Miracle-dz/UniFAR-FTUs huggingface dataset:
Limb Muscle Weakness in Chronic Obstructive Pulmonary Disease: Improving Characterization and Optimizing Exercise Prescription

Limb muscle weakness is a secondary consequence of chronic obstructive pulmonary disease (COPD). It affects approximately 30% of patients and is associated with exercise intolerance, increased health care utilization, and increased risk of mortality. There are still important gaps in the understanding about the development and management of limb muscle weakness in COPD. The overall objective of this thesis was to improve characterization of and optimize strength exercise prescription for limb muscle weakness and n in COPD. The first study of this thesis showed that an increased fatty infiltration accompanies muscle atrophy across thigh and calf muscles in people with COPD. Intramuscular fat infiltration was greater in COPD compared to what was observed in matched healthy controls and more strongly correlated with muscle weakness and impaired mobility than muscle atrophy in these individuals. The second and third studies of this provided insights on how people with COPD may respond to exercise approach that specifically target muscle weakness. In these studies the acute effects of different strength training exercises for upperand lower-limb muscles were explored in these individuals. In the second study, we showed that immediate cardiorespiratory responses during short bouts of weightlifting in COPD are independent of the exercise intensity. Although people with COPD iii reported greater levels of perceived exertion and longer time to recover after high vs. lowintensity exercise bouts, responses to different intensities were comparable to their healthy counterparts. The third study showed that responses were also independent of number of exercising limbs (double vs. single limb) during lower and upper-body exercises. In this study, however, we showed a significant effect of limb position during arm exercises in people with COPD where arm exercise overhead (above shoulder level) evoked greater responses and perceived exertion and longer recovery time than other exercise variations. The findings from the three studies reveal the importance of fatty infiltration in the development of limb muscle weakness in COPD and provide insights on tailoring exercise approaches to muscle weaknes3s that better meet the needs of people with COPD. Future studies could assess cardiorespiratory requirements during a full training program to determine the most appropriate intensity-response and to further assist in standardizing training prescription in COPD. As well, the training effects of strength exercises on intramuscular fatty infiltration in people with COPD in an area for future
Better off alone? Compared performance of monoclonal and polyclonal stands of a cultivated red alga growth

The objective of this study was to test, using a field experiment, the effect of genotypic diversity on productivity of farmed populations (Ancud and Chaica, Chile) of the domesticated red alga Agarophyton chilense (formerly known as Gracilaria chilensis), a species considered as economically important in Chile. Monoclonal and polyclonal (4 and 8 genotypes) subplots were outplanted into the mid intertidal in Metri Bay (Puerto Montt, Chile) during summer, a season in which A. chilense face higher temperatures (>18°C) and low nitrogen availability (<4.00 μmol). Ancud farm genotypes show higher growth rates in the monoclonal rather than the two polyclonal subplots. A similar tendency, yet not significant, was discernible in Chaica. In addition, whatever the population of origin of the thalli, no effect of genotypic diversity was detected neither on the agar yield and its quality, nor on the epiphyte load. Such unexpected results of a higher performance in plots with a lower genotypic diversity could be explained (a) by human‐assisted selection for dominant‐best‐performing genotypes that could counterbalance the negative effect caused by the low genotypic diversity in farms and (b) by the fact that the organisms inhabiting the algal mats do not impact the fitness of their host. Overall, the results obtained here suggest that despite farm induced selection lead to impoverished pools of genotypes, they may also have a positive effect of on the resistance of farmed populations to seasonal stressors. However, whether this may have a secondary negative effect on the longer term in a fluctuating environment remains to be determined, but may be avoided by adopting strategy of selection favoring different genotypes in space and time, as implemented in forestry.
Six-Switch Step-Up Common-Grounded Five-Level Inverter With Switched-Capacitor Cell for Transformerless Grid-Tied PV Applications

Photovoltaic string inverters with transformerless grid-connected architecture are the most commonly used solar converters owing to their appliance-friendly and cost-effective benefits. A novel circuit configuration for these converters is presented in this article, which seeks to address the shortcomings of most of the conventional topologies such as the problem of leakage current, voltage ratio transformations, and power quality. The proposed structure is based on the series–parallel switching conversion of the switched-capacitor (SC) cell and is comprised of only six unidirectional power switches with a common-grounded (CG) feature. Through the use of the SC cell and the CG connection of active and passive used elements, not only is the number of output voltage level enhanced by up to five but also a two times voltage boosting feature with a single-stage operation as well as elimination of the leakage current is acquired. Herein, to inject a tightly controlled current into the grid, a peak current controller approach has been used which can handle both the active and reactive power supports modes. Theoretical analysis, design guidelines, comparative study, and some experimental results are also given to corroborate the feasibility and accurate performance of the proposed topology.
High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating

Biological memory is known to be flexible — memory formation and recall depend on factors such as the behavioral context of the organism. However, this property is often ignored in associative memory models. Here, we bring this dynamic nature of memory to the fore by introducing a novel model of associative memory, which we refer to as the context-modular memory network. In our model, stored memory patterns are associated to one of several background network states, or contexts. Memories are accessible when their corresponding context is active, and are otherwise inaccessible. Context modulates the effective network connectivity by imposing a specific configuration of neuronal and synaptic gating – gated neurons (respectively synapses) have their activity (respectively weights) momentarily silenced, thereby reducing interference from memories belonging to other contexts. Memory patterns are randomly and independently chosen, while neuronal and synaptic gates may be selected randomly or optimized through a process of contextual synaptic refinement. Through signal-to-noise and mean field analyses, we show that context-modular memory networks can exhibit substantially increased memory capacity with random neuronal gating, but not with random synaptic gating. For contextual synaptic refinement, we devise a method in which synapses are gated off for a given context if they destabilize the memory patterns in that context, drastically improving memory capacity. Notably, synaptic refinement allows for patterns to be accessible in multiple contexts, stabilizing memory patterns even for weight matrices that do not contain any information about the memory patterns such as Gaussian random matrices. Lastly, we show that context modulates the relative stability of accessible versus inaccessible memories, thereby confirming that contextual control acts as a mechanism to temporarily hide or reveal particular memories. Overall, our model integrates recent ideas about context-dependent memory organization with classic associative memory models, highlights an intriguing trade-off between memory capacity and accessibility, and carries important implications for the understanding of biological memory storage and recall in the brain.
Studies on asthma and allergic rhinitis among occupational hazardous workers in and around Pollachi

Between 200 to 300 Million people around the glob suffer from Asthma and Allergic Rhinitis and the number is increasing. India has an estimated 15 to 20 million asthmatics, with a prevalence rate of 10 and 15 percent. In order to find out the prevalence rate of allergic diseases among occupational hazardous workers in and around Pollachi, an epidemiological study is conducted in industrial areas Surya Spinning Mill and Shri Dharma Shastha Coir Industry along with Dr.K. Sivanandhan. Blood samples are collected and analyzed using IgE ELISA kit. A total of 113 workers, Surya Spinning Mill 94, Shri Dharma Shastha Coir Industry 19 are examined clinically, data are collected using a questionnaire and blood samples are collected and analyzed and tabulated. It is found out that prevalence rate of Asthma and Allergic rhinitis in Surya Spinning Mill is 12.7% and in the Coir Industry it is 15.8 percent. The results showed that the prevalence rate of Asthma and Allergic Rhinitis are within 10 to 12 percent as in the case of urban and rural area. From the above study it is also proved that just exposure to dust or smoke or coconut husk alone will not cause Bronchial Asthma or Allergic Rhinitis.
Determination and Extraction of Carbofuran Pesticide in Different Matrices using Cloud Point Extraction Method

Pesticides are increasingly used in agriculture and households, but they are also considered a major pollutant to the environment. Carbofuran (CAR; 2,3-dihydro-2,2- dimethylbenzofuran-7-yl methylcarbamate) is a widely used pesticide due to its effectiveness on soybean aphids. A simple and green method was suggested for the extraction and determination of CAR in different matrices. A diazotization reaction involving the use of the drug compound metoclopramide was utilized in this study. A red dye product, which was formed from the diazotization coupling between CAR and diazotized metoclopramide (DMCP), was extracted using cloud point extraction with the nonionic surfactant Triton X-114 and measured at a wavelength of 515 nm. The linearity of the extracted method was over a concentration range of 0.1-0.5 µg/mL (r2 = 0.996) for CAR with a detection limit of 0.064 µg/mL and enrichment factors of about 148 folds for CAR. The mean recovery percentage was in the range of 99-102% for water and soil samples with precision (RSD%) of less than 0.4%. The described method was effectively utilized in the simultaneous extraction of CAR from water and soil samples.
Assessment of an Electrocoagulation Reactor for the Removal of Oil Content and Turbidity from Real Oily Wastewater Using Response Surface Method

Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studied and modeled. The results revealed the positive effect of the electrodes design on the studied responses. Under the optimum values of the operating variables (5.675 mA/cm2, 40 min), 85.982% and 84.439% removal efficiencies of oil content and turbidity respectively were obtained and the consumption of energy and electrodes were observed as 4.333kWh/m3 and 0.36 g respectively.
Photoplethysmogram Derived Cardio-Respiratory Biomarkers for Sleep Monitoring

Continuous monitoring of cardio-respiratory biomarkers provides critical information regarding patient health status in the clinical setting. Additionally, cardio-respiratory biomarkers play an essential role in the monitoring of sleep quality and sleep-related disorders. Although the clinicians routinely monitor the heart rate (HR), the respiratory rate (RR) is not recorded most often due to the use of the cumbersome device that it requires to monitor. One possible solution to this is to develop a wearable device that is capable of monitoring continuous RR non-invasively. We have implemented algorithms that are capable of extracting HR and RR from the short length photoplethysmogram (PPG) signal. These cardio-respiratory biomarkers are applied for sleep quality monitoring. The work presented in this thesis consists of three major parts. In the first part, a model based on spectral estimation and median filtering is proposed to estimate HR for short length PPG signal. In case of intensive motion corrupted PPG signal due to excessive physical exercise or daily living conditions, a novel algorithm based on recursive Wiener filter with history tracking is proposed to reduce intense motion artifacts from PPG signal to estimate HR for a very short length signal (8 seconds). In the second part, we propose an automatic threshold selection technique of multi-scale principal component analysis based model for PPG derived RR estimation. Similar to the conventional methods, it works better for long length PPG, but its performance decays for short length PPG. To estimate RR reliably from the short length PPG, we have proposed a novel method that comprises of ensemble empirical mode decomposition (EEMD) and principal component analysis. We have also investigated the other noise assisted variants of EEMD to improve the performance and presented a summary on EEMD variants based PPG decomposition for RR estimation. In the final part of the thesis, we propose a PPG based automated approach for sleep monitoring. We have investigated the statistical and surrogate cardio-respiratory biomarkers to classify sleep stages using supervised machine learning techniques. The results of the performance metrics show that PPG could be a promising candidate for wearable sleep monitoring. Since PPG is well for a long time continuous monitoring, it will reduce the discomfort of patients, which is the main limitation of polysomnography based conventional sleep monitoring.
Indoor path planning and obstacle avoidance simulation

The paper is describing the work performed for choosing and designing a path planning and obstacle avoidance solution for a car-like vehicle moving in an indoor environment. The proposed algorithm first consists in providing the vehicle with a set of passing points generated by a Dijkstra path planning algorithm. The vehicle is using the points for establishing its path and is avoiding the obstacles using scanned data from a distance sensor. In a simulation environment, initial tests were performed for estimating correct values of the vehicle’s forward and angular velocities and for estimating the effect of the scanning speed on the vehicle’s behaviour. Obstacle avoidance tests were performed for identifying specific situations possible to appear due to high velocities or to low scanning speed. Even not always choosing a smooth avoidance path, the algorithm proved to find a way for avoiding the obstacle in a clear and fast enough manner.
Keefektifan Strategi Multiple Intelligences Terhdap Keterampilan Imitating Mathematical Reasoning Siswa

This study aims to determine effectiveness of Multiple Intelligences (MI) strategy to the skills of imitating mathematical reasoning fourth grade students of elementari school. The research design used is quasi experimental design with form none equivalent control group design. Data analysis technique in this reasearch include independet sample t test to determine whether there is difference effect in imitating mathematical reasoning skills between the control calss and experiment class. Then, one sample t-test to determine the effectiveness of MI strategy to students’ imitating mathematical reasoning skills. Based on the result of the hypothesis test using independent sample t test, the values of treuslt is 3,351 (ttable2,032) by significance values 0,002. Next, the result of one sample t test showed the value of tresultis 7,880 (ttable 2,110) by value of significance is 0,000. Refer from the result obtained, It can be concluded 1) there are differences of students; imitating mathematical reasoning skill among the students who use the MI strategy with students who use the conventional strategy; 2) the MI strategy is effective to increase of students’ imitating mathematical reasoning skill.
Firms' perceptions of barriers to innovation and resilience: the Italian region of Friuli Venezia Giulia during the crisis

This paper connects the literature on obstacles to innovation to the concept of regional economic resilience by empirically assessing the relationship between the intensity of firms’ engagement in innovative activities and self-reported obstacles to innovation during the unfolding of the latest economic and financial downturn. The analysis is grounded on a unique dataset on firm-level accounting data (CAD) and information from two waves (2008-10 and 2010-12) of the Community Innovation Survey (CIS) for a representative sample of firms in the Italian region of Friuli Venezia Giulia. The main results support the existence of severe deterring barriers in the region, and suggest that during the economic and financial crisis after 2008 firms’ uncertainty about the market demand became dominant.
Energy-Efficient Mobile Crowdsensing by Unmanned Vehicles: A Sequential Deep Reinforcement Learning Approach

Mobile crowdsensing (MCS) is an attractive and innovative paradigm in which a crowd of users equipped with smart mobile devices (such as smartphones and iPads), and more recently unmanned vehicles (UVs, e.g., driverless cars and drones) conduct sensing tasks in mobile social networks by fully exploiting their carried diverse embedded sensors. These devices, especially UVs, are usually constrained by limited sensing range and energy reserve of devices, which contribute to the restriction of one single UV task performance, and thus UV collaborations are fully favored. In this article, we explicitly consider navigating a group of UVs to collect different kinds of data in a city, with the presence of multiple charging stations. Different from the existing approaches that solve the problem by forming a constrained optimization problem, we propose a novel sequential deep model called “PPO+LSTM,” which contains a sequential model LSTM and is trained with proximal policy optimization (PPO), for assigning tasks and planning route. We evaluate our model in different network settings when comparing with other state-of-the-art solutions, and we also show the impact of important hyperparameters of our model. Results show that our solution outperforms all others in terms of energy efficiency, data collection ratio, and geographic fairness.
Risk factors for perioperative complications in inguinal hernia repair – a systematic review

Abstract The current literature suggests that perioperative complications occur in 8%–10% of all inguinal hernia repairs. However, the clinical relevance of these complications is currently unknown. In our review, based on 571,445 hernia repairs reported in 39 publications, we identified the following potential risk factors: patient age, ASA score, diabetes, smoking, mode of admission (emergency vs. elective surgery), surgery in low resource settings, type of anesthesia, and (in men) bilateral and sliding hernias. The most commonly reported complications are bleeding (0.9%), wound infection (0.5%), and pulmonary and cardiovascular complications (0.2%). In 3.9% of the included publications, a reliable grading of the reported complications according to Clavien-Dindo classification was possible. Using this classification retrospectively, we could show that, in patients with complications, these are clinically relevant for about 22% of these patients (Clavien-Dindo grade ≥IIIa). About 78% of all patients suffered from complications needing only minor (meaning mostly medical) intervention (Clavien-Dindo grade <III). Especially with regard to the low incidence of complications in inguinal hernia repair, future studies should use the Clavien-Dindo classification to achieve better comparability between studies, thus enabling better correlation with potential risk factors.
Nature and Therapeutic Potential of Silica-based Mesoporous Bioactive Glass

Bioactive materials have received much consideration in the last couple of years because of their astounding properties in various fields. Bioactive Glasses (BGs) are utilized as part of biomedical applications, such as antibacterial materials. BGs can be delivered by means of dissolve extinguishing strategy or sol-gel technique. Bactericidal silver-doped sol-gel inferred mesoporous silica-based bioactive glasses were accounted for the first time in 2000, having the synthesis 76SiO2-19CaO-2P2O5-3Ag2O (wt%) and a mean pore width of 28 nm. Bioactive glasses doped with metallic elements such as silver, copper, zinc, cerium and gallium are the focus of this audit in which SiO2, SiO2-CaO and SiO2-CaO-P2O5 frameworks are incorporated as the parent glass creations. Run of the mill uses of mesoporous BGs doped with antibacterial particles incorporate bone tissue recovery, multifunctional earthenware coatings for orthopedic gadgets and orbital inserts, scaffolds with upgraded angiogenesis potential, osteostimulation and antibacterial properties for the treatment of various bone imperfections and also in wound recuperating.
Problems of Land Reclamation and Heat Protection of Biological Objects against Contamination by the Aviation and Rocket Launch Site

Hydrazine and its derivatives belong to the class of highly toxic compounds that cause the acute and chronic forms of intoxication with a predominant lesion of liver, blood system, as well as other human organs. At the same time, these products are absorbed by the ashen-gray and gray forest soils under the cation-exchange mechanism; however, the hydrazine fuels and their derivatives in moderate doses are not toxic to microorganisms and plants, and they can use the carbon and nitrogen contained in them as the sources of nutrition; herewith, high content of the products of transformation of aerospace fuel in the ashen-gray and gray forest soils is toxic to plants. To improve the biological properties of gray forest loamy soil contaminated with aerospace fuel, the sodium selenate is usually used in moderate doses that improve its enzymatic and nitrification activity, but it will not completely remove all the negative effects of pollution. As a result of exposure to hydrazine, it is necessary to develop an effective protection of biological objects and soil against the toxic effects of its highly toxic compounds.