Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterodonty and patterns of tooth replacement in Crocodylus niloticus

Patterns of tooth replacement in the Nile crocodile Crocodylus niloticus were evaluated in the lateral radiographs of six dried skulls of 1‐year‐old individuals. Additionally, the ontogeny of the succession of teeth in this species was investigated in four embryos and a hatchling, which were serially sectioned. Three‐dimensional, computer‐generated reconstructions of these individuals suggested that there was a regular pattern of odontogenic progression. Three morphogenetic zones could be identified in each of the age classes: an incisor, a canine, and a molar region. It was thus concluded that the Nile crocodile is hetero‐ rather than homodont. Zahnreihen, or tooth rows, with a periodicity of one were easily identified. © 1993 Wiley‐Liss, Inc.
Sensor-less torque control considering contact phase for two-mass system

This paper considers the contact phase in a sensorless torque control system for a two-mass system. A plant system is a two mass system with an environmental switch. The environmental switch is used for considering unstable contact behavior. The state observer (SOB) and zero-order disturbance observer (ZODOB) are used to estimate the state variable of a plant system. In sensor-less torque control system, the ZODOB has better performance than the SOB. When plant system is not in contact with the environment the estimated value using the SOB is not good for control system. It makes control system becomes instability in some cases. When the ZODOB is fed back to torque control system, the stability of control system is preserved. Experiments are performed to confirm the effectiveness of using the ZODOB in sensor-less torque control system.
GPU-Accelerated Gridding for Rapid Reconstruction of Non-Cartesian MRI

Introduction: Non-Cartesian acquisitions are commonly used for MR imaging of short-T2 species, such as 23-sodium or 17-oxygen where an ultra-short echo time is essential for quantification, and for rapid 2-D and 3-D MR imaging of anatomy, physiology, or function. Since the Fast Fourier Transform (FFT) cannot be directly applied to non-Cartesian kspace data, alternate methods must be used for image reconstruction. Gridding-based image reconstruction allows the FFT to be used after interpolating the non-Cartesian data onto a Cartesian grid [1]. However, despite the fact that the algorithmic complexity of gridding is O(N) (Big-O notation), this step can still take significant time when there are millions of sample points or when gridding is performed multiple times as part of a multi-frequency reconstruction. We propose a method to perform gridding using a graphics processor (GPU) to achieve up to 29X acceleration for 3-D gridding.
“I feel that life is meaningless”: Vietnamese adolescents' experiences of and reflections about interpersonal violence

Background The experiences of and reflections on interpersonal violence and victimisation among adolescents living in low- and middle-income countries are poorly understood. The aim was to describe Vietnamese adolescents’ reflections on their experiences of victimisation. Method A self-completed, cross-sectional survey investigating exposure to violence among high school students in Hanoi, Vietnam was conducted during 2013–2014. The last section invited participants to write about any of the matters covered in the questionnaire. Thematic analysis was conducted on these free-text comments. Results A total of 73/76 eligible students participated in the pilot and 1616/1745 in the main survey. Of these, a total of 239 records with free-text comments were analysed. Students described experiences of violence occurring at home, at school and in the community. Experiences of violence led to sadness, loneliness, having extremely negative thoughts about the value of life, and suicidal ideas. Adolescents’ experiences occurred in the context of poor parent–adolescent and teacher–student relationships, particularly concerning dissatisfaction with academic performance. Adolescents wanted to be trusted, to be given more autonomy, and to improve their relationships with parents and teachers. Conclusions Vietnamese adolescents experience various forms of victimisation, which are detrimental to their health and wellbeing. Understanding of their experiences of and perceptions of violence and its impact on their health and wellbeing is important in the prevention of violence against young people in Vietnam.
Predictive pinning control with communication delays for consensus of multi-agent systems

In this paper, based on the policy of model predictive control (MPC), a new method of predictive pinning control is proposed for the consensus problem of multi-agent systems. Pinning control is a method that the external control input is added to some agents (pinning nodes), e.g., leaders. By the external control input, consensus to a certain target value (not the average of the initial states) and faster consensus are achieved. In the proposed method, the external control input is calculated by the controller node connected to pinning nodes. Since all states of agents are required in calculation of the external control input, communication delays must be considered. The proposed algorithm includes not only calculation of the external control input but also delay compensation. The effectiveness of the proposed method is presented by two numerical examples.
Make Larger Vector Register Sizes New Challenges?: Lessons Learned from the Area of Vectorized Lightweight Compression Algorithms

The exploitation of data as well as hardware properties is a core aspect for efficient data management. This holds in particular for the field of in-memory data processing. Aside from increasing main memory capacities, in-memory data processing also benefits from novel processing concepts based on lightweight compressed data. To speed up compression as well as decompression, an active research field deals with the specialization of these algorithms to hardware features such as vectorization using SIMD instructions. Most of the vectorized implementations have been proposed for 128 bit vector registers. However, hardware vendors still increase the vector register sizes, whereby a straightforward transformation to these wider vector sizes is possible in most-cases. Thus, we systematically investigated the impact of different SIMD instruction set extensions with wider vector sizes on the behavior of straightforward transformed implementations. In this paper, we will describe our evaluation methodology and present selective results of our exhaustive evaluation. In particular, we will highlight some challenges and present first approaches to tackle them.
On Adaptive Length of Temporal Filter for Space-Time Equalization With Cochannel Interference

In this letter, we take the initiative in adaptively determining the optimal temporal filter (TF) length for space-time equalization (STE) schemes, where overfitting may occur under too large TF length. We specifically consider the system without employing cyclic-prefix such that the spectral efficiency could be maintained. Based on the delicately derived connection between the mean square error (MSE) of equalized training symbols and unknown data symbols, the MSE of the latter can be predicated and serves as the decision metric for determining the optimal TF length. Numerical results demonstrate that the proposed STE scheme with TF of adaptively optimized length can work properly, even in the presence of cochannel interference.
SuMo-SS: Submodular Optimization Sensor Scattering for Deploying Sensor Networks by Drones

To meet the immediate needs of environmental monitoring or hazardous event detection, we consider the automatic deployment of a group of low-cost or disposable sensors by a drone. Introducing sensors by drones to an environment instead of humans has advantages in terms of worker safety and time requirements. In this study, we define “sensor scattering (SS) ” as the problem of maximizing the information-theoretic gain from sensors scattered on the ground by a drone. SS is challenging due to its combinatorial explosion nature, because the number of possible combination of sensor positions increases exponentially with the increase in the number of sensors. In this letter, we propose an online planning method called submodular optimization sensor scattering (SuMo-SS). Unlike existing methods, the proposed method can deal with uncertainty in sensor positions. It does not suffer from combinatorial explosion but obtains a $(1-1/e)$ -approximation of the optimal solution. We built a physical drone that can scatter sensors in an indoor environment as well as a simulation environment based on the drone and the environment. In this letter, we present the theoretical background of our proposed method and its experimental validation.
Privacy-Preserving and Efficient Aggregation Based on Blockchain for Power Grid Communications in Smart Communities

Intelligence is one of the most important aspects in the development of our future communities. Ranging from smart home to smart building to smart city, all these smart infrastructures must be supported by intelligent power supply. Smart grid is proposed to solve all challenges of future electricity supply. In smart grid, in order to realize optimal scheduling, an SM is installed at each home to collect the near-real-time electricity consumption data, which can be used by the utilities to offer better smart home services. However, the near-real-time data may disclose a user's private information. An adversary may track the application usage patterns by analyzing the user's electricity consumption profile. In this article, we propose a privacy-preserving and efficient data aggregation scheme. We divide users into different groups, and each group has a private blockchain to record its members' data. To preserve the inner privacy within a group, we use pseudonyms to hide users' identities, and each user may create multiple pseudonyms and associate his/ her data with different pseudonyms. In addition, the bloom filter is adopted for fast authentication. The analysis shows that the proposed scheme can meet the security requirements and achieve better performance than other popular methods.
Geometric Distance Between Positive Definite Matrices of Different Dimensions

We show how the geodesic distance on <inline-formula> <tex-math notation="LaTeX">$\mathbb {S}^{n}_{+ + }$ </tex-math></inline-formula>, the cone of <inline-formula> <tex-math notation="LaTeX">$n\times n$ </tex-math></inline-formula> real symmetric or complex Hermitian positive definite matrices regarded as a Riemannian manifold, may be used to naturally define a distance between two such matrices of different dimensions. Given that <inline-formula> <tex-math notation="LaTeX">$\mathbb {S}^{n}_{+ + }$ </tex-math></inline-formula> also parameterizes <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-dimensional ellipsoids, inner products on <inline-formula> <tex-math notation="LaTeX">$\mathbb {R}^{n}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$n \times n$ </tex-math></inline-formula> covariances of nondegenerate probability distributions, this gives us a natural way to define a geometric distance between a pair of such objects of different dimensions.
Discriminating Schizophrenia and Bipolar Disorder by Unique Patterns of Brain Function and Structure

Introduction: Diverse structural and functional brain alterations have been identified in both schizophrenia (SZ) and bipolar disorder (BP), but with variable replicability, significant overlap and often in limited numbers of subjects. In this work, we highlighted both similarities and differences between two modalities across three diagnostic groups by fusion of functional MRI and diffusion tensor imaging data, which had not yet been attempted for a relatively large number of subjects.
Evolution of pathogen and parasite avoidance behaviours†

All free-living animals are subject to intense selection pressure from parasites and pathogens resulting in behavioural adaptations that can help potential hosts to avoid falling prey to parasites. This special issue on the evolution of parasite avoidance behaviour was compiled following a Royal Society meeting in 2017. Here we have assembled contributions from a wide range of disciplines including genetics, ecology, parasitology, behavioural science, ecology, psychology and epidemiology on the disease avoidance behaviour of a wide range of species. Taking an interdisciplinary and cross-species perspective allows us to sketch out the strategies, mechanisms and consequences of parasite avoidance and to identify gaps and further questions. Parasite avoidance strategies must include avoiding parasites themselves and cues to their presence in conspecifics, heterospecifics, foods and habitat. Further, parasite avoidance behaviour can be directed at constructing parasite-retardant niches. Mechanisms of parasite avoidance behaviour are generally less well characterized, though nematodes, rodents and human studies are beginning to elucidate the genetic, hormonal and neural architecture that allows animals to recognize and respond to cues of parasite threat. While the consequences of infection are well characterized in humans, we still have much to learn about the epidemiology of parasites of other species, as well as the trade-offs that hosts make in parasite defence versus other beneficial investments like mating and foraging. Finally, in this overview we conclude that it is legitimate to use the word ‘disgust' to describe parasite avoidance systems, in the same way that ‘fear' is used to describe animal predator avoidance systems. Understanding disgust across species offers an excellent system for investigating the strategies, mechanisms and consequences of behaviour and could be a vital contribution towards the understanding and conservation of our planet's ecosystems. This article is part of the Theo Murphy meeting issue ‘Evolution of pathogen and parasite avoidance behaviours'.
Primary Fungal Prophylaxis in Hematological Malignancy: a Network Meta-Analysis of Randomized Controlled Trials

Several new antifungal agents have become available for primary fungal prophylaxis of neutropenia fever in hematological malignancy patients. Our aim was to synthesize all evidence on efficacy and enable an integrated comparison of all current treatments. ABSTRACT Several new antifungal agents have become available for primary fungal prophylaxis of neutropenia fever in hematological malignancy patients. Our aim was to synthesize all evidence on efficacy and enable an integrated comparison of all current treatments. We performed a systematic literature review to identify all publicly available evidence from randomized controlled trials (RCT). We searched Embase, PubMed, the Cochrane Central Register of Controlled Clinical Trials, and the www.ClinicalTrials. gov website. In total, 54 RCTs were identified, including 13 treatment options. The evidence was synthesized using a network meta-analysis. Relative risk (RR) was adopted. Posaconazole was ranked highest in effectiveness for primary prophylaxis, being the most favorable in terms of (i) the RR for reduction of invasive fungal infection (0.19; 95% confidence interval [CI], 0.11 to 0.36) and (ii) the probability of being the best option (94% of the cumulative ranking). Posaconazole also demonstrated its efficacy in preventing invasive aspergillosis and proven fungal infections, with RR of 0.13 (CI, 0.03 to 0.65) and 0.14 (CI, 0.05 to 0.38), respectively. However, there was no significant difference among all of the antifungal agents in all-cause mortality and overall adverse events. Our network meta-analysis provided an integrated overview of the relative efficacy of all available treatment options for primary fungal prophylaxis for neutropenic fever in hematological malignancy patients under myelosuppressive chemotherapy or hematopoietic cell transplantation. On the basis of this analysis, posaconazole seems to be the most effective prophylaxis option until additional data from head-to-head randomized controlled trials become available.
Keeping the Lights On: A Comparison of Normal Accidents and High Reliability Organizations

Large technological systems have many modes of failure &ndash; some mundane, others exotic, some with dire consequences. Failures resulting in death and environmental degradation spring easily to mind: Chernobyl, Bhopal, Deepwater Horizon. As a large technological system, the U.S. electric power infrastructure experienced failures during major Northeast blackouts in 1965 and 2003, when large areas were left without power, and the system frequently experiences both large and small blackouts. How should we conceptualize failure in complex technological systems like electric power?
A review of haptic simulator for oral and maxillofacial surgery based on virtual reality

ABSTRACT Introduction: Traditional medical training in oral and maxillofacial surgery (OMFS) may be limited by its low efficiency and high price due to the shortage of cadaver resources. With the combination of visual rendering and feedback force, surgery simulators become increasingly popular in hospitals and medical schools as an alternative to the traditional training. Areas covered: The major goal of this review is to provide a comprehensive reference source of current and future developments of haptic OMFS simulators based on virtual reality (VR) for relevant researchers. Expert commentary: Visual rendering, haptic rendering, tissue deformation, and evaluation are key components of haptic surgery simulator based on VR. Compared with traditional medical training, virtual and tactical fusion of virtual environment in surgery simulator enables considerably vivid sensation, and the operators have more opportunities to practice surgical skills and receive objective evaluation as reference.
Optimal routing control of a construction machine by deep reinforcement learning

Deep reinforcement learning algorithms are rapidly growing, and expected to be applied to many industrial fields. In this paper, we proposed a method that combines a deep Q-network with batch normalization to generate an optimal route for a grading machine. The goal is to achieve autonomous operation of the grading machine. For the learning platform, a grading simulator was developed to emulate the grading work. The proposed method was evaluated with the grading simulator, and showed better route searching performance results than the conventional method.
Deep Continuous Conditional Random Fields With Asymmetric Inter-Object Constraints for Online Multi-Object Tracking

Online multi-object tracking (MOT) is a challenging problem and has many important applications including intelligence surveillance, robot navigation, and autonomous driving. In existing MOT methods, individual object’s movements and inter-object relations are mostly modeled separately and relations between them are still manually tuned. In addition, inter-object relations are mostly modeled in a symmetric way, which we argue is not an optimal setting. To tackle those difficulties, in this paper, we propose a deep continuous conditional random field (DCCRF) for solving the online MOT problem in a track-by-detection framework. The DCCRF consists of unary and pairwise terms. The unary terms estimate tracked objects’ displacements across time based on visual appearance information. They are modeled as deep convolution neural networks, which are able to learn discriminative visual features for tracklet association. The asymmetric pairwise terms model inter-object relations in an asymmetric way, which encourages high-confidence tracklets to help correct errors of low-confidence tracklets and not to be affected by low-confidence ones much. The DCCRF is trained in an end-to-end manner for better adapting the influences of visual information as well as inter-object relations. Extensive experimental comparisons with state-of-the-arts as well as detailed component analysis of our proposed DCCRF on two public benchmarks demonstrate the effectiveness of our proposed MOT framework.
Piecewise affine (PWA) modeling and switched damping control of two-inertia systems with backlash

Backlash degrades positioning accuracy and can induce mechanical wear and breakage by collisions. Therefore, a lot of studies have been conducted on backlash compensation. The simplest control method for the impact attenuation is torsional damping addition by feedback of torsional velocity. This paper reveals the advantages and disadvantages of the torsional damping addition. Based on the analyses, a novel switched damping control is proposed to realize the responses with smaller overshoot while attenuating the impact. The mechanical system and the proposed controller are described as piecewise affine systems for analyses. The performance of the proposed method is compared with a linear damping control method in simulations and experiments.
Effect of photoperiod on testicular function in blinded and non‐blinded marbled newts, Triturus marmoratus (caudata, salamandridae)

Adult male marbled newts (Triturus marmoratus) were collected at the beginning of the spermatogenetic period and exposed to different photoperiods (natural photoperiod with progressively increasing daylengths, total darkness, 8L:16D, 12L:12D, 16L:8D, and continuous light) for 3 months at 20°C. To evaluate the effect of photoperiodic input via pineal gland photoreceptors, two additional groups of newts were blinded by a non‐aggressive method (an elastic rubber cap was adjusted to the head to cover the eyes but not the pineal photoreceptors). These animals were exposed either to the natural photoperiod or to 12 hr of light per day. Quantitative histologic studies on testicular development and germ‐cell volume revealed no significant differences between non‐blinded and blinded animals. Testicular size and germ‐cell development increased in the following order: total darkness, constant light, 8L:12D, natural photoperiod, 12L:12D, and 16L:8D. These results suggest that (1) long photoperiods enhance testicular development, whereas short photoperiods or an environment of continuous light have the opposite effects and (2) the effect of photoperiods on testicular function in newts is independent of the ocular photoreceptors.
ProFlow: Learning to Predict Optical Flow

Temporal coherence is a valuable source of information in the context of optical flow estimation. However, finding a suitable motion model to leverage this information is a non-trivial task. In this paper we propose an unsupervised online learning approach based on a convolutional neural network (CNN) that estimates such a motion model individually for each frame. By relating forward and backward motion these learned models not only allow to infer valuable motion information based on the backward flow, they also help to improve the performance at occlusions, where a reliable prediction is particularly useful. Moreover, our learned models are spatially variant and hence allow to estimate non-rigid motion per construction. This, in turns, allows to overcome the major limitation of recent rigidity-based approaches that seek to improve the estimation by incorporating additional stereo/SfM constraints. Experiments demonstrate the usefulness of our new approach. They not only show a consistent improvement of up to 27% for all major benchmarks (KITTI 2012, KITTI 2015, MPI Sintel) compared to a baseline without prediction, they also show top results for the MPI Sintel benchmark -- the one of the three benchmarks that contains the largest amount of non-rigid motion.