derived from RA patients were kept in culture for 24 hours in the presence or absence of TNF-α. CXCL10 expression was measured by reverse transcriptase polymerase chain reaction (RT-PCR) of cultured synoviocytes. Expression of RANKL was measured by RT-PCR and western blot in cultured synoviocytes with or without CXCL10 and also measured in Jurkat/Hut 78 T cells and CD4+ T cells in the presence of CXCL10 or dexamethasone. CXCL10 induced RANKL expression in Jurkat T cells was tested upon the pertussis toxin (PTX), an inhibitor of Gi subunit of G protein coupled receptor (GPCR). The synthetic siRNA for Gαi2 was used to knock down gene expression of respective proteins. Results CXCL10 expression in RA synoviocytes was increased by TNF-α. CXCL10 slightly increased RANKL expression in RA synoviocytes, but markedly increased RANKL expression in Jurkat/Hut 78 T cell or CD4+ T cell. CXCL10 augmented the expression of RANKL by 62.6%, and PTX inhibited both basal level of RANKL (from 37.4 ± 16.0 to 18.9 ± 13.0%) and CXCL10-induced RANKL expression in Jurkat T cells (from 100% to 48.6 ± 27.3%). Knock down of Gαi2 by siRNA transfection, which suppressed the basal level of RANKL (from 61.8 ± 17.9% to 31.1 ± 15.9%) and CXCL10-induced RANKL expression (from 100% to 53.1 ± 27.1%) in Jurkat T cells, is consistent with PTX, which inhibited RANKL expression. Conclusions CXCL10 increased RANKL expression in CD4+ T cells and it was mediated by Gαi subunits of CXCR3. These results indicate that CXCL10 may have a potential role in osteoclastogenesis of RA synovial tissue and subsequent joint erosion

Accelerating HE Operations from Key Decomposition Technique

Lattice-based homomorphic encryption (HE) schemes are based on the noisy encryption technique, where plaintexts are masked with some random noise for security. Recent advanced HE schemes rely on a decomposition technique to manage the growth of noise, which involves a conversion of a ciphertext entry into a short vector followed by multiplication with an evaluation key. Prior to this work, the decomposition procedure turns out to be the most time-consuming part, as it requires discrete Fourier transforms (DFTs) over the base ring for efficient polynomial arithmetic. In this paper, an expensive decomposition operation over a large modulus is replaced with relatively cheap operations over a ring of integers with a small bound. Notably, the cost of DFTs is reduced from quadratic to linear with the level of a ciphertext without any extra noise growth. We demonstrate the implication of our approach by applying it to the key-switching procedure. Our experiments show that the new key-switching method achieves a speedup of 1.2--2.3 or 2.1--3.3 times over the previous method, when the dimension of a base ring is $2^{15}$ or $2^{16}$, respectively

A Generalized Framework for Video Instance Segmentation

The handling of long videos with complex and occluded sequences has recently emerged as a new challenge in the video instance segmentation (VIS) community. However, existing methods have limitations in addressing this challenge. We argue that the biggest bottleneck in current approaches is the discrepancy between training and inference. To effectively bridge this gap, we propose a Generalized framework for VIS, namely GenVIS, that achieves state-of-the-art performance on challenging benchmarks without designing complicated architectures or requiring extra post-processing. The key contribution of GenVIS is the learning strategy, which includes a query-based training pipeline for sequential learning with a novel target label assignment. Additionally, we introduce a memory that effectively acquires information from previous states. Thanks to the new perspective, which focuses on building relationships between separate frames or clips, GenVIS can be flexibly executed in both online and semi-online manner. We evaluate our approach on popular VIS benchmarks, achieving state-of-the-art results on YouTube-VIS 2019/2021/2022 and Occluded VIS (OVIS). Notably, we greatly outperform the state-of-the-art on the long VIS benchmark (OVIS), improving 5.6 AP with ResNet-50 backbone. Code is available at https://github.com/miranheo/GenVIS.Comment: CVPR 202

Logistic regression model training based on the approximate homomorphic encryption

Background: Security concerns have been raised since big data became a prominent tool in data analysis. For instance, many machine learning algorithms aim to generate prediction models using training data which contain sensitive information about individuals. Cryptography community is considering secure computation as a solution for privacy protection. In particular, practical requirements have triggered research on the efficiency of cryptographic primitives. Methods: This paper presents a method to train a logistic regression model without information leakage. We apply the homomorphic encryption scheme of Cheon et al. (ASIACRYPT 2017) for an efficient arithmetic over real numbers, and devise a new encoding method to reduce storage of encrypted database. In addition, we adapt Nesterov's accelerated gradient method to reduce the number of iterations as well as the computational cost while maintaining the quality of an output classifier. Results: Our method shows a state-of-the-art performance of homomorphic encryption system in a real-world application. The submission based on this work was selected as the best solution of Track 3 at iDASH privacy and security competition 2017. For example, it took about six minutes to obtain a logistic regression model given the dataset consisting of 1579 samples, each of which has 18 features with a binary outcome variable. Conclusions: We present a practical solution for outsourcing analysis tools such as logistic regression analysis while preserving the data confidentiality

Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome

Objective This study aimed to analyze intracranial vessels using brain computed tomography angiography (CTA) and scoring systems to diagnose brain death and predict poor neurologic outcomes of postcardiac arrest patients. Methods Initial brain CTA images of postcardiac arrest patients were analyzed using scoring systems to determine a lack of opacification and diagnose brain death. The primary outcome was poor neurologic outcome, which was defined as cerebral performance category score 3 to 5. The frequency, sensitivity, specificity, positive predictive value, negative predictive value, and area under receiver operating characteristic curve for the lack of opacification of each vessel and for each scoring system used to predict poor neurologic outcomes were determined. Results Patients with poor neurologic outcomes lacked opacification of the intracranial vessels, most commonly in the vein of Galen, both internal cerebral veins, and the mid cerebral artery (M4). The 7-score results (P=0.04) and 10-score results were significantly different (P=0.04) between outcome groups, with an area under receiver operating characteristic of 0.61 (range, 0.48 to 0.72). The lack of opacification of each intracranial vessel and all scoring systems exhibited high specificity (100%) and positive predictive values (100%) for predicting poor neurologic outcomes. Conclusion Lack of opacification of vessels on brain CTA exhibited high specificity for predicting poor neurologic outcomes of patients after cardiac arrest

Optimal sizing and technical assessment of a hybrid renewable energy solution for off-grid community center power

Decentralized energy generation systems based on renewable sources have significant potential to assist in the sustainable development of developing countries. The small-scale integration of hybrid renewable energy systems in off-grid communities has not been thoroughly researched. The primary objective is to develop a preliminary design for a PV/biogas hybrid system that can meet the energy needs of an off-grid community center. A survey was conducted to calculate the energy demands of an off-grid community center and a hybrid renewable system has been designed to supply the electricity. The optimum designed system is evaluated by the PVSYST simulation software and SuperPro Designer software. The annual production of the PV system is 34428 kWh/year, specific production is 1118 kWh/kWp/year, and the performance ratio is 81.72%. All the factors that contribute to energy loss are considered in designing a PV system. The average operating efficiency of the inverter is 92.6%, and global inverter losses are 2752.4 kWh. The biogas simulation findings show an adequate match with the composition of conventional biogas and contains 89.64% methane and 5.99% carbon dioxide content. Two sensitivity analyses of biogas based on hydraulic retention time and moisture content have been performed. Measurements readings of hourly data are used to analyse the performance of PV, biogas system as well as the hybrid system performance. At day time, the maximum power generation of the hybrid PV/Biogas and the maximum load demand of the community at that time are 25.2 kW and 24.31 kW, respectively. At night time, the maximum power generation of the hybrid system and the maximum load demand are 9 kW and 8.3 kW, respectively. The power factor (PF) of the system fluctuates between 0.92 and 0.98 and the frequency of the system is constant at 50 HZ

Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data

Various impedance-based and nonlinear frequency response-based methods for determining the state-of-health (SOH) of commercial lithium-ion cells are evaluated. Frequency response-based measurements provide a spectral representation of dynamics of underlying physicochemical processes in the cell, giving evidence about its internal physical state. The investigated methods can be carried out more rapidly than controlled full discharge and thus constitute prospectively more efficient measurement procedures to determine the SOH of aged lithium-ion cells. We systematically investigate direct use of electrochemical impedance spectroscopy (EIS) data, equivalent circuit fits to EIS, distribution of relaxation times analysis on EIS, and nonlinear frequency response analysis. SOH prediction models are developed by correlating key parameters of each method with conventional capacity measurement (i.e., current integration). The practical feasibility, reliability and uncertainty of each of the established SOH models are considered: all models show average RMS error in the range 0.75%–1.5% SOH units, attributable principally to cell-to-cell variation. Methods based on processed data (equivalent circuit, distribution of relaxation times) are more experimentally and numerically demanding but show lower average uncertainties and may offer more flexibility for future application