Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Vibration Control Based on Rigid-Body State Observer for Modular Joints

The vibration caused by resonance modes frequently occurs during acceleration and deceleration of the modular joint integrated with flexible harmonic drive. The conventional equivalent rigid-body velocity method with observer can suppress the residual vibration induced by resonant frequency but has poor robustness to model uncertainties and external disturbances. Moreover, it cannot eliminate the torque ripple caused by the harmonic drive during low-speed uniform motion, reducing the velocity tracking accuracy. Hence, a velocity controller with a rigid-body state observer and an adjustable damper is designed to improve the robust performance and velocity tracking accuracy. The designed rigid-body state observer allows a higher gain so that the bandwidth of the observer can increase, and the equivalent rigid-body velocity can be acquired more accurately. Notably, the high gain observer reduces the sensitivity to model uncertainties and exotic disturbances, especially near the resonant frequency. In addition, the observer combined with an adjustable damper can suppress the residual vibration and torque ripple simultaneously. The proposed method is compared experimentally with a PI method and two other rigid-body velocity methods, such as the conventional equivalent rigid-body observer method and the self-resonance cancellation method, to verify its advantages.
Multi‐Year Seasonal Trends in Sea Ice, Chlorophyll Concentration, and Marine Aerosol Optical Depth in the Bellingshausen Sea

This study presents seasonal trends in marine tropospheric aerosol arising from the interplay between physical and biological processes in the Western Antarctic Peninsula (WAP). Remote sensing‐based studies focused on aerosol distribution and links to chlorophyll‐a concentration and sea ice predominantly use passive sensor retrievals of aerosol optical properties. However, these data are subject to cloud presence, signal uncertainties, and lack of retrievals in high latitude wintertime. To address these concerns, we have developed a method of quantifying tropospheric marine aerosol with the NASA Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), which we term marine aerosol optical depth (MAOD). MAOD may be retrieved in nighttime conditions of high‐latitude winter and is devoid of cloud contamination, thereby advancing upon prior aerosol optical depth (AOD) measurements linked with biogenic aerosol. To examine trends in tropospheric marine aerosol, we undertook a multi‐year remote sensing analysis in the Bellingshausen Sea from 2006 to 2018. A seasonal increase in MAOD was observed alongside a seasonal increase in chl‐a and sea ice melt, suggesting a biogenic component to aerosol presence. To the best of our knowledge, this study is also the first to further distinguish a late winter to early spring temporal MAOD signal, likely tied to an aerosol source from either venting of biogenic aerosol from breaks in sea ice or to sea spray/salt aerosol resulting from pulses in wind speed. Our work extends upon previous findings of AOD in polar environments and now more fully characterizes interactions during polar winter.
Antecedents and consequences of green supply chain management practices: a study of Indian food processing industry

PurposeThis study aims to empirically test a comprehensive green supply chain management (GSCM) practices model. This paper incorporates green intellectual capital (GIC) and green supply chain orientation (GSCO) as antecedents to the successful implementation of GSCM practices and organizational performance as its consequence.Design/methodology/approachThis study has been conducted in the Indian food processing industry. The respondents of this study include 139 plant-level managers working in the food processing industry. The managers were contacted using a combination of personal visits, phone and mail. Structural equation modeling was performed using SPSS AMOS v26 to test the hypothesized model.FindingsThe findings of this study reveal that GIC and GSCO positively impact the implementation of GSCM practices. Further, GSCM practices improve economic and operational performance, leading to improved organizational performance.Practical implicationsThis study provides implications for managers suggesting that GSCM practices should be implemented in phases. The first phase must reflect the organization's commitment toward building GIC and the second phase must reflect managerial orientation toward implementation for GSCM practices.Originality/valueThis study adds to the existing literature by linking GIC to GSCM practices; second, this study provides a framework for implementation of GSCM practices in the food processing industry.
Efeito Antimicrobiano de Nano Partículas de Platina Sintetizadas a partir de Extratos Foliares de Anacardium occidentale L.

O incremento de bacterias multirresistentes promove a procura por novos compostos antimicrobianos de origem vegetal para o tratamento de doencas infecciosas. Nesse contexto se insere o extrato de Anacardium occidentale , conhecido como cajueiro, com conhecida atividade antimicrobiana e capacidade de sintese de nanoparticulas metalicas como as de platina. No presente trabalho foi avaliado o potencial do extrato foliar de A. occidentale para sintese de nanoparticulas de platina e sua atividade antimicrobiana contra Pseudomonas aeruginosa e Staphylococcus aureus. Para tanto, foram realizadas analises da fitocomposicao do extrato, caracterizacao das Nanoparticulas e de concentracao minima inibitoria. Os resultados mostraram que a associacao extrato de folha de cajueiro e nanoparticula de platina teve acao antimicrobiana contra as bacterias estudadas.
Understanding Sexual Agency. Implications for Sexual Health Programming

Debates on human agency, especially female and sexual agency, have permeated the social scientific literature and health educational practice for multiple decades now. This article provides a review of recent agency debates illustrating how criticisms of traditional conceptions of (sexual) agency have led to a notable diversification of the concept. A comprehensive, inclusive description of sexual agency is proposed, focusing on the navigation of goals and desires in the wider structural context, and acknowledging the many forms sexual agency may take. We argue there is no simple relation between sexual agency and sexual health. Next, we describe the implications of such an understanding of sexual agency for Comprehensive Sexuality Education (CSE) and for sexual health and rights (SHR) programming more generally. We put forward validation of agentic variety, gender transformative approaches, meaningful youth participation, and multicomponent strategies as essential in building young peoples’ sexual agency and their role as agents of wider societal change. We also show that these essential conditions, wherever they have been studied, are far from being realized. With this review and connected recommendations, we hope to set the stage for ongoing, well-focused research and development in the area.
Ultralow-Power and Secure S-Box Circuit Using FinFET Based ECRL Adiabatic Logic

Advanced Encryption Standard (AES) is the widely used technique in critical cyber security applications. In AES architecture S-box is the most important block. However, the power consumed by S-box is 75% of the total AES design. The S-box is also prone to Differential Power Analysis (DPA) attack which is one of the most threatening types of attacks in cryptographic systems. In this paper, a three-stage positive polarity Reed-Muller (PPRM) S-box is implemented with 45nm FinFET using Efficient Charge Recovery Logic (ECRL) to reduce power consumption. The simulation results indicate up to 66% power savings for FinFET based S-box as compared to CMOS design. Further, the FinFET ECRL 8-bit S-box circuit is evaluated for transitional energy fluctuations and peak current traces to compare its resistance against side-channel attacks. The lower energy variations and uniform current trace exhibit the improved security performance of the circuit to withstand DPA and Differential Electromagnetic Radiation Attacks (DEMA).
C677T methylenetetrahydrofolate reductase polymorphism, folate and homocysteine levels and the risk of colorectal cancer

Aim: Colorectal cancers are common in the world and many factors play a role. MTHFR (methylenetetrahydrofolate reductase) gene polymorphisms cause a predisposition to cancer formation. C677T polymorphism is the most common among these. To evaluate the role of MTHFR polymorphisms in colorectal carcinogenesis, we examined the associations between MTHFR mutations, homocysteine levels, plasma folate levels and colorectal cancer risk.Materials and Methods: During two years period, 101 naive colorectal cancer cases and 95 controls were enrolled to the study and groups were matched for age, sex and smoking. The presence of the mutation was determined by real-time PCR amplification of genomic DNA using Light.Results: Although only 1 of the cancer patients was homozygous mutant Val/Val, this mutation was present in 10.5% of the control group and this difference was statistically significant (p<0.05). We observed a significant increased risk of colorectal cancer (OR, 0.04; 95% CI, 0.005-0.304) among those with low plasma folate levels (≤3 ng/ml) compared to subjects with adequate levels. However, in both case and control groups mean folate levels were high (10.3 and 10.7 ng/ml, respectively). Homocysteine levels were significantly higher in patients with colorectal cancer compared to healthy volunteers (p <0.05). Conclusion: The data in our study suggested that the MTHFR val/val mutation did not cause a predisposition to cancer development. The presence of a polymorphism other than val/val mutation in the MTHFR enzyme suggests that it may be associated with elevated levels of homocysteine and low folate in cancer patients.
Structural Analysis of 8/6 Switched Reluctance Motor Linear and Non-linear Models

This work presents the process of obtaining the simplified model of a switched reluctance motor (SRM) 8/6. Subsequently, the structure of the single-phase model is analyzed, obtaining an exact linearization and zero dynamics of the system. Finally, the model is linearized at an operating point set at 2000 rpm The model includes Coulomb plus viscous friction nonlinearity and an ideal inverter circuit based on bridge converter topology. The simplified and linear models are simulated and compared in the Matlab®/Simulink software in order to validate the design of a classic controller using the linear model.
CO2 Leakage Rate Forecasting Using Optimized Deep Learning

Geologic CO2 Sequestration (GCS) is a promising engineering technology to reduce global greenhouse emissions. Real-time forecasting of CO2 leakage rates is an essential aspect of large-scale GCS deployment. This work introduces a data-driven, physics-featuring surrogate model based on deep-learning technique for CO2 leakage rate forecasting. The workflow for the development of data-driven, physics-featuring surrogate model includes three steps: 1) Datasets Generation: We first identify uncertainty parameters that affect the objective of interests (i.e., CO2 leakage rates). For the identified uncertainty parameters, various realizations are then generated based on Latin Hypercube Sampling (LHS). High-fidelity simulations based on a two-phase black-oil solver within MRST are performed to generate the objective functions. Datasets including inputs (i.e., the uncertainty parameters) and outputs (CO2 leakage rates) are collected. 2) Surrogate Development: In this step, a time-series surrogate model using long short-term memory (LSTM) is constructed to map the nonlinear relationship between these uncertainty parameters as inputs and CO2 leakage rates as outputs. We perform Bayesian optimization to automate the tuning of hyperparameters and network architecture instead of the traditional trial-error tuning process. 3) Uncertainty Analysis: This step aims to perform Monte Carlo (MC) simulations using the successfully trained surrogate model to explore uncertainty propagation. The sampled realizations are collected in the form of distributions from which the probabilistic forecast of percentiles, P10, P50, and P50, are evaluated. We propose a data-driven, physics-featuring surrogate model based on LSTM for CO2 leakage rate forecasting. We demonstrate its performance in terms of accuracy and efficiency by comparing it with ground-truth solutions. The proposed deep-learning workflow shows promising potential and could be readily implemented in commercial-scale GCS for real-time monitoring applications.
Neuroimaging of pleasantness and unpleasantness induced by thermal stimuli

ABSTRACT Functional brain imaging techniques provide unique insight into the process of human thermal regulation and its associated hedonics. Similar neuroimaging techniques have predominantly focused on the neural characterization of thermal response separately from hedonics. In this instance, there is a gap in the understanding of hedonics related to regional brain activations. Responses to localized, thermal stimuli are yet to be characterized, but it would appear that thermoregulatory regions are widely distributed throughout the hemispheres of the human brain. The distributed nature of neural activations related to temperature responses is consistent with multiple related functions contributing to thermoregulation. Estimating hedonics of thermal stimulation includes a cognitive process that could potentially interfere with identifying activation specific to hedonics. A future challenge for brain imaging studies is to more accurately dissect the functional neuroanatomy of thermoregulation and related hedonics in hemispheric regions.
Recent Progress in Rechargeable Potassium Batteries

The topic of sustainable and eco‐friendly energy storage technologies is an issue of global significance. To date, this heavy burden is solely addressed by lithium‐ion battery technology. However, the ongoing depletion of limited global lithium resources has restricted their future availability for Li‐ion battery technology, and hence, a significant price increase is expected. This grim situation is the driving force for the development of the “beyond Li‐ion battery” strategy involving alternatives that have several advantages over conventional Li‐ion batteries in terms of cost, durability, safety, and sustainability. Potassium, the closest neighboring alkali element after sodium, offers some unique advantages over lithium and sodium as a charge carrier in rechargeable batteries. Potassium intercalation chemistry in potassium‐ion batteries (KIBs) is successfully demonstrated to be compatible with Li‐ion batteries and sodium‐ion batteries. In addition to KIBs, potassium–sulfur and potassium–oxygen batteries have emerged as new energy‐storage systems due to their low costs and high specific energy densities. This review covers the key technological developments and scientific challenges for a broad range of rechargeable potassium batteries, while also providing valuable insight into the scientific and practical issues concerning the development of potassium‐based rechargeable batteries.
Racial and ethnic disparities in nasopharyngeal cancer with an emphasis among Asian Americans

Despite the overall decreasing incidence, nasopharyngeal cancer (NPC) continues to cause a significant health burden among Asian Americans (AAs), who are a fast‐growing but understudied heterogeneous racial group in the United States. We aimed to examine the racial/ethnic disparities in NPC incidence, treatment, and mortality with a specific focus on AA subgroups. NPC patients aged ≥15 years were obtained from the Surveillance, Epidemiology, and End Results (SEER) 18 (1975‐2018). AAs were divided into Chinese, Filipino, Vietnamese, Hawaiian, Japanese, Laotian, Korean, Cambodian, Indian/Pakistani and other Asian/Pacific Islanders (APIs). Age‐adjusted incidence was calculated using the SEER*Stat software. Cox proportional and Fine‐Gray subdistribution hazard models were used to calculate overall and cause‐specific mortalities after adjusting for confounders. Among the total 11 964 NPC cases, 18.4% were Chinese, 7.7% Filipino, 5.0% Vietnamese, 1.2% Hawaiian, 1.0% Japanese, 0.8% Laotian, 0.8% Korean, 0.6% Cambodian, 0.5% Indian/Pakistani and 4.4% other APIs. Laotians had the highest age‐adjusted NPC incidence (9.21 per 100 000), which was 18.04 times higher than it in non‐Hispanic Whites (NHWs). Chinese and Filipinos observed lower overall mortalities, however, Chinese saw increased NPC‐specific mortality than NHWs. Disparities in mortality were also found across different histology subtypes. This is the first and largest study examining the NPC incidence and outcomes in AA subgroups. The significant disparities of NPC within AAs underline the importance of adequate AA‐subgroup sample size in future studies to understand the prognostic role of ethnicity in NPC and advocate more ethnically and culturally tailored cancer prevention and care delivery.
Effects of PM10 on Sebocytes, Outer Root Sheath Cells, and Cutibacterium acnes-Pretreated Mice Were Inhibited by Punicalagin

Background: Particulate matter (PM) is an air pollutant that can damage human skin. Antioxidants have been tested to improve skin inflammation induced by PM. Objective: We investigated the effects of punicalagin on PM-induced inflammation on cultured human sebocytes, outer root sheath (ORS) cells, and Cutibacterium (C.) acnes-pretreated mice. Methods: Sebocytes and ORS cells were cultured and treated with 5-μM punicalagin and 100-μg/mL PM10 for 24 h. On C. acnes-pretreated mice, 5-μM punicalagin and 100-μg/mL PM10 were applied. Cell viability was measured for MTT assay. Real-time PCR and measurement of reactive oxygen species as well as sebum production were conducted to analyze its effects. Results: Upregulation of the gene expression of inflammatory cytokines, matrix metalloproteinase, aryl hydrocarbon receptor, and NF-kB by PM10 in cultured sebocytes and ORS cells and the increase in the production of reactive oxygen species (ROS) by PM10 in cultured sebocytes were inhibited by punicalagin. Moreover, punicalagin decreased inflammatory cytokines, matrix metalloproteinase, and sebum production in C. acnes-pretreated mice. Conclusions: Punicalagin effectively reduces the expression of inflammatory biomarkers and the production of sebum in cultured sebocytes, ORS cells, and C. acnes-pretreated mice.
Restoration of light parameters and forming criteria for the quality estimation of visual perception in mixed reality systems using neural networks

One of the main problems of mixed reality devices is the physically correct representation of the luminance distribution for virtual objects and their shadows in the real world. In other words, restoring the correct distribution of scene luminance is one of the key parameters that allows solving the problem of correct interaction between the virtual and real worlds. The paper proposes methods for restoring the parameters of light sources. Also, the work is aimed at the creation and formation of criteria for the quality of visual perception, allowing to evaluate the synthesized image of mixed reality and to decide how natural it is from the point of view of the observer. In this article, surveys were used to create datasets using realistic software tools. In work the neural network is trained to recognize those areas of the image that do not fit into the environment and to classify this image as a class that causes visual discomfort. As criteria for the quality of visual perception, it is proposed to use estimates of the mismatch of the parameters of shadows cast by virtual objects and the distribution of luminance over these objects in the images of scenes containing models of "real" and "virtual" objects. The level of misalignment is estimated concerning the true lighting conditions of the real world. In this work, criteria for the quality of visual perception were formed and a neural network was trained, which makes it possible to decide and analyze the quality of a synthesized mixed reality image.
Numerical Modeling of Localized Corrosion Using Phase-Field and Smoothed Boundary Methods

A modeling framework is presented for localized corrosion of metals. This model employs the phase-ﬁeld and smoothed boundary method to track the moving metal/electrolyte interface and to couple it to mass transport within the electrolyte and Butler-Volmer electrochemical kinetics. A microscopic expression of the maximum current is derived that smoothly captures the transition from activation- to IR- and transport-controlled kinetics. Simulations of pitting corrosion are performed to highlight the capabilities of this framework. One-dimensional simulations are conducted to predict corrosion-pit depth as a function of time for multiple ﬁxed applied potentials. The results indicate a transition from activation-controlled kinetics to ﬁrst IR-controlled and then transport-controlled kinetics with increasing applied potentials. Two-dimensional simulations are also performed with and without a protective surface layer. Without the inert surface layer, the pit spreads as the sides of the pit corrode faster due to facile mass transport to the bulk electrolyte. With a protective surface layer, simulation results predict semi-circular pit growth at a slower rate due to limited mass transport. Both results agree with experimental observations. Finally, simulations are conducted to illustrate the model’s capability to study polycrystalline and precipitate microstructures. from saturation throughout the simulation, and thus the maximum current is dominated by i smax , c . However, the maximum value of i rxn / i max , c is about 0.052; thus the maximum current has a minimal impact on the observed current density. In comparison, for the 100 mV vs. SCE case, the concentration is asymptotically approaching saturation and i mmax , c is the dominant component of the maximum current density. The minimum value of i rxn / i max , c is 0.889 and the maximum value is 0.999, therefore the current density is strongly transport-controlled. a typographical The second on the a sign order to be consistent with the sign convention of Eq. than the plus sign The below.
Chemical Composition and Antimicrobial Activity of Essential Oils from Xylopia aromatica (Annonaceae) Flowers and Leaves

The essential oils (EO) from flowers and leaves were obtained by hydrodistillation and analyzed by gas chromatography-mass spectrometry. The main compounds found in the flower oil were pentadecan-2-one (16.38%), bicyclogermacrene (9.74%) 7-epi-α-eudesmol (7.76%), khusinol (7.23%), n-tricosane (6.17%), heptadecan-2-one (5.83%), geranyl-α-terpinene (4.46%) and cedr-8(15)-en-9α-ol (4.40%). The leaf oil contained predominantly spathulenol (27.11%), khusinol (13.04%), bicyclogermacrene (8.52%), globulol (6.47%), cis-guaia-3,9-dien-11-ol (5.98%), 2-epi-α-cedren-3-one (4.69%) and elemicin (4.32%). The antimicrobial activity of the EO was tested against Gram-positive and Gram-negative bacterial strains and fungi. The flower and leaf oils exhibited the lowest minimum inhibitory concentrations (MIC) against Streptococcus pyogenes ATCC 12345 (200 and 100 µg mL-1 respectively). As for antifungal potential, the EO from leaves showed moderate activity (500 µg mL-1) against Candida albicans. This study offers the first report about the chemical composition and antimicrobial activity of the EO from X. aromatica flowers and contributes to the body of knowledge about this species.