Miracle-dz/UniFAR-FTUs huggingface dataset:
Patients' Perceptions of Chronic Pain During the Economic Crisis: Lessons Learned from Greece.

BACKGROUND Chronic pain is well known to be influenced by various social factors; however, the impact of financial issues on pain has not been extensively studied. OBJECTIVE The aim of this study was to investigate the impact of the economic crisis on pain and quality of life in Greek patients suffering from chronic pain. STUDY DESIGN The study employed a prospective, open-label design. SETTING The study setting was the Pain Unit of Attikon University Hospital in Athens, Greece. METHODS The study surveyed 200 randomly selected outpatients with chronic pain during two different time periods (2012 and 2016). Patients completed a structured questionnaire to assess the impact of the economic crisis on multiple aspects of pain and pain management, health care, and quality of life. Personality characteristics and stress were also evaluated using the DASS-42 and the LOT-R questionnaires. RESULTS Most patients in both periods believed that the economic crisis led to a worsening of their symptoms (75%) and quality of life (97%). Most patients (97.5%) also believed that the intensity of their pain would have been improved if their financial status had been better. Their main concerns about the future were "the possibility of not having access to health care facilities and medication" (94.5%), "stress" (43%), and "fear of financial strain" (30.5%). Higher levels of anxiety, stress, and pessimism were associated with higher levels of pain and lower quality of life. LIMITATIONS The study is based on a small sample size. CONCLUSIONS This study identified impacts of the financial crisis on chronic pain and quality of life, pointing to the need for measures to solve this problem. KEY WORDS Pain, global financial crisis, quality of life, quality of health care, psychosocial factors.
Submodular Optimization in the MapReduce Model

Submodular optimization has received significant attention in both practice and theory, as a wide array of problems in machine learning, auction theory, and combinatorial optimization have submodular structure. In practice, these problems often involve large amounts of data, and must be solved in a distributed way. One popular framework for running such distributed algorithms is MapReduce. In this paper, we present two simple algorithms for cardinality constrained submodular optimization in the MapReduce model: the first is a $(1/2-o(1))$-approximation in 2 MapReduce rounds, and the second is a $(1-1/e-\epsilon)$-approximation in $\frac{1+o(1)}{\epsilon}$ MapReduce rounds.
Low cost magnetic simulator for attitude control

The aim of this paper is to propose an aerospace project, in order to allow Master’s Space students to put in practice their knowledge in physics, which can be crucial in this engineering area. Here, we face the attitude control issue of a cubesat, using a physical 1U satellite model and a magnetic field simulator, combined with real data from a desired orbit. The satellite model will use magnetorquers controlled by an Arduino board, in the same way as the magnetic simulator.
Caching and Placement for In-Network Caching in Device-to-Device Communications

Caching content by users constitutes a promising solution to decrease the costly transmissions with going through the base stations (BSs). To improve the performance of in-network caching in device-to-device (D2D) communications, caching placement and content delivery should be jointly optimized. To this end, we jointly optimize caching decision and content discovery strategies by considering the successful content delivery in D2D links for maximizing the in-network caching gain through D2D communications. Moreover, an in-network caching placement problem is formulated as an integer nonlinear optimization problem. To obtain the optimal solution for the proposed problem, Lagrange dual decomposition is applied in order to reduce the complexity. Simulation results show that the proposed algorithm has a near-optimal performance, approaching that of the exhaustive search method. Furthermore, the proposed scheme has a notable in-network caching gain and an improvement in traffic offloading compared to that of other caching placement schemes.
Ageing with a silver‐spoon: A meta‐analysis of the effect of developmental environment on senescence

What determines variation between individuals in how they senesce, and are environmental conditions experienced during development relevant to late‐life performance? We report a meta‐analysis of studies of wild populations to determine how the quality of the environment experienced during development affects rates of survival and reproductive senescence. From studies of 14 bird or mammal species, we calculated effect sizes for the interaction between the effects of environmental quality during development and age in predicting survival (N = 18) or reproduction (N = 30) over time in late life. We found no evidence that developmental environment affected rates of survival senescence (βmean = –1.2 × 10−4 ± 0.022SE). However, a better developmental environment was associated with slower rates of reproductive senescence in late life (βmean = 0.062 ± 0.023SE), indicating a small, but significant, “silver‐spoon” effect of early‐life conditions that persisted through to late life. Our results illustrate how the effects of environmental conditions during development can persist throughout life, and indicate one possible cause of phenotypic plasticity in senescence.
Photoluminescence Properties of Layered Perovskite-Type Strontium Scandium Oxyfluoride Activated With Mn4+

In this research, we have found that layered perovskite titanate Sr2TiO4 doped with Mn4+ exhibits photoluminescence even at room temperature despite no luminescence from Mn4+-doped SrTiO3 with a three-dimensional bulky perovskite structure. The relative position of t2g orbital of Mn to the valence band is a key factor for appearance of Mn4+-emission in Sr2TiO4:Mn. This result suggested usefulness of layered perovskite-type materials as hosts for Mn4+-activated phosphors than the bulky perovskite-type materials. Our investigation into photoluminescence of Mn4+-doped layered perovskite compounds has revealed that strontium scandium oxyfluoride Sr2ScO3F activated with Mn4+ exhibits Mn4+-emission with a peak at 697 nm under excitation at 300–600 nm and its emission intensity is much stronger than that of Sr2TiO4:Mn. The internal and external quantum yields of Sr2ScO3F:Mn were determined to be 50.5 and 43.5% under excitation at 345 nm, respectively.
Genetic Analysis of Chinese Cabbage Reveals Correlation Between Rosette Leaf and Leafy Head Variation

To understand the genetic regulation of the domestication trait leafy-head formation of Chinese cabbages, we exploit the diversity within Brassica rapa. To improve our understanding of the relationship between variation in rosette-leaves and leafy heads, we phenotyped a diversity set of 152 Chinese cabbages. This showed correlation between rosette-leaf traits and both head traits and heading capacity. Interestingly, the leaf number of the mature head is not correlated to heading degree nor head shape. We then chose a non-heading pak choi genotype to cross to a Chinese cabbage to generate populations segregating for the leafy head traits. Both a large F2 (485 plants) and a smaller Doubled Haploid (88 lines) mapping population were generated. A high density DH-88 genetic map using the Brassica SNP array and an F2 map with a subset of these SNPs and InDel markers was used for quantitative trait locus (QTL) analysis. Thirty-one quantitative trait loci (QTLs) were identified for phenotypes of rosette-leaves in time and both heading degree and several heading traits. On chromosome A06 in both DH-88 and F2-485 QTLs for rosette leaf length and petiole length at different developmental days and an F2 QTL for head height co-located. Variation in head height, width and weight all correlate with variation in heading degree with co-locating QTLs, respectively, on chromosome A03, A05, and A08 in F2-485. The correlation between rosette-leaf and heading traits provides not only insight in the leaf requirements to form a head, but also can be used for selection by Chinese cabbage breeders.
Image Processing Mobile Application For Banana Ripeness Evaluation

Mobile application has been identified as the best platform for the expert system tool to reach as many users as possible. The main contribution of this paper is the development of an expert system tool for evaluating the ripeness of banana fruit. Utilizing Google Cloud Platform, the application sends the sample of banana image through Google Cloud Vision Application Programming Interface to get attribute readings from the sample image. The result of the analysis is compared with application's database of attributes datasets to determine the ripeness of the banana sample image. In this work, the ripeness of the banana is classified into three different class of maturity; unripe, ripe and overripe systematically based on their key attributes value. This work also involved the process of collecting samples of banana with different level of ripeness, application development and evaluation to improve the accuracy of the developed applications classification results using image processing and data mining techniques.
Evaluating Training Time of Inception-v3 and Resnet-50,101 Models using TensorFlow across CPU and GPU

The performance of Deep Learning models has been the region of interest for a number of researchers over the past five years. Accuracy and Speed have invariably been the indicators in this regard. With the foray of GPUs into this field it becomes necessary to evaluate the performance of the same, keeping CPUs too in the perspective. In this work we present a brief comparison of the training times of a couple of architectures across multiple hardware platforms.
Patient-Specific Computational Simulations of Hyperpolarized $^3$He MRI Ventilation Defects in Healthy and Asthmatic Subjects

Combined, medical imaging data and respiratory computer simulations may facilitate novel insight into pulmonary disease phenotypes, including the structure/function relationships within the airways. This integration may ultimately enable improved classification and treatment of asthma. Severe asthma (15<inline-formula><tex-math notation="LaTeX">${\%}$</tex-math></inline-formula> of asthmatics) is particularly challenging to treat, as these patients do not respond well to inhaled therapeutics. <italic>Methods:</italic> This study combines medical image data with patient-specific computational models to predict gas distributions and airway mechanics in healthy and asthmatic subjects. We achieve this by integrating segmental volume defect percent (SVDP), measured from hyperpolarized <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula>He MRI and computed tomography images, to create models of patient-specific gas flow within the conducting airways. Predicted and measured SVDP distributions are achieved when the prescribed resistances are increased systematically. <italic>Results:</italic> Because of differences in airway morphology and regional function, airway resistances and flow structures varied between the asthmatic subjects. Specifically, while mean SVDP was similar between the severe asthmatics (4.30 <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 5.22 versus 3.54 <inline-formula><tex-math notation="LaTeX">$\pm \text{ 5.98}\%$</tex-math></inline-formula>), one subject exhibited abnormal flow structures, high near wall flow gradients, and enhanced conducting airway resistances (17.3E-3 versus 1.1E-3 cmH<inline-formula><tex-math notation="LaTeX">$_2$</tex-math></inline-formula>O-s/mL) in comparison to the other severe asthmatic subject. <italic>Conclusion:</italic> By coupling medical imaging data with computer simulations, we provide detailed insight into pathological flow characteristics and airway mechanics in asthmatics, beyond what could be inferred independently.
Evaluation of Image Processing Techniques on a Single Chip Digital Signal Processor

Ahstract- The importance of embedded applications in image and video processing have been taking a large space in current research scenario. Image processing techniques like Histogram equalization, Filtering, Bit plane slicing, Sampling, Quantization, Edge detection, Contrast stretching, Thresholding, Gray scale conversion etc. are the basic building blocks in several fields such as satellite imaging, medical imaging, face recognition, video surveillance etc. The present paper aims at mathematical analysis of these basic building blocks and further examines their implementation on a floating point Digital Signal Processor (DSP) TMS320F28335. It also verifies the reliability of the implemented techniques using a performance parameter. The processed images have been displayed using Python for various image processing techniques to verify the theory.
Backstepping Controller for a Variable Wind Speed Energy Conversion System Based on a DFIG

In this paper we present a contribution for the modeling and control of wind energy conversion system based on a Doubly Fed Induction Generator (DFIG). Since the wind speed is random the system has to produce an optimal electrical power to the Network and ensures important strength and stability. In this work, the Backstepping controller is used to control the generator via two converter witch placed a DC bus capacitor and connected to the grid by a Filter R-L, in order to optimize capture wind energy. All is simulated and presented under Matlab/Simulink Software to show performance and robustness of the proposed controller.
Identifying bacterial biotope entities using sequence labeling: Performance and feature analysis

Habitat information is important to biodiversity conservation and research. Extracting bacterial biotope entities from scientific publications is important to large scale study of the relationships between bacteria and their living environments. To facilitate the further development of robust habitat text mining systems for biodiversity, following the BioNLP task framework, three sequence labeling techniques, CRFs (Conditional Random Fields), MEMM (Maximum Entropy Markov Model) and SVMhmm (Support Vector Machine) and one classifier, SVMmulticlass, are compared on their performance in identifying three types of bacterial biotope entities: bacteria, habitats and geographical locations. The effectiveness of a variety of basic word formation features, syntactic features, and semantic features are exploited and compared for the three sequence labeling methods. Experiments on two publicly available BioNLP collections show that, in addition to a WordNet feature, word embedding featured clusters (although not trained with the task‐specific corpus) consistently improve the performance for all methods on all entity types in both collections. Other features produce various results. Our results also show that when trained on limited corpora, Brown clusters resulted in better performance than word embedding clusters did. Further analysis suggests that the entity recognition performance can be greatly boosted through improving the accuracy of entity boundary identification.
Virtual Reality Analgesia for Burn Joint Flexibility: A Randomized Controlled Trial

Objective: We conducted a randomized controlled study to determine the effects of virtual reality (VR) distraction on pain and range of motion (ROM) in patients hospitalized for burn care during active physical therapy exercises. Method: Thirty-nine participants aged 15 to 66 (M = 36) years with significant burn injuries (mean burn size = 14% TBSA) participated. Under therapist supervision, using a within-subjects design, participants performed unassisted active ROM exercises both with and without VR distraction in a randomized order. Therapists provided participants with instructions but did not physically assist with stretches. Maximum active ROM was measured using a goniometer. A 0–100 Graphic Rating Scale (GRS) was used to assess the cognitive, affective, and sensory components of pain. A GRS rating of the amount of “fun” during stretching served as a measure of positive experience. Results: Participants reported lower mean GRS ratings during VR, relative to No VR, for worst pain, pain unpleasantness, and time spent thinking about pain. They also reported having a more positive experience during VR than during No VR. However, patients did not show greater ROM during VR. Conclusion: Immersive VR reduced pain during ROM exercises that were under the control of the patient.
Choices for long-term hypertensive control in patients after first-ever hemorrhagic stroke: a nationwide cohort study

Background: To compare the long-term clinical outcomes of different antihypertensive drugs in stable patients after acute hemorrhagic stroke (HS). Methods: From January 2001 to December 2013, patients with first-ever primary HS were identified in the National Health Insurance Research Database, Taiwan. Patients with traumatic intracerebral hemorrhage and secondary HS were excluded. Those with first-ever HS were recruited and classified into three groups: (1) angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB); (2) calcium channel blocker (CCB); and (3) other antihypertensive drugs (comparison) groups. Propensity score matching was used to balance the distribution of baseline characteristics, stroke severity, and medications between any two of the three groups. A validation study was performed using the databank of the Stroke Registry in Chang-Gung Healthcare System to reduce the bias. Primary outcomes were recurrent HS, ischemic stroke, any stroke, and all-cause mortality. Results: Compared to the comparison group, the ACEI/ARB group [35.4% versus 39.3%; hazard ratio (HR), 0.84; 95% confidence interval (CI), 0.74–0.95] and CCB group (33.0% versus 41.9%; HR, 0.72; 95% CI, 0.64–0.81) had a lower risk of all-cause mortality during long-term follow up. The CCB group had a similar risk of all-cause mortality to the ACEI/ARB group. Risks of recurrent HS, ischemic stroke, or any stroke were not different between the study groups. Conclusions: Antihypertensive drug class could be important to long-term outcomes in HS patients in addition to the target control of blood pressure. Both ACEIs/ARBs and CCBs are associated with lower risks of all-cause mortality. Our results may be applied to inform future research on hypertensive control in HS patients.
TOSS: Traffic-aware distributed object-based storage using software-defined networks

As storage systems grow to Petascale, the demand for object storage increases. In a large scale heterogeneous object storage systems, efficient selection of storage targets for placing objects is critically important since the performance depends on even distribution of objects across storage targets. An efficient storage target selection for object placement depends not only on available storage target capacity but also network bandwidth. The storage target selection based either only on the available storage capacity or only on the available network bandwidth may not result in the optimal usage of storage/network resources to achieve the performance. The object placement under heterogeneous environment considering load balancing is a challenging problem. There is a need to orchestrate the network and storage resources with efficient object to storage mapping. In this paper, we present an efficient and scalable object placement strategy using software-defined networking (SDN) technique. We demonstrate the effectiveness of our method through simulation results and compare with Distributed Hash Table (DHT) method.
The Number of Meiotic Double-Strand Breaks Influences Crossover Distribution in Arabidopsis[OPEN]

Analysis of a spo11-1 hypomorphic allele in Arabidopsis showed that reducing the number of meiotic DSBs resulted in a profound redistribution of meiotic crossovers on a genome-wide scale. Meiotic recombination generates genetic diversity and ensures proper chromosome segregation. Recombination is initiated by the programmed formation of double-strand breaks (DSBs) in chromosomal DNA by DNA Topoisomerase VI-A Subunit (SPO11), a topoisomerase-like enzyme. Repair of some DSBs leads to the formation of crossovers (COs). In most organisms, including plants, the number of DSBs greatly exceeds the number of COs and which DSBs become CO sites is tightly controlled. The CO landscape is affected by DNA sequence and epigenome features of chromosomes as well as by global mechanisms controlling recombination dynamics. The latter are poorly understood and their effects on CO distribution are not well elucidated. To study how recombination dynamics affects CO distribution, we engineered Arabidopsis thaliana plants to carry hypomorphic alleles of SPO11-1. Two independent transgenic lines showed ∼30% and 40% reductions in DSB numbers, which were commensurate with the dosage of the SPO11-1 transcript. The reduction in DSB number resulted in proportional, although smaller, reductions of the number of COs. Most interestingly, CO distribution along the chromosomes was dramatically altered, with substantially fewer COs forming in pericentromeric chromosome regions. These results indicate that SPO11 activity, and the resulting DSB numbers are major factors shaping the CO landscape.
Handover Schemes for Vehicular Ad-Hoc Networks Over Long Term Evolution Advanced: A Survey

Next generation Vehicular Ad Hoc Network (VANET) needs seamless connectivity with high level of quality of services (QoS) and high data rates services. The complexity of VANET raises concern about the QoS and the reliability of the communication handover which refer to the connectivity and operation of conveying an ongoing call or data session between Vehicles to Vehicles (V2V) and Vehicles to Infrastructure (V2I) in VANET communication mode. This communication faces a huge challenge. The vehicles are moving so fast and highly dynamic that may cause frequent handover which may cause signal delay and communication loss. This paper provides an up-to-date literature of handover schemes for VANET over LTE-A wireless network. A discussion on thumbnail of the key decision parameters to be used in the handover algorithm and comparative summary of selected scheme for VANET over LTE-A concludes this work. This study, thus contributes to the understanding of the available options and gaps for further studies and standardization activities to this area of research.
Modified Uncertainty and Disturbance Estimator for Enhanced Periodic Signals Suppression

This paper proposes a modified uncertainty and disturbance estimator (UDE) structure, aimed to improve the ability to approximate and eliminate signals characterized by periodic behavior. The algorithm combines delay action with low-pass filtering, introducing high loop gain magnitude values at multiple frequencies of interest while retaining implementation feasibility by imposing finite crossover frequency, similarly to repetitive control. For a given control bandwidth, the modified UDE is shown to outperform the classical one in terms of disturbance rejection at the expense of slight phase margin loss. Simulations and experiments are given to support the feasibility of the proposed control structure, applying the revealed modification to the current control of an LCL inverter, connected to a distorted ac grid.