Miracle-dz/UniFAR-FTUs huggingface dataset:
ENERGY AND MOMENTUM DISTRIBUTIONS OF A (2 + 1)-DIMENSIONAL BLACK HOLE BACKGROUND

Using Einstein, Landau–Lifshitz, Papapetrou and Weinberg energy–momentum complexes, we explicitly evaluate the energy and momentum distributions associated with a nonstatic and circularly symmetric three-dimensional space–time. The gravitational background under study is an exact solution of Einstein's equations in the presence of a cosmological constant and a null fluid. It can be regarded as the three-dimensional analogue of the Vaidya metric and represents a nonstatic spinless (2+1)-dimensional black hole with an outflux of null radiation. All four above-mentioned prescriptions give exactly the same energy and momentum distributions for the specific black hole background. Therefore, the results obtained here provide evidence in support of the claim that for a given gravitational background, different energy–momentum complexes can give identical results in three dimensions. Furthermore, in the limit of zero cosmological constant, the results presented here reproduce those obtained by Virbhadra. He utilized the Landau–Lifshitz energy–momentum complex for the same (2+1)-dimensional black hole background in the absence of a cosmological constant.
Assessing uncertainty in model parameters based on sparse and noisy experimental data

To perform parametric identification of mathematical models of biological events, experimental data are rare to be sufficient to estimate target behaviors produced by complex non-linear systems. We performed parameter fitting to a cell cycle model with experimental data as an in silico experiment. We calibrated model parameters with the generalized least squares method with randomized initial values and checked local and global sensitivity of the model. Sensitivity analyses showed that parameter optimization induced less sensitivity except for those related to the metabolism of the transcription factors c-Myc and E2F, which are required to overcome a restriction point (R-point). We performed bifurcation analyses with the optimized parameters and found the bimodality was lost. This result suggests that accumulation of c-Myc and E2F induced dysfunction of R-point. We performed a second parameter optimization based on the results of sensitivity analyses and incorporating additional derived from recent in vivo data. This optimization returned the bimodal characteristics of the model with a narrower range of hysteresis than the original. This result suggests that the optimized model can more easily go through R-point and come back to the gap phase after once having overcome it. Two parameter space analyses showed metabolism of c-Myc is transformed as it can allow cell bimodal behavior with weak stimuli of growth factors. This result is compatible with the character of the cell line used in our experiments. At the same time, Rb, an inhibitor of E2F, can allow cell bimodal behavior with only a limited range of stimuli when it is activated, but with a wider range of stimuli when it is inactive. These results provide two insights; biologically, the two transcription factors play an essential role in malignant cells to overcome R-point with weaker growth factor stimuli, and theoretically, sparse time-course data can be used to change a model to a biologically expected state.
An Efficient Ensemble Based Hierarchical Clustering Algorithm

Clustering is an important data mining technique which play and very important role in many application. In this paper we enhanced hierarchical clustering algorithms like single, complete and average linkage methods by using the concept of cluster ensemble techniques. Single linkage method is based on similarity of two clusters that are most similar (closest) points in the different clusters. Complete linkage method based on similarity of two clusters that are least similar (most distant) points in the different clusters. The complete-linkage clustering methods usually produce more compact clusters and more useful hierarchies than the single- linkage clustering methods, yet the single-link methods are more versatile.
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization

Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating the sensor locations, the speed of the SDP approach is not satisfactory for practical applications. In this paper we propose methods to further relax the SDP relaxation, more precisely, to relax the single semidefinite matrix cone into a set of small-size semidefinite submatrix cones, which we call a sub-SDP (SSDP) approach. We present two such relaxations. Although they are weaker than the original SDP relaxation, they retain the key theoretical property, and numerical experiments show that they are both efficient and accurate. The speed of the SSDP is even faster than that of other approaches based on weaker relaxations. The SSDP approach may also pave a way to efficiently solving general SDP problems without sacrificing the solution quality.
Investigating Satellite Precipitation Uncertainty Over Complex Terrain

The estimation of heavy precipitation events is a particularly difficult task, especially over high mountainous terrain typically associated with scant availability of in situ observations. Therefore, quantification of precipitation variability in such data‐limited regions relies on remote sensing estimates, due to their global coverage and near real‐time availability. However, strong underestimation of precipitation associated with low‐level orographic enhancement often limits the quantitative use of these data in applications. This study utilizes state‐of‐the‐art numerical weather prediction simulations, toward the reduction of quantitative errors in satellite precipitation estimates and an insight on the nature of detection limitations. Satellite precipitation products based on different retrieval algorithms (Climate Prediction Center morphing method, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks‐Cloud Classification System, and Global Satellite Mapping of Precipitation) are evaluated for their performance in a number of storm events over mountainous areas with distinct storm characteristics: Upper Blue Nile in Ethiopia and Alto Adige in NE Italy. High‐resolution (1 and 2 km) simulations from the Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System are used to derive adjustments to the magnitude of satellite estimates. Finally, a microphysical investigation is presented for occurrences of erroneous precipitation detection from the satellite instruments. Statistical indexes showcase improvement in numerical weather prediction‐adjusted satellite products and microphysical commodities among cases of no detection are discussed.
Modulation of Osteoclastogenesis with Macrophage M1- and M2-Inducing Stimuli

Macrophages are generated through the differentiation of monocytes in tissues and they have important functions in innate and adaptive immunity. In addition to their roles as phagocytes, macrophages can be further differentiated, in the presence of receptor activator of nuclear factor kappa-B ligand (RANKL) and macrophage colony-stimulating factor (M-CSF), into osteoclasts (multinucleated giant cells that are responsible for bone resorption). In this work, we set out to characterize whether various inflammatory stimuli, known to induce macrophage polarization, can alter the type of multinucleated giant cell obtained from RANKL differentiation. Following a four-day differentiation protocol, along with lipopolysaccharide (LPS)/interferon gamma (IFNγ) as one stimulus, and interleukin-4 (IL-4) as the other, three types of multinucleated cells were generated. Using various microscopy techniques (bright field, epifluorescence and scanning electron), functional assays, and western blotting for osteoclast markers, we found that, as expected, RANKL treatment alone resulted in osteoclasts, whereas the addition of LPS/IFNγ to RANKL pre-treated macrophages generated Langhans-type giant cells, while IL-4 led to giant cells resembling foreign body giant cells with osteoclast-like characteristics. Finally, to gain insight into the modulation of osteoclastogenesis, we characterized the formation and morphology of RANKL and LPS/IFNγ-induced multinucleated giant cells.
Effect of parameterized sub‐grid‐scale diffusions on the source‐receptor relationship in the WRF model

To provide a quantitative assessment of the source‐receptor relationship in an Eulerian framework, the method of artificially adding oscillatory signals with different frequencies to emission locations for a scalar is evaluated. Two‐dimensional numerical experiments of nonlinear hydrostatic mountain waves with wave breaking were used. The scalar time series were collected at a number of downstream locations and decomposed into frequency space to identify their sources and to investigate the strength of those signals with respect to different diffusion schemes. Six experiments were conducted using three sub‐grid eddy coefficients (a constant, a function of deformation, and a function of turbulence kinetic energy (TKE)) and two environmental wind conditions (shear and no shear). Simulated oscillatory signals were affected by parameterized sub‐grid‐scale diffusions. Signals experiencing more sophisticated eddy coefficients were better preserved than those with the simplest constant ones. The signals were shifted to higher frequencies when using the TKE scheme under a uniform wind environment.
Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights

MOTIVATION Phosphorylation is the most important post-translational modification in eukaryotes. Although many computational phosphorylation site prediction tools exist for mammals, and a few were created specifically for Arabidopsis thaliana, none are currently available for other plants. RESULTS In this article, we propose a novel random forest-based method called PHOSFER (PHOsphorylation Site FindER) for applying phosphorylation data from other organisms to enhance the accuracy of predictions in a target organism. As a test case, PHOSFER is applied to phosphorylation sites in soybean, and we show that it more accurately predicts soybean sites than both the existing Arabidopsis-specific predictors, and a simpler machine-learning scheme that uses only known phosphorylation sites and non-phosphorylation sites from soybean. In addition to soybean, PHOSFER will be extended to other organisms in the near future.
Performance evaluation of 3D-printed ABS and carbon fiber-reinforced ABS polymeric spur gears

Acrylonitrile butadiene styrene (ABS) polymer and carbon fiber reinforced acrylonitrile butadiene styrene (CF/ABS) spur gears were 3D-printed using fusion deposition modeling (FDM) with different fillet radii of 0.25, 0.50, and 0.75 mm. The performance of the fabricated gears was studied with the effect of fillet radius on varying load and speed conditions. The thermal properties of the gears were also investigated. The results indicated that 3D-printed CF/ABS spur gear exhibited better performance than the pure ABS. The 3D-printed CF/ABS gear with fillet radius of 0.25 mm recorded the highest wear and thermal stresses. However, the optimum performance was exhibited by the gear sample with highest fillet radius of 0.75 mm. Repeated gear tooth loading during service caused an increase in gear temperature due to the hysteresis and friction. Using optical microscopy, the tooth structures of both 3D-printed ABS and CF/ABS spur gears were analyzed before and after loading conditions to establish their failure mechanism. Evidently, various applications of the FDM 3D-printed spur gears depend on their different performances under loads and operating speeds. The methods and findings of this work can be regarded as helpful for future related work related to cellulosic reinforcing particles in a polymer matrix.
Excitatory–inhibitory imbalance in hypoglossal neurons during the critical period of postnatal development in the rat

Non‐technical summary Previously, our laboratory has reported that within a narrow window toward the end of the second postnatal week in a rat's life, many sudden neurochemical and functional changes occurred that rendered the animal less responsive to decreased oxygen supply. The present study extends these findings to the recordings of single nerve cells and documents that, during this critical period of normal postnatal respiratory network development, the responses to excitation are significantly reduced and those to inhibition are significantly enhanced. Thus, the system is under greater inhibitory influence at this time. These findings may have significant implication for understanding sudden infant death syndrome, whose victims are seemingly normal infants with no known pathologies. The peak incidence of SIDS is not at birth, but between the second and fourth months after birth, a theoretical critical period of postnatal respiratory development.
Extreme Discount Usability Engineering

This paper explores the circumstances under which extremely discounted usability engineering techniques produce results that are worthwhile to researchers and practitioners. We present a method for usability analysis where an entire evaluation can be conducted in only thirty minutes, an amount of time we suggest as perhaps the smallest possible unit of analysis (or quantum) for complete usability evaluations. Based on a quantitative and qualitative analysis of thirty-six separate trials of this method, we assess the value of discount usability engineering at extremes of time and tests, and present our observations about the nature of user testing when pushed to extreme limits, a phenomenon we call the “Quantum Usability Effect. ”
Geometry of the Majorana Neutrino and New Symmetries

Experimental observation of Majorana fermion matter gives a new impetus to the understanding of the Lorentz symmetry and its extension, the geometrical properties of the ambient space-time structure, matter–antimatter symmetry and some new ways to understand the baryo–genesis problem in cosmology. Based on the primordial Majorana fermion matter assumption, we discuss a possibility to solve the baryo–genesis problem through the the Majorana–Diraco genesis in which we have a chance to understand creation of Qem charge and its conservation in our D = 1 + 3 Universe after the Big Bang . In the Majorana–Diraco genesis approach there appears a possibility to check the idea of the proton and electron non-stability on the very low energy scale. In particle physics and in our space-time geometry, the Majorana nature of the neutrino can be related to new types of symmetries which are lying beyond the binary Cartan-Killing-Lie algebras/superalgebras. This can just support a conjecture about the non-completeness of the SM in terms of binary Cartan–Killing–Lie symmetries/supersymmetries. As one of the very important applications of such new ternary symmetries could be related with explanation of the nature of the three families and three colour symmetry. Based on the Majorana– Diraco genesis the Majorana neutrino can directly indicate the existence of a new extra-dimensional geometry (new cycle) and thanks to new ternary space-time symmetries, could lead at high energies to the unextraordinary phenomenological con
A Priority based Energy Aware Routing Algorithm for SDN Enabled Data Center Network

Recently the number of data centers has increased tremendously to transport and manage the massive volume of data generated from various sources. As the network devices in data centers continue to increase at an alarming rate hence the need for efficient routing to handle this vast amount of data has emerged as a major concern. This increase in data flow adds many devices that consume a major portion of energy. As a result, maintaining the importance of data flow, and energy conservation are the critical considerations for an efficient routing path. Recently, SDN (Software Defined Network) has been used to improve the performance of DCN (Data Center Network) by reducing the amount of physical infrastructure required. This work proposes a novel admission and routing scheme that considers arbitrarily assigned priorities for network flows and path energy for data packet transmissions. Using the SDN paradigm in DCN, we attempt to maximize the number of flows as well as minimize the energy consumption in the network. For this, a MILP (Mixed Integer Linear Programming) problem is formulated by jointly considering flow priority and path energy. Later, we introduce a greedy method named Priority Based Energy Minimization Algorithm (PEMA) to maximize the flow and minimize the energy as much as possible. Finally, the performance of the routing strategy is observed by comparing it with stat-of-the-art works.
SimMSG: Simulating Transportation of MPI Messages in High Performance Computing Systems

The simulation of interconnection network and MPI message transportation behavior is an important part of the simulation of High-performance computing systems. Current research on the simulation of message transportation in HPC systems mainly focuses on the simulation of interconnection networks of the target HPC system. However, with the development of HPC techniques, the procedure of message transportation in HPC systems has become more complicated. Firstly, the low-latency transportation techniques, e.g. RDMA or RoCE, involve not only the interconnection network but also essential operations on messages inside send/receive nodes. Secondly, collective communications generate a vast number of messages and impact performance significantly. It is necessary to accurately simulate the whole procedure for all messages. To address the above problems, this paper presents SimMSG, a message-trace-driven simulator that simulates the whole transportation procedure of MPI messages in HPC systems. SimMSG simulates message transportation by incorporating simulation of MPI communication routines, in-node underlying processing of messages and message transportation in the interconnection network. We evaluate SimMSG with a real HPC system. SimMSG simulates the real-captured message-traces from the system and can re-produce the whole message transportation behavior of the parallel program in the target system. Experimental results demonstrate the accuracy and efficiency of SimMSG.
A Single Supply Standard 8051 Microcontroller Based Medical K-grade Isolation ECG Module with Graphics LCD

Electrocardiogram (ECG) monitoring is one of the most important patient vital sign. Many design for ECG amplifier has been established. In this paper we describe a unique design of a single supply isolated single Channel ECG amplifier, based on a standard 8051 micro controller. This micro controller system includes analog circuit, digital, ADC circuit and graphical LCD. In general, the analogue circuit module carries out differential amplification, band-pass filtering, power line interference elimination, and output amplification the digital circuit part consists of an 8051 standard micro controller, an 8-channel ADC (ADC0808) converter, and graphical LCD panel. Such system features with low power, low cost and small size which can be used for home use.
Using monoclonal antibodies in developing ELISA for diagnosing bovine tuberculosis.

Three stable strains of hybridoma cells (2H10, 3A8, 1B6) producing monoclonal antibodies (Mab) reacted with Protein Purified Derivative (PPD) Mycobacterium bovis were obtained. They were incapable of binding to PPD M. avium and whole cells M. bovis, M. kansasii, M. scrofulaceum as well as to their soluble and sonicated antigens. PPD M. bovis was attached to the solid phase via Mab which were directed to its protein with a molecular weight of 66 kDa. The diagnostic efficiency of sandwich ELISA was tested as compared with skin test. Blood samples were obtained from 849 cows belonging to farms unaffected and farms affected by tuberculosis. Ninety cows (10.6%) reacted to PPD M. bovis, but among them only 22 cows (2.6%) had a positive ELISA. Average titre of M. bovis specific antibodies detected in serum samples by ELISA was equal to 1:920 – 1:6400. Diagnostic value of ELISA and skin test was determined by autopsy of 12 cows. There were M. bovis specific antibodies at rather high titres in the blood samples of 9 cows which showed positive to skin test. Three cows developed a response to PPD M. bovis but in the blood samples of these animals we failed to detect any specific antibodies. Results of autopsy showed that all cows with positive ELISA and skin test had pathological findings in lungs and lymphatic nodes specific for tuberculosis, but internal organs of cows reacted only to skin test had no alterations. The results of our research testify to the high specificity and efficiency of Mab-based sandwich ELISA in isolating animals infected with tuberculosis and represent an evaluation of the actual epizootic situation.
Surface Plasmon Resonance for Cell-Based Clinical Diagnosis

Non-invasive real-time observations and the evaluation of living cell conditions and functions are increasingly demanded in life sciences. Surface plasmon resonance (SPR) sensors detect the refractive index (RI) changes on the surface of sensor chips in label-free and on a real-time basis. Using SPR sensors, we and other groups have developed techniques to evaluate living cells' reactions in response to stimuli without any labeling in a real-time manner. The SPR imaging (SPRI) system for living cells may visualize single cell reactions and has the potential to expand application of SPR cell sensing for clinical diagnosis, such as multi-array cell diagnostic systems and detection of malignant cells among normal cells in combination with rapid cell isolation techniques.
Innovations and upgrades in virtualized network architectures

The difficulty of making changes to the internet architecture has spawned widespread interest in virtualized testbeds as a place to deploy new services. Despite the excitement, uncertainty surrounds the question of how technologies can bridge the gap from testbed to global availability. It is recognized that no amount of validation will spur today's ISPs to make architectural changes, so the testbed itself must somehow provide global availability. We investigate whether a virtualized architecture that is widely offered by commercial ISPs would support the adoption of new services or upgrades to the infrastructure, and whether ISPs would ever support such an architecture. According to our economic analysis, the answer depends critically on how money flows to network and service providers. If the virtualized network inherits the market structure prevalent on the internet today, which we call network-gatekeeper, investment levels are likely to be poor. On the other hand, we identify two superior market types, mix-and-match and service-gatekeeper, which can improve incentives to invest in services, and even in network upgrades. We discuss how these market types may be implemented.
Bounding extremal functions of forbidden 0-1 matrices using (r, s)-formations

First, we prove tight bounds of $n 2^{\frac{1}{(t-2)! }\alpha(n)^{t-2} \pm O(\alpha(n)^{t-3})}$ on the extremal function of the forbidden pair of ordered sequences $(1 2 3 \ldots k)^t$ and $(k \ldots 3 2 1)^t$ using bounds on a class of sequences called $(r,s)$-formations. Then, we show how an analogous method can be used to derive similar bounds on the extremal functions of forbidden pairs of $0-1$ matrices consisting of horizontal concatenations of identical identity matrices and their horizontal reflections.