Miracle-dz/UniFAR-FTUs huggingface dataset:
Tectonic and Climatic Control on Quaternary Exhumation in the Eastern Pamir Domes, Western China: Insights From Geomorphic Approaches

The Kongur Shan and Muztaghata massifs, bounded by the Kongur Shan extensional system (KES), represent tectonic and topographic anomalies in the eastern Pamir region. They are ideal examples to study how normal faulting and surface erosion influence Quaternary exhumation/erosion of the dome system. We apply multiple geomorphic parameters, including hypsometric integral, stream length-gradient index, drainage basin shape, drainage basin asymmetry and ratio of valley floor width to valley height, for the catchments on both sides of the range. We first evaluated the validity of various indices and chose three active tectonic-sensitive indices to establish a newly-integrated parameter (Iat) that is used to measure relative intensities of tectonic activity in active orogens. Results suggest stronger tectonic activity west of the domes along the Kongur Shan normal fault (KSF) and Muji dextral strike-slip fault, compared to the eastern side, along the Ghez and Kalagile faults. This first-order observation reflects tectonic control on the topographic development of the domal structure, consistent with eastward crustal tilting, attested by older thermochronology ages to the east. On the western flank of the range, stronger tectonic activity occurs mostly on the Muji fault, Kingata Tagh - Kongur Shan fault segment, as well as along the western and southern Muztaghata segments of the Kongur Shan fault. This is consistent with field investigations of Quaternary offsets of landforms, which suggest continuous activity of the Muji fault and KSF since the late Miocene. Average basin-wide erosion rates derived from stream power models are highest near the Kongur Shan dome, and gradually decrease southwards and northwards, in agreement with the spatial pattern of long-term exhumation rates in the footwall of the KSF obtained by low-temperature thermochronology data. Positive correlation between exhumation/erosion rates and extensional rates along the active faults located west of the domes indicates that extensional deformation likely plays a dominant role in controlling focused dome exhumation/erosion. However, considering peaked exhumation/erosion rates, stronger rock resistivity and steeper glacial landforms, attest to the important role of glacial buzz-saw in reshaping the recent dome’s landscape.
Are Cesarean Section and Appendectomy in Pregnancy and Puerperium Interrelated? A Cohort Study

Introduction It is not known whether appendectomy for acute appendicitis (AA) increases the Cesarean section (CS) rate and whether CS increases the likelihood of AA and appendectomy in the early puerperium. In this study, delivery type and delivery outcomes and appendectomy during pregnancy and puerperium were analyzed. Methods This cross-sectional retrospective study was performed on 11,513 women, delivered during 2015–2020. Inclusion criteria were patients undergoing appendectomy for AA during pregnancy and the first 6 weeks after delivery. Evaluating parameters were age, parity, gestational week at birth, delivery type, and babies' birth weight. Results Thirty-two patients underwent appendectomy: 12 during pregnancy (2 in the first trimester, 6 in the second trimester, 4 in the third trimester) and 20 women during puerperium. 58.2% of pregnant women and 65% of puerperal women were submitted to CS. Discussion Half of the women who underwent appendectomy for AA during pregnancy may require urgent CS. The cause of acute abdomen in the postpartum period, especially in the first week, could be AA, especially in women delivered by CS.
Evaluation of Muscle Mass and Stiffness with Limb Ultrasound in COVID-19 Survivors

Background acute illnesses, like COVID-19, can act as a catabolic stimulus on muscles. So far, no study has evaluated muscle mass and quality through limb ultrasound in post-COVID-19 patients. Methods cross sectional observational study, including patients seen one month after hospital discharge for SARS-CoV-2 pneumonia. The patients underwent a multidimensional evaluation. Moreover, we performed dominant medial gastrocnemius ultrasound (US) to characterize their muscle mass and quality. Results two hundred fifty-nine individuals (median age 67, 59.8% males) were included in the study. COVID-19 survivors with reduced muscle strength had a lower muscle US thickness (1.6 versus 1.73 cm, p =0.02) and a higher muscle stiffness (87 versus 76.3, p = 0.004) compared to patients with normal muscle strength. Also, patients with reduced Short Physical Performance Battery (SPPB) scores had a lower muscle US thickness (1.3 versus 1.71 cm, p = 0.01) and a higher muscle stiffness (104.9 versus 81.07, p = 0.04) compared to individuals with normal SPPB scores. The finding of increased muscle stiffness was also confirmed in patients with a pathological value (≥ 4) at the sarcopenia screening tool SARC-F (103.0 versus 79.55, p < 0.001). Muscle stiffness emerged as a significant predictor of probable sarcopenia (adjusted OR 1.02, 95% C.I. 1.002 – 1.04, p = 0.03). The optimal ultrasound cut-offs for probable sarcopenia were 1.51 cm for muscle thickness (p= 0.017) and 73.95 for muscle stiffness (p = 0.004). Discussion we described muscle ultrasound characteristics in post COVID-19 patients. Muscle ultrasound could be an innovative tool to assess muscle mass and quality in this population. Our preliminary findings need to be confirmed by future studies comparing muscle ultrasound with already validated techniques for measuring muscle mass and quality.
Curriculum-based Offline Network Training for Improvement of Peg-in-hole Task Performance for Holes in Concrete

A method for reducing the time required to train a deep neural network (DNN) via deep reinforcement learning (DRL) to enable a robot to conduct anchor-bolt insertion, a peg-in-hole task for holes in concrete, is proposed. The proposed method is also intended to reduce task execution time. The method consists of two steps. The first step involves creating a map of state observations and search results for holes opened in a concrete wall and using this map to train the DNN via DRL in an offline manner. The second step involves training the DNN with a curriculum that involves gradually increasing the step-size options the DNN can output to command the robot. Experimental evaluations of the method demonstrate that the offline training reduces DNN training time by about 87.5%, while enabling task execution with success rates and execution times that are similar to those obtained with a DNN trained online. Moreover, the evaluations show that curriculum training reduces task execution time, and enables execution of the peg-in-hole task for unknown holes with success rate of 97.5% and execution time of 7.77 s. This result represents a 12.8% higher success rate and a 4.71 s shorter execution time than those obtained with a DNN trained online. These results demonstrate the effectiveness of the proposed method and its applicability to the construction industry. Although the proposed method was applied to anchor-bolt insertion, it can be extended to any other peg-in-hole tasks conducted in discrete steps.
Auto-PUFChain: An Automated Interaction Tool for PUFs and Blockchain in Electronic Supply Chain

Physically Unclonable Functions (PUFs) primitives and blockchain technologies, also known as PUFchain, are recently taking huge attention to integrate the security parameters in Supply Chain Management (SCM) system. In this work, we devise a technique to interface an electronic chip and a blockchain platform by providing access to a unique hardware fingerprint and the stored information of chips on blockchain at one single point. To the best of our knowledge, this is the only scalable and automated technique that has been successfully implemented to authenticate the hardware device at any stage of the supply chain management system. The technique realises the concept of embedded PUF instance and the smart contract deployment on the ethereum blockchain. In the proposed technique, we have highly reduced the cost of implementing the interaction by storing the CRP on a distributed file system called as InterPlanetary File System (IPFS). Further, we implement and analyse the interfacing for ‘IC traceability’ to ensure the current ownership of a product, its point of origin, and ownership history in the SCM system. We employ Nexys 4 DDR Artix-7 FPGA board and go-ethereum blockchain library for implementing “IC traceability” to demonstrate the workflow and overhead involved in our interfacing technique.
Non-contact, Rapid and Robust Method to Determine the Optimal EEG Electrode Positions Using Optical Motion Tracking System

Electroencephalography (EEG) is a diagnostic test that involves placing electrodes at specific locations on the human head to detect and study electrical signals of brain activity. Current practitioners use a measuring tape and wax pencil to determine electrode positions and mark them using the internationally recognized 10–20 system. This meticulous procedure is time-consuming and laborious as it is manual. Hence, in this paper, we propose a rapid and robust method to determine the optimal electrode positions using an optical motion capture system (Optitrack) and a customized stylus. The stylus affixed with reflective markers is tracked by the motion capture system as it is used to trace different regions of the head in order to estimate the head geometry utilizing the 3D coordinate data of the trace throughout time. The 21 EEG electrode positions are then algorithmically predicted using the acquired spatial coordinate data. With testing under various experimental settings, the accuracy value in terms of Root Mean Square Error (RMSE) of the predicted EEG electrode positions is less than 1 cm with half the amount of time needed. Thus, the proposed method is assured to be faster and decreases errors due to imprecise electrode placement and determination.
Exploiting Intelligent Reflecting Surface for Energy Efficiency in Ambient Backscatter Communication-Enabled NOMA Networks

The growing demanding data rate requirements of future wireless networks have raised enormous concerns on energy consumption. Researchers conduct their study of green communication in terms of wireless communication environment and low power consumption communication technique. Recently, intelligent reflecting surface (IRS) and ambient backscatter communication (ABC) have been proposed, respectively, and they have attracted growing attention. In this paper, we study the ABC-enabled non-orthogonal multiple access (NOMA) networks. In such networks, environment obstacles may block the communication from the base station to the cell-edge user. To overcome this drawback, we propose an IRS-assisted relay transmission scheme. Therefore, in the ABC-enabled IRS-NOMA networks, there is a problem of how to enhance the network performance by optimizing the phase-shifts as well as the power resource allocation. We formulate an optimization problem to maximize the energy efficiency by jointly optimizing the phase-shifts of IRS’s reflecting elements and the power allocation of NOMA users. To deal with this problem, it is divided into two subproblems: 1) phase-shifts optimization and 2) power allocation optimization. The Dinkelbach-based iterative algorithm is applied to obtain maximum energy efficiency. Simulation results show that our proposed scheme always performs the best in terms of energy efficiency and throughput.
Spatiotemporal Initialization for 3D CNNs with Generated Motion Patterns

The paper proposes a framework of Formula-Driven Supervised Learning (FDSL) for spatiotemporal initialization. Our FDSL approach enables to automatically and simultaneously generate motion patterns and their video labels with a simple formula which is based on Perlin noise. We designed a dataset of generated motion patterns adequate for the 3D CNNs to learn a better basis set of natural videos. The constructed Video Perlin Noise (VPN) dataset can be applied to initialize a model before pre-training with large-scale video datasets such as Kinetics-400/700, to enhance target task performance. Our spatiotemporal initialization with VPN dataset (VPN initialization) outperforms the previous initialization method with the inflated 3D ConvNet (I3D) using 2D ImageNet dataset. Our proposed method increased the top-1 video-level accuracy of Kinetics-400 pre-trained model on {Kinetics-400, UCF-101, HMDB-51, ActivityNet} datasets. Especially, the proposed method increased the performance rate of Kinetics-400 pre-trained model by 10.3 pt on ActivityNet. We also report that the relative performance improvements from the baseline are greater in 3D CNNs rather than other models. Our VPN initialization mainly helps to enhance the performance in spatiotemporal 3D kernels. The datasets, codes and pre-trained models used in this study will be publicly available1.
Semantic Segmentation Guided Real-World Super-Resolution

Real-world single image Super-Resolution (SR) aims to enhance the resolution and reconstruct High-Resolution (HR) details of real Low-Resolution (LR) images. This is different from the traditional SR setting, where the LR images are synthetically created, typically with bicubic down-sampling. As the degradation process for real-world LR images are highly complex, SR of such images is much more challenging. Recent promising approaches to solve the Real-World Super-Resolution (RWSR) problem include the use of domain adaptation to create realistic training-pairs, and self-learning based methods which learn an image specific SR model at test time. However, as domain adaptation is an inherently challenging problem in itself, SR models based solely on this approach are limited by the domain gap. In contrast, while self-learning based methods remove the need for paired-training data by utilizing internal information in the LR image, these methods come with the cost of slow prediction times. This paper proposes a novel framework, Semantic Segmentation Guided Real-World Super-Resolution (SSG-RWSR), which uses an auxiliary semantic segmentation network to guide the SR learning. This results in noise-free reconstructions with accurate object boundaries, and enables training on real LR images. The latter allows our SR network to adapt to the image specific degradations, without Ground-Truth (GT) reference images. We support the guidance with domain adaptation to faithfully reconstruct realistic textures, and ensure color consistency. We evaluate our proposed method on two public available datasets, and present State-of-the-Art results in terms of perceptual image quality on both real and synthesized LR images.
Erratum for: Analysis of antenna gain enhancement using new frequency selective surface superstate

face current distribution, it seems that the physical origin is similar to polarization conversion that we have researched [2]–[5]. What’s more, similar structure has been designed to realize broad band polarization conversion at Terahertz [6]. Our conclusion is that it should be cross-polarization conversion rather than absorption. The structure in [1] is resimulated by a commercial software CST MICROWAVE STUDIO and the simulation results confirm with our conclusion. The resimulated reflectance with different polarization are illustrated in Figure 1. The copolarized reflection is low; however, the cross-polarized reflection is very strong. According to the polarization conversion effect of this structure, it can be concluded that |S11| 2 5 |Sco| 2 1 |Scross| 2 [7], where |S11| is the total reflection, |Sco| and |Scross| are coand cross-polarized reflection coefficients respectively. In Figure 2, the |S11| 2 is shown and its value is over 0.84 in the simulation frequency range. The absorption is expressed as A 5 1 2 |S11| 2 2 |S21| , where |S21| is the transmittance. The correct absorption is depicted in Figure 3. As is shown, the structure do not have strong microwave absorption effect and should not be considered as an absorber. For other incident angle, the conclusion is similar. The surface currents shown in Figures 6 and 7 from [1] are similar to the previous work which performance as a cross polarization convertor [2]. The explanation in section 4 of [1] should be the mechanism of the polarization conversion rather than the mechanism of absorption. Finally, we hope our work may reduce the misunderstanding of [1].
Investigation on Mass Flux Distribution and Asymmetrical Cooling in A Plate-Type Fuel Reactor

A program was developed to calculate the mass flux distribution in the whole core and the asymmetrical cooling of fuel pins for a plate type fuel reactor by applying the proper physical model.Three iterative algorithms for mass flux distribution calculation and two iterative algorithms for temperature field calculation of plate fuel element under asymmetrical cooling condition were proposed and compared by ap-plying in a subassembly.The results showed that the flow distribution is mainly determined by the core struc-ture,although it is also impacted by the power distribution in the core.The asymmetrical cooling condition seriously impacts the temperature field and power distribution of the fuel pins.
Large-scale shaking table test for subway station structure built in liquefiable saturated fine sand soil

A large-scale shaking table test for subway station structure built in the liquefiable saturated fine sand soil is implemented.Partial test results are analyzed in this paper.The acceleration time-histories and the dynamic pore water pressure ratio time-histories of ground soils are given.During the whole process of testing,it is obvious that the soils at the top of model ground and beside the subway station structure is liquefied firstly.Then the soil far from the subway station structure and at the bottom of model ground is liquefied with the increasing of the peak value of acceleration inputted by the surface of shaking table.However,the soils under the subway station structure is not liquefied during the whole process of testing.At the same time,the subway station structure uplifts badly during the soil liquefaction.
A Survey and Taxonomy of Latency Compensation Techniques for Network Computer Games

Computer games, one of the most popular forms of entertainment in the world, are increasingly online multiplayer, connecting geographically dispersed players in the same virtual world over a network. Network latency between players and the server can decrease responsiveness and increase inconsistency across players, degrading player performance and quality of experience. Latency compensation techniques are software-based solutions that seek to ameliorate the negative effects of network latency by manipulating player input and/or game states in response to network delays. We search, find, and survey more than 80 papers on latency compensation, organizing their latency compensation techniques into a novel taxonomy. Our hierarchical taxonomy has 11 base technique types organized into four main groups. Illustrative examples of each technique are provided, as well as demonstrated use of the techniques in commercial games.
Kemampuan Literasi Matematika Siswa SMP Negeri se-Kabupaten Bantul

Penelitian ini bertujuan untuk mendeskripsikan kemampuan literasi matematika siswa SMP Negeri di Kabupaten Bantul Yogyakarta. Teknik pengambilan sampel menggunakan cluster random sampling (teknik sampling kelompok). Jumlah anggota sampel penelitian ini 484 siswa kelas IX SMP dari 17 SMP Negeri yang dipilih dari setiap kecamatan di Kabupaten Bantul Daerah Istimewa Yogyakarta. Pengumpulan data menggunakan tes dengan instrumen 10 butir soal literasi yang memliliki reliabilitas dengan kualifikasi baik. Hasil penelitian menunjukkan bahwa kemampuan literasi matematika siswa SMP Negeri di Kabupaten Bantul masih tergolong kategori sangat rendah. Kemampuan literasi matematika siswa SMP Negeri di Kabupaten Bantul untuk domain konten bilangan, peluang dan data termasuk kategori sedang, sedangkan untuk konten aljabar termasuk dalam kategori rendah, dan geometri termasuk kategori sangat rendah. Kemampuan literasi matematika siswa SMP Negeri di Kabupaten Bantul untuk domain proses memformulasikan situasi matematika termasuk kategori tinggi, untuk domain proses menggunakan konsep, fakta, prosedur, dan penalaran matematika termasuk kategori rendah , dan untuk domain proses menafsirkan, menerapkan, dan mengevaluasi hasil matematika termasuk kategori sangat rendah. Kata kunci: literasi matematika Mathematic al literacy of state junior secondary school student s in Bantul Regency Abstract The aim of this research was to describe mathematic al literacy of State Junior Secondary School students in Bantul Regency Yogyakarta . The sampling was cluster random sampling. The number of member of sample used was 4 84 students that were choosen from 17 th Junior Secondary School s in each subdistrict in Bantul Regency. The data collection was by tests. The student s w ere tested with 1 0 items of mathematic al literacy problem which have good reliability qualification. The research finding reveal ed that mathematic al literacy of State Junior Secondary School students in Bantul Regency was in very low category . Mathematical literacy of State Junior Secondary School students in Bantul Regency for quantity, uncertainty and data belongs to average category, whereas for algebra belongs to low category, and for geometry belongs to very low category. Mathematical literacy of State Junior Secondary School students in Bantul Regency for formulating situations mathematically domains belongs to high category, for employing mathematical concepts, fact, procedures, and reasoning domains belongs to low category, and for interpreting, applying, and evaluating mathematical outcomes domains belongs to very low category. Keywords: mathematic al literacy
Combating Weapons of Mass Destruction: Models, Complexity, and Algorithms in Complex Dynamic and Evolving Networks

Abstract : This project considers attack and defense problems on networks with respect to WMD attacks. It provides novel optimization models and solutions for network vulnerability assessment and defense measurement in the face of cascading failures and dynamic attacks. The critical infrastructures considered are complex systems which consist of multiple dynamic independent networks interacting to each other. The attacks we considered are dynamic, that is, another attack may be launched during the recovery.
The life history and control of Pityophthorus juglandis Blackman on Juglans nigra L. in eastern Tennessee

44 Introduction 44 Materials and Methods 46 Results and Discussion 49 Conclusions 61 CHAPTER IV 62 Concentration Levels of Imidacloprid and Dinotefuran in Juglans nigra 62 Abstract 62 Introduction 62 Materials and Methods 65 Results and Discussion 70 Conclusions 79 Overall Conclusions 80 List of References 83 Vita 93
Experimental results for optimal placement piezoelectric plates for active vibration control for cantilever beam

Abstract—The fatigue phenomena correlated to the gas turbine blades vibrations can lead to catastrophic failure. To damp the vibrations amplitude typically damping passive systems are used. In the last years the interest in the piezoelectric materials, and their use as damping elements, has received considerable attention by many researchers. Recently different research groups have started to study their use in blades of turbomachinery. Because of their effectiveness strongly depends on their position, some of the authors have proposed ([15], [17]) a new model to find the optimal position to control the multimode vibrations. Such model has been corroborated by experimental results for different combinations of excited eigenmodes ([16], [18]]). In this paper the authors present new experimental results with the aim to increase the knowledge of the optimal position of the piezoelectric plates when different eigenmodes are involved.