Miracle-dz/UniFAR-FTUs huggingface dataset:
On-Chip Implementable Autocalibration of Sensor Offset for Differential Capacitive Sensor Interfaces

In this article, we propose an autocalibration method to cancel out the mismatch between the sensing capacitors in differential capacitive sensors. The proposed autocalibration logic is implemented with the help of a field-programmable gate array (FPGA) and a few discrete components that can be integrated fully on-chip. The calibration logic is based on successive approximation principle and integrated with a low offset capacitive sensor interfacing application-specific integrated circuit (ASIC). The interfacing ASIC employs switched-capacitor-based time-multiplexed chopper modulation and demodulation principles to reduce the low-frequency noise and offset from the circuit components. In the proposed design, an array of programmable on-chip capacitors is included within the ASIC for automatic calibration. It also includes a 16-bit serial-input parallel-output (SIPO) shift register for calibration and to configure the control signals required for other blocks in the ASIC. The interfacing ASIC is designed and fabricated in the United Microelectronics Corporation (UMC) 180-nm CMOS process technology. The ASIC along with the autocalibration logic is integrated with a MEMS-based capacitive acceleration sensor, and the measurement results are presented. The measurement results show that the proposed scheme is able to compensate for the mismatch between the sensing capacitors, keeping zero offset less than 2 mV, and provides a sensitivity of 200 mV/g with 300- $\mu \text{g}/\sqrt {Hz} $ noise floor.
Robust estimation of mean squared prediction error in small‐area estimation

The nested‐error regression model is one of the best‐known models in small area estimation. A small area mean is often expressed as a linear combination of fixed effects and realized values of random effects. In such analyses, prediction is made by borrowing strength from other related areas or sources and mean‐squared prediction error (MSPE) is often used as a measure of uncertainty. In this article, we propose a bias‐corrected analytical estimation of MSPE as well as a moment‐match jackknife method to estimate the MSPE without specific assumptions about the distributions of the data. Theoretical and empirical studies are carried out to investigate performance of the proposed methods with comparison to existing procedures.
Evaluating the use of the autodiametric method for estimating fecundity of Reinhardtius hippoglossoides, a species with an unusual oocyte development strategy

Evaluating the use of the autodiametric method for estimating fecundity of Reinhardtius hippoglossoides, a species with an unusual oocyte development strategy R. Dominguez-Petit*, R. M. Rideout, D. Garabana, Y. Lambert, M. Hermida, and M. J. Morgan Spanish Institute of Oceanography, Oceanographic Centre of Vigo, Vigo, Spain Institute of Marine Research-CSIC, Vigo, Spain Fisheries and Oceans Canada, Northwest Atlantic Fisheries Centre, St John’s, NL, Canada Spanish Institute of Oceanography, Oceanographic Centre of A Coru~na, A Coru~na, Spain Fisheries and Oceans Canada, Institute Maurice-Lamontagne, Mont-Joli, QC, Canada *Corresponding author: tel: þ34 98 646 2271; fax: 986498626; e-mail: rosario.dominguez@ieo.es.
A Fast Weakly-Coupled Double-Layer ESKF Attitude Estimation Algorithm and Application

Aimed at the problem of small unmanned aerial vehicle (UAV) attitude solution accuracy and real-time performance in short-range navigation flight, in this paper, we propose a fast weakly-coupled double-layer error-state Kalman filter (DL-ESKF) attitude estimation algorithm. Considering the application of short-range navigation, we designed an improved attitude error model for low-cost gyroscope/accelerometer/magnetometer devices. In addition, we reasonably simplified certain factors that affect the attitude solution to reduce the filtering calculation burden. For the data coupling phenomenon caused by the different sampling frequencies of the attitude sensor data in the filtering process, we designed a new attitude algorithm combined with the ESKF and hierarchical filter. The first layer of filters used an accelerometer and the second layer used a magnetometer to correct the attitude error. We also built an offline and real-time test platform to verify the performance of the proposed algorithm in a simulation and flight test environment compared with the classic attitude algorithms. The experimental results demonstrated that the proposed algorithm not only improved the attitude solution accuracy and stability but also reduced the filter running time.
Self-adaptive Cobots in Cyber-Physical Production Systems

Absolute automation in certain industries, such as the automotive industry, has proven to be disadvantageous. Robots are fairly capable when performing tasks that are repetitive and demand precision. However, a hybrid solution comprised of the adaptability and resourcefulness of humans cooperating, in the same task, with the precision and efficiency of machines is the next step for automation. Manipulators, however, lack self-adaptability and true collaborative behaviour. And so, through the integration of vision systems, manipulators can perceive their environment and also understand complex interactions. In this paper, a vision-based collaborative proof-of-concept framework is proposed using the Kinect v2, a UR5 robotic manipulator and MATLAB. This framework implements 3 behavioural modes, 1) a Self-Adaptive mode for obstacle detection and avoidance, 2) a Collaborative mode for physical human-robot interaction and 3) a standby Safe mode. These modes are activated with recourse to gestures, by virtue of the body tracking and gesture recognition algorithm of the Kinect v2. Additionally, to allow self-recognition of the robot, the Region Growing segmentation is combined with the UR5’s Forward Kinematics for precise, near real-time segmentation. Furthermore, self-adaptive reactive behaviour is implemented by using artificial repulsive action for the manipulator’s end-effector. Reaction times were tested for all three modes, being that Collaborative and Safe mode would take up to 5 seconds to accomplish the movement, while Self-Adaptive mode could take up to 10 seconds between reactions.
THz to Inspect Graphene and Thin Film Materials

In this paper, we present a system that provides meso-scale characterization of thin film materials, covering the gap between nano-scale and macro-scale methods. Nano-scale methods are slow and cannot characterize large surfaces. Macroscale methods generate characterization that averages the magnitudes and, thus, cannot provide localized information. Our system works in reflection as opposed to state-of-the-art methods and provides mobility, carrier density, and conductance maps in the THz range. Moreover, it can be integrated with reactors and enables monitoring of the fabrication of materials in real-time, supporting, for instance, the production of graphene at industrial scale.
Profiles of Upcoming HPC Applications and Their Impact on Reservation Strategies

With the expected convergence between HPC, BigData and AI, new applications with different profiles are coming to HPC infrastructures. We aim at better understanding the features and needs of these applications in order to be able to run them efficiently on HPC platforms. The approach followed is bottom-up: we study thoroughly an emerging application, Spatially Localized Atlas Network Tiles (SLANT, originating from the neuroscience community) to understand its behavior. Based on these observations, we derive a generic, yet simple, application model (namely, a linear sequence of stochastic jobs). We expect this model to be representative for a large set of upcoming applications from emerging fields that start to require the computational power of HPC clusters without fitting the typical behavior of large-scale traditional applications. In a second step, we show how one can use this generic model in a scheduling framework. Specifically we consider the problem of making reservations (both time and memory) for an execution on an HPC platform based on the application expected resource requirements. We derive solutions using the model provided by the first step of this work. We experimentally show the robustness of the model, even with very few data points or using another application, to generate the model, and provide performance gains with regards to standard and more recent approaches used in the neuroscience community.
Cultivation and genomic analysis of Candidatus Nitrosocaldus islandicus, a novel obligately thermophilic ammonia-oxidizing Thaumarchaeon

Ammonia-oxidizing archaea (AOA) within the phylum Thaumarchaea are the only known aerobic ammonia oxidizers in geothermal environments. Although molecular data indicate the presence of phylogenetically diverse AOA from the Nitrosocaldus clade, group 1.1b and group 1.1a Thaumarchaea in terrestrial high-temperature habitats, only one enrichment culture of an AOA thriving above 50 °C has been reported and functionally analyzed. In this study, we physiologically and genomically characterized a novel Thaumarchaeon from the deep-branching Nitrosocaldaceae family of which we have obtained a high (∼85 %) enrichment from biofilm of an Icelandic hot spring (73 °C). This AOA, which we provisionally refer to as “Candidatus Nitrosocaldus islandicus”, is an obligately thermophilic, aerobic chemolithoautotrophic ammonia oxidizer, which stoichiometrically converts ammonia to nitrite at temperatures between 50 °C and 70 °C. Ca. N. islandicus encodes the expected repertoire of enzymes proposed to be required for archaeal ammonia oxidation, but unexpectedly lacks a nirK gene and also possesses no identifiable other enzyme for nitric oxide (NO) generation. Nevertheless, ammonia oxidation by this AOA appears to be NO-dependent as Ca. N. islandicus is, like all other tested AOA, inhibited by the addition of an NO scavenger. Furthermore, comparative genomics revealed that Ca. N. islandicus has the potential for aromatic amino acid fermentation as its genome encodes an indolepyruvate oxidoreductase (iorAB) as well as a type 3b hydrogenase, which are not present in any other sequenced AOA. A further surprising genomic feature of this thermophilic ammonia oxidizer is the absence of DNA polymerase D genes - one of the predominant replicative DNA polymerases in all other ammonia-oxidizing Thaumarchaea. Collectively, our findings suggest that metabolic versatility and DNA replication might differ substantially between obligately thermophilic and other AOA.
The Ambivalence of Job Autonomy and the Role of Job Design Demands

With its positive influence on such outcomes as performance, work motivation and health, job autonomy has long been considered one of the most important job resources by different models of job design (e.g., Bakker & Demerouti, 2007; Gagné & Deci, 2005; Hacker, 2003; Hackman & Oldham, 1976; Humphrey et al., 2007; Karasek & Theorell, 1990; Spector, 1986). Most models of job design assume a linear relationship between autonomy and the abovementioned outcome variables, which implies that the more autonomy workers have, the better off they are. However, some scholars also state that there can be negative side effects or too much of a good thing (TMGT; Grant & Schwartz, 2011; Pierce & Aguinis, 2013). The vitamin model (Warr, 1994) assumes curvilinear relationships between workers’ autonomy and well-being. ‘Too much autonomy as well as too little is often seen as undesirable’ (Warr, 1987: 30). According to Warr (1987), too much autonomy may entail difficult decision making and unremitting personal responsibility, which can lead to an overload of strain. Some recent studies have found empirical evidence for this assumption (e.g., Joensuu et al., 2010; Kubicek, Korunka, & Tement, 2014; Meyerding, 2015). Although the vitamin model and the TMGT approach offer a general theoretical framework for potentially negative effects of autonomy, they do not provide evidence for specific explanations of these effects on employee well-being. We still do not know why, under what conditions and through which processes autonomy may have detrimental effects. The present study tries to fill this research gap by uncovering the path by which autonomy may have demanding effects. We introduce the concept of job design demands (JDD), which is the demand to make decisions on various aspects of one’s own job design. We propose that high autonomy is associated with this need to make decisions regarding the design and pursuit of one’s job. This can be considered a job demand, as it can be associated with supplemental efforts and psychological costs (Bredehoeft et al., 2015). By investigating the intervening role of JDD within the association between autonomy and impaired well-being in a cross-sectional and longitudinal study, this paper expands the existing research on job autonomy. The paper challenges the assumption that autonomy is related to well-being only in a positive way by demonstrating that autonomy can—at least partially—lead to increased effort and experiences of stress. Thus, this paper provides a more differentiated view of job autonomy as a fundamental job characteristic.
Deletion of Cu/Zn Superoxide Dismutase Gene sodC Reduces Aspergillus niger Virulence on Chinese White Pear

A BSTRACT . Aspergillus niger is a common pathogenic fungus causing postharvest rot of fruit and vegetable, whereas the knowledge on virulence factors is very limited. Superoxide dismutase [SOD (EC 1.15.1.10)] is an important metal enzyme in fungal defense against oxidative damage. Thus, we try to study whether Cu/Zn-SOD is a virulence factor in A. niger . Cu/Zn-SODencoding gene sodC wasdeleted in A. niger [MA70.15(wildtype)]byhomologousrecombination.Thedeletion of sodC led to decreased SOD activity in A. niger , suggesting that sodC did contribute to full enzyme activity. D sodC strain showed normal mycelia growth and sporulation compared with wild type. However, sodC deletion markedly increased the cell’s sensitivity to intracellular superoxide anion generator menadione. Besides, spore germination under menadione and H 2 O 2 stresses were signiﬁcantly retarded in D sodC mutant compared with wild type. Further results showed that sodC deletion induced higher superoxide anion production and higher content of H 2 O 2 and malondialdehyde (MDA) compared with wild type, supporting the role of SOD in metabolism of reactive oxygen species (ROS). Furthermore, D sodC mutant had a reduced virulence on chinese white pear ( Pyrus bretschneideri ) as lesion development by D sodC was signiﬁcantly less than wild type. The determination of superoxide anion, H 2 O 2 , and MDA in A. niger -infected pear showed that chinese white pear infected with D sodC accumulated less superoxide anion, H 2 O 2 , and MDA compared with that of wild type A. niger , implying that D sodC induced an attenuated response in chinese white pear during fruit–pathogen interaction. Our results indicate that sodC gene contributes to the full virulence of A. niger during infection on fruit. Aspergillus niger is one of the most common species found in fungal communities. It is an important fermentation industrial strain and is also known to cause the most severe symptoms in fruit during long-term storage (Pel et al., 2007). Meanwhile, plants activate their signaling pathways to trigger defense responses to limit pathogen expansion. One of the earliest host responses after pathogen attack is oxidative burst, during which large quantities of ROS are generated by different host enzyme systems, such as glucose oxidase(Govrin and Levine, 2000). ROS such as singlet oxygen, superoxideanion, hydroxyl (OH L ), and H 2 O 2 are released to hinder the advance of pathogens (Gara et al., 2003). ROS can react with and damage cellular molecules, such as DNA, protein, and lipids, which will limit fungal propagation in the host plant (Apel and Hirt, 2004).
Caveats in the monitoring of fetal growth using ultrasound estimated fetal weight

Introduction Ultrasound estimated fetal weight is increasingly being used in the monitoring of fetal growth. Differences between estimated fetal weight formulae, curves and measurement methods could lead to significant differences in results. The aim of this study was to investigate the potential impact of these differences on estimated fetal weight and its use in monitoring fetal growth, both by modelling and by analysis of ultrasound scan data. Methods Four estimated fetal weight curves were compared in their original form and also normalised to term weight. Estimated fetal weight was calculated from 50th centiles of widely used charts of abdominal and head circumference and femur length and plotted on a widely used estimated fetal weight curve. Fetal measurement data were used to assess the impact of fetal proportions on estimated fetal weight error and on growth trajectory when different estimated fetal weight formulae are used. Results Estimated fetal weight curves differ significantly, but after normalisation there is closer agreement. Estimated fetal weight modelled using modern measurement methods differs from the widely used estimated fetal weight growth curve. Errors in estimated fetal weight are correlated with differences in fetal proportions and this can lead to significant changes in estimated fetal weight growth trajectory if different estimated fetal weight formulae are used. Conclusions Choice of measurement methods, estimated fetal weight formulae and growth curves have a significant effect on estimated fetal weight growth trajectories relative to normal ranges. It is important to understand these caveats when using estimated fetal weight to monitor fetal growth.
Effects of 1‐methylcyclopropene on postharvest storage performance and the transcriptome of cactus pear fruit

Summary Prestorage exposure to the ethylene-action inhibitor 1-methylcyclopropene (1-MCP) at a concentration of 1 μL L−1 at 20 °C for 24 h significantly retarded peel color change and reduced decay development of cactus pear fruit after 3 weeks of cold storage at 7 °C and 5 days at 20 °C. Exposure to 1-MCP had no significant effects on other fruit-quality attributes, including firmness, weight loss, total soluble solids and acidity levels, and flavor. Exposure to 1-MCP significantly reduced fruit respiration and ethylene production rates. RNA sequencing analysis revealed that 1-MCP mitigated the overall changes in the transcriptome of cactus pear fruit upon cold storage. Functional categorization analysis using the MapMan software revealed that the most pronounced effects of 1-MCP were in averting the massive down-regulation of transcripts belonging to stress, RNA and transcription, signaling and cell categories. Furthermore, exposure to 1-MCP significantly reduced pheophytinase and chlorophyllase transcript levels and increased chitinase transcript levels, thus providing molecular evidence for its observed effects on retardation of peel color change and enhancement of pathogen resistance. In commercial practice, 1-MCP could be applied to cactus pear fruit in order to retard ripening and reduce decay development.
Can lean management change the managerial culture in higher education?

ABSTRACT Problems associated with managerialism are well established in Higher Education. Driven by pressures of funding cuts, league tables and the associated competitive environment, Higher Education followed other public sector bodies in adopting Lean Management principles. While there is scepticism about Lean Management because it is seen as an instrument of managerialism, it is a philosophy that can resolve issues created by the managerialism movement. It offers ways of working with reduced resources without increasing pressure on staff. This paper proposes a Lean Management framework for Higher Education that focusses on creating value for stakeholders rather than cost-cutting. This framework was developed through a grounded theory approach, examining key features, successes and lessons learned from established programmes. This study shows that the framework could benefit universities and resolve some of the problems associated with managerialism.
Coupling of Phosphorus Processes With Carbon and Nitrogen Cycles in the Dynamic Land Ecosystem Model: Model Structure, Parameterization, and Evaluation in Tropical Forests

The biogeochemical processes of carbon (C), nitrogen (N), and phosphorous (P) are fully coupled in the Earth system, which shape the structure, functioning, and dynamics of terrestrial ecosystems. However, the representation of P cycle in terrestrial biosphere models (TBMs) is still in an early stage. Here we incorporated P processes and C‐N‐P interactions into the C‐N coupled Dynamic Land Ecosystem Model (DLEM‐CNP), which had a major feature of the ability in simulating the N and P colimitation on vegetation C assimilation. DLEM‐CNP was intensively calibrated and validated against daily or annual observations from four eddy covariance flux sites, two Hawaiian sites along a chronosequence of soils, and other 13 tropical forest sites. The results indicate that DLEM‐CNP significantly improved simulations of forest gross and net primary production (R2: 0.36–0.97, RMSE:1.1–1.49 g C m−2 year−1 for daily GPP at eddy covariance flux sites; R2 = 0.92, RMSE = 176.7 g C m−2 year−1 for annual NPP across 13 tropical forest sites). The simulations were also consistent with field observations in terms of biomass, leaf N:P ratio and plant response to fertilizer addition. A sensitivity analysis suggests that simulated results are reasonably robust against uncertainties in model parameter estimates and the model was very sensitive to parameters of P uptake. These results suggest that incorporating P processes and N‐P interaction into terrestrial biosphere models is of critical importance for accurately estimating C dynamics in tropical forests, particularly those P‐limited ones.
STRUCTURE FROM MOTION PROCESSING OF ANALOGUE IMAGES CAPTURED BY ROLLEI METRIC CAMERA, DIGITIZED WITH VARIOUS SCANNING RESOLUTION

SfM processing of archived analogue images gives an opportunity to efficiently create new and valuable 2D and 3D results. The SfM processing of digitized analogue images brings some challenges. How to digitize negatives of photogrammetric images? What scanning resolution is the most beneficial for processing? How to preprocess the digitized images to be able to process them using the SfM method? What accuracy of results is possible to expect? This paper tries to deal with all these questions. For this paper, 7 negatives of former photogrammetric documentation of a vault were chosen. The negatives were captured by Rollei 3003 metric camera in 1999. Two pieces of software were chosen for the SfM processing. A commercial alternative Agisoft PhotoScan and free open-source alternative MicMac. The results of the SfM processing were compared to the results of an original photogrammetric method, which was used for former processing in 1999.