Analytical solution proposal for fast numerical algorithm in special structured higher order differential equations

We suggest a practical method for obtaining the particular solution of non-homogeneous higher order linear differential equations with constant coefficients. The proposed method can be applied directly and simply to such problems. We revealed that is valid for the different type of problem by using sample solutions. This simple analytical solution that we have introduced will help to create a fast numerical algorithm for computers and thus simplify the numerical solutions of higher order physical problems.Peer Reviewe

PENALARAN BERBASIS KASUS UNTUK MENDIAGNOSA PENYAKIT INFEKSI MENULAR SEKSUAL (IMS) MENGGUNAKAN ALGORITMA WEIGHTED EUCLIDEAN DISTANCE

Case-based reasoning is a methodology for solving problems by utilizing previous experience. In this study the authors apply case-based reasoning to diagnose sexually transmitted infection using the weighted Euclidean distance method. Source of the knowledge base was obtained by collecting medical record of patients with sexually transmitted infections in 2016-2017. The process of finding a solution starts with eliminating irrelevant data using the C4.5 method and continues with the calculation of the similarity value using the Weighted Euclidean Distance algorithm. This system can diagnose 5 types of sexually transmitted infections based on 123 existing symptoms. System result in the form of sexually transmitted infections based on symptoms experienced by the patient, treatment solution and presentation of similarities between new cases and old cases. Based on the result of testing with 127 cases of sexually transmitted infections obtained result: testing uses the K-Fold Cross Validation scenario, the total data is divided into 10fold and the testing process is divided into 2 parts, namely testing using indexing and testing without using indexing. For testing using the highest accuracy indexing obtained at 90.84% in the second fold, and the average accuracy of the entire fold is 88.55% with the average time generated 9498 ms (millisecond), while testing without using the highest accuracy indexing obtained by 63.03% in the second fold, and the average accuracy of the entire fold is 53.48% with the average time generated 9975 ms (millisecond).  Penalaran Berbasis Kasus adalah sebuah metedologi untuk penyelesaian masalah dengan memanfaatkan pengalaman sebelumnya. Pada penelitian ini penulis menerapkan penalaran berbasis kasus untuk mendiagnosa penyakit infeksi menular seksual menggunakan metode weighted euclidean distance. Sumber basis pengetahuan diperoleh dengan mengumpulkan berkas rekam medis pasien penyakit infeksi menular seksual pada tahun 2016-2017. Proses pencarian solusi dimulai dengan mengeliminasi data yang tidak relevan menggunakan C4.5 dan berlanjut dengan perhitungan nilai kemiripan menggunakan algoritma weighted euclidean distance. Sistem ini dapat mendiagnosis 5 jenis penyakit infeksi menular seksual berdasarkan 123 gejala yang ada. Hasil sistem berupa jenis penyakit infeksi menular seksual berdasarkan gejala yang dialami pasien, solusi pengobatan dan presentasi kemiripan kasus baru dengan kasus lama. Berdasarkan hasil pengujian dengan 127 kasus infeksi menular seksual (IMS) didapatkan hasil: Pengujian menggunakan skenario K-Fold Cross Validation, total data dibagi menjadi 10 fold dan proses pengujian dibagi menjadi 2 bagian yaitu pengujian menggunakan indexing dan pengujian tanpa menggunakan indexing. Untuk pengujian menggunakan indexing akurasi tertinggi yang didapat sebesar 90.84% pada fold ke-2, dan rata-rata akurasi dari keseluruhan fold adalah sebesar 88.55% dengan rata-rata waktu yang dihasillkan 9498 ms (milidetik) sedangkan pengujian tanpa menggunakan indexing akurasi tertinggi yang didapat sebesar 63.03% pada fold ke-2, dan rata-rata akurasi dari keseluruhan fold adalah sebesar 53.48% dengan rata-rata waktu yang dihasilkan 9975 ms (milidetik). &nbsp

Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network

SDF1 in the dorsal corticospinal tract promotes CXCR4+ cell migration after spinal cord injury

<p>Abstract</p> <p>Background</p> <p>Stromal cell-derived factor-1 (SDF1) and its major signaling receptor, CXCR4, were initially described in the immune system; however, they are also expressed in the nervous system, including the spinal cord. After spinal cord injury, the blood brain barrier is compromised, opening the way for chemokine signaling between these two systems. These experiments clarified prior contradictory findings on normal expression of SDF1 and CXCR4 as well as examined the resulting spinal cord responses resulting from this signaling.</p> <p>Methods</p> <p>These experiments examined the expression and function of SDF1 and CXCR4 in the normal and injured adult mouse spinal cord primarily using CXCR4-EGFP and SDF1-EGFP transgenic reporter mice.</p> <p>Results</p> <p>In the uninjured spinal cord, SDF1 was expressed in the dorsal corticospinal tract (dCST) as well as the meninges, whereas CXCR4 was found only in ependymal cells surrounding the central canal. After spinal cord injury (SCI), the pattern of SDF1 expression did not change rostral to the lesion but it disappeared from the degenerating dCST caudally. By contrast, CXCR4 expression changed dramatically after SCI. In addition to the CXCR4+ cells in the ependymal layer, numerous CXCR4+ cells appeared in the peripheral white matter and in the dorsal white matter localized between the dorsal corticospinal tract and the gray matter rostral to the lesion site. The non-ependymal CXCR4+ cells were found to be NG2+ and CD11b+ macrophages that presumably infiltrated through the broken blood-brain barrier. One population of macrophages appeared to be migrating towards the dCST that contains SDF1 rostral to the injury but not towards the caudal dCST in which SDF1 is no longer present. A second population of the CXCR4+ macrophages was present near the SDF1-expressing meningeal cells.</p> <p>Conclusions</p> <p>These observations suggest that attraction of CXCR4+ macrophages is part of a programmed response to injury and that modulation of the SDF1 signaling system may be important for regulating the inflammatory response after SCI.</p

Sparsity-based single-shot sub-wavelength coherent diffractive imaging

We present the experimental reconstruction of sub-wavelength features from the far-field intensity of sparse optical objects: sparsity-based sub-wavelength imaging combined with phase-retrieval. As examples, we demonstrate the recovery of random and ordered arrangements of 100 nm features with the resolution of 30 nm, with an illuminating wavelength of 532 nm. Our algorithmic technique relies on minimizing the number of degrees of freedom; it works in real-time, requires no scanning, and can be implemented in all existing microscopes - optical and non-optical

Visualizing Escherichia coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Tomography

Studying the 3D sub-cellular structure of living cells is essential to our understanding of biological function. However, tomographic imaging of live cells is challenging mainly because they are transparent, i.e., weakly scattering structures. Therefore, this type of imaging has been implemented largely using fluorescence techniques. While confocal fluorescence imaging is a common approach to achieve sectioning, it requires fluorescence probes that are often harmful to the living specimen. On the other hand, by using the intrinsic contrast of the structures it is possible to study living cells in a non-invasive manner. One method that provides high-resolution quantitative information about nanoscale structures is a broadband interferometric technique known as Spatial Light Interference Microscopy (SLIM). In addition to rendering quantitative phase information, when combined with a high numerical aperture objective, SLIM also provides excellent depth sectioning capabilities. However, like in all linear optical systems, SLIM's resolution is limited by diffraction. Here we present a novel 3D field deconvolution algorithm that exploits the sparsity of phase images and renders images with resolution beyond the diffraction limit. We employ this label-free method, called deconvolution Spatial Light Interference Tomography (dSLIT), to visualize coiled sub-cellular structures in E. coli cells which are most likely the cytoskeletal MreB protein and the division site regulating MinCDE proteins. Previously these structures have only been observed using specialized strains and plasmids and fluorescence techniques. Our results indicate that dSLIT can be employed to study such structures in a practical and non-invasive manner

Nonlinear Time Series Analysis of Nodulation Factor Induced Calcium Oscillations: Evidence for Deterministic Chaos?

Legume plants form beneficial symbiotic interactions with nitrogen fixing bacteria (called rhizobia), with the rhizobia being accommodated in unique structures on the roots of the host plant. The legume/rhizobial symbiosis is responsible for a significant proportion of the global biologically available nitrogen. The initiation of this symbiosis is governed by a characteristic calcium oscillation within the plant root hair cells and this signal is activated by the rhizobia. Recent analyses on calcium time series data have suggested that stochastic effects have a large role to play in defining the nature of the oscillations. The use of multiple nonlinear time series techniques, however, suggests an alternative interpretation, namely deterministic chaos. We provide an extensive, nonlinear time series analysis on the nature of this calcium oscillation response. We build up evidence through a series of techniques that test for determinism, quantify linear and nonlinear components, and measure the local divergence of the system. Chaos is common in nature and it seems plausible that properties of chaotic dynamics might be exploited by biological systems to control processes within the cell. Systems possessing chaotic control mechanisms are more robust in the sense that the enhanced flexibility allows more rapid response to environmental changes with less energetic costs. The desired behaviour could be most efficiently targeted in this manner, supporting some intriguing speculations about nonlinear mechanisms in biological signaling