Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the properties of optimal sensory and motor synergies in a nonlinear model of arm dynamics

The vertebrate nervous system produces a wide range of movements flexibly and efficiently, in spite of high complexity and nonlinearity of their motor system. The existence of building blocks in motor system known as synergies can be a convincing solution to overcome the computational complexity. In mathematical perspective, optimal feedback control as a theory of motor coordination provides a coherent framework that leads to optimal synergies. Alternatively, some experiments in vertebrates have shown the involvement of spinal motor primitives in movement execution. The goal of this study is first extracting optimal synergies in nonlinear dynamics case and then investigating their biological plausibility according to reported experimental evidences. We investigated the theoretical properties of optimal synergies of reaching tasks in a 2-joint 6-muscle arm model. Our results show that optimal motor synergies have properties similar to the properties of motor primitives.
Forthcoming in special issue of RSSM in honor of Archibald Haller

The postmodernist critics of class analysis continue to claim that the life chances, attitudes, and behaviors of individuals have become decoupled from their class locations. In a prior paper, we argued that class analysis is vulnerable to this claim in part because conventional big-class and gradational models conceal much of the association between the site of production and individual-level outcomes, and we developed a micro-class scheme that better represented variability in life chances, attitudes, and behaviors by disaggregating big classes into detailed occupations (i.e., “micro-classes”). The present paper addresses the possibility that our micro-class scheme is too extreme in presuming that all conventional big classes are occupationally fractured and therefore untenable. The rationale for an alternative, middle-range solution is straightforward: Namely, occupations are more strongly developed and institutionalized in some sectors of the site of production than in others, and where they are only weakly developed, big-class formulations may be more defensible. We evaluate this hybrid solution by comparing, for 55 individual-level outcomes culled from the Current Population Survey (CPS) and General Social Survey (GSS), the explanatory losses incurred by aggregating occupations to the big-class level, the extent of internal homogeneity characterizing these big classes, and their distinctiveness relative to other classes. The middle-range solution, plausible though it may be, proves to be empirically unattractive. Although conventional arguments treat occupationalization as especially well developed in the crafts, professions, and perhaps services, we find that occupationalizing forces are at work throughout the class structure.
Multimodal Indexing of Multilingual News Video

The problems associated with automatic analysis of news telecasts are more severe in a country like India, where there are many national and regional language channels, besides English. In this paper, we present a framework for multimodal analysis of multilingual news telecasts, which can be augmented with tools and techniques for specific news analytics tasks. Further, we focus on a set of techniques for automatic indexing of the news stories based on keywords spotted in speech as well as on the visuals of contemporary and domain interest. English keywords are derived from RSS feed and converted to Indian language equivalents for detection in speech and on ticker texts. Restricting the keyword list to a manageable number results in drastic improvement in indexing performance. We present illustrative examples and detailed experimental results to substantiate our claim.
An Unsupervised Approach for Inferring Driver Behavior From Naturalistic Driving Data

Intelligent transportation systems are able to collect large volumes of high-resolution data. The amount of data collected by these systems can quickly overwhelm the ability of human analysts to draw meaningful conclusions from the data, particularly in large-scale multivehicle field trials. As advanced driver assistance systems develop, they will also be required to form a rich and high-level understanding of the world from the data they receive, including the behavior of the driver. These applications motivate the need for unsupervised tools capable of forming a high-level summary of low-level driving data. This paper presents an unsupervised method for converting naturalistic driving data into high-level behaviors. The proposed method works in two steps. In the first step, inertial data are automatically decomposed into linear segments. In the second step, the segments are assigned to high-level driving behaviors. The proposed method is computationally efficient and completely unsupervised and requires minimal preprocessing. Although the method is unsupervised, the clusters produced exhibit high-level patterns that can easily be associated with driving behaviors such as braking, turning, accelerating, and coasting. The effectiveness of the proposed algorithms is demonstrated in an offline application where the objective is to summarize inertial data into driving behaviors. The method is also demonstrated in an online application where the aim is to infer the current driving behavior using only inertial data. Both experiments were conducted using driving data collected in natural driving conditions.
Mind the Gap: How Students Differentially Perceive Their School's Attendance Policies in Germany

ABSTRACT Truant student behavior can be due to various reasons. Some of these reasons are located in schools. So far, little is known about how student perception of school rules is related to truancy. This study aims to identify types of school attendance policies and how these policies are associated with individual truancy. Self-reports from the German student sample of PISA 2012 (N = 5,001) were analyzed to evaluate truancy and student perception of school attendance policies. A linear regression model was specified to predict truancy. Two styles of school attendance policies as perceived by students could be distinguished: active and passive. Students who perceived their school's attendance policy to be active were truant less often than students who thought their school's attendance policy was passive.
A novel high gain DC-DC multilevel boost converter using voltage-lift switched-inductor cell

This paper presents a novel high gain DC-DC multilevel boost converter using voltage-lift switched-inductor (VLSI) cell. Cascading of conventional boost converters is not a viable solution to achieve high voltage gain. Thus, DC-DC multilevel converters are employed to achieve high conversion ratio. The proposed high gain DC-DC multilevel boost converter topology is non-isolated which combines the function of voltage-lift switched-inductors (VLSI) cell and voltage multiplier cell. In this paper voltage-lift switched-inductor (VLSI) cell is used to improve the boost capability of multilevel DC-DC converter. 2N capacitors, 2N+3 diodes, two inductors and single switch are needed to design proposed N-level DC-DC topology. Proposed DC-DC multilevel converter topology can be synthesized by using low voltage rating devices because blocking voltage across each power devices is less. The main advantage of this multilevel topology is high conversion ratio is achieved without using coupled inductor, transformer and extreme duty cycle. The conversion ratio of this multilevel DC-DC converter is depends upon the duty cycle and number of levels present in the voltage multiplier cell. The proposed DC-DC multilevel converter has been designed for three levels with rated power 200W, input supply voltage is 12V, output voltage is 288V and switching frequency is 50kHz. The proposed DC-DC multilevel converter topology is simulated in MATLAB/SIMULINK. The simulation results will verify the validity of the analytical design.
Towards user-centric metrics for denial-of-service measurement

To date, the measurement of user-perceived degradation of quality of service during denial of service (DoS) attacks remained an elusive goal. Current approaches mostly rely on lower level traffic measurements such as throughput, utilization, loss rate, and latency. They fail to monitor all traffic parameters that signal service degradation for diverse applications, and to map application quality-of-service (QoS) requirements into specific parameter thresholds. To objectively evaluate an attack's impact on network services, its severity and the effectiveness of a potential defense, we need precise, quantitative and comprehensive DoS impact metrics that are applicable to any test scenario. We propose a series of DoS impact metrics that measure the QoS experienced by end users during an attack. The proposed metrics consider QoS requirements for a range of applications and map them into measurable traffic parameters with acceptable thresholds. Service quality is derived by comparing measured parameter values with corresponding thresholds, and aggregated into a series of appropriate DoS impact metrics. We illustrate the proposed metrics using extensive live experiments, with a wide range of background traffic and attack variants. We successfully demonstrate that our metrics capture the DoS impact more precisely than the measures used in the past.
A Context Based Scheduling Approach for Adaptive Business Process in the Cloud

A BP is a series of logically related tasks implemented by a set of applications/services performed together to produce a defined set of results. The cloud resources scheduling to BP tasks is a difficult problem. Due that, first, it considers the dependencies and communication between tasks within a BP. Second, it takes into account several objectives like minimizing the execution time, minimizing the execution cost, maximizing the resource utilization. Besides, BP execution can be affected by a set of contextual information such as the unavailability of resources, the overloading of network, etc. which make the scheduling problem more complex. In this paper, we propose a context-based scheduling approach for adaptive BP in the cloud.
The role of Parf, a novel partner of ARF, in pancreatic ductal adenocarcinoma and in ARF signaling

Approved: _______________________________________________________ Thesis Supervisor _______________________________________________________ Title and Department _______________________________________________________ Date THE ROLE OF PARF, A NOVEL PARTNER OF ARF, IN PANCREATIC DUCTAL ADENOCARCINOMA AND IN ARF SIGNALING by Viviane Palhares Muniz A thesis submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in Molecular and Cellular Biology in the Graduate College of The University of Iowa
Interaction of Acid-sensing Ion Channel (ASIC) 1 with the Tarantula Toxin Psalmotoxin 1 is State Dependent

Acid-sensing ion channels (ASICs) are Na+ channels gated by extracellular H+. Six ASIC subunits that are expressed in neurons have been characterized. The tarantula toxin psalmotoxin 1 has been reported to potently and specifically inhibit homomeric ASIC1a and has been useful to characterize ASICs in neurons. Recently we have shown that psalmotoxin 1 inhibits ASIC1a by increasing its apparent affinity for H+. However, the mechanism by which PcTx1 increases the apparent H+ affinity remained unclear. Here we show that PcTx1 also interacts with ASIC1b, a splice variant of ASIC1a. However, PcTx1 does not inhibit ASIC1b but promotes its opening; under slightly acidic conditions, PcTx1 behaves like an agonist for ASIC1b. Our results are most easily explained by binding of PcTx1 with different affinities to different states (closed, open, and desensitized) of the channel. For ASIC1b, PcTx1 binds most tightly to the open state, promoting opening, whereas for ASIC1a, it binds most tightly to the open and the desensitized state, promoting desensitization.
Channel Estimation Algorithms for Uplink OFDMA Tiles

OFDM is known to be robust to wireless multipath channels since interferences are alleviated by the frequency-domain signal construction and the use of a cyclic prefix. However, it is still necessary to estimate the channel at each subcarrier position and to equalize the flat fading distortion. In the context of orthogonal frequency division multiple access (OFDMA) where uplink data from multiple users are grouped in a time and frequency structure, the use of conventional channel estimation algorithms based on statistic acquisition is not practical. In this paper, four channel estimation algorithms designed for the high diversity uplink OFDMA tile structure are compared. Simulations results for an averaging algorithm, an interpolation algorithm, a regression algorithm and of a novel method combining both previously mentioned with decision guiding are presented for channel models similar to SUI. The novel two-steps algorithm outperforms other algorithms in terms of bit-error rate. This is observed for a range of coding and modulation configurations and varying the multipath channel conditions
Soluble epidermal growth factor receptor (sEGFR) and carcinoembryonic antigen (CEA) concentration in patients with non-small cell lung cancer: correlation with survival after erlotinib and gefitinib treatment

Background: In patients with non-small cell lung cancer (NSCLC), a higher response rate can be achieved with epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) when selection for therapy is guided by mutation analysis or gene amplification. However, both tests are complex and require tumour tissue. Simple methods to identify responders prior to EGFR-TKI treatment are urgently needed. This study aimed to define the relation between serum sEGFR levels, carcinoembryonic antigen (CEA) and survival in NSCLC patients treated with EGFR-TKIs. Methods: Patients with stage III/IV NSCLC treated with gefitinib or erlotinib between July 2002 and December 2005 were reviewed. Levels of serum soluble EGFR (sEGFR) were determined by a sandwich quantitative enzyme-linked immunosorbent assay. A chemiluminescence immunoassay was used for CEA. The relation between sEGFR and survival was investigated. Results: One hundred and two NSCLC patients, mainly stage IV (80%), were identified. Mean sEGFR at baseline was 55.9 μg/l (range 35.3–74.5 μg/l). The median CEA level was 11.1 μg/l (range <1.0–2938.0 μg/l). Median overall survival was 5.2 months (range 1–52 months). Decreasing log CEA values (HR 1.51, 95% CI 1.11–2.04, multivariate analysis) and increasing sEGFR values (HR 0.96, 95% CI 0.93–0.99, multivariate analysis) were both independently associated with prolonged survival. Higher levels of pre-treatment sEGFR were associated with lower risk of progressive disease within three months (p=0.04). Conclusions: Both baseline sEGFR and CEA levels in NSCLC patients receiving EGFR-TKIs showed a significant correlation with survival. To distinguish whether these factors have a predictive or a prognostic value, validation is warranted in an independent patient series containing a control arm without EGFR-TKI treatment.
Certifying Kalman Filters 1

Formal code certification is a rigorous approach to demonstrate software quality. Its basic idea is to require that code producers provide formal certificates, or proofs, that their code satisfies certain quality properties. In this paper, we focus on certifying software developed for state estimation of dynamic systems, which is an important problem found in spacecraft, aircraft, geophysical, and in many other applications. The most common way of solving state estimation problems consists of using Kalman filters, which are stochastic, recursive algorithms providing statistically optimal estimates of the state of a system based on noisy sensor measurements. We present a certifier for Kalman filter programs, which is a program that takes as input a program claiming to implement a Kalman filter together with a specification of that Kalman filter, as well as a certificate under the form of assertions and proof scripts merged within the program via annotations, and tells whether the code correctly implements the state estimation problem specified. We tested our certifier on three Kalman filters: simple Kalman filter, information filter and extended Kalman filter. So far we have played both the role of the producer of these programs and the role of the consumer, but our next step is to merge the presented technology with AutoFilter, a state estimation program sysnthesis system developed by researchers at NASA Ames, the idea being to have AutoFilter synthesize the correctness certificates together with the code.
Design of an assistive wrist orthosis using conductive nylon actuators

This project outlines the design of an innovative wearable wrist orthosis which potentially can be used for rehabilitation therapy and for assisting with daily tasks. The orthosis uses recently discovered nylon artificial muscles as a means to actuate the device. Constructed from silver coated nylon sewing thread, these newly developed actuators have been shown to exhibit power to weight ratios that exceed that of human skeletal muscle. In this paper, we develop an electromechanical model for the force generated by the actuators and propose a simple closed loop controller to control the actuators. This system is then implemented in a wrist exoskeleton prototype to demonstrate the potential use of nylon actuators in biomedical applications.
RICTOR Amplification Defines a Novel Subset of Patients with Lung Cancer Who May Benefit from Treatment with mTORC1/2 Inhibitors.

UNLABELLED We identified amplification of RICTOR, a key component of the mTOR complex 2 (mTORC2), as the sole actionable genomic alteration in an 18-year-old never-smoker with lung adenocarcinoma. Amplification of RICTOR occurs in 13% of lung cancers (1,016 cases) in The Cancer Genome Atlas and at a similar frequency in an independent cohort of 1,070 patients identified by genomic profiling. In the latter series, 11% of cases harbored RICTOR amplification as the only relevant genomic alteration. Its oncogenic roles were suggested by decreased lung cancer cell growth both in vitro and in vivo with RICTOR ablation, and the transforming capacity of RICTOR in a Ba/F3-cell system. The mTORC1/2 inhibitors were significantly more active against RICTOR-amplified lung cancer cells as compared with other agents targeting the PI3K-AKT-mTOR pathway. Moreover, an association between RICTOR amplification and sensitivities to mTORC1/2 inhibitors was observed. The index patient has been treated with mTORC1/2 inhibitors that led to tumor stabilization for more than 18 months. SIGNIFICANCE RICTOR amplification may define a novel and unique molecular subset of patients with lung cancer who may benefit from treatment with mTORC1/2 inhibitors.
When Are New Hippocampal Neurons, Born in the Adult Brain, Integrated into the Network That Processes Spatial Information?

Adult-born neurons in the dentate gyrus (DG) functionally integrate into the behaviorally relevant hippocampal networks, showing a specific Arc-expression response to spatial exploration when mature. However, it is not clear when, during the 4- to 6-week interval that is critical for survival and maturation of these neurons, this specific response develops. Therefore, we characterized Arc expression after spatial exploration or cage control conditions in adult-born neurons from rats that were injected with BrdU on one day and were sacrificed 1, 7, 15, 30, and 45 days post-BrdU injection (PBI). Triple immunostaining for NeuN, Arc, and BrdU was analyzed through the different DG layers. Arc protein expression in BrdU-positive cells was observed from day 1 to day 15 PBI but was not related to behavioral stimulation. The specific Arc-expression response to spatial exploration was observed from day 30 and 45 in about 5% of the BrdU-positive cell population. Most of the BrdU-positive neurons expressing Arc in response to spatial exploration (∼90%) were located in DG layer 1, and no Arc expression was observed in cells located in the subgranular zone (SGZ). Using the current data and that obtained previously, we propose a mathematical model suggesting that new neurons are unlikely to respond to exploration by expressing Arc after they are 301 days old, and also that in a 7-month-old rat the majority (60%) of the neurons that respond to exploration must have been born during adulthood; thus, suggesting that adult neurogenesis in the DG is highly relevant for spatial information processing.
HVS-Optimized Vector Quantilizer for Remote Sensing Texture Compression

As remote sensing texture has properties like strong randomness and weak local correlation, it is hard to design a good vector quantizer for compression. A novel self-adaptive HVS-optimized quantizer is presented. The method defines a similarity measurement function based on Human Visual System (HVS) model. Threshold that judge the similarity between blocks is computed based on the property of image. Thus, the compression method may deal with different resolution images automatically. In addition, a self-adaptive threshold adjustment during the compression is designed to improve the reconstruct quality for remote sensing textures with large regional differences. Experiment on various resolution images indicates that the new quantizer can achieve satisfied compression rate and reconstruct quality at the same time. Furthermore, the compression and decompression process is speed up with the usage of GPU, on account of their parallelism. Keywords-texture compression; self-adaptive; HVS-optimized; quantizer; GPU
EVIDENCE FOR THE DISKY ORIGIN OF LUMINOUS VIRGO DWARF ELLIPTICALS FROM THE KINEMATICS OF THEIR GLOBULAR CLUSTER SYSTEMS

We report evidence for dynamically significant rotation in the globular cluster systems of two luminous Virgo dwarf ellipticals, VCC1261 and VCC1528. Including previous results for VCC1087, the globular cluster systems of all three Virgo dwarf ellipticals studied in detail to date exhibit vrot/σlos>1. Taking the rotation seen in the globular clusters as a maximal disk rotation, and accounting for the possible fading of any hypothetical progenitor galaxy, we find all three dwarf elliptical galaxies (dEs) lie on the r-band Tully–Fisher relation. We argue that these data support the hypothesis that luminous dEs are the remnants of transformed disk galaxies. We also obtained deep, longslit data for the stars in VCC1261 and VCC1528. Both these galaxies show rapid rotation in their inner regions, with spatial scales of ∼0.5 kpc. These rotation velocities are surprisingly similar to those seen in the globular cluster systems. At larger radii, we see little rotation in the dEs themselves. Since our longslit data for Virgo dEs extend out to 1–2 effective radii (typical of deep observations), whereas the globular clusters extend out to 4–7 effective radii, we conclude that nondetections of rotation in many luminous dEs may simply be due to a lack of radial coverage in the stellar data, and that globular clusters represent singularly sensitive probes of the dynamics of dEs. Based on these data, we suggest that gas disks are significant sites of globular cluster formation in the early universe.
Implementing label filters on a shared tree mobile multicast architecture

This paper describes an architecture that filters packets within a subset of nodes on an existing shared multicast tree. The path connecting the group of nodes that want to communicate privately on the existing tree was given a label. These labels are used to route one-to-one and group communication traffic for selected nodes on a multicast tree. Nodes connected to the tree but are not on this label path do not receive any filtered packets. This filter architecture reduces network resource waste by utilising the existing network resources on the multicast tree like quality of service (QoS). In this paper, we also describe how this architecture can be used for mobile communication when implemented in a shared tree mobile multicast architecture.