Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy cost of twitch and tetanic contractions of rat muscle estimated in situ by gated 31P NMR

The phosphagen cost of maximal isometric twitch and tetanic contractions in rat gastrocnemius muscle was measured in situ by 31P NMR with acquisitions gated to precise time points after a brief (< 10 s) burst of contractions. Alteration of twitch stimulation frequency did not affect the energy cost per contraction. Pooled results of four twitch rates from 1 to 8 Hz produced an average cost of 0.257±0.012 μmol ATP/g/twitch. This value was compared with the initial twitch cost estimated from the time zero derivative of an exponential fit of averaged scan phosphocreatine (PCr) data from a previous study of 8 min of contraction in situ at 0.75 Hz. Agreement of the two estimates validates the use of the fitting/derivative method to assess energy cost and confirms the monoexponential character of the PCr time course. Evaluation of muscle pH changes demonstrated that all ATP use during the brief twitch contraction bouts could be accounted for by PCr hydrolysis. Results also showed a brief delay in onset of PCr recovery, consistent with the response time of oxidative systems. Tetanic contractions of 100 ms duration at 100 Hz required 2.17±0.07 μmol ATP/g muscle/contraction, in general agreement with estimates reported using a variety of other methods.
Mutual Benefits or Managerial Control? The Role of Appraisal in Performance Related Pay for Teachers

In its proposals for a Performance Related Pay (PRP) scheme for teachers the Labour Government has presented appraisal as having a dual role. It is to be used to determine the pay of teachers making reference to quantitative targets; and to facilitate teachers'professional development. This article examines the tensions between these two functions of appraisal.
Body Composition Comparison: Bioelectric Impedance Analysis with Dual-Energy X-Ray Absorptiometry in Adult Athletes

The primary purpose of this study was to investigate the accuracy of the DF50 (ImpediMed Ltd, Eight Mile Plains, Queensland, Australia) bioelectrical impedance analysis device using dual-energy x-ray absorptiometry as the criterion in two groups: endurance athletes and power athletes. The secondary purpose was to develop accurate body fat percentage prediction equations for each group based on bioelectrical impedance analysis data and/or the combination of bioelectrical impedance analysis and anthropometric data. Eighty male athletes (40 elite endurance athletes and 40 were power athletes), age 19–48 with body mass indexes ranging from 18.9 to 37.4 were recruited. Anthropometric measurements were taken. Body composition was assessed by dual-energy x-ray absorptiometry and bioelectrical impedance analysis. An athlete-specific bioelectrical impedance analysis prediction equation was developed by stepwise regression analysis using dual-energy x-ray absorptiometry as the criterion and bioelectrical impedance analysis data and anthropometric measurements as predictor variables. The DF50 bioelectrical impedance analysis significantly overestimated body fat percentage by 6.4 ± 0.5 in the entire group (p < .001) and in both the endurance group (6.1 ± .6, p < .001) and the power group (6.7 ± 0.7, p < .001). The endurance and power group showed no significant difference in the error of estimation by bioelectrical impedance analysis (p = .554), indicating that bioelectrical impedance analysis has the same error in both groups. The final prediction equation incorporated both anthropometric variables as well as bioelectrical impedance analysis variables and produced an adjusted r2 of . 982 and a standard error of the estimate (SEE) of 1.98 for the entire group. This prediction equation used bioelectrical impedance analysis measurements and anthropometric measurements, specifically trunk measurements, to account for trunk size, a common source of error in bioelectrical impedance analysis equations. Follow-up validation studies are necessary to further validate the equations produced.
Knee rehabilitation robot control by Sliding-Backstepping and Admittance control

In this paper, a knee rehabilitation robot will be developed and controlled. The structure of the system containing the robot and some parts of patient body will be described and modeled using Newton-Euler approach. Two controllers containing Admittance and Sliding-Backstepping are composed to control the system. In this hybrid control scheme, the Sliding-Backstepping controller is considered to track the prescribed trajectory commanded by the expert physiotherapist, and the admittance control is considered to produce a soft and smooth interaction between the robot and human leg. The simulation results show the performance of the designed hybrid controller with suggested structure, in presence of involuntary movement of the leg and noisy measured signals.
The Theoretical Background of Henry George's Value Theory*

Abstract. Henry George intended that his last work. The Science of Political Economy, (which his untimely death left unfinished), should recast economics in a new mold. He argued that if economics is the science of the nature of wealth and the laws of its production and distribution and if in present society there is some deep and widespread wrong in its distribution, if not in its producton, it is the office of an honest science to disclose that. He therefore sought a philosophical basis for an investigation into the nature of wealth which led him into an investigation of the idea of value. These investigations were preceded by an attempt to set out a philosophy of science with respect to one of the sciences, economics.
The Knowledge Transfer Process: From Field Studies to Technology Development

Knowledge transfer in an organization is the process through which one unit (e.g., group, department, or division) is affected by the experience of another. Yet, experience has shown that transferring knowledge, whether at the individual, group, product line, department, or division level, is usually a laborious, time-consuming, and difficult task. In this article, we review 20 recent empirical studies on knowledge transfer and suggest a four-stage process model to summarize and organize their findings. This resulted in a framework where determinants for success at each stage of the knowledge transfer process are defined. Based on this knowledge transfer framework, we propose a knowledge transfer management system that integrates current knowledge management tools and technologies to support the needs at different stages of the knowledge transfer process.
Intelligent SDN based traffic (de)Aggregation and Measurement Paradigm (iSTAMP)

Fine-grained traffic flow measurement, which provides useful information for network management tasks and security analysis, can be challenging to obtain due to monitoring resource constraints. The alternate approach of inferring flow statistics from partial measurement data has to be robust against dynamic temporal/spatial fluctuations of network traffic. In this paper, we propose an intelligent Traffic (de)Aggregation and Measurement Paradigm (iSTAMP), which partitions TCAM entries of switches/routers into two parts to: 1) optimally aggregate part of incoming flows for aggregate measurements, and 2) de-aggregate and directly measure the most informative flows for per-flow measurements. iSTAMP then processes these aggregate and per-flow measurements to effectively estimate network flows using a variety of optimization techniques. With the advent of Software-Defined-Networking (SDN), such real-time rule (re)configuration can be achieved via OpenFlow or other similar SDN APIs. We first show how to design the optimal aggregation matrix for minimizing the flow-size estimation error. Moreover, we propose a method for designing an efficient-compressive flow aggregation matrix under hard resource constraints of limited TCAM sizes. In addition, we propose an intelligent Multi-Armed Bandit based algorithm to adaptively sample the most “rewarding” flows, whose accurate measurements have the highest impact on the overall flow measurement and estimation performance. We evaluate the performance of iSTAMP using real traffic traces from a variety of network environments and by considering two applications: traffic matrix estimation and heavy hitter detection. Also, we have implemented a prototype of iSTAMP and demonstrated its feasibility and effectiveness in Mininet environment.
Parallel K-Means Algorithm for Shared Memory

Clustering is the task of assigning a set of instances into groups in such a way that is dissimilarity of instances within each group is minimized. Clustering is widely used in several areas such as data mining, pattern recognition, machine learning, image processing, computer vision and etc. K-means is a popular clustering algorithm which partitions instances into a fixed number clusters in an iterative fashion. Although k-means is considered to be a poor clustering algorithm in terms of result quality, due to its simplicity, speed on practical applications, and iterative nature it is selected as one of the top 10 algorithms in data mining [1]. Parallelization of k-means is also studied during the last 2 decades. Most of these work concentrate on shared-nothing architectures. With the advent of current technological advances on GPU technology, implementation of the k-means algorithm on shared memory architectures recently start to attract some attention. However, to the best of our knowledge, no in-depth analysis on the performance of k-means on shared memory multiprocessors is done in the literature. In this work, our aim is to fill this gap by providing theoretical analysis on the performance of k-means algorithm and presenting extensive tests on a shared memory architecture.
Automatic driving risk detection based on hands activity

In this paper a novelty methodology to measure driving risk based on hands activity is presented. The proposed algorithm has been developed and tested on several driving sessions executed on a highly realistic truck simulator. The hands positions are used to feed a risk buffer that is in charge of penalizing wrong hands activities and praising good hands activities to generate a measure of the driving risk. In order to select the parameters of the proposed system, a genetic algorithm (GA) and a ground truth acquired from a group of traffic safety experts were considered. The results of the proposed methodology on several driving sessions showed its effectiveness to automatically detect risky situations related to bad driver's hands behavior. The present system will be integrated in a global alarm system that will be included in an intelligent truck cabin for road transportation.
Evaluation of an Online Peer Support Network for Adolescents with Chronic Kidney Disease

This study reports on the development and evaluation of an online social support network for adolescents with chronic kidney disease. Twenty-four adolescents were enrolled in a six-month online intervention in which asynchronous and synchronous online peer support was facilitated. Online dialogue transcripts were analyzed, as were postintervention qualitative interviews with network participants. Findings identify both benefits and challenges of online social support for adolescents and provide guidelines for future support initiatives. The study indicates online support as a valuable resource for adolescents with chronic kidney disease.
Factors Influencing International Students’ Career Choice

This study examines the career development behavior of Asian international, non-Asian international, and domestic students, specifically the certainty of career and major choice and environmental factors that have influenced their choices. Environmental factors include family, school counselors, teacher, friends, and government. The results show no difference in the level of career certainty between the three groups. In contrast, influences of family, school counselors, and friends varied among these three groups. Furthermore, only the Asian international students exhibited a positive correlation between level of career certainty and intent to persist. Implications and recommendations for counseling are given based on the research findings.
The Metamorphosis of 'Germany Inc.': The Case of Executive Pay

The German system of corporate governance differs considerably from its counterparts in the United States and the United Kingdom. There is anecdotal evidence, however, that suggests market forces are serving to destabilize traditional structures in Germany and are causing some form of convergence along "Anglo-American" lines. One by-product of this trend could be that German companies will adopt an increasingly Anglo-American approach when they deal with managerial remuneration issues. This paper examines the implications of such a trend. If shareholder-oriented Anglo-American corporate governance patterns become well-established in Germany, German executives will likely earn more than they do at present, though future increases in pay will be partly conditional upon corporate performance. An increasingly globalized market for executive talent will reinforce the momentum for change. Various factors could delay the process (e.g., tax policy, interest group hostility, regulation) but these seem to be diminishing in importance. If the Anglo-American approach to executive pay becomes influential in German companies, issues that have been controversial in the US and the UK likely will capture attention in Germany. For instance, there will be debate about disclosure regulation and the role that board committees and shareholders should play in the setting of managerial remuneration policy. It remains an open question, though, whether it will be beneficial for German companies to change radically their approach to executive pay.
All-optical ACP-OPLL photonic integrated circuit

The optical-phase-locked-loop linear phase demodulator is the most critical component for a high dynamic range phase modulated RF/Photonic link. Due to the stringent loop latency requirement, the OPLL should be implemented as a photonic integrated circuit. In this paper we address the design and implementation of an all optical attenuation-counter-propagating (ACP) optical-phase-locked-loop photonic integrated circuit. The preliminary experimental results for this device are also presented.
Lands of Fog: Helping Children with Autism in Social Interaction through a Full-Body Interactive Experience

Autism Spectrum Disorder is characterized by impaired social communication capacities which can prevent the formation of social relationships with peers. In recent years, potential programs for people with ASD have increasingly used Information and Communication Technologies mainly motivated by the affinity that people with ASD show towards technology-supported tasks. We present the design of a full-body interaction experience called Lands of Fog, in which a child with ASD plays together with a typically developed child. The system is aimed towards fostering social interaction behaviors and collaboration. We have undertaken user trials with 34 ASD children through which Lands of Fog has proven to be a useful tool to foster social interaction. In this paper, we focus on the description of the interaction design process, methods and criteria that support the final experience. We then provide preliminary results from the user trials which provide a first hint of the efficacy of the system in fostering user's engagement and making socialization attitudes emerge.
Dealing with synchronization and timing variability in the playback of interactive session recordings

In this paper, we describe scheduling and synchronization support for a novel multimedia document, referred to as a session object. The session object captures a voice-annotated, interactive session with an application | it contains audio and window streams. This paper addresses media scheduling and synchronization issues for the support of faithful replay of session objects when subject to timing variability at the replay workstation. The replay is supported by an adaptive scheduling algorithm. The algorithm preserves relative interstream synchronization between window and audio streams. Run-time temporal deformations are applied over the schedule of the window stream. We show that the inter-stream asynchrony oats under statistical control as a function of the scheduling interval. The mechanisms could be generalized to the replay of streams that are subject to timing variability. Our object-oriented toolkit, ReplayKit, enables an application to become replay-aware through access to session capture and replay functionality.
The Use of Social Media to Foster Trust, Mentorship, and Collaboration in Scientific Organizations

Many domains are well known for their resistance to social media. Currently, there is a dearth of literature that explores social media use in these contexts. This study seeks to help address this gap by evaluating the use of social media within a scientific organization (anonymized as SciCity) that has a strong virtual presence and quarterly face-to-face meet-ups. We evaluated SciCity’s use of social media to foster trust, collaboration, and mentorship. We found that the prominent social media platform Twitter fosters trust among organizational members and plays a role in creating and maintaining lightweight collaborative relationships. Additionally, Twitter-based relationships often act as precursors to collaborations that occur face-to-face. However, Twitter, by itself, was not found to be successful in promoting formal collaborations. Though the medium did facilitate sporadic mentoring, supplementary non-social media-based communication was needed to form mentorship relationships. Twitter was also found to serve as a “social lubricant,” making contact easier and faster, thereby helping foster a scientific social network. Though minor in its role in specifically fostering scientific collaboration, the use of social media by SciCity indicates a shift toward acceptable uses of social media for scientific organizations that have traditionally been hesitant to use social media.
Self-Reflective Risk-Aware Artificial Cognitive Modeling for Robot Response to Human Behaviors

In order for cooperative robots ("co-robots") to respond to human behaviors accurately and efficiently in human-robot collaboration, interpretation of human actions, awareness of new situations, and appropriate decision making are all crucial abilities for co-robots. For this purpose, the human behaviors should be interpreted by co-robots in the same manner as human peers. To address this issue, a novel interpretability indicator is introduced so that robot actions are appropriate to the current human behaviors. In addition, the complete consideration of all potential situations of a robot's environment is nearly impossible in real-world applications, making it difficult for the co-robot to act appropriately and safely in new scenarios. This is true even when the pretrained model is highly accurate in a known situation. For effective and safe teaming with humans, we introduce a new generalizability indicator that allows a co-robot to self-reflect and reason about when an observation falls outside the co-robot's learned model. Based on topic modeling and two novel indicators, we propose a new Self-reflective Risk-aware Artificial Cognitive (SRAC) model. The co-robots are able to consider action risks and identify new situations so that better decisions can be made. Experiments both using real-world datasets and on physical robots suggest that our SRAC model significantly outperforms the traditional methodology and enables better decision making in response to human activities.
(De) focusing on global light transport for active scene recovery

Most active scene recovery techniques assume that a scene point is illuminated only directly by the illumination source. Consequently, global illumination effects due to inter-reflections, sub-surface scattering and volumetric scattering introduce strong biases in the recovered scene shape. Our goal is to recover scene properties in the presence of global illumination. To this end, we study the interplay between global illumination and the depth cue of illumination defocus. By expressing both these effects as low pass filters, we derive an approximate invariant that can be used to separate them without explicitly modeling the light transport. This is directly useful in any scenario where limited depth-of-field devices (such as projectors) are used to illuminate scenes with global light transport and significant depth variations. We show two applications: (a) accurate depth recovery in the presence of global illumination, and (b) factoring out the effects of defocus for correct direct-global separation in large depth scenes. We demonstrate our approach using scenes with complex shapes, reflectances, textures and translucencies.
Unsecured consumer debt and mental health outcomes in middle-aged and older Americans.

OBJECTIVES Unsecured consumer debt may affect well-being negatively. We evaluated the association between unsecured debt and two distinct outcomes: depressive symptomatology and psychological well-being. METHOD Data were obtained from the 2006 Health and Retirement Study. There were 5,817 adults aged ≥ 51 who responded to a core survey and psychosocial leave-behind questionnaire. Depressive symptoms were assessed using the revised 8-item Center for Epidemiologic Studies Depression Scale. Psychological well-being was evaluated in a leave-behind questionnaire that had 3 dimensions: self-acceptance, personal growth, and purpose in life. RESULTS Thirty percent of the respondents had unsecured debt. The magnitude or amount of unsecured debt and the occurrence of unsecured debt were significant predictors of depressive symptoms and lower psychological well-being. Perceived control over personal financial circumstances was a significant predictor of higher psychological well-being. DISCUSSION In middle-aged and older Americans, unsecured debt has negative effects on mental health because of the associated depressive symptoms and decreased psychological well-being. The deleterious effects of unsecured debt on mental health are largely accounted for by perceived control over personal financial circumstances. Interventions enhancing older adults' control over personal financial circumstances may protect against the psychological decrements experienced by those grappling with unsecured debt.
Multi-functional foot use during running in the zebra-tailed lizard (Callisaurus draconoides)

SUMMARY A diversity of animals that run on solid, level, flat, non-slip surfaces appear to bounce on their legs; elastic elements in the limbs can store and return energy during each step. The mechanics and energetics of running in natural terrain, particularly on surfaces that can yield and flow under stress, is less understood. The zebra-tailed lizard (Callisaurus draconoides), a small desert generalist with a large, elongate, tendinous hind foot, runs rapidly across a variety of natural substrates. We use high-speed video to obtain detailed three-dimensional running kinematics on solid and granular surfaces to reveal how leg, foot and substrate mechanics contribute to its high locomotor performance. Running at ~10 body lengths s−1 (~1 m s−1), the center of mass oscillates like a spring-mass system on both substrates, with only 15% reduction in stride length on the granular surface. On the solid surface, a strut-spring model of the hind limb reveals that the hind foot saves ~40% of the mechanical work needed per step, significant for the lizard's small size. On the granular surface, a penetration force model and hypothesized subsurface foot rotation indicates that the hind foot paddles through fluidized granular medium, and that the energy lost per step during irreversible deformation of the substrate does not differ from the reduction in the mechanical energy of the center of mass. The upper hind leg muscles must perform three times as much mechanical work on the granular surface as on the solid surface to compensate for the greater energy lost within the foot and to the substrate.