Miracle-dz/UniFAR-FTUs huggingface dataset:
A training programme to improve hip strength in persons with lower limb amputation.

OBJECTIVE To investigate the effect of a 10-week training programme on persons with a lower limb amputation and to determine if this training is sufficient to enable running. SUBJECTS Seven transtibial, 8 transfemoral and 1 bilateral amputee (all resulting from trauma, tumour or congenital) were randomly assigned to a training (n =8) or control group (n = 8). METHODS Isokinetic hip flexor and extensor strength at 60 and 120º/s and oxygen consumption while walking at 1.0 m/s were tested pre- and post- a 10-week period. The training group followed a twice weekly hip strengthening programme, while the control group continued with their usual activities. Running ability was determined pre-testing, and attempted after post-testing for the training group only. RESULTS The training group increased hip strength and decreased oxygen consumption. Six amputees who were previously unable to run were able to after training. The control group decreased intact limb hip extensor strength. CONCLUSION The training programme is sufficient to improve hip strength and enable running in persons with a lower limb amputation. As hip strength was reduced in those not following the training programme, it is recommended that strength training be undertaken regularly in order to avoid losing limb strength following amputation.
Detection of a Tyrosine Phosphatase LAR on Intestinal Epithelial Cells and Intraepithelial Lymphocytes in the Human Duodenum

Studies of tyrosine phosphorylation in the human duodenum have indicated that proliferating cells in the middle portion of the duodenal crypt were devoid of this feature, suggesting that tyrosine kinase activation is not a dominant factor in crypt cell proliferation, and that consequently tyrosine phosphatase activity may be a more critical factor in crypt cell development. We investigated the expression of the leukocyte common antigen-related receptor (LAR) family of tyrosine phosphatases. A flow cytometry system was used to examine cells from the surface, mid-portion, and lower part of the crypt. Individual cell populations were immunostained with anti-LAR antibodies using phycoerythrin-conjugated anti-CD3 to discriminate between epithelial cells (CD3−) and intraepithelial lymphocytes (CD3+). Epithelial cells expressed LAR throughout the crypt. Expression of LAR was maximal in the mid-portion of the crypt with lower expression at the top of the villi. Intraepithelial lymphocytes expressed low levels of LAR at the tips of the villi with stronger expression extending towards the base of the crypt. These findings were confirmed by immunohistochemistry on paraffin-fixed sections. Of note, peripheral blood lymphocytes expressed less LAR than IEL. These observations suggest the possibility that tyrosine phosphatase LAR may be of importance in the regulation of crypt cell proliferation. Moreover, as the extracellular domain of LAR has homology with adhesion molecules, the finding of this molecule on IEL could suggest a possible functional role in homing of this unique lymphocyte.
Combing RGB and Depth Map Features for human activity recognition

We study the problem of human activity recognition from RGB-D sensors when the skeletons are not available. The skeleton tracking in Kinect SDK works well when the human subject is facing the camera and there are no occlusions. In surveillance or senior home monitoring scenarios, the camera is usually mounted higher than human subjects and there may be occlusions. Consequently, the skeleton tracking does not work well. In RGB image based activity recognition, a popular approach that can handle cluttered background and partial occlusions is the interest point based approach. When both RGB and depth channels are available, one can still use the interest point based approach. But there are questions on whether we should extract interest points independently on each channel or extract interest points from one of the channels. The goal of this paper is to compare the performances of different ways of extracting interest points. In addition, we have developed a depth map based descriptor. We show that the best performance is achieved when we extract interest points solely from RGB channels, and combine the RGB based descriptors and depth map based descriptors.
Issues and Challenges in Symmetric Key based Cryptographic Algorithm for Videos and Images

Modern era is fully dependent on internet communication. Through internet we can transfer data anywhere in the world. Through these various activities can be done such as online bill payment, shopping. The network is currently used for carrying personal information as well as financial data. Thus, it is necessary to secure the network, in order that unauthorized person cannot access personal information. Cryptography is used for protecting data in network channel on the move. Encrypting information in transit helps to secure it from hacker, because it is difficult to physically secure all access to networks. Standards cryptographic software and hardware is used to perform encryption. There are many cryptographic algorithms which are being used to secure data including images and video, but all of them have some advantages and disadvantages. So there is need to develop a strong cryptography algorithm for securing the image and video while transferring. Graphical data is complicated in comparison with other data like text, so the method of securing them will also be complicated. Keyword: Digital Rights Management (DRM), Data Encryption Standard (DES), elliptic curve cryptography (ECC), Video Object Plane (VOP), cryptography, encryption, decryption.
The Umbral Transfer-Matrix Method , III : Counting Animals

Abstract: This is the third part of the 5-part saga on the Umbral Transfer-Matrix method, based on Gian-Carlo Rota's seminal notion of the umbra. In this article we describe the Maple package ZOO that for any speci c k, automatically constructs an Umbral Scheme for enumerating, \k-board" lattice animals (polyominoes), on the two-dimensional square lattice. Such Umbral Schemes enable counting these important classes of animals in polynomial time as opposed to the exponential time that is required for counting all animals.
PEAKSAVE: energy monitoring service

PEAKSAVE system is an energy monitoring service based on Wireless Sensor Networks (WSN). A smartphone is an important point of a system. Users can understand the energy consumption of each electric device and lighting in real time. Responsive energy monitoring service can help in reducing the waste of energy, especially in shaving electric load in a peak time.
The Self-Employed and Lifetime Incomes: Some UK Evidence

Abstract: This article notes that recent self-employment growth in advanced economies has often been accompanied by changes in the composition and dynamics of self-employment. In particular, more people and different types of people’ are now experiencing self-employment during their working lives. The article goes on to examine, using UK data, the implications of growing self-employment for income potential. Several types of analysis are undertaken. Initially, short-term panel data are used to model the determinants of transitions into and out of self-employment. The rest of the article then focuses on the implications of such transitions for incomes in the short, medium, and long terms. Cross-sectional data reveal the high level of dispersion of self-employed incomes, and suggest that self-employment increases the likelihood that an individual will have a very low income. We then look at the effect of previous self-employment spells on current incomes, showing that those who leave self-employment for wage employment do not appear to have a higher risk of low incomes. Finally, we look at older people, close to and beyond retirement age, and find that those with work histories including self-employment have a higher chance of low incomes in later life, with low levels of savings and low pension entitlements. The findings contradict popular stereotypes of high income self-employed people, raising policy questions regarding the extent to which social security and pension systems are well designedfor a labor market with a growing and heterogeneous group of self-employed people.
Classification techniques for big data: A survey

Big Data is an immense term for working with large volume and complex data sets. When data set is large in volume and traditional processing applications are inadequate then distributed databases are needed. Big data came into existence because earlier technologies were not able to handle such large data from autonomous sources. To find meaningful and accurate data from large unstructured data, is a dreary task for any user. This is the reason why classification techniques came into picture for big data. With the help of classification methods unstructured data can be turned into organized form so that a user can access the required data easily. These classification techniques can be applied over big transactional databases to provide data services to users from large volume data sets. Classification is an aspect of machine learning and there are basically two broad categories: Supervised and unsupervised classification. In this paper we worked on to study variants of supervised classification methods. A comparison is also done on the basis of their advantages and limitations.
Absent without leave; a neuroenergetic theory of mind wandering

Absent minded people are not under the control of task-relevant stimuli. According to the Neuroenergetics Theory of attention (NeT), this lack of control is often due to fatigue of the relevant processing units in the brain caused by insufficient resupply of the neuron's preferred fuel, lactate, from nearby astrocytes. A simple drift model of information processing accounts for response-time statistics in a paradigm often used to study inattention, the Sustained Attention to Response Task (SART). It is suggested that errors and slowing in this fast-paced, response-engaging task may have little to due with inattention. Slower-paced and less response-demanding tasks give greater license for inattention—aka absent-mindedness, mind-wandering. The basic NeT is therefore extended with an ancillary model of attentional drift and recapture. This Markov model, called NEMA, assumes probability λ of lapses of attention from 1 s to the next, and probability α of drifting back to the attentional state. These parameters measure the strength of attraction back to the task (α), or away to competing mental states or action patterns (λ); their proportion determines the probability of the individual being inattentive at any point in time over the long run. Their values are affected by the fatigue of the brain units they traffic between. The deployment of the model is demonstrated with a data set involving paced responding.
The architectural design of networks of protein domain architectures

Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.
Polarizing T and B Cell Responses by APC-Targeted Subunit Vaccines

Current influenza vaccines mostly aim at the induction of specific neutralizing antibodies. While antibodies are important for protection against a particular virus strain, T cells can recognize epitopes that will offer broader protection against influenza. We have previously developed a DNA vaccine format by which protein antigens can be targeted specifically to receptors on antigen presenting cells (APCs). The DNA-encoded vaccine proteins are homodimers, each chain consisting of a targeting unit, a dimerization unit, and an antigen. The strategy of targeting antigen to APCs greatly enhances immune responses as compared to non-targeted controls. Furthermore, targeting of antigen to different receptors on APCs can polarize the immune response to different arms of immunity. Here, we discuss how targeting of hemagglutinin to MHC class II molecules increases Th2 and IgG1 antibody responses, whereas targeting to chemokine receptors XCR1 or CCR1/3/5 increases Th1 and IgG2a responses, in addition to CD8+ T cell responses. We also discuss these results in relation to work published by others on APC-targeting. Differential targeting of APC surface molecules may allow the induction of tailor-made phenotypes of adaptive immune responses that are optimal for protection against various infectious agents, including influenza virus.
In Defense of the Independent Payment Advisory Board.

O ne of the most challenging aspects of controlling health care costs is the unpopularity of most health care cost controls. We seem not to like what we want when we see the details. As exhibit A, I offer the IPAB, or Independent Payment Advisory Board, among the most reviled sections of the Affordable Care Act (ACA), sometimes referred to as the law’s “death panel. ”1 Though high on the hit list of many congressional Republicans and Democrats, as well as a jumbo jet load of health care interest groups, it’s a smart provision that just might provide a way to circumvent Congress’s inability to confront exploding prescription drug costs. Here is how IPAB is supposed to work. When Medicare per enrollee spending in any year rises above the ACA’s target growth rate—as determined by the chief actuary of the US Centers for Medicare and Medicaid Services—IPAB is required by law to develop and submit formal recommendations to reduce Medicare’s per capita growth rate down to the target level. Since the ACA’s signing in 2010, Medicare spending has not risen to the target level; 2017 or 2018 may be the first year, though not by a huge amount. At a Brookings Institution event last year, Medicare Chief Actuary Paul Spitalnic said: “Based on the current Medicare trustees report projections, it will be expected . that there would be a determination for the IPAB in 2017. That means that I would have to issue that the Medicare growth rates exceeds the targets and that savings will need to be generated to effectively account for this . 2 percent of difference. ”2 As of early-July, the chief actuary’s projections had yet to be released. Though the increase may be small, it will be a moment of truth to see how serious the Trump administration and Congress are in terms of confronting rising costs in this new era. Or, they might just try to repeal the IPAB (ACA’s section 3403) instead. Originally called the
Parametric Approximation of Willmore Flow and Related Geometric Evolution Equations

We present various variational approximations of Willmore flow in $\mathbb{R}^d$, $d=2,3$. As well as the classic Willmore flow, we also consider variants that are (a) volume preserving and (b) volume and area preserving. The latter evolution law is the so-called Helfrich flow. In addition, we consider motion by Gaus curvature. The presented fully discrete schemes are easy to solve as they are linear at each time level, and they have good properties with respect to the distribution of mesh points. Finally, we present numerous numerical experiments, including simulations for energies appearing in the modeling of biological cell membranes.
Dissociable Effects of Motivation and Expectancy on Conflict Processing: An fMRI Study

Abstract Previous studies suggest that both motivation and task difficulty expectations activate brain regions associated with cognitive control. However, it remains an open question whether motivational and cognitive determinants of control have similar or dissociable impacts on conflict processing on a neural level. The current study tested the effects of motivation and conflict expectancy on activity in regions related to processing of the target and the distractor information. Participants performed a picture–word interference task in which we manipulated the size of performance-dependent monetary rewards (level of motivation) and the ratio of congruent to incongruent trials within a block (level of conflict expectancy). Our results suggest that motivation improves conflict processing by facilitating task-relevant stimulus processing and task difficulty expectations mainly modulate the processing of distractor information. We conclude that motivation and conflict expectancy engage dissociable control strategies during conflict resolution.
An integrated model of Kano and quality function deployment for evaluation of lean production tools in assembly environment

The idea of introducing decision support system in manufacturing is to enable companies work more economically by using their manufacturing skills, time, space, money, and other manufacturing influencing factors more efficiently and effectively. The challenges associated with decision-making in manufacturing are numerous and sometimes complicated, most especially when faced with large number of factors and criteria to choose from. Many of the decisions in practice are usually made without a formal method or discussion and in most cases often leads to conflicts and waste of resources. In this study, a decision making model was developed for the evaluation and selection of lean production tools for the implementation of lean technique in a product assembly environment using a combined Kano model and Quality Function Deployment (QFD). The combined Kano model and QFD method was tested and applied in a simulated multiple decision-making problems with numerical examples. The proposed model in this study was found to be helpful and effective in dealing with multi-criteria problems.
From Mickey Mouse to Marilyn Manson: A Search Experience

Describes the Multiple Intelligence search (used by the author with 6th and 9th graders) based on Ken Macrorie’s “I-Search” and Howard Gardner’s theory of multiple intelligences. Describes the process as students conducted a search using library resources and technology; became experts on topics they are passionate about; created a professional presentation; and explored topics through multiple intelligences.
Relationship between XRCC1 polymorphisms and susceptibility to prostate cancer in men from Han, Southern China.

AIM To investigate the association among XRCC1 polymorphisms, smoking, drinking and the risk of prostate cancer (PCa) in men from Han, Southern China. METHODS In a case-control study of 207 patients with PCa and 235 cancer-free controls, frequency-matched by age, we genotyped three XRCC1 polymorphisms (codons 194, 280 and 399) using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RELP) method. RESULTS Among the three polymorphisms, we found that the XRCC1 Arg399Gln variant allele was associated with increased PCa risk (adjusted odd ratio [OR]: 1.67, 95% confident interval [CI]: 1.11-2.51), but the XRCC1 Arg194Trp variant allele had a 38% reduction in risk of PCa (adjusted OR: 0.62, 95% CI: 0.41-0.93). However, there was no significant risk of PCa associated with Arg280His polymorphism. When we evaluated the three polymorphisms together, we found that the individuals with 194Arg/Arg wild-type genotype, Arg280His and Arg399Gln variant genotypes had a significantly higher risk of PCa (adjusted OR: 4.31; 95% CI: 1.24-14.99) than those with three wild-type genotypes. In addition, we found that Arg399Gln variant genotypes had a significant risk of PCa among heavy smokers (adjusted OR: 2.04; 95% CI: 1.03-4.05). CONCLUSION These results suggest that polymorphisms of XRCC1 appear to influence the risk of PCa and may modify risks attributable to environmental exposure.
Optimal Brain Surgeon: Extensions and performance comparisons

We extend Optimal Brain Surgeon (OBS) - a second-order method for pruning networks - to allow for general error measures, and explore a reduced computational and storage implementation via a dominant eigenspace decomposition. Simulations on nonlinear, noisy pattern classification problems reveal that OBS does lead to improved generalization, and performs favorably in comparison with Optimal Brain Damage (OBD). We find that the required retraining steps in OBD may lead to inferior generalization, a result that can be interpreted as due to injecting noise back into the system. A common technique is to stop training of a large network at the minimum validation error. We found that the test error could be reduced even further by means of OBS (but not OBD) pruning. Our results justify the t → 0 approximation used in OBS and indicate why retraining in a highly pruned network may lead to inferior performance.
Utility-based routing in wireless ad hoc networks

This work presents a novel utility-based routing (UBR) algorithm for wireless ad hoc networks. In multi-hop ad hoc networks, each node may be responsible for forwarding data packets for others. Thus, some nodes may consume more energy than others, and consequently die earlier This leads to unbalanced usage of the power among the nodes, network partition, and the decrease in network lifetime. The UBR algorithm we develop takes into account not only the status of each intermediate node but also the characteristic of applications. Specifically, each application is assumed to be associated with a utility function, which maps to the quality of service (QoS). Each intermediate node sets a price to signal its willingness to participate, and then the cost for involving this intermediate node is calculated as price times the transmit power. Instead of choosing the shortest routing path, the destination node picks up the routing path that gives the maximum surplus defined as utility minus cost. Our performance study based on the PARSEC simulator shows that the proposed utility based algorithm improves the energy balance when compared with the original DSR.