Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiobjective Vector Modulation for Improved Control of NPC-Based Multi-Source Inverters in Hybrid Traction Systems

The concept of a multi-source inverter (MSI) based on NPC topology was recently introduced for hybrid-electric powertrains to connect several dc sources to the traction load in a single conversion stage without magnetics. This work proposes a new modulation algorithm that integrates the tasks of dc currents and ac voltages control at the level of pulsewidth modulation by means of the space-vector formalism. The proposed algorithm allows the MSI to have full control of the dc input currents and fundamental ac output voltages, and enables a higher number of feasible operating modes, including load power sharing between sources and controlled recharging of one source from the other, both in motion and at standstill. Hence, improved control capability of the load and sources is achieved with respect to the state-of-literature modulation approach. To validate the proposed modulation under different operating conditions, steady-state and dynamic tests are performed on a small-scale traction system fed by a primary dc supply and a battery pack. The results are compared with those of the baseline control approach and show that the proposed technique improves the smoothness and flexibility of the control action and reduces the distortion of currents and voltages while ensuring the same converter efficiency.
Multivariate Kalman filter regression of confounding physiological signals for real-time classification of fNIRS data

Abstract. Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human cortex related to neural function. Due to its potential for miniaturization and relatively low cost, fNIRS has been proposed for applications, such as brain–computer interfaces (BCIs). The relatively large magnitude of the signals produced by the extracerebral physiology compared with the ones produced by evoked neural activity makes real-time fNIRS signal interpretation challenging. Regression techniques incorporating physiologically relevant auxiliary signals such as short separation channels are typically used to separate the cerebral hemodynamic response from the confounding components in the signal. However, the coupling of the extra-cerebral signals is often noninstantaneous, and it is necessary to find the proper delay to optimize nuisance removal. Aim: We propose an implementation of the Kalman filter with time-embedded canonical correlation analysis for the real-time regression of fNIRS signals with multivariate nuisance regressors that take multiple delays into consideration. Approach: We tested our proposed method on a previously acquired finger tapping dataset with the purpose of classifying the neural responses as left or right. Results: We demonstrate computationally efficient real-time processing of 24-channel fNIRS data (400 samples per second per channel) with a two order of selective magnitude decrease in cardiac signal power and up to sixfold increase in the contrast-to-noise ratio compared with the nonregressed signals. Conclusion: The method provides a way to obtain better distinction of brain from non-brain signals in real time for BCI application with fNIRS.
Solar flare hard X-rays measured by spectrometer “IRIS”: spectral and temporal characteristics

Sub-second time structure of hard X-rays observed during solar flares by spectrometer “IRIS” on a board of CORONAS satellite are discussed. The burst duration of 80ms and FWHM about 30ms are recorded in powerful flare of August 20, 2002 year at 0828:16.77 UT. A confidence level of this peak is 6$\sigma$. To search for other articles by the author(s) go to: http://adsabs.harvard. edu/abstract_service. html
Generalized conifolds and four dimensional Script N = 1 superconformal theories

This paper lays groundwork for the detailed study of the non-trivial renormalization group flow connecting supersymmetric fixed points in four dimensions using string theory on AdS spaces. Specifically, we consider D3-branes placed at singularities of Calabi-Yau threefolds which generalize the conifold singularity and have an ADE classification. The = 1 superconformal theories dictating their low-energy dynamics are infrared fixed points arising from deforming the corresponding ADE = 2 superconformal field theories by mass terms for adjoint chiral fields. We probe the geometry with a single D3-brane and discuss the near-horizon supergravity solution for a large number N of coincident D3-branes.
Controversies in cleft lip & palate: A literature review

Orthodontics is the branch where great pioneers exists and they come with varying opinion leading to controversies. Nasoalveolar molding (NAM) is a form of presurgical infant orthopedics (PSIO) whose goal is to reduce the severity of the cleft deformity and improve surgical outcomes. The data on efficacy and benefit of NAM are mixed. Those in favor of NAM report improved nasal symmetry and appearance, reduced overall costs, psychosocial benefit to family, and decreased need for early nasal revision. Those in opposition to NAM argue NAM causes increased caregiver burden, poor patient compliance, increased costs in the short term, relapse of nasal symmetry in the first year, and no conclusive data of improved outcomes. For cleft palate repair controversy exist with timing of cleft repair, each with it’s own advantage and disadvantage with no conclusive results. These two controversies has been discussed here.
Slopes of powers of Frobenius on crystalline cohomology

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A Low-Power Delta-Modulation-Based ADC for Wearable Electrocardiogram Sensors

In this brief, a new ultra-low power analog-to-digital converter (ADC) based on delta (<inline-formula> <tex-math notation="LaTeX">${\Delta }$ </tex-math></inline-formula>)-modulation approach is presented for wearable Electrocardiogram (ECG) sensor systems. In the proposed structure, a voltage-to-time converter (VTC) is employed as the residue quantizer in <inline-formula> <tex-math notation="LaTeX">${\Delta }$ </tex-math></inline-formula>-modulation based ADC circuit. So, the requirement on the high-frequency sampling rate in such ADCs is relaxed and it can be realized with low-power consumption. This structure produces one-bit output data wherein the pulse-width of output data at every clock cycle is proportional to the input signal variation. Therefore, the output data rate is significantly reduced. The proposed ADC is designed in TSMC 0.18 <inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> CMOS technology and post-layout simulation results exhibit maximum 10.9 effective number of bits (ENOB) with 68.12 nW power from a 0.8 V power supply. This ADC circuit achieves a peak signal-to-noise and distortion ratio (SNDR) about 67.4 dB over ECG signal bandwidth with 4 kHz sampling frequency and occupies about 0.02 mm<sup>2</sup> silicon die area.
A Parallel Fast-Track Service Restoration Strategy Relying on Sectionalized Interdependent Power-Gas Distribution Systems

In the distribution networks, catastrophic events especially those caused by natural disasters can result in extensive damage that ordinarily needs a wide range of components to be repaired for keeping the lights on. Since the recovery of system is not technically feasible before making compulsory repairs, the predictive scheduling of available repair crews and black start resources not only minimizes the customer downtime but also speeds up the restoration process. To do so, this article proposes a novel three-stage buildup restoration planning strategy to combine and coordinate repair crew dispatch problem for the interdependent power and natural gas systems with the primary objective of resiliency enhancement. In the proposed model, the system is sectionalized into autonomous subsystems (i.e., microgrid) with multiple energy resources, and then concurrently restored in parallel considering cold load pick-up conditions. Besides, topology refurbishment and intentional microgrid islanding along with energy storages are applied as remedial actions to further improve the resilience of interdependent systems while unpredicted uncertainties are addressed through stochastic/information gap decision theory (IGDT) method. The theoretical and practical implications of the proposed framework push the research frontier of distribution restoration schemes, while its flexibility and generality support application to various extreme weather incidents.
Does Air Pollution Impact on Semen Parameters? Findings from a Real-Life, Cross-Sectional Study in Italian Infertile Men

Purpose In industrialized countries, air pollutants levels have been monitored closely for environmental and research issues. Using Italian data, we aimed to investigate the association between air pollutants levels and semen parameters in a cohort of non-Finnish white-European men presenting for couple’s infertility. Materials and Methods Complete demographic and laboratory data from 1,152 infertile men consecutively assessed between January 2015 and January 2018 were analyzed. Semen analyses were based on the 2010 World Health Organization reference criteria. Health-significant comorbidities were scored with the Charlson Comorbidity Index (CCI). We analyzed the annual average level of the three main markers of air pollution (Pm10, Pm2.5, and NO2) between 2014 and 2018. Descriptive statistics, linear and logistic regression analyses tested the association between air pollutants levels and semen parameters. Results Of 1,152 men, 87 (7.55%) had normal sperm parameters at first semen analysis. Of 1,065 patients with abnormal semen analyses, 237 (22.25%), 324 (30.42%), and 287 (26.95%) patients presented 1, 2 or 3 abnormalities, respectively, and 217 (20.38%) were azoospermic. At linear regression analysis, Pm10, Pm2.5, and NO2 were negatively associated with sperm morphology (Pm10: β=-0.5288 µg/m3, p=0.001; Pm2.5: β=-0.5240 µg/m3, p=0.019; NO2: β=-0.4396 µg/m3, p<0.0001). Furthermore, the adjusted odds of normal sperm morphology <4% were 1.06 (95% confidence interval [CI], 1.03–1.09; p=0.007) for Pm10, 1.07 (95% CI, 1.03–1.11; p=0.007) for Pm 2.5, and 1.03 (95% CI, 1.02–1.05; p=0.001) for NO2, respectively. Conclusions In a large homogenous cohort of infertile men, Pm10, Pm 2.5, and NO2 levels were negatively associated with sperm morphology. Conversely, no clear association was observed with other macroscopic sperm parameters.
Adaptive sliding mode-based active disturbance rejection control for a quadcopter

This paper presents an adaptive sliding mode-based active disturbance rejection control (ASM-ADRC) strategy for the altitude and attitude control of an unmanned quadcopter with disturbances. The quadcopter is an underactuated system subject to parametric perturbations, nonlinearity, unmodeled dynamics, strong coupling, and external disturbances. The proposed algorithm is based on the quadcopter’s dynamic model, where the effects of noise and wind are considered additive disturbances. The central concept is to combine the advantages of adaptive sliding mode control (SMC) to accurately track the reference trajectory with the ability of ADRC to reject the parameter uncertainties and external disturbances. The proposed control scheme is verified in simulation studies with sensor noise and external disturbances. The simulation results show that the proposed algorithm can significantly reduce the chattering phenomenon, owing to the estimation capability of the extended state observer (ESO). The proposed method also improves the robustness against modeling errors and disturbances and smoothly tracks the reference trajectory.
Validation of the Effect of Some Nutritional Manipulations on the Productive Performance of Broiler Chickens

The objectives of the experiment were to investigate the effects of different nutritional manipulations on the performance and carcass traits of broiler chickens. Seven treatments were used: control, super pre-starter diet (25% P) during the first three days of age, mix. of 2g of both yeast and glucose anhydrous, 2g synbiotic / Kg feed, 20g / 500 ml water of synbiotic spraying, mix. of 2g synbiotic / Kg feed+20g / 500 ml water of synbiotic spraying and mix. of super pre-starter diet (25% P) and 2g synbiotic / Kg feed. Two hundred eighty, one day old of broiler chicks were randomly selected in experiment lasted in 6 weeks of age. Body weight, feed consumption, body weight gain, feed conversion ratio and some carcass traits were studied. The results indicated that there was significant (P<0.05) increase in body weight due to super pre-starter supplementation at 4, 5 and 6 weeks of age. Body weight gain, feed consumption and feed conversion ratio were significantly (P<0.05) improved during the periods from (3-6) and (0-6) weeks of age. Dressed carcass percentage was increased significantly (P<0.05) in chicks fed mix. of synbiotic in feed and spray compared to the other treatments, the increased was 79.77% compared to control one (75.14%). Breast% was increased in chicks fed mix. of yeast and glucose anhydrous and also in chicks fed synbiotic in feed. Results concluded that using of super pre-starter diet during the first 3 days of age at level of (25% P) improved growth performance of broiler chicks.
Validity and Reliability of the Vietnamese Version of Chronic Obstructive Pulmonary Disease-Questionair for Measuring Knowledge of Chronic Obstructive Pulmonary Disease Patients

Objective: The purpose of this study was to translate, and verify the validity and reliability of the Vietnamese version of Chronic Obstructive Pulmonary Disease-Questionair (COPD-Q), so as to measure the knowledge level of COPD patients in Vietnam.Material and Methods: The adaptation and psychometric characteristics test of Vietnamese-COPD-Q was performed, with 90 participants; from July 2021 to February 2022. Our study included 30 COPD patients for pre-testing and adaptation of the translated version; whereas, 60 patients were considered for test-retest reliability. The content validity of the questionnaire was measured by the opinions of five experts. For concurrent validity assessment, Pearson's correlation coefficient was used to test the association between COPD-Q and the COPD assessment test (CAT) scale; the modified British Medical Research Council (mMRC) dyspnea scale. The Kuder-Richardson 20 (KR20) statistical test was used to measure the internal consistency of the questionnaire, while the test-retest reliability was measured using Intra-Class Correlation.Results: The Vietnamese version of COPD-Q demonstrated good content validity, with the Items content validity index (I-CVI) score for all 13 items >0.79. Negative, significant correlations with mMRC scale (r=-0.859, p-value=0.000), and CAT scale (r=-0.861, p-value=0.000) demonstrated good, concurrent validity. Additionally, internal consistency (KR20 with pre-and post-test as 0.883 and 0.866, respectively) and test–retest reliability (r=0.996, p-value=0.000) was identified with good result.Conclusion: The knowledge measurement properties of the V-COPD-Q for COPD patients with low health literacy skills were satisfactory.
Direct quantification of epistemic and aleatoric uncertainty in 3D U-net segmentation

Abstract. Purpose: To derive a multinomial probability function and quantitative measures of the data and epistemic uncertainty as direct output of a 3D U-Net segmentation network. Approach: A set of T1 brain MRI images were downloaded from the Connectome Project and segmented using FMRIB’s FAST algorithm to be used as ground truth. A 3D U-Net neural network was trained with sample sizes of 200, 500, and 898 T1 brain images using a loss function defined as the negative logarithm of the likelihood based on a derivation of the definition of the multinomial probability function. From this definition, the epistemic and aleatoric uncertainty equations were derived and used to quantify maps of the uncertainty along with tissue segmentations. Results: Maps of the tissue segmentation along with the epistemic and aleatoric uncertainty, per voxel, are presented. The uncertainty decreased based on the increasing number of training data used to train the neural network. The neural network trained with 898 volumes resulted in uncertainty maps that were high primarily in the tissue boundary regions. The epistemic and aleatoric uncertainty were averaged over all test data (connectome and tumor separately), and the epistemic uncertainty showed a decreasing trend, as expected, with increasing numbers of data used to train the model. The aleatoric uncertainty showed a similar trend which was also expected as the aleatoric uncertainty is not expected to be as dependent on the number of training data. Conclusion: The derived uncertainty equations from a multinomial probability distribution were able to quantify the aleatoric and epistemic uncertainty per voxel and are applicable for all two-dimensional and three-dimensional neural networks.
Mapping the long‐term influence of river discharge on coastal ocean chlorophyll‐a

Although the potential of river discharge to support ocean productivity and marine ecosystems is known, the specifics of this relationship are poorly understood in many regions of the world. Global estimates of river flow indicate that river discharge is decreasing due to the increasing fragmentation, extraction and regulation of rivers. This likely means that the contribution of river flow to coastal productivity and water quality is changing, potentially leading to fewer and smaller magnitude ocean fertilisation events. We developed a simple analysis method, based on Earth observation data, to investigate where coastal ocean chlorophyll‐a is most strongly influenced by river discharge. The per‐pixel spatiotemporal correlation technique (implemented using Python) correlates chlorophyll‐a concentration (a proxy for phytoplankton biomass and indicator of primary productivity) from MODIS ocean colour data with river discharge data. The method was tested globally on 11 different rivers discharging into coastal ocean regions. Our findings suggest some of the world's largest river systems, such as the Amazon River, have zones of elevated coastal chl‐a that extend hundreds to thousands of km from the river mouth. These findings suggest the influence of river discharge may have been underestimated in many coastal regions of the world. The method appears more effective for larger river systems discharging to ocean waters with less complex nutrient dynamics and weaker seasonal productivity patterns, most notably in temperate regions. Increasing our understanding of the specific areas influenced by river discharge, and the degree of influence over space and time, is an important step towards the improved river and coastal management. This method will increase the capacity of researchers to monitor how, when and where coastal waters are affected as river discharge continues to change into the future.
Exploring qualitative data as predictors for M&A: Empirical analysis of target firms’ letters to shareholders

Abstract M&A prediction is a growing interest in the field of business studies. However, prevailing M&A prediction techniques are still widely based from the analyses of financial variables through quantitative approaches. This has led M&A scholars’ attention to call for the contribution of non-financial studies coupled with the opportunity for qualitative approaches to supplement new methodological insights. Accordingly, this study delved to explore the potential of qualitative data to describe M&A target firms and develop an M&A completion prediction model that is based on categorical patterns found among American and European owned firms’ letters to shareholders ranked in fortune/global/fast 500. This study postulates that analyzing M&A targets’ letters to shareholders could provide relevant categories to describe the attractiveness of firms as M&A targets that are also indicative to the prediction of the completion of the offered deals. This study employed a mixed methodology using content analysis and decision tree analysis. The results of the study had led to provide four interesting category observations that described M&A target firms’ letters to shareholders, which showed less sensitivity to ownership and border-related offers. Further, the study developed an M&A completion prediction model with 67% predictive accuracy. This study provides implications for firms’ management on the posturing contents featured in firm’s letters to shareholders could expose to signal their firms as M&A targets and to readers as such as stock traders and corporate investors to look into the posturing contents of firms’ letters to shareholders, so as to identify potential M&A targets.
The influence of reproductive hormones on systemic lupus erythematosus

Humans are afflicted by a wide spectrum of autoimmune disorders, ranging from those affecting just one or a few organs to those associated with more systemic effects. In most instances, the etiology of such disorders remains unknown; a consequence of this lack of knowledge is a lack of specific treatment options. Systemic lupus erythematosus (SLE) is the prototypic systemic autoimmune disorder; pathology is believed to be antibody-mediated, and multiple organs are targeted. Periods of disease “flares” are often followed by long periods of remission. The fact that SLE is more commonly observed in females, and also that it more particularly manifests in females in the reproductive age group, has quite naturally drawn attention to the potential roles that hormones play in disease onset and progression. This review attempts to shed light on the influences that key hormones might have on disease indicators and pathology. Databases (Google Scholar, PubMed) were searched for the following keywords (sometimes in certain combinations), in conjunction with the term “lupus” or “SLE”: autoantibodies, recurrent abortion, polycystic ovarian syndrome (PCOS), preeclampsia, pre-term delivery, estrogens, progesterone, androgens, prolactin, leptin, human chorionic gonadotropin (hCG). Cited publications included both research articles and reviews.