Miracle-dz/UniFAR-FTUs huggingface dataset:
FUNCTIONAL ORGANIZATION AND INTEGRATIVE MECHANISM ON THE AUDITORY CORTEX OF THE CAT

1. Single unit analyses have been done in 180 cortical auditory neurons of cats anesthetized with barbiturate.2. A new type of the response area was found besides the flat type and the sharp peak type. The neurons of this type had multi-peaks in their response area.3. An example of the multi-peak type was shown, and its response area and pattern suggested the direct projection of afferent fibers from the neurons of the medial geniculate body.4. The flat type had the longest mean latency, followed the multi-peak type, and the sharp peak type.5. The type of the response area changed from the flat type to the multipeak tpe or sharp peak type after the depth of the neurons encountered in a penetration.6. The neurons obtained from a vertical penetration had the same characteristic frequency, and were presumed to be in a functional vertical column which was determined by the best frequency.7. Many types of the response areas were involved in the neurons of the same penetration, and an integrative mechanism of the frequency was consid ered to be the convergence from the sharp peak type to the flat type via multi-peak type.8. The changes in response properties caused by the two-tone stimulation were studied. The effect was more conspicuous in facilitation rather than inhibition, and observed mainly in the neurons with the narrow response area.9. Facilitation occurred even when the two stimulating sounds did not give a beat, and the effective frequency range of some neurons was three bands far apart from their characteristic frequencies.10. The effect differed after the frequency and intensity relation of the two tones.11. In some cortical cells, the on response underwent different changes from that of the off response.12. The threshold values were lowered especially at the high threshold frequency range of the response areas, and a new peak appeared in the response areas.13. This facilitatory effect caused by the two-tone stimulation suggests that the cortical cells were sensitive to the change in frequency and intensity of the tonal stimuli, which seemed to be related to the discrimination of the complex sound.
Direct Drive Hand Exoskeleton for Robot-assisted Post Stroke Rehabilitation

This article introduces novel rehabilitation hand module development for the physiotherapy of the hand of patients suffering from spastic hemiplegia. Spasm is basically a muscle cramp, it practically involves the sudden, unintended and painful contraction of a muscle or muscle group, which is caused by nerve damage resulting from a stroke. Stroke is the main reason for permanent disability in adulthood, and so the socialand medical care systems require a huge amount of healthcare resources due to the inactivity of the patients concerned. The robotically facilitated rehabilitation assists the physicians in providing repeated therapies of great intensity, and so the patients may enjoy the benefits of rehabilitation, while the therapists may reduce their own workload at the same time. Furthermore, the robotic devices offer an objective and reliable opportunity for tracing and accurately assessing the improvement of the patients’ motor skills. This article introduces the electricaland mechanical design of a therapeutic device and the inverse kinematic and dynamic modules which control this device. The rehabilitation device is capable of moving the thumb, the index-, the middleand the ring fingers, and allows the rehabilitation of the leftand right hands as well. The device is a completely new design with direct drive approach and several benefits. It has two components: a planar module with serial kinematics of rotational joints with three degrees of freedom (3DoF RRR), and another module with two degrees of freedom (2DoF). The modules integrated load cells, which are built in between each joint to measure the reaction forces. The 3DoF finger moves the index, the middle and the ring fingers, using a load distributor placed above the fingers. The finger orthoses are connected to the load distributor via magnets. The 2DoF finger moves the thumb performing the opening/closing along the plane tilted in two angles.
The beginning phases of the early childhood caries (circular caries) - clinical evaluation of remineralization

Early childhood caries (circular caries) can occur at an early age, with the eruption of deciduous teeth of the age of 1 to 1.5 years old. This is a multifactorial dental disease that has become a worldwide problem with high prevalence in recent decades. The purpose of the study was clinical evaluation of the remineralizing effect of the topical treatment, in patients with starting stages of circular caries. This study was conducted at the Clinic for Pediatric and Preventive Dentistry, Skopje, and included 117 patients of both sexes, with the starting stages of circular caries. They were aged of 1.5 to 3.5 years old, with a fully formed primary tooth. It was selected 61 patients with initial lesion – white spot and 56 patients with superficial form. From both groups 30 patients were treated with topical fluoride preparation, for a period of six months, applied once a week. The remaining patients had regular check-ups and instructions, but they did not undergo fluoride treatment. After the fluoride treatment, we followed the remineralizing effect, i.e. which initial lesions were reversed or where the intracrystal spaces were filled and the crystals were repaired after six months of topical application. In some patients who were able to satisfy other preventative factors, we were able to obtain a clinical picture of complete remineralization on initial lesion (restitution ad integrum) in vivo, approximately similar to a healthy tooth. How successful the remineralization will be depends on the predominant, protective, or pathogenic factors. Keywords: circular caries, early childhood caries, remineralization, initial lesion, white spot
Parameterization and Surface Reconstruction

In this paper we study parameterization as a tool for both constructing and smoothing spatial triangulations. Most of the parameterization methods we study are based on convex combination maps, which have the property that the image of each interior vertex is a convex combination of its neighbours. When mapping an existing triangulation, this latter property ensures that whenever the image of the map is convex, the map is one-to-one, and thus a homeomorphism. At the same time, convex combination maps are very general because every one-to-one piecewise linear map is a convex combination map. Suitable convex combination maps for parameterization arise naturally as discretizations of harmonic maps, but can also be constructed explicitly, in order to satisfy important properties such as linear precision.
Generalization of Habituation: When Non-essential Notifications Cause Users to Tune Out Critical Security Warnings

This research measures how decreased attention to frequent software notifications negatively influences responses to uncommon security warnings that are truly critical. We examine the factors that influence this generalization of habituation. These factors include the similarity of visual appearance and mode of interaction (i.e., the “look and feel”) between notifications and warnings and the volume of notifications. We measure the impacts of generalization in terms of diminished attention via mouse cursor tracking data, as well as individuals’ ability to behaviorally respond successfully to security warnings by adhering to the warning recommendations. Through an online image classification experiment, we find this generalization of habituation occurs in security warnings with a similar look and feel as the notifications. We find less of an effect in security warnings with a more distinct look and feel. The implications of this research will guide software developers in creating security warnings that are more effective.
Notes on Complexity Theory Last updated : November , 2011 Lecture 25

Randomization provides unconditional benefits in many settings; examples include cryptography (where random keys are used to provide protection against an adversary) and distributed computing (where randomness can be used as a means to break symmetry between parties). Randomness also appears to help in algorithm design. But is it possible that, from a complexity-theoretic perspective, randomness does not help? E.g., might it be the case that every problem that can be solved in randomized polynomial time can also be solved in deterministic polynomial time? (That is, is P = BPP? ) Historically, guided by progress in designing efficient randomized algorithms, most researchers believed that randomness does help. Research over the past 25 years on (timebounded) derandomization has now led many to change their views; the consensus nowadays is that randomization does not help.1 One natural approach to derandomize algorithms is to use a pseudorandom generator (PRG) that expands a small, truly random input into a larger, random-looking output. In the next section we define PRGs and then describe their application to derandomization. The remainder of these notes will focus on constructing a PRG based on a (plausible) complexity assumption.
Epidemiological Characteristics of Human Rhinovirus with Acute Respiratory Tract Infection in Children and Its Correlation with Climate in Suzhou during 2013-2015

基金项目:国家自然科学基金项目,编号 81573167;苏州市科技项目,编号 sys201436。 作者简介:周丹(1982郾 11-),女,硕士,主治医师,主要从事儿科临床工作,E鄄mail: 15949203867@ 163郾 com。 通讯作者:王宇清(1976郾 10-),男,博士,副主任医师,副教授,主要从事小儿呼吸系统疾病研究,E鄄mail: wang_yu_qing@ 126郾 com。 [摘要] 目的:探讨苏州地区儿童急性呼吸道感染鼻病毒(hRV)感染的流行特点及与气候因素的相关性。 方法:对 2013 年 1 月 至 2015 年 12 月因呼吸道感染在苏州大学附属儿童医院呼吸科住院的儿童,应用 RT鄄PCR 方法检测 hRV 和 7 种常见呼吸道病 毒、人类偏肺病毒、人类博卡病毒、痰肺炎支原体 DNA、血清肺炎支原体特异性抗体,痰培养检测细菌;同时收集苏州地区有关 气象资料,采用直线回归和逐步回归法研究 hRV 感染流行与气候因素的相关性。 结果:5 994 例患儿中,病原检出率排在前 3 位分别为肺炎支原体(34郾 37% )、呼吸道合胞病毒(11郾 09% )、hRV(10郾 78% )。 hRV 秋季检出率(13郾 32% )高于其他季节。 hRV 常见混合感染的病原依次为:肺炎支原体(30郾 96% )、肺炎链球菌(10郾 84% )、人类博卡病毒(6郾 66% )。 气候温度与 hRV 检 出率呈正相关(茁=0郾 499,t=2郾 112,P=0郾 043)。 结论:hRV 是引起苏州地区住院儿童呼吸道感染的重要病毒病原体之一。 苏州 地区 hRV 感染的流行季节在秋季。 hRV 常见混合感染的病原是肺炎支原体、肺炎链球菌、人类博卡病毒。 气候因素尤其是气 温与 hRV 检出率呈正相关。 [关键词] 呼吸道感染;鼻病毒;流行特征;气候;儿童 [中图分类号]R725郾 6摇 摇 摇 摇 摇 摇 [文献标识码]A 摇 摇 摇 摇 摇 摇 [文章编号]1672鄄108X(2018)08鄄0008鄄04
Group Activity Matching with Blockchain Backed Credible Commitment

Humans are social creatures which enjoy participating in group activities. Existing platforms such as event-based social networks and social-matching applications empower people to organize and participate in different kinds of interest-based activities. However, credibility issues are inevitable since the participants’ commitment to participate in activities on time can hardly be guaranteed. As a result, many activities are canceled due to lack of participation, which impairs people’s will for attending activities and increases the difficulty of coalescing activity groups. In this work, we propose an approach, called BC-GAM, for matching group activities with blockchain backed credible commitment. Based on a formalization of the matching problem, BC-GAM works as follows. During user requesting (for certain type of activity), the user is required to pay a variable deposit which reflects his/her level of commitment for participating in the activity. Our matching algorithm then automatically coalesces the users according to the user requests and availability of facilities. Our algorithm is designed to maximally allow the enrolled users to participate in activities based on their commitment. Furthermore, BC-GAM utilizes blockchain techniques and smart contracts so that the user requesting, commitment and participation are automatically executed in a distributed and trusted way. We implemented BC-GAM on a hyperledger and developed a user interface for requesting and inquiry of the activities. Based on the blockchain platform, we performed experiments with not only simulated data but also actual user studies. The experiment results show that the matching algorithm is effective and efficient, and BC-GAM can be potentially applied in practice.
Testing for Dynamic Software Update: An Object-State-Oriented Approach

Dynamic software update (DSU) can patch programs without stopping them. The updating process includes replacing changed code, transforming stale objects with object transformers, and resuming the execution of the updated program. However, flawed object transformers currently hinder DSU from the wide application, since they may introduce the inconsistencies between the transformed objects with expected new ones, that are created by the new program executing from scratch with the same inputs. To detect such inconsistencies, our approach first utilizes fuzzing testing to explore test inputs, then executes them over the old and new versions of a program within our specially designed parallel executor. Any inconsistency and the corresponding test will be issued. The evaluation over default transformer in 50 updates (14 of them have the inconsistency problem) showed that our approach discovered inconsistency in 16 updates, with 5 false positives and 3 false negatives. We also optimized the seed selection strategy in fuzzing process and improved the efficiency by 25.0%.
Enhancing FSCS-ART through Test Input Quantization and Inverted Lists

Fixed-size-candidate-set adaptive random testing (FSCS-ART) is an ART technique well-known for its best failure-detection effectiveness and usages in testing many real-life applications. However, it faces substantial computational overhead in terms of O(n2) time cost for generating n test inputs, which becomes worse for high dimensional input domains (number of inputs a software takes). As real-life programs generally have low failure-rates and have high dimensional input domains, it is vital to reduce the computational overhead while preserving the failure-detection effectiveness for efficient software testing. In this work, we adopted Quantization and InVerted File structure approach to enhance the original FSCS-ART, called QIVFSCS-ART. The proposed method preprocesses the software input domain by partitioning it into discrete cells by using K-means clustering using a uniform random dataset. After this, the quantized form of each executed test input is stored in the inverted list of its cell’s center, called centroid. Results show that the proposed method significantly relieves the computational overhead of FSCS-ART while preserving its failure-detection effectiveness, especially for the high-dimensional software input domains.
Least squares for programmers: with color plates

This course explains least squares optimization, nowadays a simple and well-mastered technology. We show how this simple method can solve a large number of problems that would be difficult to approach in any other way. This course provides a simple, understandable yet powerful tool that most coders can use, in the contrast with other algorithms sharing this paradigm (numerical simulation and deep learning) which are more complex to master.
Contact and friction simulation for computer graphics

Efficient simulation of contact is of interest for numerous physics-based animation applications. For instance, virtual reality training, video games, rapid digital prototyping, and robotics simulation are all examples of applications that involve contact modeling and simulation. However, despite its extensive use in modern computer graphics, contact simulation remains one of the most challenging problems in physics-based animation. This course covers fundamental topics on the nature of contact modeling and simulation for computer graphics. Specifically, we provide mathematical details about formulating contact as a complementarity problem in rigid body and soft body animations. We briefly cover several approaches for contact generation using discrete collision detection. Then, we present a range of numerical techniques for solving the associated LCPs and NCPs. The advantages and disadvantages of each technique are further discussed in a practical manner, and best practices for implementation are discussed. Finally, we conclude the course with several advanced topics, such as anisotropic friction modeling and proximal operators. Programming examples are provided on the course website to accompany the course notes.
Journal Pre-proofs

The segmentation of COVID-19 lesions from computed tomography (CT) scans is crucial to develop an efficient automated diagnosis system. Deep learning (DL) has shown success in different segmentation tasks. However, an efficient DL approach requires a large amount of accurately annotated data, which is difficult to aggregate owing to the urgent situation of COVID-19. Inaccurate annotation can easily occur without experts, and segmentation performance is substantially worsened by noisy annotations. Therefore, this study presents a reliable and consistent temporal-ensembling (RCTE) framework for semi-supervised lesion segmentation. A segmentation network is integrated into a teacher-student architecture to segment infection regions from a limited number of annotated CT scans and a large number of unannotated CT scans. The network generates reliable and unreliable targets, and to evenly handle these targets potentially degrades performance. To address this, a reliable teacher-student architecture is introduced, where a reliable teacher network is the exponential moving average (EMA) of a reliable student network that is reliably renovated by restraining the student involvement to EMA when its loss is larger. We also present a noise-aware loss based on improvements to generalized cross-entropy loss to lead the segmentation performance toward noisy annotations. Comprehensive analysis validates the robustness of RCTE over recent cutting-edge semi-supervised segmentation techniques, with a 65.87% Dice score.
Macrophages govern antiviral responses in human lung tissues protected from SARS-CoV-2 infection

The majority of SARS-CoV-2 infections among healthy individuals result in asymptomatic to mild disease. However, the immunological mechanisms defining effective lung tissue protection from SARS-CoV-2 infection remain elusive. Unlike mice solely engrafted with human fetal lung xenograft (fLX), mice co-engrafted with fLX and a myeloid-enhanced human immune system (HNFL mice) are protected against SARS-CoV-2 infection, severe inflammation, and histopathology. Effective control of viral infection in HNFL mice associated with significant macrophage infiltration, and the induction of a potent macrophage-mediated interferon response. The pronounced upregulation of the USP18-ISG15 axis (a negative regulator of IFN responses), by macrophages was unique to HNFL mice and represented a prominent correlate of reduced inflammation and histopathology. Altogether, our work shed light on unique cellular and molecular correlates of lung tissue protection during SARS-CoV-2 infection, and underscores macrophage IFN responses as prime targets for developing immunotherapies against coronavirus respiratory diseases. HIGHLIGHTS Mice engrafted with human fetal lung xenografts (fLX-mice) are highly susceptible to SARS-CoV-2. Co-engraftment with a human myeloid-enriched immune system protected fLX-mice against infection. Tissue protection was defined by a potent and well-balanced antiviral response mediated by infiltrating macrophages. Protective IFN response was dominated by the upregulation of the USP18-ISG15 axis.
Connectivity and dynamics in the olfactory bulb

Dendrodendritic interactions between excitatory mitral cells and inhibitory granule cells in the olfactory bulb create a dense interaction network, reorganizing sensory representations of odors and, consequently, perception. Large-scale computational models are needed for revealing how the collective behavior of this network emerges from its global architecture. We propose an approach where we summarize anatomical information through dendritic geometry and density distributions which we use to calculate the probability of synapse between mitral and granule cells, while capturing activity patterns of each cell type in the neural dynamical systems theory of Izhikevich. In this way, we generate an efficient, anatomically and physiologically realistic large-scale model of the olfactory bulb network. Our model reproduces known connectivity between sister vs. non-sister mitral cells; measured patterns of lateral inhibition; and theta, beta, and gamma oscillations. It in turn predicts testable relations between network structure, lateral inhibition, and odor pattern decorrelation; between the density of granule cell activity and LFP oscillation frequency; how cortical feedback to granule cells affects mitral cell activity; and how cortical feedback to mitral cells is modulated by the network embedding. Additionally, the methodology we describe here provides a tractable tool for other researchers. Author summary The function of the olfactory bulb (OB) critically depends on connectivity patterns between its excitatory and inhibitory cells. Here, we develop an anatomically grounded algorithm for efficiently determining the probability of synapses between mitral cells and granule cells in the OB. We use this algorithm to generate a large-scale network model of the OB with characteristic connectivity distributions between cell types, as well as between sister mitral cells. We simulate the network using the dynamical systems approach of Izhikevich for describing neurons, and show how network structure affects GC-mediated processes, including LFP oscillation frequency, lateral inhibition, odor decorrelation, and cortical feedback. Our results suggest how alterations to the OB network through processes like neurogenesis, or via injury or disease, can have significant effects on function.
Pre-trauma memory contextualization as predictor for PTSD-like behavior in male rats

While many people experience potentially threatening events during their life, only a minority develops posttraumatic stress disorder (PTSD). The identification of individuals at risk among those exposed to trauma is crucial for PTSD prevention in the future. Since re-experiencing trauma elements outside of the original trauma-context is a core feature of PTSD, we investigate if the ability to bind memories to their original encoding context (i.e. memory contextualisation) predicts PTSD vulnerability. We hypothesize that pre-trauma neutral memory contextualization (under stress) negatively relates to PTSD-like behavior, in a prospective design using the cut-off behavioral criteria rat model for PTSD. 72 male Sprague Dawley rats were divided in two experimental groups to assess the predictive value of 1) memory contextualization without acute stress (NS-group) and 2) memory contextualization during the recovery phase of the acute stress-response (S-group) for susceptibility to PTSD-like behavior. A powerful extension to regression analysis-path analysis-was used to test this specific hypothesis, together with secondary research questions. Following traumatic predator scent stress, 19.4% of the rats displayed PTSD-like behavior. Results showed a negative relation between pre-trauma memory contextualization and PTSD-like behavior, but only in the NS-group. Pre-trauma memory contextualization was positively related to fear association in the trauma environment, again only in the NS group. If the predictive value of pre-trauma contextualization of neutral information under non-stressful conditions for PTSD susceptibility is replicated in prospective studies in humans, this factor would supplement already known vulnerability factors for PTSD and improve the identification of individuals at risk among the trauma exposed, especially those at high trauma risk such as soldiers deployed on a mission.