Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of Input Power Factor Control Techniques in Matrix Converters Based on Model Predictive and Space Vector Control Schemes

Model Predictive Control (MPC) with a finite control set and space vector modulation (SVM) are the most common control methods for the matrix converters (MCs). This paper is focused on the input and output currents performance analysis of the matrix converter controlled by SVM and MPC. A closed-loop control of the input current displacement angle is employed in the SVM strategy to provide unity input power factor over a wide range of voltage transfer ratio. For MPC, a discrete-time model of the converter, including the input filter and load, are used to predict the input and output currents for each valid switching state. The MPC, SVM, and power factor controlled SVM (PFC-SVM) methods are analyzed in detail, and their performance in controlling the input power factor, current quality, and transient response are compared through numerical simulations and experimental tests.
Off-Target Impacts: Tracing Public Participation in Policy Making for Agricultural Biotechnology

Drawing on public comments and drafts of an environmental impact statement, this article examines public participation in policy making via the federal Web site Regulations.gov. Aiming to be our “voice” in federal decision making, Regulations.gov encourages citizens to submit comments on proposed actions. Drawing on Callon, Lascoumes, and Barthe’s “hybrid forum,” the author suggests that ethical and effective participatory policy making should be hybrid in scope, inclusion, and agency. While public participation in policy making is commonly positioned as an antidote to the crisis of trust in science, the author argues that such participation gone wrong could have off-target impacts, raising questions about the promise of Regulations.gov.
ASSOCIATION BETWEEN MATERNAL UNDERNUTRITION AND LOW BIRTH WEIGHT: A HOSPITAL-BASED STUDY IN CHENNAI

Background: Birth weight is an important predictor of a child’s growth and survival and this is dependent on the maternal health and nutrition during pregnancy. Objective: The objective of this study was to study the association between maternal nutritional status as measured by anthropometry, sociodemographic characteristics, and the birth weight of neonates. Materials and Methods: A hospital-based cross-sectional study was conducted among 100 singleton term newborns and their mothers between September 2017 and December 2018. Demographic and socioeconomic details such as maternal age, education, occupation, religion, and household income were recorded using a pre-structured questionnaire. The weight and height of all the mothers were measured. The babies were examined and the weight was recorded at birth. Results: The prevalence of low birth weight was found to be 21%. The mean birth weight was 2955±418 g. Maternal undernutrition (p=0.03), maternal short stature (p=0.04), maternal illiteracy (p=0.01), and lower socioeconomic status (p=0.05) were significantly associated with increased prevalence of low birth weight. Conclusion: The prevalence of low birth weight was found to be high. Maternal undernutrition was significantly associated with low birth weight. Hence, there is a need for continued focus on maternal nutrition for optimal intrauterine growth, thereby reducing the prevalence of low birth weight in India.
Static use of options in dynamic portfolio optimization under transaction costs and solvency constraints

We study a dynamic portfolio optimization problem where it is possible to invest in a risk-free bond, in a risky stock modeled by a lognormal diffusion and in call options written on the stock. The use of the options is limited to static strategies at the beginning of the investment period. The investor faces transaction costs with a fixed component and solvency constraints and the objective is to maximize the expected utility of the final wealth. We characterize the value function as a constrained viscosity solution of the associated quasi-variational inequality and we prove the local uniform convergence of a Markov chain approximation scheme to compute numerically the optimal solution. Because of transaction costs and solvency constraints the options cannot be pefectly replicated and despite the restriction to static policies our numerical results show that in most cases the investor will keep a significant part of his portfolio invested in options.
Novel Method of Double Innervated Free Gracilis Muscle Functional Transfer for Facial Reanimation

METHODS AND MATERIALS: One hundred forty-two subjects undergoing migraine surgery were prospectively enrolled. Preoperatively, patients were asked to complete a questionnaire on MH history, including the MH index (MHI) and information on prior head or neck injury. This included data on the nature of the injury, timing in relation to their MH, and whether they attributed their MH pain to the injury itself (precipitating event). The senior author performed all surgical procedures. Follow-up surveys were sent to all patients at 12 months postoperatively.
Antidiabetic and Antihyperlipidemic Effects of Aqueous Extract of Carica papaya Leaf on the Experimental Model against Single Alloxan Toxicity

Antidiabetic and antihyperlipidemic effects of aqueous extract of Carica papaya leaf on the toxicity were investigated. A total of thirty rats were divided into six groups of 5 rats: Group A: Normal control, Group B: Negative control, Group C: Positive control I, Group D: Positive control II, Group E: Test control I, Group F: Test control II. Diabetes was induced with a single dose of alloxan (120mg/kg) body weight and serum glucose was taken 72hrs after induction to confirm diabetes. The oral administration for hyperglycemia and hyperlipidemia started on the 4th and 8th day of the experiment respectively. The result showed that Carica papaya leaf extract significantly and progressively lowered the glucose level, TG, TC and LDL dose dependently while significantly causing a dose-related elevation in HDL concentration when compared to the untreated control and positive control groups (I & II) treated rats. Phytochemical analysis revealed the presence of alkaloids, flavonoids, saponins and tannins. The aqueous extract of this plant can be used to brew a tonic that will allay the metabolic disruption produced by diabetes.
Virtual histology of dried and mummified biological samples by laboratory phase-contrast tomography

Ancient remains from humans, animals and plants hold valuable information about our history. X-ray imaging methods are often, because of their non-destructive nature, used in the analysis of such samples. The classical x-ray imaging methods, radiography and computed tomography (CT), are based on absorption, which works well for radiodense structures like bone, but gives limited contrast for textiles and soft tissues, which exhibit high x-ray transmission. Destructive methods, such as classical histology, have historically been used for analysing ancient soft tissue but the extent to which it is used today is limited because of the fragility and value of many ancient samples. For detailed, non-destructive analysis of ancient biological samples, we instead propose x-ray phase-contrast CT, which like conventional CT gives volume data but with the possibility of better resolution through the detection of phase shift. Using laboratory x-ray sources, we here demonstrate the capabilities of phase-contrast tomography of dried biological samples. Virtual histological analysis of a mummified human hand from ancient Egypt is performed, revealing remains of adipose cells in situ, which would not be possible with classical histology. For higher resolution, a lab-based nano-CT arrangement based on a nanofocus transmission x-ray source is presented. With an x-ray emission spot of 300 nm the system shows potential for sub-micronresolution 3D imaging. For characterisation of the performance of phase-contrast imaging of dried samples a piece of wood is imaged. Finally, we present the first phase-contrast CT data from our nano-CT system, acquired of the dried head of a bee.
Automatic Depression Level Detection via ℓp-Norm Pooling

Related physiological studies have shown that Mel-frequency cepstral coefficient (MFCC) is a discriminative acoustic feature for depression detection. This fact has led to some works using MFCCs to identify individual depression degree. However, they rarely adopt neural network to capture high-level feature associated with depression detection. And the suitable feature pooling parameter for depression detection has not been optimized. For these reasons, we propose a hybrid network and p-norm pooling combined with least absolute shrinkage and selection operator (LASSO) to improve the accuracy of depression detection. Firstly, the MFCCs of the original speech are divided into many segments. Then, we extract the segment-level feature using the proposed hybrid network, which investigates the depression-related information in the spatial structure, temporal changes and discriminative representation of short-term MFCC segments. Thirdly, p-norm pooling combined with LASSO is adopted to find the optimal pooling parameter for depression detection to generate the utterance-level feature. Finally, depression level prediction is accomplished using support vector regression (SVR). Experiments are conducted on AVEC2013 and AVEC2014. The results demonstrate that our proposed method achieves better performance than the previous algorithms.
Substantiation of auxiliary substances
of in the composition of tablets with dry extract of zingiber
officinale

Topicality. Due to its rich chemical composition and pharmacological activity, Zingiber officinale is a promising raw material for creating various drugs, including ones for the treatment of type 2 diabetes. Aim. To obtain tablets with dry ginger extract by direct pressing using polyfactorial dispersion analysis (taking into account the quality factors). Materials and methods. The objects of the study were dry ginger extract, filler – Galen IQ 721 and excipients of three technological groups: dry binders, moisture regulators and lubricants. The effect of auxiliary substances on such indicators as bulk density, tapped density and the Carr index of the tablet mass, as well as disintegration, mechanical strength and friability of the obtained tablets have been investigated. Results and discussion. Using the mathematical planning of the experiment by the 3 × 3 Latin square method, the influence of qualitative factors on the pharmacological indicators of tablets with a dry extract of ginger has been studied. Conclusions. According to the results of analysis of variance, the optimal excipients in the composition of tablets with ginger extract were chosen: from the group of binders – Kollidone k30, as a moisture regulator – Neusilin UFL 2 and lubricant – calcium stearate.
Vibrational spectra, normal coordinate analysis, and structure of keto form of acetylacetone. A DFT approach

In this paper, we discuss the stability, structure, and vibrational assignment of possible keto forms (Ket1 and Ket2) of acetylacetone, AA, in the gas phase and solutions. The geometry optimization and harmonic and anharmonic vibrational frequencies are calculated at the B3LYP/6-311++G** level. In addition, we also optimize the molecular structure at the MP2/6-311++G(p,d) level. The investigation in solutions is carried out by means of the PCM-SCRF method. We study the relative stability of Ket1 and Ket2 in different media using B2PLYP/6-31+G(d,p) and CBS-QB3 levels. By comparing the IR spectra of AA in a polar solvent, CH3CN, and a nonpolar solvent, CCl4, and considering the theoretical results, the vibrational band frequencies of both keto and enol tautomers are distinguished. Our calculations and vibrational spectra confirm the coexisting of two keto forms in the solutions, designated as Ket1 and Ket2. According to both theoretical and experimental results, Ket1 and Ket2 are predominant in the nonpolar and polar solutions, respectively. In addition, we also do a normal coordinate analysis by using the normal mode eigenvectors obtained at the B3LYP/6-311++ G(d,p) level. The observed vibrational wavenumbers, IR and Raman relative intensities, and Raman depolarization ratios of AA and its deuterated analogous agree satisfactorily with the calculated results obtained at the B3LYP/6-311++G(d,p) method.
Nitric oxide reduction with hydrogen over carbon-supported copper-iron oxides catalysts

Nitric oxide (NO) is an air pollutant generated during fuel combustion which is responsible for ground-level ozone, acid rain and smog formation. Current abatement technologies include reducing NO to nitrogen (N2) in the presence of a reductant, usually ammonia, and a catalyst. Replacing ammonia with a less-toxic reductant such as hydrogen (H2-SCR) requires the utilization of expensive precious metal as a catalyst supported on metal oxides. This study aims to evaluate the potential use of hydrogen as a renewable reductant; activated carbon as a sustainable catalyst support; and less-precious metals as a catalyst to selectively convert NO to N2. Mono- and bimetallic oxide catalysts were synthesized via incipient wetness method using copper, iron and manganese oxides supported over palm kernel shell activated carbon. Copper-based catalysts were proven to totally convert NO (100 %) in an oxidizing condition starting at 250 °C, while co-impregnating with iron oxide (PKSFeCu) improved N2 selectivity (eg. from 80 to 100 % at 200 °C) as well as lowering the carbon combustion rate (eg. from 3.1 to 2.3 μmol CO+CO2/s). The catalysts were characterized via elemental and metal content analyses, nitrogen adsorption-desorption, ammonia-temperature-programmed desorption, Fourier-Transform infra-red spectroscopy, hydrogen-temperature-programmed reduction, thermogravimetric analysis, and NO-temperature-programmed desorption. The conversion and selectivity were found to correlate strongly with the catalyst reducibility and acidity. Kinetic experiments revealed that the rate of reaction for H2-SCR using PKSFeCu obeys a power rate law with an order of 0.82 with respect to NO concentration. The stability test showed that the catalyst is susceptible to changes in physical properties under prolonged exposure to high temperatures and feed gas disturbance. Therefore, improvements in terms of catalyst stability should be the main focus of future work for this sustainable H2-SCR system to become an attractive alternative to NH3-SCR.
Rates of Mental Illnesses, Nativity and Generational Status in the U.S.: Heterogeneity among Caribbean Born Blacks, Blacks of Caribbean Descent and U.S. Born Blacks

America has continued to be increasingly diverse in culture and ethnicities. As such, these diverse populations require those in health and mental health fields to adjust to the cultural differences that arise. Central to these conversations is the impact of the acculturation process on immigrant populations. Researchers posit the stress of immigration and the acculturation process leads to increased rates of mental illness (Lang, Munoz, Bernal & Sorenson 1982; Masten, Penland & Nayani 1994; Neff & Hoppe 1993). Assuming that the acculturation process impacts first generation immigrants most, this study investigated U.S. born Blacks with and without Caribbean descent and Caribbean born Blacks residing in the U.S. to determine if nativity status and generational status impacts rates of mental illness. Using the National Survey of American Life (NSAL) dataset which is one of three research projects conducted from 2001 to 2003 by the Program for Research on Black Americans (PBRA), as part of the Research Center for Group Dynamics project, analyses were conducted to determine if relationships existed for these groups. Results indicated that mental illness is dependent on country of origin and U.S. born Blacks do self-report mental illnesses significantly more than Caribbean Blacks. Caribbean Blacks who are first generation in the U.S. are significantly less likely to report mental illness than second generation Caribbean Blacks. Differences in gender, work, number of years living in the U.S., age at immigration and wealth and poverty indicators all show some relationships with mental illnesses.
An Analysis of Local Monotonic Attention Variants

Speech recognition using attention-based models is an effective approach to transcribing audio directly to text within an integrated end-to-end architecture. Global attention approaches compute a weighting over the complete input sequence, whereas local attention mechanisms are restricted to only a localized window of the sequence. For speech, the latter approach supports the monotonicity property of the speech-text alignment. Therefore, we revise several variants of such models and provide a comprehensive comparison, which has been missing so far in the literature. Additionally, we introduce a simple technique to implement windowed attention. This can be applied on top of an existing global attention model. The goal is to transition into a local attention model, by using a local window for the otherwise unchanged attention mechanism, starting from the temporal position with the most recent most active attention energy. We test this method on Switchboard and LibriSpeech and show that the proposed model can even be trained from random initialization and achieve results comparable to the global attention baseline.
The Mechanism of Internet Capability Driving Knowledge Creation Performance: The Effects of Strategic Flexibility and Informatization Density

First, this study expands research on knowledge creation and focuses on the further achievement of knowledge creation performance. The study also enriches the exploration of KCP in the Internet context and deepens the research on the internal mechanism by which Internet capability influences KCP. Second, this study highlights the important role of informatization density in the Internet context and expands the research on the impact of external factors on the internal mechanism.
Millimeter-Wave Radar for Low-Power Applications

Radar technology has developed rapidly during the last century. Besides its initial use for military, it is nowadays also applied for many civil applications. Improvements in circuit technology make integrated radar sensors possible, allowing a significant reduction of the production cost. Integrated radio circuits in the low gigahertz range are widely available, not least driven by wireless communications. Even circuits at millimeter-wave frequencies are available, as they, for instance, are used for automotive radar. New semiconductor materials, devices, and circuit topologies offer interesting possibilities to increase the operation frequency and to reduce the power-consumption of radar circuits. With these developments, novel applications might open up, for instance the integration of radar in battery powered devices. In this thesis, different aspects of developing low-power millimener-wave radar technology are investigated. An efficient, coherent radar pulse generator is implemented. The circuit is based on a resonant-tunneling diode implemented with III-V semiconductors. A fast metal-oxide-semiconductor field-effect transistor is used to shape short pulses. A novel modulation technique is presented, enabling the generation of a phase modulated radar waveform, without additional power loss. Various low-power radar applications of the circuit are investigated. The characterization of porcine-skin is demonstrated, which might open up biomedical applications. It is shown that the scattering of low-power pulses on different hand postures can be detected with a pulsed radar. A setup for the real time acquisition of hand gestures with a pulsed radar is implemented and the successful classification of 12 hand gestures is demonstrated. Using this technique low-power systems with low duty cycle waveforms might be implemented.
Realizing the Interface Tuned Thermoelectric Transport Performance in Bi2Te3-Based Hierarchical Nanostructures

Hierarchical Te/Bi2Te3 and Bi2Te3 nanostructures are synthesized by using a one-pot solvothermal method and sintered into pellets by spark plasma sintering (SPS), individually. The thermoelectric properties measurement indicates the electrons/phonon transport is directly influenced by interface state of the hierarchical nanostructures. As compared to Te/Bi2Te3 heterostructures, the higher energy barrier at the interface of homostructured Bi2Te3 (71 meV) leads to the energy filtering effect on the electronic transport and the optimized power factor in the Bi2Te3 pellet. The thermal conductivity is remarkably reduced because of the strong scattering between phonons and high-density defects in both samples. As a result, an enhanced ZT value (0.58) of the Bi2Te3 nanowires was obtained at 353 K. Importantly, the average ZT (0.56), which is comparable to the peak ZT of both samples, is dramatically improved in these hierarchical nanostructures in the temperature range of 313–433 K.
Advances in Domain Adaptation Theory

All machine learning algorithms that correspond to supervised and semi-supervised learning work under a common assumption: training and test data follow the same distribution. When the distribution changes, most statistical models must be reconstructed from new data that may be costly or even impossible to get for some applications. It therefore becomes necessary to develop approaches that reduce the need for obtaining new labeled samples. This is accomplished by exploiting data available in related areas and using it further in similar fields. This has given rise to a new family of machine learning algorithms called transfer learning: a learning setting inspired by the capability of a human being to extrapolate knowledge across tasks to learn more efficiently. This book provides an overview of the state-of-the-art theoretical results in a specific – and arguably the most popular – subfield of transfer learning called domain adaptation.
The influence of different BRIR modification techniques on externalization and sound quality

In the context of binaural audio, externalization refers to the sensation of virtual sound sources being located outside of the listener's head. Binaural reproduction using anechoic head-related impulse responses is known to suffer from poor externalization. The degree of externalization can be increased by reverberation, as contained in binaural room impulse responses. However, the presence of reverberation is not always desired since the original sound of a recording should usually be preserved. This study concerns the dilemma of creating well-externalized dry-sounding signals. We investigated the manipulation of either the impulse response length, the reverberation time, or the direct-to-reverberant energy ratio regarding externalization and attributes of sound quality. As expected, each condition is a compromise between externalization and sound quality. While externalization increases with increasing amount of reverberation for all methods in a similar way, our findings show that the differences between them lie in sound color and perceived naturalness.