Miracle-dz/UniFAR-FTUs huggingface dataset:
Consciousness and integrated energy differences in the brain

To understand consciousness within the framework of natural science we must acknowledge the role of energy in the brain. Many contemporary neuroscientists regard the brain as an information processor. However, evidence from brain imaging experiments demonstrates that the brain is actually a voracious consumer of energy, and that functionality is intimately tied to metabolism. Maintaining a critical level of energy in the brain is required to sustain consciousness, and the organisation of this energy distinguishes conscious from unconscious states. Meanwhile, contemporary physicists often regard energy as an abstract mathematical property. But this view neglects energy's causal efficacy and actuality, as identified by Aristotle and later appreciated by many important biologists, psychologists and physicists. By reconsidering the nature of energy and recasting its role in neural activity, we arrive at a theory of consciousness that is consistent with the laws of physics, chemistry and biology. The argument draws on the integrated information theory (IIT) developed by Tononi et al. but reinterprets their findings from the perspective of energy exchange. In IIT, the conscious state in a system, such as a brain, is defined by the quantity of integrated differences, or information, it contains. According to the approach outlined here, it is in the nature of energy to manifest differences of motion and tension. The level of complexity of the energy differences in a system determines its conscious state. Consciousness occurs because, in Nagel's terminology, there is 'something it is like' to be a sufficiently complex state of energy differences.
Quasi‐linear diffusion coefficients for highly oblique whistler mode waves

Quasi‐linear diffusion coefficients are considered for highly oblique whistler mode waves, which exhibit a singular “resonance cone” in cold plasma theory. The refractive index becomes both very large and rapidly varying as a function of wave parameters, making the diffusion coefficients difficult to calculate and to characterize. Since such waves have been repeatedly observed both outside and inside the plasmasphere, this problem has received renewed attention. Here the diffusion equations are analytically treated in the limit of large refractive index μ. It is shown that a common approximation to the refractive index allows the associated “normalization integral” to be evaluated in closed form and that this can be exploited in the numerical evaluation of the exact expression. The overall diffusion coefficient formulas for large μ are then reduced to a very simple form, and the remaining integral and sum over resonances are approximated analytically. These formulas are typically written for a modeled distribution of wave magnetic field intensity, but this may not be appropriate for highly oblique whistlers, which become quasi‐electrostatic. Thus, the analysis is also presented in terms of wave electric field intensity. The final results depend strongly on the maximum μ (or μ∥) used to model the wave distribution, so realistic determination of these limiting values becomes paramount.
Optimization of Environmental Factors to Measure Physiological Parameters of Two Rose Varieties

Rose (Rosa hybrida L.) is one of the most important specialty cut flowers produced. Characterization of physiological variability in photosynthetic efficiencies, respiration rate and chlorophyll content is one of the greatest challenges in assessing rose net primary production of flowering, quality of cut flowers and other rose uses. Two modern rose varieties Floribunda and Hybrid Tea were used to optimize different methods for analysing physiological characteristics (photosynthesis rate, respiration rate and chlorophyll content). Many parameters were optimized, five different lights intensity were used (600, 900, 1200, 1500 and 2000 μmol·m-2·s-1) of which 1200 μmol·m-2·s-1 gave the highest photosynthesis rate. Five different measuring times were used (8 am, 10 am, 12 pm, 2 pm and 4 pm) and 12 pm was shown to be the optimum time for measuring photosynthesis rate. Among two different weather conditions (sunny day and cloudy day) sunny day was selected. For respiration rate two different measuring times (1 and 2 hours) after darkness were studied and 1 hour was chosen. Among three different times (10 am, 12 pm and 2 pm) for measuring chlorophyll content, 12 pm was selected. Using these optimized variables will allow researchers to collect robust and reproducible results to be obtained from different studies, and in turn lead to improved yields of horticultural plants.
Target recognition in synthetic aperture radar images via joint multifeature decision fusion

Abstract. Multifeature decision fusion is an effective way to promote the performance of target recognition of synthetic aperture radar (SAR) images. This paper proposes a joint multifeature decision fusion strategy for target recognition in SAR images based on multitask compressive sensing (MtCS). The proposed method can exploit the intercorrelations among different features by enforcing the constraint on the sparsity pattern. Furthermore, the time consumption for MtCS is almost the same with that of single feature-based compressive classification, such as sparse representation-based classification. Experiments on the moving and stationary target acquisition and recognition dataset and comparison with several state-of-the-art methods demonstrate the validity of the proposed method.
Arterielle Hypertonie - Individuelle Risikostratifikation und Therapieziele

Epidemiologische Studien haben eindeutig gezeigt, dass das Risiko für Herz-Kreislauferkrankungen mit dem Blutdruck ansteigt. Dies gilt nicht nur für Herzinfarkt, plötzlichen Herztod und Schlaganfall, sondern auch für die Herzinsuffizienz. Für die Festlegung der Blutdrucknormalwerte gibt es keinen Schwellenwert, ab dem das kardiovaskuläre Risiko ansteigt. Vielmehr scheint die Beziehung zwischen Blutdruck und kardiovaskulärem Risiko kontinuierlich wahrscheinlich schon ab 120 mmHg systolisch und 80 mmHg diastolisch anzusteigen. In der vorliegenden Arbeit soll dargestellt werden, welches die aktuellen Blutdruckgrenzwerte sind und wie das kardiovaskuläre Risiko in Abhängigkeit von Begleiterkrankungen die Therapieindikation und die Blutdruckzielwerte bestimmt. Eine Schwierigkeit besteht darin, dass sich alle gebräuchlichen Grenzund Zielwerte auf Gelegenheitsmessungen des Blutdrucks in der Praxis beziehen. Auch wenn sich in der Praxis zunehmend komplementäre Blutdruckmessmethoden wie Blutdruckselbstmessung und ambulante 24 h-Messung durchsetzen, existieren nur in sehr begrenztem Umfang pro-
From shape to shell: a design tool to materialize freeform shapes using gridshell structures

This paper introduces and explains the design process of a gridshell in composite materials built in Paris in 2011 for the festival Soliday. A brief introduction presents the structural concept and the erection methodology employed. It explains why composite materials are relevant for such applications. Following this practical case, the whole process from 3D-shape to real-shell is then detailed. Firstly, the shape is rationalized and optimized to smooth local curvature concentrations. Secondly, a specific computing tool is used to mesh the surface according to the compass method. This tool allows designers to look for optimal mesh orientations regarding the elements curvature. Finally, a full structural analysis is performed to find the relaxed shape of the grid and check its stability, strength and stiffness under loads. The authors conclude on the overall relevance of such structures.
Luminosity Dependence of the Covering Factor of the Dust Torus in Active Galactic Nuclei Revealed by Akari

We demonstrate the luminosity dependence of the covering factor (CF) of active galactic nuclei (AGNs), based on AKARI mid-infrared all-sky survey catalog. Combining the AKARI with Sloan Digital Sky Survey (SDSS) spectroscopic data, we selected 243 galaxies at 9 µ m and 255 galaxies at 18 µ m. We then identiﬁed 64 AGNs at 9 µ m and 105 AGNs at 18 µ m by their optical emission lines. Following that, we estimated the CF as the fraction of type 2 AGN in all AGNs. We found that the CF decreased with increasing 18 µ m luminosity, regardless of the choice of type 2 AGN classiﬁcation criteria.
Chaotic Signal Denoising Based on Hierarchical Threshold Synchrosqueezed Wavelet Transform

In order to overcoming the shortcoming of single threshold synchrosqueezed wavelet transform(SWT) denoising method, an adaptive hierarchical threshold SWT chaotic signal denoising method is proposed. Firstly, a new SWT threshold function is constructed based on Stein unbiased risk estimation, which is two order continuous derivable. Then, by using of the new threshold function, a threshold process based on the minimum mean square error was implemented, and the optimal estimation value of each layer threshold in SWT chaotic denoising is obtained. The experimental results of the simulating chaotic signal and measured sunspot signals show that, the proposed method can filter the noise of chaotic signal well, and the intrinsic chaotic characteristic of the original signal can be recovered very well. Compared with the EEMD denoising method and the single threshold SWT denoising method, the proposed method can obtain better denoising result for the chaotic signal.
Information theory and maximum entropy principles in non-equilibrium statistical physics

Complexity is often envisaged as the impossibility of reconstructing the whole of a system from the knowledge of its parts. When a probabilistic description is in order, a mathematically rigorous way to formalize this intuition is to rely on the principle of maximum entropy as a tool to infer probability distributions from structural or observational constraints. This thesis aims at evaluating this heuristic criterion in three different contexts. First, we consider the case where the transition matrix generating a discrete and finite Markov process has to be rebuilt from observed autocorrelation, with an emphasis on short historical samples. Second, we examine how maximum entropy methods and information theory can be linked to complexity as usually expressed in the particular context of cellular automata. The last part reconsiders key assumptions underlying kinetic theory of gases from the perspective of information theory, aiming in particular at generalizing Boltzmann's molecular chaos hypothesis.
Identifying Duplicate Questions with Siamese Neural Networks

The task of identifying questions that have the same intent has a variety of applications, including information centralization and question redirection. We believe that deep learning techniques are capable of performing well in this task, and use a Siamese neural network architecture to achieve results that are comparable to state-of-the-art. As this research is still in progress, we also articulate modiﬁcations to our model architecture that could potentially result in even better performance
The Impact of Technological Innovation on Improving the Financial Performance of Iraqi Commercial Banks: An Empirical Study

: Due to the increase in the volume of banking activity and the expansion of its spread, the management of banks has paid increasing attention to introducing mechanization in the banking work in order to keep pace with the increasing development in banking services by providing the latest machines and advanced computers. On the basis that the banking sector is the stepping stone for economic activities, the movement of money and investment, and is obligated to keep pace with the rapid and active development of the movement. The current research aims to evaluate modern technology technologies and their impact on the level of performance of Iraqi banks, as the research sample consisted of 19 banks listed on the Iraq Stock Exchange, and the research concluded that despite the electronic banking services provided by the bank, they remain limited and are not up to par.To the required level, as it was compared to what is witnessed in the global banking arena, as well as the existence of a large discrepancy between the performance levels of private banks resulting from the variation in the expertise and efficiency of the departments of these banks and the level of technological techniques used, which is clearly reflected in their success in performing their banking activities. The research recommended a set of recommendations, the most important of which is not to be satisfied with a limited number of electronic services, as banks in Iraq must provide more electronic services and innovate new electronic services, benefit from the experiences of international banks and competition, and pay attention to employing the Internet more in banking operations, which will facilitate the communication process. Whether in other banks or with customers.
Simplified fuzzy-Padé controller for attitude control of quadrotor helicopters

In this study, a simplified fuzzy-Pade controller (FPC) for attitude control of quadrotor helicopters is proposed, which is non-linear, fractional, and model independent. To determine some of the unknown coefficients of the Pade approximant, a proportional-derivative-type fuzzy logic controller (FLC) is first designed. The responses of the simplified FPC due to step set-point manoeuvres are compared with those of the FLC in terms of several performance indices such as rise time, settling time, percentage overshoot, integral absolute error, integral of time multiplied by AE, central processing unit time, and energy consumption. Simulation results demonstrate that in each case the proposed FPC presents an improved performance over the FLC. The asymptotic stability of the simplified FPC is proved with Lyapunov stability theory and La Salle's invariant set theorem. Unlike the FLC, the proposed FPC is simple enough to be implemented on the on-board electronics of the quadrotor. Flight experiments in hovering conditions are given to demonstrate the effectiveness of the simplified FPC.
Sparse reconstruction methods in x-ray CT

Recent progress in X-ray CT is contributing to the advent of new clinical applications. A common challenge for these applications is the need for new image reconstruction methods that meet tight constraints in radiation dose and geometrical limitations in the acquisition. The recent developments in sparse reconstruction methods provide a framework that permits obtaining good quality images from drastically reduced signal-to-noise-ratio and limited-view data. In this work, we present our contributions in this field. For dynamic studies (3D+Time), we explored the possibility of extending the exploitation of sparsity to the temporal dimension: a temporal operator based on modelling motion between consecutive temporal points in gated-CT and based on experimental time curves in contrast-enhanced CT. In these cases, we also exploited sparsity by using a prior image estimated from the complete acquired dataset and assessed the effect on image quality of using different sparsity operators. For limited-view CT, we evaluated total-variation regularization in different simulated limited-data scenarios from a real small animal acquisition with a cone-beam microCT scanner, considering different angular span and number of projections. For other emerging imaging modalities, such as spectral CT, the image reconstruction problem is nonlinear, so we explored new efficient approaches to exploit sparsity for multi-energy CT data. In conclusion, we review our approaches to challenging CT data reconstruction problems and show results that support the feasibility for new clinical applications.
The robust machine availability problem – bin packing under uncertainty

Abstract We define and solve the robust machine availability problem in a parallel machine environment, which aims to minimize the number of identical machines required while completing all the jobs before a given deadline. The deterministic version of this problem essentially coincides with the bin packing problem. Our formulation preserves a user-defined robustness level regarding possible deviations in the job durations. For better computational performance, a branch-and-price procedure is proposed based on a set covering reformulation. We use zero-suppressed binary decision diagrams for solving the pricing problem, which enable us to manage the difficulty entailed by the robustness considerations as well as by extra constraints imposed by branching decisions. Computational results are reported that show the effectiveness of a pricing solver with zero-suppressed binary decision diagrams compared with a mixed integer programming solver.
Influence of Product Diversification on Financial Performance of Microfinance Institutions in Nairobi County, Kenya.

Purpose: To examine the influence of product diversification on financial performance of microfinance institutions in Nairobi County, Kenya. Methodology: The study applied descriptive research design during the collection of data. The study’s target population was 14 microfinance banks. The sample size was selected using simple random sampling method after determination using Kothari (2004) sampling formular to obtain 19 operations managers, 34 tellers, 40 credit officers, and 28 customer care officers. The study collected primary and secondary data. The study conducted a pre-test study of the questionnaires in Cooperative bank and I&M banks in Nairobi County. Further, the study tested reliability and validity. Further, quantitative data was analyzed using SPSS software version 25 to generate descriptive and inferential statistics. The various descriptive analysis was frequencies, percentage and mean, while linear and multiple regression analysis was done as part of inferential statistics analysis. Results: The questionnaire results disclosed that 87(89%) strongly agreed and 9(9%) agreed (mean of 4.83) that there were efforts from the management to allow the existence of different types of loan products with various requirements. Nevertheless, 21(21%) strongly disagreed and 19(20%) disagreed (mean of 2.92) that the staff were always encouraged to offer suggestions to the management on how products could be improved further to incorporate the needs of each customer. Additionally, under model summary, R was 0.746 and R-square was . 557 at a Durbin-Watson value of 1.442. Further, the significance coefficient of ANOVA was 0.001 hence less than 0.05. The results therefore enabled the study reject the null hypothesis. Unique contribution to theory, policy and practice: The conclusions made on product diversification was that the management failed to incorporate various improvement suggestions made on the different implemented products. The issues gave a major reason why MFIs revenue was declining in Kenya. That is, in as much as they had different products, the specific client needs were not being met and if they were met, it was very expensive to maintain the products. The study recommends that the management of MFIs should commission a special committee of expert to review the requirement of each and every product being offered.
Faktor Sukses Kunci Untuk Meningkatkan Kinerja Perusahaan Melalui Manajemen Risiko Basis COSO-2017

Penelitian ini berupaya untuk mengidentifikasi faktor sukses kunci dalam meningkatkan kinerja perusahaan melalui penerapan manajemen risiko basis COSO-2017. Metode COSO-2017 dipilih sebagai alat manajemen risiko dalam riset ini setelah melalui beberapa pertimbangan, salah satunya adalah kesesuaian antara karakteristik metode dengan kebutuhan perusahaan akan manajemen risiko. Obyek penelitian ini adalah salah satu Badan Usaha Milik Negara (BUMN) di sektor konstruksi dan properti. Satu hal unik yang ada dalam penelitian ini adalah bahwa kajian dilakukan pada perusahaan yang mengalami kesulitan keuangan, sehingga salah satu indikator efektivitas manajemen risiko adalah ketika sistim mampu menjadi detektor dini dalam mengidentifikasi kerugian yang jauh lebih besar. Alhasil efisiensi dan ketepata biaya menjadi indikator acuannya. Melalui metode penelitian stud kasus, penelitian ini berhasil mengidentifikasi 5 (lima) faktor sukses kunci yakni: pemahaman risiko, struktur organisasi, budaya risiko, kelengkapan dan kesesuaian antara dokumen manajemen risiko dengan karakteristik khusus yang ada dalam industri serta pendampingan yang tepat dalam implementasi manajemen risiko. Kelima faktor tersebut terbukti menjadi kunci sukses bagi perusahaan dalam meningkatkan efektivitas sistim manajemen risikonya demi teraihnya sasaran kinerja dalam jangka menengah maupun panjang. Ketika laporan ini disusun perusahaan masih berusaha untuk menyukseskan restrukturisasinya namun kelima faktor tersebut dapat menjadi referensi bagi perusahaan lain yang menghadapi realitas yang sama. Penelitian ini ditutup dengan agenda berikutnya yakni pengujian secara empiris atas kelima faktor kunci sukses tersebut.
Unsteady MHD bio-nanoconvective anistropic slip flow past a vertical rotating cone

The MHD bioconvective of nanofluid flow past a rotating cone with anistropic velocity slips, thermal slip, mass slip and microorganism slips is studied theoretically and numerically. Suitable similarity transformations are used to transform the governing boundary-layer equations into non-linear ODE which were then solved numerically. The effect of the governing parameters on the dimensionless velocities, temperature, nanoparticle volume fraction (concentration), density of motile microorganisms as well as on the local skin friction, local Nusselt, Sherwood number and the local motile microorganism numbers are examined. Results from this investigation were compared with previous related investigations and good agreement was found. It is found that for both in the presence and absence of magnetic field, increasing velocity slips reduce the friction factor. It is also found that increasing thermal slip, mass slip and microorganism slips strongly reduce heat, mass and microorganism transfer, respectively. This study is relevant in bio-chemical industries in which microfluidic devices involved.
Segmentation of MR Images of the Brain to Detect WM, GM, and CSF Tissues in the Presence of Noise and Intensity Inhomogeneity

ABSTRACT Segmentation of brain MR images for the detection of various healthy brain tissues such as white matter, gray matter, and cerebrospinal fluid is of immense interest to detect and to diagnose different brain-related disorders at the primitive level. MR image segmentation becomes a difficult task owing to the presence of intensity inhomogeneity (IIH), noise, partial volume effects, and intrinsic nature of the MR images. This paper proposes an efficient, region-based, energy minimization technique named as anisotropic multiplicative intrinsic component optimization (AMICO) to segment the brain image in the presence of IIH and noise and to detect different healthy brain tissues. The proposed algorithm utilizes a powerful anisotropic diffusion filter to denoise the image. The MICO algorithm segment the denoised image after correcting IIH. In the proposed technique, MR brain image is decomposed into two multiplicative and intrinsic components, such as the true image component and the bias field component. Brain tissue physical properties are represented by the component of true image and the IIH is characterized by the bias field component. Optimization of these two multiplicative and intrinsic components by employing the proposed effective energy minimization process, result in IIH correction and tissue segmentation simultaneously. The pursuance of the proposed technique is compared with some other existing techniques using the parameters, dice similarity coefficient, sensitivity, specificity, and segmentation accuracy. The results validated the excellent performance of the AMICO in detecting various brain tissues consisting of various levels of IIH and noise.