Miracle-dz/UniFAR-FTUs huggingface dataset:
A Learning-Based Multisensor Fingertip Force Measurement Method With Fast Data Generation

Force measurements become important once contact has occurred and the object is held or explored by the hand. The uncertainty associated with the fingertip contact position and the soft finger contact torque can lead to inaccurate force measurement when using a model-based method. To address this issue, we utilized a learning-based method that leverages neural networks to concatenate data from tactile, position, and torque sensors to improve force measurement accuracy in soft finger contacts. Due to the requirement for a large volume of data to train the network, we propose a data collection method that is independent of the fingers. This method utilizes the physical model of the finger to rapidly generate a large dataset. The effectiveness of this data collection method is validated on real-world datasets. Comparing the model-based method and the data-driven method using solely tactile input, our proposed force measurement method achieves the lowest force errors in all three axes and magnitude. Particularly, in the ${x}$ -axis and force magnitude, the proposed method reduces the error by more than 50% compared to the model-based method. Furthermore, our method demonstrates effectiveness and robustness on unseen objects. This method is not only suitable for dexterous hands but also applicable to underactuated hands equipped with torque sensors and high-dimensional tactile.
Quantum Sensing of Fast Time-Varying Magnetic Field With Daubechies Wavelets

The waveform of the time-varying magnetic field can be reconstructed by combining the use of quantum sensing technology and orthogonal functions, such as Walsh and Haar wavelet functions, as the control sequences of qubits. However, the piecewise-constant nature of Walsh and Haar wavelet functions induces pulse-shaped artifacts in the reconstructed waveform. In this article, we propose a robust quantum sensing protocol by driving the qubits with control sequences based on high-smoothness Daubechies wavelets. The time-varying magnetic field waveform is reconstructed with negligible artifacts and higher accuracy. The essential mathematical relations between the qubit readout, the accumulated phase of the quantum state, and the wavelet coefficient are derived based on an intuitive model represented on the Bloch sphere. By controlling each qubit with a continuous microwave control sequence modulated by a Daubechies wavelet function, the yielded qubit readout can be related to a designated wavelet coefficient. These coefficients are then used to reconstruct the time-varying magnetic field waveform with higher smoothness and accuracy via an inverse wavelet transform. The reconstructions of single-tone, triple-tone, and noisy waveforms are simulated under various parameter designs of Daubechies wavelets to manifest the efficacy and accuracy of the proposed method. The waveform reconstruction method based on Daubechies wavelets can also be applied in magnetic resonance spectroscopy and measurements of gravity, electric fields, and temperature.
Exploring the Diaconal Working Approaches of One Norwegian Mission Organization; HimalPartner in Nepal

iv Table of contents. v Abbreviations. vii CHAPTER I; INTRODUCTION. 1-4 1.0 Background. 1 1.1 Objective of the study. 2 1.2 Focus of the study. 2 1.3 Research questions. 3 1.4 structure of the thesis. 3 CHAPTER II: CONTEXT AND BACKGROUND. 4-13 2.0 Introduction . 4 2.
A Variable Turn-Off Time Control Method for Light Load Efficiency Improvement in Totem Pole PFC

Nowadays, the efficient totem pole power factor correction (PFC) converter is increasingly needed in various distributed power system applications to save energy. For the totem pole PFC converter, the traditional fixed switching frequency control method is inefficient at light load, because of the high switching frequency. The fixed turn-off time control method can reduce the switching frequency at light load; thus, the light-load efficiency can be improved. However, for fixed turn-off time control method, the average switching frequency is still high, resulting in the light load efficiency of PFC converter needs to be further improved. Thus, a variable turn-off time control method based on the fixed turn-off time control method is proposed to further improve the light load efficiency. The performance of this control method is verified by simulation. Compared with the fixed turn-off time control method, the switching frequency is reduced by 75% on average when the power is 50W. Through theoretical calculation of the loss of each part of the converter, the efficiency of the proposed control method can be increased by about 2% at light load.
Plant Reproductive Success Mediated by Nectar Offered to Pollinators and Defensive Ants in Terrestrial Bromeliaceae

Most plants produce floral nectar to attract pollinators that impact pollination and seed production; some of them also secrete extrafloral nectar harvested by insects that may influence the plant reproductive success. The aim of this study was to analyze the effects of excluding pollinators and/or ants on the per-plant reproductive success in two species (Dyckia floribunda Griseb. and Dyckia longipetala Baker, Bromeliaceae) that produce floral and extrafloral nectar. The hypothesis states that both ecological processes (pollination and ant defense) involving nectar-mediated animal–plant interactions are beneficial for plant reproductive success. We expected the highest decrease in the plant fruit and seed sets when the pollinators and ants were excluded, and a moderate decrease when solely ants were excluded, compared to the control plants (those exposed to pollinators and ants). In addition, a lower natural reproductive success was also expected in the self-incompatible D. longipetala than in the self-compatible D. floribunda, as the former totally depends on animal pollination for seed production. D. floribunda and D. longipetala presented similar trends in the response variables, and the expected results for the experimental treatments were observed, with some variations between species and among populations. The ecological function of nectar is important because these two plant species depend on pollinators to produce seeds and on ants to defend flowers from the endophytic larvae of Lepidoptera. The study of multispecies interactions through mechanistic experiments could be necessary to clarify the specific effects of different animals on plant reproductive success.
Transforming Growth Factor α Evokes Aromatase Expression in Gastric Parietal Cells during Rat Postnatal Development

Estrogen, well known as a female hormone, is synthesized primarily by ovarian aromatase. However, extra-glandular tissues also express aromatase and produce estrogen. It is noteworthy that aromatase in gastric parietal cells begins expression around 20 days after birth and continues secreting considerable amounts of estrogen into the portal vein throughout life, supplying it to the liver. Estrogen, which is secreted from the stomach, is speculated to play a monitoring role in blood triglyceride, and its importance is expected to increase. Nevertheless, the regulatory mechanisms of the aromatase expression remain unclear. This study investigated the influence of transforming growth factor α (TGFα) on gastric aromatase expression during postnatal development. The administration of TGFα (50 μg/kg BW) to male Wistar rats in the weaning period resulted in enhanced aromatase expression and increased phosphorylated ERK1+2 in the gastric mucosa. By contrast, administration of AG1478 (5 mg/kg BW), a protein tyrosine kinase inhibitor with high selectivity for the epidermal growth factor receptor and acting as an antagonist of TGFα, led to the suppression of aromatase expression. In fact, TGFα expression in the gastric fundic gland isthmus began around 20 days after birth in normal rats as did that of aromatase, which indicates that TGFα might induce the expression of aromatase in the parietal cells concomitantly.
Schools as Living Laboratories for Architectural Engineering Research Experiences for Teachers

Through a collaboration between the Department of Architectural Engineering and the Center for Science and the Schools (CSATS) at Pennsylvania State University, the Building Education RET project launched a strategic approach to address global challenges in energy, ecological systems, and human health through transformational integration of technical research into precollege curriculum. Schools are critical instruments for advancing knowledge about sustainability, and they provide the ideal context for active research and teaching in sustainability-focused topics designed to cultivate a new generation of STEM leaders. Our strategy involves engaging teachers and students with their school facilities as “Living Laboratories” to provide a place-based context for math and science education. The Building Education RET site at Pennsylvania State University has immersed teachers in both fundamental and applied research on building science topics including indoor air quality, lighting effectiveness, thermal comfort, and energy efficiency and automation. Systems Thinking is an increasingly recognized competency in sustainability and serves as the overarching learning objective of the Building Education RET program. To date, 12 secondary teachers were prepared to utilize experimentation on air quality, lighting systems, and energy use in their respective school buildings as hands-on and applied STEM-based teaching modules. In the spring of 2020, the Building Education team decided to implement the RET program remotely with teachers conducting research in their homes or in their schools. Teachers from multiple states were able to participate in the program. To engage in research projects, we equipped teachers to collect data through instruments and observations about the quality of lighting, indoor air quality, occupant thermal comfort and health, building automation, building energy consumption, etc. in their teaching environments and other spaces in their school building, or their homes, and they learned different methods to analyze the results. We also engaged teachers in the mapping and evaluation of control systems in either their school facilities or their homes to manage heating, cooling, and fresh air. They learned state-of-the-art data analysis methods to identify opportunities to reduce energy demand. To translate their research into curriculum, science education faculty from CSATS engaged teachers in professional development focused on engineering practices. Weekly sessions supported teachers in identifying engineering practices that were translatable to secondary classrooms. As a culminating product, the teachers developed a classroom research project plan for their students to complete in the academic year.
Assessment of soil nitrogen oxides emissions and implementation in LOTOS-EUROS

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
How Shifting Focus from Register to Data Functionality Can Enhance Register and Bus Management

Bus and register management is one of the crucial aspects of application-specific integrated circuit-, system-on-chip-, or field-programmable gate array-based designs. The problems related to it are well known, and multiple tools or approaches are already trying to solve or mitigate them. However, all available solutions share the same register-centric paradigm. A user defines registers and then manually lays out the data into the registers. Such an approach has its limitations. A description does not contain information on data spanning multiple registers or data forming a broader context, for example, procedure arguments. It also does not contain information on the purpose of the data. As a result, the generated access code is low-level and usually needs an extra wrapper, which leaves room for potential human mistakes. For instance, it is the user’s responsibility to guarantee proper access order to registers or to provide an atomic change of data wider than a single register width. This article proposes a new approach, the functionality-centric approach. In the functionality-centric approach, the user defines the data with the type of their functionality. The registers and bus hierarchy are later implicitly inferred. By defining the functionality of the data placed in the registers, it is possible to generate more access code, increase code robustness, improve system design readability, and shorten the implementation process.
Investigating ecosystem connections in the shelf sea environment using complex networks

Abstract. We use complex network theory to better represent and understand the ecosystem connectivity in a shelf sea environment. The baseline data used for the analysis are obtained from a state-of-the-art coupled marine physics–biogeochemistry model simulating the North West European Shelf (NWES). The complex network built on model outputs is used to identify the functional groups of variables behind the biogeochemistry dynamics, suggesting how to simplify our understanding of the complex web of interactions within the shelf sea ecosystem. We demonstrate that complex networks can also be used to understand spatial ecosystem connectivity, identifying both the (geographically varying) connectivity length-scales and the clusters of spatial locations that are connected. We show that the biogeochemical length-scales vary significantly between variables and are not directly transferable. We also find that the spatial pattern of length-scales is similar across each variable, as long as a specific scaling factor for each variable is taken into account. The clusters indicate geographical regions within which there is a large exchange of information within the ecosystem, while information exchange across the boundaries between these regions is limited. The results of this study describe how information is expected to propagate through the shelf sea ecosystem, and how it can be used in multiple future applications such as stochastic noise modelling, data assimilation, or machine learning.
The Prognostic Role of Global Longitudinal Strain and NT-proBNP in Heart Failure Patients Receiving Cardiac Resynchronization Therapy

Background: We aimed to evaluate whether baseline GLS (global longitudinal strain), NT-proBNP, and changes in these after cardiac resynchronization therapy (CRT) can predict long-term clinical outcomes and the echocardiographic-based response to CRT (defined by 15% relative reduction in left ventricular end-systolic volume). Methods: We enrolled 143 patients with stable ischemic heart failure (HF) undergoing CRT-D implantation. NT-proBNP and echocardiography were obtained before and 6 months after. The patients were followed up (median: 58 months) for HF-related deaths and/or HF hospitalizations (primary endpoint) or HF-related deaths (secondary endpoint). Results: A total of 84 patients achieved the primary and 53 the secondary endpoint, while 104 patients were considered CRT responders and 39 non-responders. At baseline, event-free patients had higher absolute GLS values (p < 0.001) and lower NT-proBNP serum levels (p < 0001) than those achieving the primary endpoint. A similar pattern was observed in favor of CRT responders vs. non-responders. On Cox regression analysis, baseline absolute GLS value (HR = 0.77; 95% CI, 0.51–1.91; p = 0.002) was beneficially associated with lower primary endpoint incidence, while baseline NT-proBNP levels (HR = 1.55; 95% CI, 1.43–2.01; p = 0.002) and diabetes presence (HR = 1.27; 95% CI, 1.12–1.98; p = 0.003) were related to higher primary endpoint incidence. Conclusions: In HF patients undergoing CRT-D, baseline GLS and NT-proBNP concentrations may serve as prognostic factors, while they may predict the echocardiographic-based response to CRT.
Antenatal factors and risk of postpartum hyperglycemia in women with gestational diabetes mellitus: A central India prospective cohort study

ABSTRACT Introduction: Global prevalence of gestational diabetes mellitus (GDM) ranges from <1% to 28%. Risk of postpartum diabetes (PPDM) is 7 times higher in women with GDM. We aimed to identify antenatal risk factors associated with postpartum hyperglycemia so that these women may be subjected to targeted screening in a low resource setting. Methods: Screening for GDM was done with a 75gram GTT using IADPSG criteria in women between 28-29 weeks and post-partum screening for hyperglycemia was done using 75 gm 2hour OGTT. Results: Mixed effect linear regression model to assess PPDM as outcome against age, pre pregnancy weight, baby weight at birth, HbA1C and postpartum BMI as predictors was significant at overall level (p=0.00). HbA1C (p =0.00) and pre pregnancy weight (p=0.001) were significant at individual level. Same model for postpartum prediabetes was significant at overall level and assumed significance for pre pregnancy weight (p=0.00), baby birth weight (p= 0.001), postpartum BMI (p=0.00) and HbA1C (p= 0.05) at individual level. The same model for postpartum abnormal sugars (PPDM or prediabetes) was significant at overall level (p = 0.00). Conclusion: Women with GDM represent a vulnerable population that is likely to develop a chronic metabolic disease at a young age exposing them to morbidity associated with unrecognized untreated hyperglycemia. Easily detectable clinical and biochemical antenatal risk factors may help identify women eligible for targeted screening for early diagnosis and treatment as well as use of preventive interventions against type2 diabetes after GDM
Two-Stage Sea-Surface Small Target Detection Using Multifeature-Fusion-Based Binary Classifier and SCR Enhancement

Sea-surface small target detection is challenging for the reason that the small target with low signal-to-clutter ratio (SCR) would be submerged by strong sea spikes in the complex marine environment. Against this background, a two-stage detection method using multifeature-fusion-based binary classifier and SCR enhancement is proposed in this article. In stage 1, the binary classifier extracts multifeatures in the temporal, frequency and time-frequency domains using convolutional neural networks (CNNs) and performs weighted feature fusion by minimizing cross entropy loss. Afterward, in stage 2, SCR enhancement is divided into two steps, which are clutter suppression by modified orthogonal projection (MOP) and interframe incoherent accumulation by Kalman filter, respectively. Specifically, according to the range cells classified as clutter in stage 1, MOP is performed in the range-Doppler (RD) domain to improve SCR by using the projection operator composed by main clutter components via first-order difference method. Then, Kalman filter combines the predict state after RD compensation and observation state with the gain coefficient to realize target energy accumulation and SCR stabilization. Finally, the final decision is made by the constant false alarm rate (CFAR) detector. The simulation results indicate that the proposed binary classifier attains a significant binary classification performance improvement, laying foundations for effective sea clutter suppression and SCR enhancement so as to improve the final detection performance of target location and Doppler frequency.
COVID-19 and Political Trust in Local Governments: Evidence From Nepal

The COVID-19 pandemic has reinvigorated debates about the drivers of political trust. Research so far has mainly focused on national-level institutions, during the early stages of the pandemic and using data from established democracies. However, how does this relationship look like if we pay attention to subnational institutions in non-consolidated democracies, and further away from the initial COVID-19 outbreak? To contribute to this line of research, this article focuses on the local level and explores the association between individuals’ satisfaction with COVID-19 performance and political trust in Nepal. For that, it uses novel data collected via telephone interviews (N = 1400) conducted between 25 April and 24 May 2021, during the second wave of COVID-19. Our main results reveal that satisfaction with local institutions’ COVID-related performance is significantly and robustly associated with levels of political trust at the local level. The association holds even when geographical and time specifications are added, trust towards national institutions or expectations about local governments are included in the analysis and the dependent variable is disaggregated to discard measurement biases. The study thereby provides important insights into the role performance plays for institutional trust beyond the national level and in an unconsolidated democracy.
Géochronologie et géochimie des éclogites du Léon : nouvelles contraintes sur l'évolution géodynamique du Nord-Ouest du Massif Armoricain

La presence de reliques eclogitiques dans la region du Leon (NO du Massif Armoricain, France) indique l'existence d'un evenement metamorphique de haute pression, inconnu jusqu'alors dans tout le domaine Nord-armoricain. Les conditions thermobarometriques du metamorphisme ont ete determinees a 650-700 °C pour une pression minimale de 13-14 kbar. Le caractere oceanique des protolithes des eclogites et la datation en U-Pb sur zircon du metamorphisme haute pression a 439 M.a. revelent la similitude des eclogites du Leon avec celles de Vendee dans le domaine Sud-armoricain. Ces nouvelles donnees s'integrent parfaitement dans l'hypothese d'une evolution hercynienne du Leon, comparable a celle du domaine Sud-armoricain (Bale et Brun, 1986).
The Effects of Weather on Crime Rates in Malaysia

This study estimates the effects of temperature and rainfall on the prevalence of criminal activity in Malaysia. The analysis is based on annual data for the period 1973-2009, on temperature, rainfall and crime rates – total crime, violent and property crime. By using the generalized one-step error-correction model, we examine the short-run and long-run dynamics between crime rates with varying temperatures and rainfall in Malaysia. Our results suggest that there is long-run relationship between total crime and property crimes with weather in Malaysia. The long-run coefficients indicate a positive impact of temperature (hot weather) on criminal activity. Our results imply that the law enforcement would have a better understanding of how the weather affects crime and a chance for the authorities to better prepare their departments during weather conditions that influence certain criminal activities.Keywords: Crime; Temperature; Rainfall; Generalized error-correction model; Malaysia.