Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of Reduced and Oxidized Coenzyme Q10 in Canine Plasma and Heart Tissue by HPLC-ECD: Comparison with LC-MS/MS Quantification

Coenzyme Q10 (Q10) plays an important role in mammals for energy production in the mitochondria, and as a potent antioxidant. Oxidation ratio (% oxidized in relation to total Q10) has been proposed as an important biomarker. A sensitive and reproducible HPLC-ECD method was developed for determination of reduced and oxidized Q10 in canine plasma and heart tissue. Chromatographic separation was achieved in 10 min using a Waters Nova-pak C18 column and a mobile phase with lithium perchlorate in ethanol/methanol/2-propanol. The validation showed satisfying results. Excellent linear correlation was found (r2 > 0.9997), intra- and inter-day precisions were below 6.5% (n = 5) and recoveries were between 89 and 109% (n = 5). Sensitivity stated as Lower Limit of Quantification (LLOQ) was 10 nM. Acceptable stability of both extracted and un-extracted samples was observed. The plasma concentration range of total Q10 was found to be between 0.64 and 1.24 µg/mL. Comparison with a developed LC-MS/MS method showed a correlation of r = 0.85 for reduced Q10 and r = 0.60 for oxidized Q10 (N = 17). However, average results were around 30% lower for ubiquinol using the LC-MS/MS method as compared with the HPLC-ECD analysis. The two methods are therefore not considered to be interchangeable.
Text reading speed in a language with a shallow orthography benefits less from comprehension as reading ability matures.

BACKGROUND Reading can be assessed using different materials, including non-words and texts. Unlike reading words or non-words, reading a text may be supported by reading comprehension, and the extent of this support could change with the amount of schooling. AIM The present study aimed to examine how reading decoding in a shallow orthography like Italian changed with years of schooling, depending on the type of material and the contribution of non-word reading and reading comprehension to text reading speed. METHODS Six hundred and forty two typically developing Italian students from 8 to 16 years old were involved. They were administered grade-appropriate tasks assessing text reading speed, non-word reading speed, and reading comprehension. RESULTS The results showed that, although the two reading speed measures correlated closely, non-word reading speed improved only slightly with age, while the increase in text reading speed was steeper. Reading comprehension was a significant direct predictor of text reading speed after controlling for non-word reading speed. Importantly, however, while the difference in reading speed between non-words and text widened with schooling, the role of reading comprehension declined significantly, the ΔR2 dropping from . 10 in primary school to just . 01 in high school. CONCLUSIONS These findings and their implications are discussed in the light of the relationship between reading comprehension and reading speed in a language with a shallow orthography across school grades.
The diagnosis of sarcoidosis.

PURPOSE OF REVIEW To review the diagnostic approach to sarcoidosis. There is no gold standard diagnostic test, procedure or algorithm for sarcoidosis. The diagnosis is based on a compatible clinical presentation, histologic findings of granulomatous inflammation, exclusion of alternative diseases, and evidence of systemic involvement. Occasionally, there may be exceptions to several of these requirements. RECENT FINDINGS The diagnostic specificity of several specific clinical features are discussed. Typical histologic findings of sarcoidosis are described. Several diseases that may mimic sarcoidosis are reviewed. SUMMARY The diagnosis of sarcoidosis usually involves weighing the clinical evidence for and against the diagnosis, coupled in most cases with histologic evidence of granulomatous inflammation. This approach requires knowledge of the varied presentations of the disease and other alternative conditions as well as histologic examination of an affected tissue in most instances.
Combined Brain/Heart Magnetic Resonance Imaging in Systemic Lupus Erythematosus

Cardiovascular Disease (CVD) in Systemic Lupus Erythematosus (SLE) and Neuropsychiatric SLE (NPSLE) has an estimated prevalence of 50% and 40%, respectively and both constitute major causes of death among SLE patients. In this review, a combined brain/heart Magnetic Resonance Imaging (MRI) for SLE risk stratification has been proposed. The pathophysiologic background of NPSLE includes microangiopathy, macroscopic infarcts and accelerated atherosclerosis. Classic brain MRI findings demonstrate lesions suggestive of NPSLE in 50% of the NPSLE cases, while advanced MRI indices can detect pre-clinical lesions in the majority of them, but their clinical impact still remains unknown. Cardiac involvement in SLE includes myo-pericarditis, valvular disease/endocarditis, Heart Failure (HF), coronary macro-micro-vascular disease, vasculitis and pulmonary hypertension. Classic and advanced Cardiovascular Magnetic Resonance (CMR) indices allow function and tissue characterization for early diagnosis and treatment follow-up of CVD in SLE. Although currently, there are no clinical data supporting the combined use of brain/heart MRI in asymptomatic SLE, it may have a place in cases with clinical suspicion of brain/heart involvement, especially in patients at high risk for CVD/stroke such as SLE with antiphospholipid syndrome (SLE/APS), in whom concurrent cardiac and brain lesions have been identified. Furthermore, it may be of value in SLE with multi-organ involvement, NPSLE with concurrent cardiac involvement, and recent onset of arrhythmia and/or heart failure.
Radionuclide therapy: current status and prospects for internal dosimetry in individualized therapeutic planning

The efficacy and toxicity of radionuclide therapy are believed to be directly related to the radiation doses received by target tissues; however, nuclear medicine therapy continues to be based primarily on the administration of empirical activities to patients and less frequently on the use of internal dosimetry for individual therapeutic planning. This review aimed to critically describe the techniques and clinical evidence of dosimetry as a tool for therapeutic planning and the main limitations to its implementation in clinical practice. The present article is a nonsystematic review of voxel-based dosimetry. Clinical evidence pointing to a correlation between the radiation dose and therapeutic response in various diseases, such as thyroid carcinoma, neuroendocrine tumors and prostate cancer, is reviewed. Its limitations include technical aspects related to image acquisition and processing and the lack of randomized clinical trials demonstrating the impact of dosimetry on patient therapy. A more widespread use of dosimetry in therapeutic planning involves the development of user-friendly dosimetric protocols and confirmation that dose estimation implies good efficacy and low treatment-related toxicity.
Patient Understanding of “Flare” and “Remission” of Inflammatory Bowel Disease

Supplemental Digital Content is Available in the Text. Patients with inflammatory bowel disease have adopted medical jargon terms of “flare” and “remission,” but what they mean by these terms is ill-defined and may have implications for nurse–patient communication and treatment expectancy. The aim of this study was to elicit patients' understanding of “flare” and “remission. ” Individuals with self-reported inflammatory bowel disease were recruited through social media. A web-based survey, with closed and open-ended questions, was administered. Conventional content analysis was used to evaluate respondents' perceptions of jargon terms. A word cloud was generated to augment analysis by visualization of word use frequency. A majority of the 34 respondents had a symptom-focused understanding and described these terms as alternating states. Various symptoms were understood to signify “flare,” which was largely attributed to lifestyle factors. Corroborated by the word cloud, there was rare mention of inflammation or tissue damage. This study demonstrates that an understanding of “flare” and “remission” by patients with inflammatory bowel disease is largely symptom-based. The role of inflammation, medication failure, and targets of inflammatory bowel disease treatment beyond symptom control are not currently well known to patients with inflammatory bowel disease. To create a shared understanding of symptoms and treatment goals between the patient and the nurse, patient education on emerging expectations of inflammatory bowel disease care should be prioritized.
Quasi-Static Rheological Properties of Lithium-Based Magnetorheological Grease under Large Deformation

This paper investigates the quasi-static rheological properties of lithium-based magnetorheological (MR) grease under large deformation. Three types of lithium-based MR grease comprising different mass ratios of carbonyl iron (CI) particles and lithium-based grease were prepared. The dependence of the magneto-induced stress–strain curves for MR grease on CI particles content, shear rate, and shear deformation under quasi-static monotonic shear conditions were tested and discussed. The results demonstrate that the shear rate dependence of the maximum yield stress is significantly weakened by the magnetic field, and this weakening is further enhanced as the CI particles content of MR grease increases. In addition, to evaluate and characterize the behavior of the cyclic shear–stress curves of MR grease under quasi-static condition, cyclic shear tests under different controlled conditions, i.e., CI particles content, shear rate, shear strain amplitude, and magnetic field strength, were conduct and analyzed. The magneto-induced shear stress of MR grease with higher CI particles content shows a sharp decrease during the transition from loading to unloading. Moreover, the experiment results also show that the damping characteristics of MR grease are highly correlated with CI particles content, shear strain, and magnetic field strength.
SDN-Assisted IoT Architecture: A Review

Nowadays, Internet of Things (IoT) has become a trending technology with its various applications in different fields. It contains heterogeneous amount of devices connected to Internet and to each other. As the nature of IoT network is that it has low resources to consume less energy as well as to be more portable, it is difficult to control those amount of devices. Software Defined Network (SDN) is a new network paradigm which makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. This paper provides a survey of both technologies IoT and SDN with an overview of their architectures. The core of this paper is to review the IoT architectures based on SDN which have been proposed by different researchers.
A hybrid trilateration and fingerprinting approach for indoor localization based on wifi

Indoor localization based on WiFi is growing at a fast pace. Among different indoor localization techniques based on WiFi, the fingerprint based indoor localization systems, gained more attention recently. Despite its simplicity, still it needs ample amount of work to build fingerprint database in calibration phase. Furthermore, in online localization phase, for finding a match between observed signal vector and entire fingerprint collection is not feasible. The goal is to minimize both calibration and searching effort in online stage. This paper presents kernel online sequential extreme learning machine (KOS-ELM) based approach to lessen the site survey effort for radio map construction. Furthermore, a hybrid Wireless LAN(WLAN) based approach for online localization phase is presented. Proposed solution incorporate both trilateration and fingerprinting algorithms in localization phase to further improve the localization accuracy. At first, the radio signatures have been collected at few positions from the environment in a usual manner after that based on collected data, the KOS-ELM algorithm has been trained. Later, the trained KOS-ELM was able to successfully predict radio signatures at other unknown coordinates of the environment. In localization stage first, trilateration finds a location based on path loss model, afterward, that location will be fed into K-Nearest Neighbor(KNN) which will search for fingerprint matching within two meter radius of location returned by trilateration algorithm.
A Widely Tunable Compact Bandpass Filter Based on a Switched Varactor-Tuned Resonator

This paper presents a compact tunable bandpass filter (BPF) based on a switched varactor tuned resonator with a wide frequency-tuning range and a constant absolute bandwidth (ABW). The proposed switched varactors are adopted to overcome the limited tunability of varactor diodes by switching the stubs. The pass-band can be easily tuned by controlling two resonant frequencies of each state. After the separation of the two resonant frequencies, the ABW of the filter is maintained constant by tuning the external coupling of the tapped-line input and output matching capacitors. To verify the proposed structure, a two-pole tunable BPF has been fabricated and measured. It exhibits a low in-band insertion loss of 1.4−2.9 dB, maintaining a constant 3-dB ABW of 75 MHz with a large tuning range from 255 to 725 MHz (1:2.85). The proposed two-pole filter shares the resonator for the low- and high-band states, and therefore the overall size is only $0.2\lambda _{g} \times 0.14\lambda _{g}$ . In addition, this two-pole tunable filter is extended to a four-pole tunable one as an estimation of the measured results by using the simulated results. They have the wide frequency tuning ratios of 2.85 and 2.92, with the low insertion losses, respectively.
Locating Usability Critical Factors for Mobile Applications Using ELECTRE-TRI Method

The development of qualitative software has been considered as an important aspect of software engineering. With the increased demand of Mobile applications users, the quality of the mobile applications becomes a major concern. The number of studies shows issues while the usability of mobile applications and proposed various methods for its evaluation. But none of the models proposed gives a holistic way for assessing the usability of mobile applications. For this, one needs to first identify the factors on which usability depends and then evaluate it. The paper, discuss the key concept of usability of mobile applications and proposes 11 usability critical factors for the measurement of usability. These factors are evaluated and prioritized based on ELECTRE-TRI outranking method, a Multi-Criteria Decision Analysis approach.
Two novel graph theory based algorithms for salient object detection

Salient object detection deals with location of the salient object in a given scene followed by segmentation. For efficient detection of salient object from the background, graph theory proved to be a very powerful tool. To improve the performance of the graph cut algorithm for salient object detection, two different models based on color channels have been proposed. Both of the models deals with the estimated features from each available color channels of a given scene. Both of the models also considered the neighbourhood information based on the estimated features from given color channels. To prove the superiority of the proposed models, different experiments are carried out on images taken from Berkley database and Corel database. The effectiveness of the proposed algorithms over Otsu and K-means clustering are successfully tested based on three validity indices.
A Review of Ambient Intelligence Based Activity Recognition for Ageing Citizens

There have been many emerging solutions to complement the lifestyle of the ever growing ageing population. One such technology is human activity recognition (HAR). Along with ageing, there is a potential cognitive impairment that happens with the elderly and this will eventually lead to a need for supervision. With the help of various sensors, many activities of the elderly can be detected and those data can be used as input for Internet of Things devices. These devices are programmed to perform certain tasks accordingly and sometimes even send emergency notifications to caretakers or the busy family members of the elderly. The current HAR is being refined to fit elderly’s lifestyle while, its most effective processes are still being studied. This study will review, activity recognition in ambient assisted living and similar environments such as smart homes. It also includes a review on current HAR for elderly and the effective placement of sensors. Lastly, this study also covers the challenges of implementing activity recognition.
Smart Lightning and Security System

As Electric Power is one of the major concerns, so the concept of the automatic lighting and security system saves the electrical energy. By using the automatic lightning, the consumption of electrical power can be minimized to a greater extent and for that sensors and microcontrollers can be designed in such a manner such that lights get ON/OFF based on motion in a room. The various sensors used for sensing the motion in an area are PIR motion sensor, IR Motion Sensor. An IR sensor senses the heat of an object and detects its motion within some range as it emits infrared radiations and this complete process can be controlled by microcontroller. Along with that security system can be applied in this concept by programming the microcontroller in such a way that if there is some movement in an area then lights must get ON/OFF automatically or any alarm must start. This chapter proposes the framework for the smart lightning with security systems in a building so that electrical power can be utilized efficiently and secures the building.
RNN-Based On-Line Continuous Gait Phase Estimation from Shank-Mounted IMUs to Control Ankle Exoskeletons

Several research groups have developed and studied powered ankle exoskeletons to improve energetics of healthy subjects and the mobility of elderly subjects, or to reduce asymmetry in gaits induced by strokes. To achieve optimal effect, the timing of assistive torque has been proved to be of crucial importance. Previous studies estimated the onset timings mostly by extrapolating the time horizon from past gait events observed with sensors. Such methods have inherently limited performance when subjects are not walking at steady frequencies. To overcome such limitation and allow the use of exoskeletons in various scenarios in a daily life, we propose to estimate the gait phase as a continuous variable progressing over a gait cycle, hence allowing immediate response to frequency changes rather than iteratively correcting it after each cycle. Our method uses recurrent neural networks to estimate gait phases out of an inertial measurement unit (IMU) every 10 ms. By replacing foot sensors with an IMU we can obtain rich enough information to estimate gait phase continuously as well as avoid physical damage in sensors from ground impacts. Our preliminary tests with 2 healthy subjects showed qualitatively positive outcomes regarding the gait phase estimation and the assistive torque control.
The Relationship between EEG and Depression under Induced Emotions Using VR Scenes

This study attempts to establish a relationship between EEG signals and depression under induced emotions using VR. The VR scenes were obtained from third party sources as a trigger. Due to the immersion and visualization of the whole environment, it makes this method different and in some case superior to the traditional music or video simulations. In this study, EEG signals of 463 participants were recorded as each watched two VR scenes chosen from our VR database with two 60s resting state before each scene. The results demonstrated that the power of alpha frequency band is related to depression and beta frequency band of high risking depression group is higher than the no depression group. The feedback will be future used in the next stage of machine learning of detecting depressive group.
A Short-Time Autocorrelation Method for Noncontact Detection of Heart Rate Variability Using CW Doppler Radar

Contactless detection of human heart rate variability using radars has been a promising area for healthcare and clinical practice. In this paper, a continuous-wave 2.45 GHz Doppler radar is used for wirelessly measuring heartbeat rate and inter-beat interval variation. Relying on the characteristics of an autocorrelation function, an algorithm for heart rate variability extraction using short-time autocorrelation is proposed. The autocorrelation algorithms achieves the high accurate estimation of heartbeat inter-interval variation, compared with the Electrocardiography (ECG).
A New Learning Scheme of Emotion Recognition From Speech by Using Mean Fourier Parameters

Recently, the research attention of emotional speech signals has been boosted in human machine interfaces due to the availability of high computation capability. Based on different feature extraction on audio data, it is possible to achieve good accuracy on speech emotion recognition, thus feature extraction plays an important role in speech emotion recognition. However, there are still dilemmas in speech emotion recognition, such as the heavy computation burden due to the high data dimension. In this paper, we propose a new learning scheme with mean Fourier parameters using the perceptual content of voice quality for speaker-independent speech emotion recognition. The dimension of the acoustic feature is greatly reduced and the computational performance is improved with big extent. Two speech databases (German emotional corpus, Interactive Emotional Dyadic Motion Capture) are used in the experiment, and the combination of different features with different classifiers are implemented in the recognition for performance comparison. The recognition results show that the proposed scheme with mean Fourier Parameters combined with the Random Forest classifier is efficient in classifying various emotional states in speech signals and is excellent than other features and classifiers.