Miracle-dz/UniFAR-FTUs huggingface dataset:
ANFIS data driven modeling and real-time Fuzzy Logic Controller test for a Two Tanks Hydraulic System

This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic Controller optimized with Genetic Algorithms (GA). The controller was designed and tested in simulation with the obtained ANFIS model and validated in real-time with the actual TTHS. Obtained model shows an accurate and adequate description of the real system, useful for many applications that require a non-linear functioning representation of the TTHS. The designed controller also demonstrates excellent performance by being able to follow diverse shaped references. This work successfully demonstrates the utility of soft-computing techniques in their application to real world industrial complex systems.
Concealed Ownership: Americans’ Perceived Comfort Sharing Gun Ownership Status with Others

ABSTRACT While much is known about how Americans feel about guns and gun control policy, less is known about how Americans perceive gun owners, or how gun owners and nonowners view themselves. The present study examines how comfortable individuals feel disclosing their gun ownership status with family, friends, coworkers, employers, doctors, teachers, police, and strangers. This article uses stigma theory as a guiding framework. Data were obtained from a nationwide survey conducted in February 2016 of more than 250 current gun owners and more than 250 nonowners. Analyses utilize ordered logistic regression. Findings show that whites, older Americans, and those with more pro-gun attitudes express more comfort sharing whether they own a gun. Respondents also indicate that familiarity with the individual requesting gun ownership information and concern over how that person might react are key factors that affect comfort with disclosure. Implications and directions for future research are discussed.
Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers

Long non-coding RNAs (lncRNAs), transcription factors and microRNAs can form lncRNA-mediated feed-forward loops (L-FFLs), which are functional network motifs that regulate a wide range of biological processes, such as development and carcinogenesis. However, L-FFL network motifs have not been systematically identified, and their roles in human cancers are largely unknown. In this study, we computationally integrated data from multiple sources to construct a global L-FFL network for six types of human cancer and characterized the topological features of the network. Our approach revealed several dysregulated L-FFL motifs common across different cancers or specific to particular cancers. We also found that L-FFL motifs can take part in other types of regulatory networks, such as mRNA-mediated FFLs and ceRNA networks, and form the more complex networks in human cancers. In addition, survival analyses further indicated that L-FFL motifs could potentially serve as prognostic biomarkers. Collectively, this study elucidated the roles of L-FFL motifs in human cancers, which could be beneficial for understanding cancer pathogenesis and treatment.
Good and Bad Investment : An Inquiry into the Causes of Credit Cycles By Kiminori Matsuyama

This paper presents dynamic general equilibrium models of imperfect credit markets, in which the economy fluctuates endogenously along its unique equilibrium path. During a recession, the net worth of the agents is too low and they cannot finance their trading activities. Much of the saving thus goes to business investment, which creates jobs, thereby making the next generation of the agents richer. As the economy booms and the net worth of the agents improves, they can eventually finance their trading activities, which do not create any job. As more credit is extended to trading at the expense of business investment, the economy plunges into a recession. The whole process repeats itself. Endogenous fluctuations occur because, as in ecological cycles driven by predator-prey interaction, good investment breeds bad investment, which destroys good investment. JEL classification numbers: E32 (Business Fluctuations; Cycles), E44 (Financial Markets and the Macroeconomy)
Implementation of the Soft Switching DC/DC Converter

A new soft switching dc/dc converter is presented to achieve zero voltage switching (ZVS) of all switching devices. In the proposed converter, an auxiliary switch and clamp capacitor is used to recycle the energy stored in the leakage inductor, limit the voltage stress of switches and achieve resonance between the transition interval between the main and auxiliary switches. During the transition interval, the resonance based on the junction capacitance of switches and transformer leakage inductance can achieve ZVS operation of power switches. The pulse-width modulation (PWM) waveforms of two switches are generated in a complementary way with a time delay. Two modules of the series-connected transformers with center-tapped rectifier are used in the proposed converter to share the load current. Since these two modules are connected in series in the primary side and parallel-connected in the secondary side. The load current can be equally shared by these two center-tapped rectifiers. Based on the operation behavior, each transformer in the proposed converter can be operated as an inductor or a transformer. No output filter inductor is needed in the proposed converter. The circuit analysis, principle of operation, steady state analysis and design considerations of the proposed converter are provided in detail. Finally, experimental results for a 220 W prototype converter at a constant switching frequency of 150 kHz are obtained to show the performance of the proposed converter.
Adaptive observer for Intake leakage detection in diesel engines described by Takagi-Sugeno model

The problem is motivated by the need to guarantee high-performance engine behavior and in particular to respect the environmentally-based legislative regulations. The complexity of the intake systems of this type of engine makes this task particularly arduous and requires constantly monitoring and diagnosing the engine operation. First of all, a mean value model of a diesel engine subject to leakage in the intake manifold is presented and transformed into Takagi-Sugeno's model. Then, an adaptive observer for intake leakage estimation is developed. The proposed observer approach allows to estimate simultaneously the system states and a variable that is directly related to the presence of leakage. The diagnosis system is successfully evaluated using an advanced diesel engine professional simulator AMEsim(LMS).
Does Endurance Training Compensate for Neurotrophin Deficiency Following Diabetic Neuropathy?

Background A lack of neurotrophic support is believed to contribute to the development of diabetic neuropathy. On the other hand, neurotrophins have consistently been shown to increase in the central and peripheral nervous system following exercise, but the effects of exercise intervention on brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) in diabetic neuropathy are not understood. Objectives This experimental study was designed and carried out at the Tarbiat Modares university (TMU) in Tehran, Iran, to investigate the hypothesis that increased activity as endurance training can help to increase the endogenous expression of neurotrophins in diabetic rats. Methods This was an experimental study with 2 × 2 factorial plans performed at TMU in Iran. Sampling was accidental and 28 adult male Wistar rats in the body mass range of 326.3 ± 8.4 g comprised the sample, with each rat randomly assigned to four groups: diabetic control (DC), diabetic training (DT), healthy control (HC), and healthy training (HT). To induce diabetic neuropathy, after 12 hours of food deprivation, an intraperitoneal injection of streptozotocin (STZ) solution (45 mg/Kg) method was used. Two weeks after STZ injection, the endurance training protocol was performed for 6 weeks; 24 hours after the last training session, the rats were sacrificed. Real-time PCR was used for BDNF and NGF expression. Results The data indicate that diabetes decreases BDNF and NGF expression in sensory (92%, P = 0.01; 90%, P = 0.038, respectively) and motor (93%, P = 0.05; 60%, P = 0.029, respectively) roots. However, NGF mRNA levels in the DT group were significantly higher than in the HC group ((7.1-fold), P = 0.01; (2.2-fold), P = 0.001, respectively, for sensory and motor roots), but this was not shown for BDNF. In addition, endurance training can increase NGF expression in healthy rats ((7.4-fold), P = 0.01; (3.8-fold), P = 0.001, respectively, for sensory and motor roots). Conclusions This study shows that BDNF and NGF expression decreases in diabetic neuropathy. However, this decrease can be reversed through endurance training. These results also indicate that endurance training may have a potential role in compensating for neurotrophin deficiency following diabetic neuropathy.
Upper Ocean Carbon Export and the Biological Pump

coastal and open Pacific Ocean. They also demonstrated that the flux of particles out of the surface layer, as measured by sediment traps, generally approximated the large-scale rate of new production. In 1967, Richard Dugdale and John Goering had defined new production as the fraction of the overall net primary production that was supported by external, or “new” inputs of nutrients. They focused on nitrate in deep ocean water supplied to the euphotic zone by vertical mixing and upwelling as the principal new nutrient, but they did explicitly identify N2 fixation as a potential source of new nitrogen (see Michaels et al., this issue). They also highlighted sinking particles as the major pathway for export in the oceanic nitrogen budget. But it was Eppley and Peterson (1979) who articulated the paradigm that came to govern ocean flux studies over the coming decades: We estimate the sinking flux of POC [Particulate Organic Carbon] in the deep ocean by assuming that new production, as defined by Dugdale and Goering, is quantitatively equivalent to the organic matter that can be exported from the total production in the euphotic zone without the production system running down (Eppley and Peterson, 1979, p. 679). Eppley and Peterson also defined the ratio of new to total production as the f-ratio and showed that f was an asymptotic function of the magnitude of total production. This relationship provided an explicit link between remotely-sensed primary production rates and the ocean carbon cycle. If total production could be estimated from remotely-sensed properties, one could apply the Eppley-Peterson algorithm and calculate the export rates as functions of time and space. The f-ratio thus provided both a means to define the efficiency of the biological pump quantitatively and a step toward quantifying the functioning of the pump on a global scale. Upper Ocean Carbon Export and the Biological Pump SPECIAL ISSUE – JGOFS
Learning Graphical Model for Human Motion Characterization Using Genetic Optimization

In this paper we present a novel method of using genetic algorithm (GA) to learn a graphical model which is used for human motion characterization. The modeling of human movements will involve a high dimensional joint probability density function. With this graphical model, the joint probability distribution can be decomposed into a number of low dimensional distributions which are represented as tree models and triangulated models. To automatically search for such a model from a database of cases is a NP-hard problem. We use GA to solve this problem, which can optimize both the ordering structure and the conditional independence relationship of the graphical model. The searched graphical models are used to classify different types of human motions. The experimental results demonstrate that, compared with a previous greedy search algorithm, the GA is more effective for optimization of the graphical model
Registering a MultiSensor Ensemble of Images

Many registration scenarios involve aligning more than just two images. These image sets-called ensembles-are conventionally registered by choosing one image as a template, and every other image is registered to it. This pairwise approach is problematic because results depend on which image is chosen as the template. The issue is particularly acute for multisensor ensembles because different sensors create images with different features. Also, pairwise methods use only a fraction of the available data at a time. In this paper, we propose a maximum-likelihood clustering method that registers all the images in a multisensor ensemble simultaneously. Experiments involving rigid-body and affine transformations show that the clustering method is more robust and accurate than competing pairwise registration methods. Moreover, the clustering results can be used to form a rudimentary segmentation of the image ensemble.
An Improved Dynamic Password-based User Authentication Scheme for Hierarchical Wireless Sensor Networks

User authentication is an important issue in wireless sensor networks (WSN). Das et al. recently proposed a dynamic password-based user authentication scheme for hierarchical wireless sensor networks (HWSN), which provides high security and a simple authentication approach. In this paper we present a flaw in Das et al.’s scheme that makes it infeasible for real-life implementation. Additionally, we demonstrate that Das et al.’s scheme has redundant elements. To overcome these imperfections we propose an enhanced user authentication scheme based on Das et al.’s, which is both efficient and secure. DOI: http://dx.doi. org/10.5755/j01.eee. 19.6. 2038
Experimental Results of Compact Dual Frequency Microstrip Slot Antenna

Owing to the compactness of communication equipment, designs for reducing the size of the microstrip antenna have received much attention in today’s era. Keeping in view of this, a microstrip slot antenna is designed and fabricated on FR 4 dielectric material suiting for various communication applications such as WiMax, RADAR, fixed satellite services, WLAN, satellite communication applications. The practical results show that the proposed antenna, having compactness of 27 % has a bandwidth of 180 MHz (VSWR < 2:1) with moderate gain of 5.20 dB showing omnidirectional radiation patterns across the whole operating frequency band.
Antimicrobial Susceptibility of Proteus mirabilis: Impact of Biofield Energy Treatment

Proteus mirabilis (P. mirabilis) is widespread in nature, mainly found in soil, water, and the flora of human gastrointestinal tract. The current study was attempted to investigate the effects of Mr. Trivedi’s biofield energy treatment on P. mirabilis both in lyophilized as well as revived state for antimicrobial susceptibility, biochemical characteristics, and biotype. P. mirabilis cells were procured from MicroBioLogics Inc., USA, in a sealed pack bearing the American Type Culture Collection (ATCC 25933) number and stored according to the recommended storage protocol until needed for experiments. Two sets of ATCC samples were taken in this experiment and denoted as A and B. The ATCC A sample was revived and divided into two parts Gr.I (control) and Gr.II (revived); likewise, the ATCC B was labeled as Gr.III (lyophilized). Group II and III were given with biofield treatment. All experimental parameters were studied using automated MicroScan Walk-Away® system. The result of antimicrobial susceptibility and minimum inhibitory concentration showed 6.67% and 9.38% alteration, respectively in treated cells of P. mirabilis as compared to the control. In addition, the overall biochemical reactions were significantly altered (42.42%) in the treated groups with respect to the control. Moreover, biotype number was changed in the treated cells, Gr. II, day 5 (40061546) and day 10 (77365764), while without alteration of organism as compared to the control (40061544; Proteus mirabilis). The results suggested that biofield treatment has an impact on P. mirabilis in revived state predominately.
Brain-Derived Neurotrophic Factor Regulates Cholesterol Metabolism for Synapse Development

Brain-derived neurotrophic factor (BDNF) exerts multiple biological functions in the CNS. Although BDNF can control transcription and protein synthesis, it still remains open to question whether BDNF regulates lipid biosynthesis. Here we show that BDNF elicits cholesterol biosynthesis in cultured cortical and hippocampal neurons. Importantly, BDNF elicited cholesterol synthesis in neurons, but not in glial cells. Quantitative reverse transcriptase-PCR revealed that BDNF stimulated the transcription of enzymes in the cholesterol biosynthetic pathway. BDNF-induced cholesterol increases were blocked by specific inhibitors of cholesterol synthesis, mevastatin and zaragozic acid, suggesting that BDNF stimulates de novo synthesis of cholesterol rather than the incorporation of extracellular cholesterol. Because cholesterol is a major component of lipid rafts, we investigated whether BDNF would increase the cholesterol content in lipid rafts or nonraft membrane domains. Interestingly, the BDNF-mediated increase in cholesterol occurred in rafts, but not in nonrafts, suggesting that BDNF promotes the development of neuronal lipid rafts. Consistent with this notion, BDNF raised the level of the lipid raft marker protein caveolin-2 in rafts. Remarkably, BDNF increased the levels of presynaptic proteins in lipid rafts, but not in nonrafts. An electrophysiological study revealed that BDNF-dependent cholesterol biosynthesis plays an important role for the development of a readily releasable pool of synaptic vesicles. Together, these results suggest a novel role for BDNF in cholesterol metabolism and synapse development.
Identification of Key Causal Regulators in Gene Networks

One primary goal of gene network analysis is to identify key regulatory components, or key drivers, of sub-networks with respect to various biological contexts. Here we developed a general algorithm to identify key drivers in gene regulatory networks. The generalized key driver analysis (KDA) uncovers not only the well-known regulators for the expression quantitative trait locus (eQTL) hotspots but also many novel drivers underlying certain eQTL hotspots. This algorithm also identifies a number of key regulators for immune response involved in multiple common chronic diseases and the predicted drivers appear to be more important than the non-drivers genes to induce phenotypic changes when perturbed.
Mood And Transitivity In The Tourism Brochure Of Qantas Holidays Magazine: A Functional Grammar Study

Thesis ini berjudul Mood and Transitivity in the Tourism Brochure of Qantas Holiday Magazine: a Functional Grammar Study. Penulis menganalisis brosur pariwisata dalam majalah Qantas Holidays berdsarkan aspek tata bahasa fungsional. Analisis tata bahasa fungsional berfokus pada mood (clause as exchange), transitivity (clause as representation) and taxis (parataxis and hypotaxis) yang digunakan dalam brosur pariwisata di dalam majalah Qantas Holidays. Penelitian ini bertujuan untuk mengetahui bentuk dan unsur-unsur pembentuk mood, transitivity and taxis yang digunakan pada brosur pariwisata. Teori yang digunakan dalam penelitian ini adalah teori tata bahasa fungsional. Analisis mood, transitivity and taxis menggunakan teori yang dikemukakan oleh Halliday and Matthiessen (2004) dalam bukunya An Introduction to Functional Grammar. Penelitian ini menggunakan metode analisis deskriptif. Hasil penelitian ini menunjukan terdapat tiga puluh satu (31) declarative moodrelational processes, lima (5) declarative mood-existential process, enam (6) declarative mood-material processes, satu (1) declarative mood-mental process, lima (5) imperative mood-material processes dan satu (1) imperative moodmental process. I, Gifta Firdiana, do herewith declare that the material contained in my thesis entitled Mood and Transitivity in the Tourism Brochure of Qantas Holidays Magazine: A Study Functional Grammar original work performed by me under the guidance and advice of my faculty advisor, Dr. Sutiono Mahdi and Dr. Heriyanto. I certify that, to the best of my knowledge, my thesis does not infringe upon anyones copyright nor violate any proprietary rights and that any ideas, techniques, or any other material from the work of other people included in my thesis, published or otherwise, are fully acknowledged in accordance with the standard referencing practices. I declare that this thesis has not previously been submitted for the basis of award of any degree or diploma/examining body, or university or instituation Untuk keterangan lebih lanjut silahkan menghubungi http://cisral.unpad. ac.id
Alignment Method for Spectrograms of DNA Sequences

DNA spectrograms express the periodicities of each of the four nucleotides A, T, C, and G in one or several genomic sequences to be analyzed. DNA spectral analysis can be applied to systematically investigate DNA patterns, which may correspond to relevant biological features. As opposed to looking at nucleotide sequences, spectrogram analysis may detect structural characteristics in very long sequences that are not identifiable by sequence alignment. Alignment of DNA spectrograms can be used to facilitate analysis of very long sequences or entire genomes at different resolutions. Standard clustering algorithms have been used in spectral analysis to find strong patterns in spectra. However, as they use a global distance metric, these algorithms can only detect strong patterns coexisting in several frequencies. In this paper, we propose a new method and several algorithms for aligning spectra suitable for efficient spectral analysis and allowing for the easy detection of strong patterns in both single frequencies and multiple frequencies.
How do leader facial expressions, and affective and cognitive trust in the leader, affect follower perceptions of leadership effectiveness?

The present study examines the effect of facial expressions on followers’ level of affective and cognitive trust in the leader and leadership effectiveness, perceived by followers. The sample consists of 20 leaders, operating in a large public-sector organization. In order to observe facial expressions, the leaders’ nonverbal behaviors were video-recorded, during a regularly occurring staff meeting. The research design includes surveys, filled out by followers and experts. The results show that there are correlations between negative facial expressions and affective trust, transformational and transactional leader behavior and leadership effectiveness. Furthermore, it is found that smiling has a positive effect on follower job satisfaction.