Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Pulmonary Rehabilitation for Chronic Obstructive Pulmonary Disease and Associated Conditions

Pulmonary rehabilitation (PR) is an evidenced-based, proven treatment as mentioned recent guidelines in patients with chronic obstructive pulmonary disease (COPD). Exercise training is a cornerstone of PR programs, Inspiratory muscle training, neuro- muscular electrical stimulation (NMES) are effective in selected patients. Water-based rehabilitation and tai chi are well tolerated recent modalities. Although there is an absence of a specific PR protocol for special conditions, PR is recommended before and also after endobronchial volume reduction (EBVR), lung volume reduction surgery (LVRS), both before and after lung transplantation periods, before, after surgery, during the intensive care unit (ICU) period, the chemotherapy period and as a component of palliative care. After COPD exacerbation, it is recommended within 3 weeks of hospital discharge. Modifying PR programs while considering comorbidities might lead to greater improve- ment in outcomes. After PR, the important points are to follow prescribed home exercise programs, control programs in the PR center/unit, and being more active in daily living life for the purpose of preserving improvements. Tele-PR is an alternative to conventional modalities due to similar improvements. Although PR is effective, it is an under- utilized resource. The awareness of PR should be increased in patients and among health professionals.
Inferences about a Probabilistic Measure of Effect Size When Dealing with More Than Two Groups

For two independent random variables, X and Y , let p = P (X > Y ) + 0:5P (X = Y ), which is sometimes described as a probabilistic measure of eect size. It has been argued that for various reasons, p represents an important and useful way of characterizing how groups dier. In clinical trials, for example, an issue is the likelihood that one method of treatment will be more eective than another. The paper deals with making inferences about p when three or more groups are to be compared. When tied values can occur, the results suggest using a multiple comparison procedure based on an extension of Cli's method used in conjunction with Hochberg's se- quentially rejective technique. If tied values occur with probability zero, an alternative method can be argued to have a practical advantage. As for a global test, extant rank-based methods are unsatisfactory given the goal of comparing groups based on p. The one method that performed well in sim- ulations is based in part on the distribution of the dierence between each pair of random variables. A bootstrap method is used where a p-value is based on the projection depth of the null vector relative to the bootstrap cloud. The proposed methods are illustrated using data from an intervention study.
Importance of peakedness in sea surface slope measurements and applications

We recall the simple statistical concept that non-Gaussian distribution peakedness results from the compounding of random processes. This idea is applied to observations and analysis of sea surface slopes as inferred using optical and microwave-scattering measurements. Our study emphasizes the importance of identifying and quantifying the distribution variance and kurtosis from observations. Data are shown to indicate consistently non-Gaussian peakedness, to indicate the need to report at least two parameters in an even order analysis, and to indicate near equivalence between radar and optical data. Physical interpretation for observed infrequent steep slopes is given via compounding statistical processes where normally distributed short-scale waves are modulated because of random fluctuations mainly associated with the underlying long wave field. Implications of non-Gaussian peakedness are provided for altimeter backscatter theory and for modeling wave-breaking probability.
Stereo Vision in Smart Camera Networks

Stereo vision inherently comes with high computational complexity, which previously limited its deployment to high-performance, centralized imaging systems. But recent advances in embedded systems and algorithm design have paved the way for its adoption for and migration into smart camera networks, which notoriously suffer from limited processing and energy resources. Such networks consist of a collection of relatively low-cost smart camera motes, which—in their simplest form—integrate a microcontroller, an image sensor, and a radio into a single, embedded unit capable of sensing, computation, and wireless communication. When deployed in an in- or outdoor environment, they form ad-hoc or mesh networks that can perform a wide range of applications. Their application areas range from ambient intelligence, building automation, elderly care, autonomous surveillance, and traffic control to smart homes. The underlying network tasks include object localization, target tracking, occupancy sensing, object detection and classification. Stereo vision can bring increased performance and robustness to several of these tasks possibly even at overall reductions in energy consumption and prolonged network lifetime. This chapter will provide a brief description of the building blocks, characteristics, limitations and applications of smart camera networks. We will then present a discussion of their requirements and constraints with respect to stereo vision paying special attention to differences to conventional stereo vision systems. The main issue arises from the high data rate, which image sensors particularly in a stereoscopic configuration generate. Conventional centralized computing systems can easily handle such rates. But for smart camera networks, their resource constraints pose a serious challenge to effective acquisition and processing of this high-rate data. Two possible approaches to address this problem have emerged in recent publications: one suggests the design of a custom image processor whereas the other solution proposes utilization of off-the-shelf, general-purpose microprocessors in conjunction with resolution-scaled image sensors. Our discussion focuses on these two state-of-the-art stereo architectures. NXP's WiCa mote is the primary example deploying a dedicated image processor, while Stanford's MeshEye mote pioneered the idea of resolution-scaled stereo vision. More specifically, the WiCa mote deploys an application-specific image processor based on a vector single-instruction, multiple-data architecture, which is able to process the data streams of two VGA camera modules. In contrast, Stanford's MeshEye mote deploys a low-resolution stereo vision system requiring only a general-purpose 32-bit ARM7 processor. Additionally, it hosts a VGA camera module for more detailed image acquisition.
Optimization of FIR Filter Using PSO Based Algorithm

– In this dissertation, a digital filter is being optimized using Particle Swarm Optimization and compared with conventional frequency sampling method of optimization. Among IIR and FIR filter, here we discuss FIR filter optimization where firstly a single particle is being studied and then iterations are done for the rest. As for FIR filter, an important point to keep in notice is that an FIR filter is designed using convolution rather than recursion which results in higher quality of stability. An FIR filter is a linear phase filter where both phase delay and group delays are constant. The PSO is a population-based algorithm where a set of potential solutions evolve to approach a convenient solution (or set of solutions) for a problem. Being an optimization method, the aim is to find the global optimum of a real-valued function (fitness function) defined in a search space. In this, a population of individuals (referred to as particles) adapts by returning stochastically toward previously successful regions. Every particle's movement is a composition of initial random velocity and two randomly weighted influences i.e. individuality (the tendency to return to the particle's best previous position) and sociality (the tendency to move towards the neighborhood's best previous position). After every cycle of iteration, a new value of velocity for each particle is calculated based on its current velocity, its distance from the previous best position, and its distance from the global best position. The new velocity value is then used to calculate the next position of the particle in the search space. We use PSO as an optimization technique to optimize the output parameters of the FIR filter. PSO initializes a group of random particles (solutions) and then searches for optimal solution by updating generated values. The particle swarm algorithm is used here in terms of social cognitive behavior. It is widely used for problem solving method in engineering. When the search space is too large to search exhaustively, population based searches may be a good alternative.
A Review on Methodologies for CapacityImprovement with Minimum Delay in WMN

In recent years there is explosive growth towards wireless broadband technologies which accelerating the need to design an efficient “last mile” access network in a cost-effective manner. Wireless Mesh Network (WMN) is emerging as promising technology for many useful applications. Over the past decade the size, cost and power requirements of radios has declined, enabling multiple radios to be contained within a single mesh node, thus allowing for greater modularity each can handle multiple frequency bands and support a variety of functions as needed such as client access, packet forwarding and scanning with minimum relays between nodes in wireless network. In order to making cost –efficient network different routing protocols are proposed. In this paper after analysing the different methodologies we use improved methodology that will not only find the shortest path but also making an efficient network by minimizing the delay from source to destination nodes in wireless network.
Dust Motions in Magnetized Turbulence: Source of Chemical Complexity

In addition to the manufacture of complex organic molecules from impacting cometary and icy planet surface analogs, which is well-established, dust grain–grain collisions driven by turbulence in interstellar or circumstellar regions may represent a parallel chemical route toward the shock synthesis of prebiotically relevant species. Here we report on a study, based on the multi-scale shock-compression technique combined with ab initio molecular dynamics approaches, where the shock-wave-driven chemistry of mutually colliding isocyanic acid (HNCO) containing icy grains has been simulated by first principles. At the shock-wave velocity threshold triggering the chemical transformation of the sample (7 km s−1), formamide is the first synthesized species, thus being the springboard for the further complexification of the system. Also, upon increasing the shock impact velocity, formamide is formed in progressively larger amounts. More interestingly, at the highest velocity considered (10 km s−1), impacts drive the production of diverse carbon–carbon bonded species. In addition to glycine, the building block of alanine (i.e., ethanimine) and one of the major components of a plethora of amino acids including, e.g., asparagine, cysteine, and leucine (i.e., vinylamine), have been detected after shock compression of samples containing the most widespread molecule in the universe (H2) and the simplest compound bearing all of the primary biogenic elements (HNCO). The present results indicate novel chemical pathways toward the chemical complexity typical of interstellar and circumstellar regions.
The place of podcasting in Physiotherapy skills based education

Background, aims and methods: Video podcasts are increasingly used by a range of healthcare students. Video podcasts have great potential when used as a pedagogical tool, embedded within a curriculum and this has relevance to the teaching of physiotherapy. This article aims to consider the existing literature regarding podcasting in medical education and then contemplate the implications of the use of mobile technologies for the acquisition of clinical skills in the physiotherapy curriculum. Results: The educational theories underpinning such interventions are also discussed, and recommendations for the use and integration of video podcasts into the physiotherapy curriculum are provided. Video podcasting has been well explored within the existing medical education literature and video podcasting could serve to further engage and enhance the experiences of student Physiotherapists when learning and mastering clinical skills. Conclusions: The challenge in Physiotherapy education is to develop and embed innovative and engaging ways of delivering the Physiotherapy curriculum into traditional curricula, that meet the needs of this generation’s busy learner, promote mobile learning and enhance the teaching of skills, at the same time as taking into consideration students’ learning preferences.
Matrix Production by Nucleus Pulposus and Bone Marrow Stem Cells Extracellular Matrix Production by Nucleus Pulposus and Bone Marrow 1 Stem Cells in Response to Altered Oxygen and Glucose Microenvironments

20 Bone marrow (BM) stem cells may be an ideal source of cells for intervertebral disc (IVD) 21 regeneration. However the harsh biochemical microenvironment of the IVD may 22 significantly influence the biological and metabolic vitality of injected stem cells and impair 23 their repair potential. This study investigated the viability and production of key matrix 24 proteins by nucleus pulposus (NP) and BM stem cells cultured in the typical biochemical 25 microenvironment of the IVD consisting of altered oxygen and glucose concentrations. 26 Culture expanded NP cells and BM stem cells were encapsulated in 1.5% alginate and 27 ionically crosslinked to form cylindrical hydrogel constructs. Hydrogel constructs were 28 maintained under different glucose concentrations (1mM, 5mM and 25mM) and external 29 oxygen concentrations (5% and 20%). Cell viability was measured using the Live/Dead® 30 assay and the production of sulphated glycosaminoglycans (sGAG) and collagen was 31 quantified biochemically and histologically. For BM stem cells, IVD-like micro32 environmental conditions (5mM glucose and 5% oxygen) increased the accumulation of 33 sGAG and collagen. In contrast, low glucose conditions (1mM glucose) combined with 5% 34 external oxygen concentration promoted cell death inhibiting proliferation and the 35 accumulation of sGAG and collagen. NP-encapsulated alginate constructs were relatively 36 insensitive to oxygen concentration or glucose condition in that they accumulated similar 37 amounts of sGAG under all conditions. Under IVD-like microenvironmental conditions, NP 38 cells were found to have a lower glucose consumption rate compared to BM cells and may in 39 fact be more suitable to adapt and sustain the harsh microenvironmental conditions. 40 Considering the highly specialised microenvironment of the central NP, these results indicate 41 that IVD-like concentrations of low glucose and low oxygen are critical and influential for 42 the survival and biological behaviour of stem cells. Such findings may promote and 43 accelerate the translational research of stem cells for the treatment of IVD degeneration. 44 Matrix Production by Nucleus Pulposus and Bone Marrow Stem Cells
Kalman Filter and Analog Schemes to Postprocess Numerical Weather Predictions

Two new postprocessing methods are proposed to reduce numerical weather prediction’s systematic and random errors. The first method consists of running a postprocessing algorithm inspired by the Kalman filter (KF) through an ordered set of analog forecasts rather than a sequence of forecasts in time (ANKF). The analog of a forecast for a given location and time is defined as a past prediction that matches selected features of the current forecast. The second method is the weighted average of the observations that verified when the 10bestanalogswerevalid(AN). ANKFandANaretestedfor10-mwindspeedpredictionsfromtheWeather ResearchandForecasting(WRF)model,withobservations from400surfacestationsoverthewesternUnited States for a 6-month period. Both AN and ANKF predict drastic changes in forecast error (e.g., associated with rapid weather regime changes), a feature lacking in KF and a 7-day running-mean correction (7-Day). TheANalmosteliminates thebiasoftherawprediction(Raw),whileANKFdrasticallyreducesitwithvalues slightly worse than KF. Both analog-based methods are also able to reduce random errors, therefore improvingthepredictiveskill ofRaw. TheAN isconsistentlythebest, withaverageimprovements of10%,20%, 25%,and 35%with respecttoANKF,KF, 7-Day,andRaw, asmeasuredby centeredroot-mean-squareerror, and of 5%, 20%, 25%, and 40%, as measured by rank correlation. Moreover, being a prediction based solely on observations, AN results in an efficient downscaling procedure that eliminates representativeness discrepancies between observations and predictions.
Hepatoprotective Effects of Deuterium Depleted Water(DDW)Adjuvant with Satureja rechingeri Essential Oils

This study was carried out to investigate the hepatoprotective effect of deut erium depleted water (DDW) with and without Satureja rechingeri essential oil (E.O) mixture on paracetamol induced hepatotoxicity in rats. The animals were divided into 24 groups (n=5): The negative control group used tap water in 14 days following DMS O i.p injection at day 15th. The control group received tap water in 14 days following 500 mg/kg b.w. i.p injection of acetaminophen dissolved in DMSO. The treatment groups received only DDW (30 and 60 ppm) in 14 days concomitant with treatment groups receiving DDW plus i.p injection of S. rechingeri oil following acetaminophen injection at day 15th. Indeed, hepatoprotective activity was evaluated by the biochemical estimation of acetaminophen metabolism enzymes; cytochrome P450(CYP450), glutathione s-transferase (GST) together with the level of glutathione (GSH). The markers of liver injuries (ALT, AST, and ALP ) were also estimated in plasma. The results indicated that administration of DDW and DDW+E.O resulted in liver damage compensation as manifested by significant decrease in the activities of CYP450 and AST as well as significantly elevating the levels of GSH and GST. The present study reveals that the DDW could afford a significant protection against paracetamol? induced hepatocellular injuries.
INVESTIGATION OF EFFECTIVE PLASMA FREQUEN- CIES IN ONE-DIMENSIONAL PLASMA PHOTONIC CRYSTALS

In this work, a detailed investigation on the efiective plasma frequency fp;efi for one-dimensional binary and ternary plasma- dielectric photonic crystals is made. We extract and then analyze the efiective plasma frequency from the calculated photonic band structures at distinct conditions. In the binary photonic crystal, it is found that fp;efi in a photonic crystal is usually smaller than the plasma frequency fp of a bulk plasma system. fp;efi will increase when the electron concentration in the plasma layer increases. It also increases as the thickness of the plasma layer increases, but decreases with the increase in the thickness of dielectric layer. In the ternary photonic crystal, fp;efi is shown to be decreased compared to that of in the binary one. Our results are compared with the analytical expression for fp;efi derived from the concept of efiective medium. Fairly good consistence has been obtained for both results. Additionally, a discussion on the efiect of loss on fp;efi is also given. The study is limited to the case of normal incidence.
Band gap reduction in GaNSb alloys due to the anion mismatch

The structural and optoelectronic properties in GaNxSb1−x alloys (0⩽x<0.02) grown by molecular-beam epitaxy on both GaSb substrates and AlSb buffer layers on GaAs substrates are investigated. High-resolution x-ray diffraction (XRD) and reciprocal space mapping indicate that the GaNxSb1−x epilayers are of high crystalline quality and the alloy composition is found to be independent of substrate, for identical growth conditions. The band gap of the GaNSb alloys is found to decrease with increasing nitrogen content from absorption spectroscopy. Strain-induced band-gap shifts, Moss-Burstein effects, and band renormalization were ruled out by XRD and Hall measurements. The band-gap reduction is solely due to the substitution of dilute amounts of highly electronegative nitrogen for antimony, and is greater than observed in GaNAs with the same N content.
Emergent universal critical behavior of the 2D N-color Ashkin-Teller model in the presence of correlated disorder

We study the critical behavior of the 2D $N$-color Ashkin-Teller model in the presence of random bond disorder whose correlations decays with the distance $r$ as a power-law $r^{-a}$. We consider the case when the spins of different colors sitting at the same site are coupled by the same bond and map this problem onto the 2D system of $N/2$ flavors of interacting Dirac fermions in the presence of correlated disorder. Using renormalization group we show that for $N=2$, a "weakly universal" scaling behavior at the continuous transition becomes universal with new critical exponents. For $N>2$, the first-order phase transition is rounded by the correlated disorder and turns into a continuous one.
Spatial patterns of phytoplankton composition and upper‐ocean biogeochemistry do not follow carbonate chemistry gradients in north‐west European Shelf seas: Towards a Broader Perspective on Ocean Acidification Research Part 2 A special issue of the ICES Journal of Marine Science

&NA; A key difficulty in ocean acidification research is to predict its impact after physiological, phenotypic, and genotypic adaptation has had time to take place. Observational datasets can be a useful tool in addressing this issue. During a cruise in June‐July 2011, measurements of upper‐ocean biogeochemical variables, climatically active gases and plankton community composition were collected from northwestern European seas. We used various multivariate statistical techniques to assess the relative influences of carbonate chemistry and other environmental factors on these response variables. We found that the spatial patterns in plankton communities were driven more by nutrient availability and physical variables than by carbonate chemistry. The best subset of variables able to account for phytoplankton community structure was the euphotic zone depth, silicic acid availability, mixed layer average irradiance, and nitrate concentration (59% of variance explained). The spatial variations in phytoplankton and coccolithophores species composition were both found to be more strongly associated with nutrients and physical variables than carbonate chemistry, with the latter only explaining 14 and 9% of the variance, respectively. The plankton community composition and contribution of calcifying organisms was not observed to change under lower calcite saturation state (&OHgr;) conditions, although no regions of undersaturation (&OHgr; < 1) were encountered during the cruise. Carbonate chemistry played a more prominent, but still secondary, role in determining dinoflagellate and diatom assemblage composition (20 and 13% of total variance explained, respectively). Nutrient and physical variables also explained more of the spatial variations of most climatically active gases and selected biogeochemical response variables, although some also appeared to be influenced by carbonate chemistry. This observational study has demonstrated that ocean acidification research needs to be set in context with other environmental forcing variables to fully appreciate the primary, or indeed secondary, role that increasing fugacity of carbon dioxide has on biological communities and associated biogeochemical rates.