Miracle-dz/UniFAR-FTUs huggingface dataset:
Log‐ratio transformation is the key to determining soil organic carbon fractions with near‐infrared spectroscopy

Information about soil organic carbon fractions is important in understanding the vulnerability of soil carbon to climate change and land management. Soil organic carbon can be divided into fractions that are labile and others that are more stable. All existing methods to fractionate soil organic carbon are time consuming and complex. Near‐infrared reflectance spectroscopy (NIRS) is a rapid analytical technique. In this study we evaluated and optimized the use of NIRS to predict soil organic carbon fractions with the constraint that the carbon fractions (labile and stabilized) should add up to 100% (total organic carbon content). We used samples from two datasets from agricultural and forest sites in Germany (dataset A) and Europe (dataset B). Samples were fractionated by two different methods (density and physical‐chemical fractionation) as reference methods. Soil samples were scanned in the NIR range and calibration models were developed using partial least squares regression. The key to improving model performance was the log‐ratio transformation proposed by Aitchison for compositional data that enabled us to model the fractions as dependent variables. Traditional methods for the optimization of NIRS models, such as selection of wavelength range and pretreatment of spectra, showed no effective reduction in error. With the constraint that both fractions add to 100% (log‐ratio transformation), the ratio of performance to deviation (RPD) increased from 1.6 to 2.8 for the labile C fraction and from 1.5 to 3.2 for the stabilized C fraction. Root mean square error of cross‐validation of the labile fraction was 4.3 g C kg−1 for dataset A and 2.7 g C kg−1 for dataset B, which corresponds to an R2 of 0.88–0.80 and RPD of 2.9–2.2, respectively. The models performed equally well for different soil textures and land‐use types. With log‐ratio transformation, more precise calibrations of NIRS for C fractions could be obtained.
Reconstruction of Severely Atrophic Mandible by Installing Dental Implants Using the Modified “Tent Pole” Technique: Case Report

Patients who use full dental prostheses for long periods of time usually experience bone resorption in the alveolar process and in keratinized mucosa. This can cause instability, low prosthetic retention, and subsequent loss of function. Treating a patient with a severely atrophic mandible is quite challenging due to the low bone height and thickness, potentially impairing rehabilitation, aesthetics, and functional recovery. Several techniques are used to reconstruct major vertical defects for the installation of dental implants. Among these is the “tent pole” technique, which features low morbidity and generally produces good results in the form of increased height of the alveolar ridge bone. Herein we describes a patient with a severely atrophic mandible, reconstructed using a plate and dental implants. We employed a modified “tent pole” technique using an autogenous graft of the iliac crest and without use of platelet-rich plasma concentrate. Our results indicate that the modified tent pole technique using the iliac crest graft, and without use of platelet-rich plasma, is a safe and effective method for achieving mandibular reconstruction while restoring function, aesthetics, and the patients’ quality of life.
Synergistic effect of well-defined dual sites boosting the oxygen reduction reaction

Herein, we construct a novel electrocatalyst with Fe–Co dual sites embedded in N-doped carbon nanotubes ((Fe,Co)/CNT), which exhibits inimitable advantages towards the oxygen reduction reaction. The electrocatalyst shows state-of-the-art ORR performance with an admirable onset potential (Eonset, 1.15 V vs. 1.05 V) and half-wave potential (E1/2, 0.954 V vs. 0.842 V), outperforming those of the commercial Pt/C. The ORR test reveals that the performance of the (Fe,Co)/CNT is superior to most of the reported non-precious catalysts in alkaline electrolytes. Furthermore, when employed as a cathode catalyst in a Zn–air battery, the (Fe,Co)/CNT exhibits high voltages of 1.31 V and 1.23 V at discharge current densities of 20 mA cm−2 and 50 mA cm−2, respectively. In addition, the power density and the specific energy density reach 260 mW cm−2 and 870 W h kgZn−1. We discover that the Fe–Co dual sites embedded in N-doped porous carbon are beneficial for the activation of oxygen by weakening the OO bonds.
Study Coordination Design of Over Current Relay on The Kiln Area Electrical System

PT. Semen Padang is one of the largest cement producers in western Indonesia, along with the development of the cement industry PT. Semen Padang added a new Indarung VI factory to support the production process to meet market demand. With the addition of this new factory, a good safety design is needed in the design of the electrical system so that production continuity is not disturbed and reliability values are high. Therefore, over-current protection coordination studies are needed on the electrical system of the kiln area at Trafo 2 Indarung VI PT. Semen Padang to get a safe and reliable system. In the final task, this time will be done modeling, simulation of load flow and short circuit, calculation of relay settings, and simulation of coordination of overcurrent protection phase interference in the electrical system kiln area in Transformer 2 Factory Indarung VI PT. Semen Padang. The plot results of the coordination of the time flow curve obtained through the results of analysis and manual calculations recommended tuning pick-up overcurrent relayand grading time overcurrent relaytuning phase interference. Grading time between overcurrent relay is coordinated by 0.2 seconds. With the protection coordination setting, the electrical system of the kiln area at the Indarung VI factory PT. Semen Padang is safer and more reliable.
False Memory in Children: Data, Theory, and Legal Implications

False memory is an area of intense research interest for both theoretical and practical reasons. From a theoretical perspective, false memories have been the subject of hot debates about the nature of human memory and a focal point for old and new memory theories. From a practical perspective, false memories are a threat to the validity of eyewitness testimony, a misleading source of autobiographical information in psychotherapy, and a biased representation of lessons taught in educational settings. True memories represent events as they really happened, whereas false memories shade, distort, or entirely misrepresent what really happened. False memories may sometimes seem to be only subtly different from strictly accurate reports of experienced events, as when witnesses misremember true inferences about events as though the inferences were directly experienced. Such false memories, which are often confidently reported as directly witnessed, are ubiquitous in everyday life. However, the distinction between inference and experience is crucial in many real-world contexts, especially in legal settings (Reyna & Brainerd, 1998). Eyewitnesses are not called upon to report their theories of events, but, rather, what they actually remember experiencing. Although some inferences turn out to be consistent with the facts, others are based on prejudice, ignorance, and unfounded suppositions (Nisbett & Ross, 1980). Thus, justice requires that we minimize the influence of false memories in legal proceedings at every stage in which children are interviewed, from the crime scene to the courtroom In this chapter we review evidence concerning false memories of multiple types in children, whose perceived competence as witnesses has shifted dramatically in the last 20 years. The general question that concerns us is whether children’s memory is essentially
Electronic and Structural Dynamics of Complex Materials

The time-resolved determination of dynamics in complex materials is an important goal for understanding and controlling material properties, especially on ultrafast timescales. This thesis reports on the development of broadband spectroscopic techniques for characterising electronic and structural dynamics in such materials and their application to the quasi-twodimensional charge-density-wave Mott insulator 1T -TaS2. The experiments take two main approaches. First, optical pump-probe spectroscopy from the terahertz to the visible regions of the electromagnetic spectrum is used to investigate the collective response. Secondly, timeand angle-resolved photoemission spectroscopy monitors single-electron dynamics on the earliest timescales across the Brillouin zone. In the photoinduced phase of TaS2, terahertz spectroscopy demonstrates an increase in conductivity as the phase transition occurs and reveals the evolution of three phonon modes, which undergo transient Fano reshaping due to electron-lattice interactions. Pump-probe measurements at higher energy highlight coherent excitation of the charge density wave amplitude mode and the emergence of a broad resonance feature associated with polaron formation in the new phase. The photoemission experiments show that photoexcitation causes prompt collapse of the Mott gap and leads to partial unfolding of the Brillouin zone on longer timescales, as structural distortions relax. The emerging picture of this transient phase is one in which the Mott gap is melted but the low-temperature symmetry is retained. Meanwhile, transport is dominated by polaronic conductivity. This unique phase is only accessible by photo-doping. Finally, a new method of ultrafast control, in which light is coupled to vibrational modes of the system rather than electronic excitations, is introduced and demonstrated in the manganites. An exploration of this technique using FELs promises to reveal the role of different types of distortion in driving ultrafast processes, while phase stabilisation of excitation pulses opens up new paths to coherent control.
Inhibitory Effects of Probenecid on Pharmacokinetics of Tenofovir Disoproxil Fumarate and Emtricitabine for On‐Demand HIV Preexposure Prophylaxis

In a randomized, crossover pharmacokinetic study in healthy volunteers (N = 14), a single dose of 2 g probenecid (PRO)‐boosted 600 mg tenofovir disoproxil fumarate (TDF)/400 mg emtricitabine (FTC) (test (T) +PRO) was compared with the current on‐demand HIV preexposure prophylaxis from the IPERGAY study (a 600 mg TDF/400 mg FTC on day 1 and 300 mg TDF/200 mg FTC on days 2 and 3) (control, C IPERGAY). PRO increased mean single‐dose area under the plasma concentration‐time curve extrapolated to infinity (AUC0–∞,SD) of tenofovir (TFV) and FTC by 61% and 68%, respectively. The TFV‐diphosphate (TFV‐DP) concentrations in peripheral blood mononuclear cells were higher (~30%) at 24 hours in T +PRO but then fell significantly lower (~40%) at 72 hours compared with C IPERGAY. The interaction between FTC and PRO was unexpected and novel. Further study is needed to determine if this PRO‐boosted TDF/FTC regimen would be clinically effective.
Modelling an Efficient Three-Tier Fault Tolerance Approach for Resource Provisioning over Cloud

INTRODUCTION: Nowadays, the cloud computing paradigm encounters newer challenges in offering fault tolerance methods during service provisioning. The failures during service provisioning are unavoidable in the large-scale heterogeneous network. Therefore, the adoption of appropriate fault tolerance techniques can improve the provided service's efficiency and reliability. OBJECTIVES: Thus, fault tolerating metrics give better accuracy to enhance the QoS, where the three-tier fault-tolerance approach is proposed to resolve the various failures in service provisioning. METHODS: Initially, a Collector Model collects the request and ranks it based on the service to be provided. Secondly, the redundancy filter module is designed to filter out the request replication and avoid the unnecessary process to be carried out. Finally, the fairness resource allocation module is designed to perform the prominent request received from the users based on the available resources without service congestion. RESULTS: This three-tier model operates concurrently to handle the multiple requests from the users of various connected nodes. The experimental analysis demonstrates that the three-tier fault tolerance model can enhance the cloud reliability over the large-scale heterogeneous network by ensuring QoS. CONCLUSION: The well-realized fault tolerance approach can efficiently demonstrate the structural model and fault tolerance process over the computing environment, therefore enhancing the cloud extendibility. Moreover, the computing environment's failure is hugely complex, and failure has to be handled efficiently.
Peculiarities of Activity Renovation of Zeolite Catalysts Coked in Hexane Cracking

1 The initial activity of acid zeolites in n -hexane cracking and influence of their regeneration depth on residual activity using the method of discrete-consecutive coke micro oxidation have been investigated. It was found that oxidation by 5-10 pulses of oxygen properly reflects the activity of catalysts based on faujasite and pentasil, while for mordenite which has increased susceptibility to blocking of channels by coke, such quantity oxygen is not enough.
Three-dimensional ultrasound imaging and measurement of nasal bone length, prenasal thickness and frontomaxillary facial angle in normal second- and third-trimester fetuses

Objectives To assess the feasibility of nasal bone length (NBL), prenasal thickness (PT) and frontomaxillary facial (FMF) angle measurements performed on the same three-dimensional (3D) multiplanar-corrected profile view in euploid secondand third-trimester fetuses, to create reference ranges and to review published measurement techniques. Methods 3D volumes of 219 euploid secondand third-trimester fetuses were retrospectively analyzed. The quality of images and measurability of the markers were assessed with 5-point and 3-point scoring systems, respectively. Measurements of NBL (with care to exclude the frontal bone), PT and FMF were obtained in the exact midsagittal plane. Reference ranges were constructed based on measurements from images with high-quality (4 or 5 points) and high measurability (2 or 3 points) scores and compared with those in the most relevant published literature. Results A high-quality score was assigned to 111 images. Among these, a high measurability score was significantly more often achieved for NBL (98.2%) and PT (97.3%) than for the FMF angle (26.1%) (p < 0.001). Both NBL (NBL = –6.927 + (0.83 × GA)-(0.01 × GA2)) and PT (PT = (0.212 × GA)-0.873) (where GA = gestational age) showed growth with gestation, with less pronounced growth for NBL after 28 weeks. Our reference range for the NBL showed a systematically smaller length than those in other two-dimensional (2D) ultrasound based publications. The FMF angle measurements that we obtained did not show a significant change with GA. Conclusions NBL and PT, are easily measured using 3D ultrasound, whereas the FMF angle is more challenging. When it is measured in the exact midsagittal plane and care is taken to exclude the frontal bone, measurements of the NBL are systematically smaller than those in previous 2D ultrasound-based publications.
A Pattern Analysis-based Segmentation to Localize Early and Late Blight Disease Lesions in Digital Images of Plant Leaves

This study reports a disease symptom classification algorithm using a proposed pattern recognition approach to individually localize early and late blight visual disease symptoms. The algorithm uses the pathological analogy hierarchy of the diseases to produce a novel homogeneous pattern localization, more informative to extract features that would be utilized for a machine learning system to classify the two diseases in digital photographs of vegetable plants. One of the most significant advantages of the proposed pattern analysis is localizing symptomatic and necrotic regions based on pathological disease analogy using soft computing, with which the pattern of each disease manifestation along the leaf surface can be tracked and quantified for characterization. In the 1st phase of the experiment, individual symptomatic (Rs), necrotic ($\mathrm{R}_{\mathrm{N}}$), and blurred ($\mathrm{R}_{\mathrm{B}}$, in-between healthy and symptomatic) regions were identified, segmented, and quantified. The 2nd phase focuses on the extraction of pattern features for classification and severity estimation with a machine learning classifier. The obtained results are encouraging, successfully localizing and quantifying individual disease lesions. This also indicates the enhanced applicability of the proposed approach discriminating the two diseases based on their dissimilarity. It is also envisaged that the algorithm can be extended to other plant disease symptoms. Moreover, it provides opportunities for early identification and detection of subtle changes in plant growth, disease stage, and severity estimation to assisting crop diagnostics in precision agriculture.
Facial Expression Analysis by K-Means Clustering on Fiducial Points of Face

Human beings produce thousands of facial actions and emotions in a single day. These come up while communicating with someone and at times even when alone. These expressions vary in complexity, intensity, and meaning. This paper proposes a novel method to predict what emotion is being expressed by analyzing the face. The algorithm, because of the speed of execution, could also be used for micro expression analysis. 11 fiducial points are taken on the image after a face recognition algorithm is used. 7 classes of images are formed. These classes are the main expressions: sadness, happiness, anger, fear, disgust, surprise and neutral. Training is done by studying the relationship between the fiducial points for each class of image. Using this relationship a new image is classified by making use of the k-means algorithm.
CATARO: a robot that tells caregivers a patient's current non-critical condition indirectly

Currently, a system is being developed that gathers information about a dementia patient's condition and sends it to a smartphone. Through this system, caregivers in a nursing facility could always check on their patients' current condition and act accordingly. However, they are generally too busy to constantly check their smartphones for "non-critical" information about patients. This research proposes putting a small robot in front of a patient to speak to the patient in a professional manner in reaction to his/her current condition. Caregivers nearby could hear the robot and then determine the patient's condition. When the caregiver is free, he/she could approach the patient and start talking to him/her in the same manner as the robot just did1.
Flexible Bayesian Inference by Weight Transfer for Robust Deep Neural Networks

SUMMARY Adversarial attacks are viewed as a danger to Deep Neural Networks (DNNs), which reveal a weakness of deep learning models in security-critical applications. Recent ﬁndings have been presented adversarial training as an outstanding defense method against adversaries. Nonetheless, adversarial training is a challenge with respect to big datasets and large networks. It is believed that, unless making DNN architectures larger, DNNs would be hard to strengthen the robustness to adversarial examples. In order to avoid iteratively adversarial training, our algorithm is Bayes without Bayesian Learning (BwoBL) that performs the ensemble inference to improve the robustness. As an application of transfer learning, we use learned parameters of pretrained DNNs to build Bayesian Neural Networks (BNNs) and focus on Bayesian inference without costing Bayesian learning. In comparison with no adversarial training, our method is more robust than activation functions designed to enhance adversarial robustness. Moreover, BwoBL can easily integrate into any pre-trained DNN, not only Convolutional Neural Networks (CNNs) but also other DNNs, such as Self-Attention Networks (SANs) that outperform convolutional counterparts. BwoBL is also convenient to apply to scaling networks, e.g., ResNet and E ﬃ cientNet, with better performance. Especially, our algorithm employs a variety of DNN architectures to construct BNNs against a diversity of adversarial attacks on a large-scale dataset. In particular, under l 1 norm PGD attack of pixel perturbation ϵ = 4 = 255 with 100 iterations on ImageNet, our proposal in ResNets, SANs, and E ﬃ cientNets increase by 58.18% top-5 accuracy on average, which are combined with naturally pretrained ResNets, SANs, and E ﬃ cientNets. This enhancement is 62.26% on average below l 2 norm C&W attack. The combination of our proposed method with pretrained E ﬃ cientNets on both natural and adversarial images (E ﬃ cientNet-ADV) drastically boosts the robustness resisting PGD and C&W attacks without additional training. Our E ﬃ cientNet-ADV-B7 achieves the cutting-edge top-5 accuracy, which is 92.14% and 94.20% on adversarial ImageNet generated by powerful PGD and C&W attacks, respectively.
University of Groningen Structural and mutational characterization of the catalytic A-module of the mannuronan C-5- epimerase AlgE4 from Azotobacter vinelandii Rozeboom,

Citation for published version (APA): Rozeboom, H. J., Bjerkan, T. M. , Kalk, K. H. , Ertesvag, H. , Holtan, S. , Aachmann, F. L. , Valla, S. , Dijkstra, B. W. , Ertesvåg, H. , & Holtan, S. (2008). Structural and mutational characterization of the catalytic Amodule of the mannuronan C-5-epimerase AlgE4 from Azotobacter vinelandii. The Journal of Biological Chemistry, 283(35), 23819-23828. https://doi.org/10.1074/jbc.M804119200
Agent-Based Simulation for Evaluating the Effect of Different Walking and Driving Speed on Disaster Evacuation in Aceh

⎯ Agent-Based Modeling and Simulation (ABMS) was implemented to build and develop an evacuation simulation model. In this research, ABMS is simulated in several evacuation scenarios with an output: the evacuation rate of two different decision choice evacuation modes (walking or driving to the evacuation points). The result of this tsunami evacuation simulation shows that different control parameters such as evacuation mode, percentage of car and pedestrian, walking speed and driving speed confirmed their significance on the evacuation planning in Aceh. There is a typical choice that leads to the higher evacuation rate, the choice is by maximizing the pedestrian agents on the population. Walking speed has significant importance and impact on the evacuation rate. Moderate walking speed (4 ft/s) is recommended as reference for walking speed in disaster situations. Driving speed also has a significant impact on the evacuation rate if we keep the limits at 20 mph. Since the maximum driving speed higher than 20 mph has no impact on the evacuation rate.
Compatibility of wind and solar energy with electricity demand in Argentina

One of the greatest obstacles in the exploitation of wind and solar resources is the uncertainty in their availability, usually known as intermittency effects. These effects can be greatly diminished by combining wind and solar resources from different locations. In this article we study the temporal variability of solar irradiance and wind speeds in Argentina, focusing on current projects and those included in GENREN and RENOVAR tenders. We also converted two year wind speeds and irradiance time series into power production, analyzing its compatibility with demand. Finally we numerically search the best distribution of additional capacity that minimizes a basic measure of the intermittency effect.