Miracle-dz/UniFAR-FTUs huggingface dataset:
Cellular Responses to Mechanical Stress Invited Review : Engineering approaches to cytoskeletal mechanics

Stamenović, Dimitrije, and Ning Wang. Invited Review: Engineering approaches to cytoskeletal mechanics. J Appl Physiol 89: 2085–2090, 2000. —An outstanding problem in cell biology is how cells sense mechanical forces and how those forces affect cellular functions. Various biophysical and biochemical mechanisms have been invoked to answer this question. A growing body of evidence indicates that the deformable cytoskeleton (CSK), an intracellular network of interconnected filamentous biopolymers, provides a physical basis for transducing mechanical signals into biochemical signals. Therefore, to understand how mechanical forces regulate cellular functions, it is important to know how cells respond to changes in the CSK force balance and to identify the underlying mechanisms that control transmission of mechanical forces throughout the CSK and bring it to equilibrium. Recent developments of new experimental techniques for measuring cell mechanical properties and novel theoretical models of cellular mechanics make it now possible to identify and quantitate the contributions of various CSK structures to the overall balance of mechanical forces in the cell. This review focuses on engineering approaches that have been used in the past two decades in studies of the mechanics of the CSK.
Mode selection for CoMP transmission with quasi timing synchronization

This paper proposes a mode selection strategy to improve the spectral efficiency for coordinated multi-point (CoMP) transmission with quasi timing synchronization. Upper bounds of average achievable rate for different CoMP transmission modes, such as coordinated beamforming (CB) and joint processing (JP), are derived. According to these upper bounds, we find that the performance of JP has been significantly degraded by quasi timing synchronization, while the performance of CB remains unchanged. The proposed mode selection strategy can switch CoMP transmission mode between CB and JP adaptively to maximize the average achievable rate. In addition, the proposed mode selection strategy requires low extra overhead and has ease of implementation. Simulation results show that the proposed mode selection strategy outperforms single mode CoMP transmission when just quasi timing synchronization is achieved.
A New Compact Double-Negative Miniaturized Metamaterial for Wideband Operation

The aim of this paper is to introduce a compact double-negative (DNG) metamaterial that exhibits a negative refractive index (NRI) bandwidth of more than 3.6 GHz considering the frequency from 2 to 14 GHz. In this framework, two arms of the designed unit cell are split in a way that forms a Modified-Z-shape structure of the FR-4 substrate material. The finite integration technique (FIT)-based Computer Simulation Technology (CST) Microwave Studio is applied for computation, and the experimental setup for measuring the performance is performed inside two waveguide ports. Therefore, the measured data complies well with the simulated data of the unit cell at 0-degree and 90-degree rotation angles. The designed unit cell shows a negative refractive index from 3.482 to 7.096 GHz (bandwidth of 3.61 GHz), 7.876 to 10.047 GHz (bandwidth of 2.171 GHz), and 11.594 to 14 GHz (bandwidth of 2.406 GHz) in the microwave spectra. The design also exhibits almost the same wide negative refractive index bandwidth in the major region of the C-band and X-band if it is rotated 90 degrees. However, the novelty of the proposed structure lies in its effective medium ratio of more than 4, wide bandwidth, and compact size.
Zinc supplementation in infants with asymmetric intra uterine growth retardation; effect on growth, nutritional status and leptin secretion.

OBJECTIVES To analyse the effect of zinc supplementation in growth and nutritional status of a homogeneous group of newborns with intra uterine growth retardation and asymmetric growth. The effect of changes of zinc status on growth and leptin serum concentrations was also analysed. POPULATION AND METHODS A double blind, randomised clinical trial was designed in order to detect differences in growth between zinc and placebo groups during the first 6 months of life. 31 infants were included either to the zinc group (n = 14) (38.8+/-1.4 weeks GA, 2,171+/-253 g body weight) or the placebo group (n = 17) (38.9+/-1.1 weeks GA, 2,249+/-220 g body weight). The zinc group received a supplement of 3 mg elemental zinc per day (as zinc sulphate). RESULTS There were not significant differences between groups for anthropometric measurements through the study period. We found a significant effect of the study group, in hair zinc concentrations, but not in serum zinc concentrations; post-hoc comparisons for hair zinc revealed that there were significant differences between groups at 1, 2, and 6 months of age. Changes in serum and hair zinc concentrations from baseline to 6 months, showed significant correlations with changes in weight/age and length/age z-scores, in the supplement group. Changes in leptin serum concentrations during follow-up, showed significant correlations with changes in sum of 4 skinfolds and weight/age z-score, in the placebo group. Changes in hair zinc concentration through the study period showed significant correlations with changes in leptin serum concentrations from baseline to 6 months of follow-up. CONCLUSIONS In a homogeneous group of intra uterine growth retardation infants with asymmetric growth, 3 mg/day zinc supplementation do not show significant improvements in weight and length growth. Changes in zinc status were related with changes in weight and length during the first 6 months of life. Changes in leptin serum concentrations were related with changes in the anthropometric indices of body fat accretion.
Big location‐based social media messages from China's Sina Weibo network: Collection, storage, visualization, and potential ways of analysis

China's social media platform, Sina Weibo, like Twitter, hosts a considerable amount of big data: messages, comments, pictures. Collecting and analyzing information from this treasury of human behavior data is a challenge, although the message exchange on the network is readable by everyone through the web or app interface. The official Application Programming Interface (API) is the gateway to access and download public content from Sina Weibo and is used to collect messages for all mainland China. The nearby_timeline() request is used to harvest only messages with associated location information. This technical note serves as a reference for researchers who do not speak Mandarin but want to collect data from this rich source of information. Ways of data visualization are presented as a point cloud, density per areal unit, or clustered using Density‐Based Spatial Clustering of Applications with Noise (DBSCAN). The relation of messages to census information is also given.
Dynamic feedback and biasing for a linear CMOS power amplifier with envelope tracking

This paper presents a fully integrated CMOS power amplifier (PA) with a dynamic feedback and gate biasing. The two dynamic circuits improve the linearity and efficiency of the stand-alone PA and ET PA. The proposed CMOS ET PA including the dynamic control circuits is fabricated using 0.18-μm CMOS process. For a long-term evolution (LTE) signal at 1.85 GHz with a 10-MHz bandwidth and a 16-QAM 7.5 dB PAPR, the CMOS envelope tracking (ET) PA module achieves a power-added efficiency (PAE) of 35.4%, an error vector magnitude (EVM) of 3.6%, and an ACLRE-UTRA of -33.3 dBc at an average output power of 26.5 dBm. The ET PA with the control circuits improves the gain deviation within 2 dB and the PAE up to 5%, respectively, according to the output power level, over those of the ET PA without the dynamic control for the same LTE signal.
An Association of Genotypes and Antimicrobial Resistance Patterns among Salmonella Isolates from Pigs and Humans in Taiwan

We collected 110 Salmonella enterica isolates from sick pigs and determined their serotypes, genotypes using pulsed-field gel electrophoresis (PFGE), and antimicrobial susceptibility to 12 antimicrobials and compared the data with a collection of 18,280 isolates obtained from humans. The pig isolates fell into 12 common serovars for human salmonellosis in Taiwan; S. Typhimurium, S. Choleraesuis, S. Derby, S. Livingstone, and S. Schwarzengrund were the 5 most common serovars and accounted for a total of 84% of the collection. Of the 110 isolates, 106 (96%) were multidrug resistant (MDR) and 48 (44%) had PFGE patterns found in human isolates. S. Typhimurium, S. Choleraesuis, and S. Schwarzengrund were among the most highly resistant serovars. The majority of the 3 serovars were resistant to 8–11 of the tested antimicrobials. The isolates from pigs and humans sharing a common PFGE pattern displayed identical or very similar resistance patterns and Salmonella strains that caused severe infection in pigs were also capable of causing infections in humans. The results indicate that pigs are one of the major reservoirs to human salmonellosis in Taiwan. Almost all of the pig isolates were MDR, which highlights the necessity of strictly regulating the use of antimicrobials in the agriculture sector in Taiwan.
Learning Spectral Embedding for Semi-supervised Clustering

In recent years, semi-supervised clustering (SSC) has aroused considerable interests from the machine learning and data mining communities. In this paper, we propose a novel semi-supervised clustering approach with enhanced spectral embedding (ESE) which not only considers structure information contained in data sets but also makes use of prior side information such as pair wise constraints. Specially, we first construct a symmetry-favored k-NN graph which is highly robust to noisy objects and can reflect the underlying manifold structure of data. Then we learn the enhanced spectral embedding towards an ideal representation as consistent with the pair wise constraints as possible. Finally, through taking advantage of Laplacian regularization, we formulate learning spectral representation as semi definite-quadratic-linear programs (SQLPs) under the squared loss function or small semi definitive programs (SDPs) under the hinge loss function, which both can be efficiently solved. Experimental results on a variety of synthetic and real-world data sets show that our approach outperforms the state-of-the-art SSC algorithms on both vector-based and graph-based clustering.
Using Subgoal Learning and Self-Explanation to Improve Programming Education

The present study combined subgoal learning and self-explanation frameworks to improve problem solving performance. Subgoal learning has been used to promote retention and transfer in procedural domains, such as programming. The primary method for learning subgoals, however, has been through passive learning methods, and passive learning methods are typically less effective than constructive learning methods. To promote constructive methods of learning subgoals, a subgoal learning framework was used to guide self-explanation. Self-explanation is an effective method for engaging learners to make sense of new information based on prior knowledge and logical reasoning. Self-explanation is typically more effective when learners receive some guidance, especially if they are novices, because it helps them to focus their attention on relevant information. In the present study, only some of the constructive learning methods produced better problem solving performance than passive learning methods. Learners performed best when they learned constructively and either received hints about the subgoals of the procedure or received feedback on the self-explanations that they constructed, but not when they received both hints and feedback. When students received both types of guidance, they did not perform better than those who learned subgoals through passive learning methods. These findings suggest that constructive learning of subgoals can further improve the benefits of learning subgoals, but there is an optimal level of guidance for students engaging in constructive learning. Providing too much guidance can be as detrimental as providing too little. This nuance is important for educators who engage their students in constructive learning and self-explanation to recognize and promote the best results.
Feedback-Directed Pipelining for Multi-threaded Workloads

Extracting performance from Chip Multiprocessors require s that the application be parallelized. A common software technique to parallelize loops is pipeline parallelismin which the programmer/compiler splits each loop iteration into stages and each stage runs on a certain nu mber of cores. It is important to choose the number of cores for each stage carefully because the core-to -stage allocation determines performance and power consumption. Finding the best core-to-stage allocat i n for an application is challenging because the number of possible allocations is typically quite large, an d the best allocation changes with the input set and machine configuration. This paper proposes Feedback-Directed Pipelining (FDP) , a software framework that chooses the core-tostage allocation at run-time. FDP first maximizes the perfor mance of the workload and then saves power by reducing the number of active cores, without impacting perf ormance. Our evaluation of FDP on a real 8-core SMP system (2x Core2Quad) shows that FDP provides an average speedup of 4.2x which is significantly higher than the 2.3x speedup obtained with a practical profile-base d allocation. We also show that FDP is robust to changes in machine configuration and input set variation.
List context effects in reading Italian words and nonwords: Can the word frequency effect be eliminated?

It has been suggested that when words and nonwords are presented mixed in the same blocks in transparent scripts the word frequency effect can be eliminated. This is either because in reading mixed blocks the lexical route is deemphasised in favour of the nonlexical route (route deemphasis) or because a homogenisation of reaction times occurs for words and nonwords by adjustment of a time criterion for articulation (time criterion). In five experiments using different list manipulations and experimental designs, we assessed the effects of frequency and length in reading aloud words and nonwords in the Italian transparent orthography. The effect of word frequency remained constant irrespective of context manipulation and nonword characteristics. As reading nonwords may be easier in Italian than in English, control over reading processing may be unnecessary for Italian readers. The results are discussed with respect to current computational models of reading.
Reliable OFDM Receiver With Ultra-Low Resolution ADC

The use of low-resolution analog-to-digital converters can significantly reduce power consumption and hardware cost. However, their resulting severe nonlinear distortion makes achieving reliable data transmission challenging. For orthogonal frequency division multiplexing (OFDM) transmission, the orthogonality among subcarriers is destroyed. This invalidates conventional OFDM receivers relying heavily on this orthogonality. In this paper, we move on to quantized OFDM (Q-OFDM) prototyping implementation based on our previous achievement in optimal Q-OFDM detection. First, we propose a novel Q-OFDM channel estimator by extending the generalized Turbo (GTurbo) framework formerly applied for optimal detection. Specifically, we integrate a type of robust linear OFDM channel estimator into the original GTurbo framework, and derive its corresponding extrinsic information to guarantee its convergence. We also propose feasible schemes for automatic gain control, noise power estimation, and synchronization. Combined with the proposed inference algorithms, we develop an efficient Q-OFDM receiver architecture. Furthermore, we construct a proof-of-concept prototyping system and conduct over-the-air (OTA) experiments to examine its feasibility and reliability. This is the first work that focuses on both algorithm design and system implementation in the field of low-resolution quantization communication. The results of the numerical simulation and OTA experiment demonstrate that reliable data transmission can be achieved.
Coverage optimization for DVB-T/H single frequency networks using a PSO algorithm

In this work, the usefulness and limitations of a planning tool that combines a propagation prediction method and a modern heuristic technique when applied to improve the coverage area in single frequency networks (SFN) is presented. The propagation prediction method uses 3D digital terrain maps along with a propagation model to estimate the contribution of any transmitter of the SFN at each location within the region in which the SFN is intended to be deployed, given in terms of parameters such as the received power and propagation delay. Furthermore, a particle swarm optimization (PSO) algorithm is used to optimize the transmission parameters of any of the transmitters within the SFN, including transmitters delay or gain for their sector antennas, in order to exploit the multipath tolerance in OFDM receivers. Preliminary results comparing the performance of different PSO schemes considering as the canonical problem a SFN consisting of eighteen transmitters, in which transmitters and receivers have been simplified, are reported and discussed. Moreover, results considering sector and directive antennas at the transmitter and receiver sides, respectively, are also included.
Simultaneous Localization and Mapping with Monocamera : Detection of Landing Zones

The development of autonomous systems has been growing throughout the years. The capacity systems have to, simultaneously, locate and map unknown environments, without any kind of human intervention, empowered the unknown’s exploration evolution to levels never considered before. It is therefore necessary for this kind of system to have capabilities of action and decision in the required mission phases for which it was designed. The development of tools that can interact in the decision process of certain situations, constitutes an advance, bringing the systems closer to the desired autonomy level. However, complete autonomy is yet to be reached. The work presented on this thesis focus on the development of a simultaneous tracking and mapping system, which employs only one camera as a sensor. This system allows to determine the tridimensional movement completed by the specific camera and, estimate with a relative precision, the position of the reference points used in the process to locate itself. Furthermore, an algorithm was developed aiming for the detection of flat areas in the real world, using the previously obtained reference points, which can be considered feasible landing areas for aerospace vehicles. All the results showed in this thesis concern to simulations obtained in controlled environments, noting that the system was not implemented in real time.
Combining the union model and missing feature method to improve noise robustness in ASR

In this paper, we propose a combination of the probabilistic union model and the missing feature method to improve noise robustness in ASR. Specifically, the missing feature method is employed to eliminate the acoustic frames in which all frequency bands are corrupted and the union model is employed to extract useful information from the frames involving only partial frequency -band corruption. This combination enhances the capability of the union model for dealing with wide-band noise corruption, and moreover, it reduces the dependence of the missing-feature method on information about the noise - only a knowledge on the bandwidth of the noise is required. We have tested the new system based on the TIDigits database, corrupted by various types of wide-band and narrow-band noise. The experimental results show significant performance improvement by the proposed system, compared to a previous model without using the combination.
Lung volumes and forced ventilatory flows

Lung volumes are subdivided into static and dynamic lung volumes. Static lung volumes are measured by methods which are based on the completeness of respiratory manoeuvres, so that the velocity of the manoeuvres should be adjusted accordingly. The measurements taken during fast breathing movements are described as dynamic lung volumes and as forced inspiratory and expiratory flows. ### 1.1 Static lung volumes and capacities The volume of gas in the lung and intrathoracic airways is determined by the properties of lung parenchyma and surrounding organs and tissues, surface tension, the force exerted by respiratory muscles, by lung reflexes and by the properties of airways. The gas volumes of thorax and lung are the same except in the case of a pneumothorax. If two or more subdivisions of the total lung capacity are taken together, the sum of the constituent volumes is described as a lung capacity. Lung volumes and capacities are described in more detail in § 2. #### 1.1.1 Determinants Factors which determine the size of the normal lung include stature, age, sex, body mass, posture, habitus, ethnic group, reflex factors and daily activity pattern. The level of maximal inspiration (total lung capacity, TLC) is influenced by the force developed by the inspiratory muscles (disorders include e.g. muscular dystrophy), the elastic recoil of the lung (disorders include e.g. pulmonary fibrosis and emphysema) and the elastic properties of the thorax and adjacent structures (disorders include e.g. ankylosis of joints). The level of maximal expiration (residual volume, RV) is determined by the force exerted by respiratory muscles (disorders include e.g. muscle paralysis), obstruction, occlusion and compression of small airways (disorders include e.g. emphysema) and by the mechanical properties of lung and thorax (disorders include diffuse fibrosis, kyphoscoliosis). Assessing the total lung capacity is indispensable in establishing a restrictive ventilatory defect or in diagnosing abnormal lung distensibility, as may occur in patients …
Importance Sampling for Continuous Time Bayesian Networks

A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact inference in a CTBN is often intractable as the state space of the dynamic system grows exponentially with the number of variables. In this paper, we first present an approximate inference algorithm based on importance sampling. We then extend it to continuous-time particle filtering and smoothing algorithms. These three algorithms can estimate the expectation of any function of a trajectory, conditioned on any evidence set constraining the values of subsets of the variables over subsets of the time line. We present experimental results on both synthetic networks and a network learned from a real data set on people's life history events. We show the accuracy as well as the time efficiency of our algorithms, and compare them to other approximate algorithms: expectation propagation and Gibbs sampling.
Literacies crossing borders: transfronterizo literacy practices of students in a dual language program on the USA–Mexico border

Abstract Research on transnational literacies has generally focused on youth who live in one country and communicate using digital literacies across national boundaries. Our work contributes to this literature by providing a view of transnational literacies that are unique to the USA–Mexico border region. The students in this ethnographic study navigate two countries, two languages, and two homes on a weekly and sometimes daily basis. This article describes the literacies that these transfronterizo youth acquire as border crossers. Our focus is on the print and digital literacies learned outside of the classroom and how these are being used by the students in academic settings.