Miracle-dz/UniFAR-FTUs huggingface dataset:
Model of Impedance Changes in Unmyelinated Nerve Fibers

Objective: Currently, there is no imaging method that is able to distinguish the functional activity inside nerves. Such a method would be essential for understanding peripheral nerve physiology and would allow precise neuromodulation of organs these nerves supply. Electrical impedance tomography (EIT) is a method that produces images of electrical impedance change (dZ) of an object by injecting alternating current and recording surface voltages. It has been shown to be able to image fast activity in the brain and large peripheral nerves. To image inside small autonomic nerves, mostly containing unmyelinated fibers, it is necessary to maximize SNR and optimize the EIT parameters. An accurate model of the nerve is required to identify these optimal parameters as well as to validate data obtained in the experiments. Methods: In this study, we developed two three-dimensional models of unmyelinated fibers: Hodgkin–Huxley (HH) squid giant axon (single and multiple) and mammalian C-nociceptor. A coupling feedback system was incorporated into the models to simulate direct and alternating current application and simultaneously record external field during action potential propagation. Results: Parameters of the developed models were varied to study their influence on the recorded impedance changes; the optimal parameters were identified. The negative dZ was found to monotonically decrease with frequency for both HH and C fiber models, in accordance with the experimental data. Conclusion and significance: The accurate realistic model of unmyelinated nerve allows the optimization of EIT parameters and matches literature and experimental results.
Growth and quality of Chinese journals from 1949 to 2013

In recent years, substantial investments in science and technology have led to an increase in Chinese academic journals. Previous investigations have used international indexes to track growth, but this article uses the China Academic Journal Network Publishing Database along with Web of Science and SCImago to avoid inclusion bias and analyse the complete landscape of Chinese academic journals (in all disciplines). This article investigated the rate of growth of new journals, the regional distribution of journals, and the quality of the journals (calculated domestically and internationally). Our results indicate that: (1) the average annual growth rate of Chinese academic journals has been 2.74%, but this might probably be affected by different periods of China’s economic and cultural development; (2) the number of journals published in Eastern China is higher than that in Central and Western China; (3) journal quality has improved somewhat in recent years; (4) 84.48% of journals demonstrate domestic impact factors below 1; and (5) China performs better than other developing countries when using the impact factor but equals them when using the SCImago Journal and Country Rank indicator.
Leader-Following Practical Cluster Synchronization for Networks of Generic Linear Systems: An Event-Based Approach

In network systems, a group of nodes may evolve into several subgroups and coordinate with each other in the same subgroup, i.e., reach cluster synchronization, to cope with the unanticipated situations. To this end, the leader-following practical cluster synchronization problem of networks of generic linear systems is studied in this paper. An event-based control algorithm that can largely reduce the amount of communication is first proposed over directed communication topologies. In the proposed algorithm, each node decides itself when to transmit its current state to its neighbors and how to update its controller according to the estimations of the states of it and its neighbors. Then, the Lyapunov method is utilized to perform the convergence analysis. It shows that the practical cluster synchronization can be ensured by choosing appropriate parameters no matter what kind of estimation for the state is applied. Furthermore, the Zeno behavior is also excluded for each node under some mild assumptions. Besides, three kinds of common estimations for the states including zero-order hold model, first-order approximate model, and high-order model-based estimations are, respectively, analyzed from the perspective of the exclusion of Zeno behavior. Finally, the validity of the proposed algorithm is demonstrated, the effects of the concerned parameters are simply presented, and the effects of the three estimations are also compared through several simulations.
Genetic Lineage Tracing of Sca-1+ Cells Reveals Endothelial but Not Myogenic Contribution to the Murine Heart

Background: The adult mammalian heart displays a cardiomyocyte turnover rate of ≈1%/y throughout postnatal life and after injuries such as myocardial infarction (MI), but the question of which cell types drive this low level of new cardiomyocyte formation remains contentious. Cardiac-resident stem cells marked by stem cell antigen-1 (Sca-1, gene name Ly6a) have been proposed as an important source of cardiomyocyte renewal. However, the in vivo contribution of endogenous Sca-1+ cells to the heart at baseline or after MI has not been investigated. Methods: Here we generated Ly6a gene–targeted mice containing either a constitutive or an inducible Cre recombinase to perform genetic lineage tracing of Sca-1+ cells in vivo. Results: We observed that the contribution of endogenous Sca-1+ cells to the cardiomyocyte population in the heart was <0.005% throughout all of cardiac development, with aging, or after MI. In contrast, Sca-1+ cells abundantly contributed to the cardiac vasculature in mice during physiological growth and in the post-MI heart during cardiac remodeling. Specifically, Sca-1 lineage-traced endothelial cells expanded postnatally in the mouse heart after birth and into adulthood. Moreover, pulse labeling of Sca-1+ cells with an inducible Ly6a-MerCreMer allele also revealed a preferential expansion of Sca-1 lineage-traced endothelial cells after MI injury in the mouse. Conclusions: Cardiac-resident Sca-1+ cells are not significant contributors to cardiomyocyte renewal in vivo. However, cardiac Sca-1+ cells represent a subset of vascular endothelial cells that expand postnatally with enhanced responsiveness to pathological stress in vivo.
Webquest and blog as educational strategies in school health

Objective: To describe health education strategy on healthy eating using WebQuest and blog with elementary school students from a public school. Method: To report the health education activity carried out in 2014 with fourteen students from the 8th year of public school. The “Healthy Food Blog” was developed by the students using the WebQuest methodology guided by the nurse during four periods of the science discipline. Results: In three work groups, the students performed the WebQuest made available on the website with the introduction, task, process and resource stages. The blog was written in a free website in response to WebQuest questions. The students’ evaluation highlighted the positives, difficulties and recommendations for future activities. Conclusion: This technology makes the search for knowledge participatory and active, besides being a space for integration of health professionals in the school environment.
A Novel Neural Networks Ensemble Approach for Modeling Electrochemical Cells

Accurate modeling of electrochemical cells is nowadays mandatory for achieving effective upgrades in the fields of energetic efficiency and sustainable mobility. Indeed, these models are often used for performing accurate State-of-Charge (SoC) estimations in energy storage systems used in microgrids or powering pure electric and hybrid cars. To this aim, a novel neural networks ensemble approach for modeling electrochemical cells is proposed in this paper. Herein, the system identification has been faced by means of a gray box technique, in which different and specialized neural networks are used for identifying the unknown internal behaviors of the cell. In particular, the a priori knowledge on the system dynamic is used for defining the network architecture. Specifically, each nonlinear function appearing in the system equations is approximated by a distinct neural network. The proposed model has been validated upon three different data sets both in terms of model accuracy and effectiveness in the SoC estimation task. The achieved performances have been compared with those of other computational intelligence approaches proposed in the literature. The results prove the effectiveness of the gray box scheme, achieving very promising performances in both the system identification accuracy and the SoC estimation task.
Marinobufagenin and left ventricular mass in young adults: The African-PREDICT study

Background The endogenous steroidal inhibitor of sodium–potassium-dependent adenosine triphosphate and natriuretic hormone, marinobufagenin, plays a physiological role in ionic homeostasis. Animal models suggest that elevated marinobufagenin adversely associates with cardiac and renal, structural and functional alterations. It remains uncertain whether marinobufagenin relates to the early stages of target organ damage development, especially in young adults without cardiovascular disease. We therefore explored whether elevated 24-hour urinary marinobufagenin excretion was related to indices of subclinical target organ damage in young healthy adults. Design This cross-sectional study included 711 participants from the African-PREDICT study (black 51%, men 42%, 24.8 ± 3.02 years). Methods We assessed cardiac geometry and function by two-dimensional echocardiography and pulse wave Doppler imaging. 24-Hour urinary marinobufagenin and sodium excretion were measured, and the estimated glomerular filtration rate determined. Results Across marinobufagenin excretion quartiles, left ventricular mass (P < 0.001), end diastolic volume (P < 0.001), stroke volume (P = 0.004) and sodium excretion (P < 0.001) were higher within the fourth compared with the first quartile. Partial regression analyses indicated that left ventricular mass (r = 0.08, P = 0.043), end diastolic volume (r = 0.10, P = 0.010) and stroke volume (r = 0.09, P = 0.022) were positively related to marinobufagenin excretion. In multivariate-adjusted regression analysis, left ventricular mass associated positively with marinobufagenin excretion only in the highest marinobufagenin excretion quartile (adjusted R2 = 0.20; β = 0.15; P = 0.043). This relationship between left ventricular mass and marinobufagenin excretion was evident in women (adjusted R2 = 0.06; β = 0.127; P = 0.015) but not in men (adjusted R2 = 0.06; β = 0.007; P = 0.92). Conclusions Left ventricular mass positively and independently associates with marinobufagenin excretion in young healthy adults with excessively high marinobufagenin excretion. Women may be more sensitive to the effects of marinobufagenin on early structural cardiac changes.
Competition: BigBangBus

A wireless bus based on flooding and the capture effect is proposed to achieve highly reliable broadcast communication in a Wireless Sensor Network (WSN) working in harsh environments in a multi-source-to-multi-sink topology where multiple hops are required (Fig. 1). Different sources access the medium without colliding using network-wide predefined time slots and frequency channels. Frequency-, spatial- and time-diversity is exploited using redundant retransmissions.
Spectral Tuning of White Light Allows for Strong Reduction in Melatonin Suppression without Changing Illumination Level or Color Temperature

Studies with monochromatic light stimuli have shown that the action spectrum for melatonin suppression exhibits its highest sensitivity at short wavelengths, around 460 to 480 nm. Other studies have demonstrated that filtering out the short wavelengths from white light reduces melatonin suppression. However, this filtering of short wavelengths was generally confounded with reduced light intensity and/or changes in color temperature. Moreover, it changed the appearance from white light to yellow/orange, rendering it unusable for many practical applications. Here, we show that selectively tuning a polychromatic white light spectrum, compensating for the reduction in spectral power between 450 and 500 nm by enhancing power at even shorter wavelengths, can produce greatly different effects on melatonin production, without changes in illuminance or color temperature. On different evenings, 15 participants were exposed to 3 h of white light with either low or high power between 450 and 500 nm, and the effects on salivary melatonin levels and alertness were compared with those during a dim light baseline. Exposure to the spectrum with low power between 450 and 500 nm, but high power at even shorter wavelengths, did not suppress melatonin compared with dim light, despite a large difference in illuminance (175 vs. <5 lux). In contrast, exposure to the spectrum with high power between 450 and 500 nm (also 175 lux) resulted in almost 50% melatonin suppression. For alertness, no significant differences between the 3 conditions were observed. These results open up new opportunities for lighting applications that allow for the use of electrical lighting without disturbance of melatonin production.
Generative Kernels for Tree-Structured Data

This paper presents a family of methods for the design of adaptive kernels for tree-structured data that exploits the summarization properties of hidden states of hidden Markov models for trees. We introduce a compact and discriminative feature space based on the concept of hidden states multisets and we discuss different approaches to estimate such hidden state encoding. We show how it can be used to build an efficient and general tree kernel based on Jaccard similarity. Furthermore, we derive an unsupervised convolutional generative kernel using a topology induced on the Markov states by a tree topographic mapping. This paper provides an extensive empirical assessment on a variety of structured data learning tasks, comparing the predictive accuracy and computational efficiency of state-of-the-art generative, adaptive, and syntactical tree kernels. The results show that the proposed generative approach has a good tradeoff between computational complexity and predictive performance, in particular when considering the soft matching introduced by the topographic mapping.
Automated Detection of Convulsive Seizures Using a Wearable Accelerometer Device

Epileptic seizure detection requires specialized approaches such as video/electroencephalography monitoring. However, these approaches are restricted mainly to hospital setting and requires video/EEG analysis by experts, which makes these approaches resource- and labor-intensive. In contrast, we aim to develop a wireless remote monitoring system based on a single wrist-worn accelerometer device, which is sensitive to multiple types of convulsive seizures and is capable of detecting seizures with short duration. Simple time domain features including a new set of Poincaré plot based features were extracted from the active movement events recorded using a wrist-worn accelerometer device. The best features were then selected using the area under the ROC curve analysis. Kernelized support vector data description was then used to classify nonseizure and seizure events. The proposed algorithm was evaluated on <inline-formula><tex-math notation="LaTeX">$\text{5576}\;\text{h}$</tex-math></inline-formula> of recordings from 79 patients and detected 40 (<inline-formula><tex-math notation="LaTeX">$\text{86.95}\%$</tex-math></inline-formula>) of 46 convulsive seizures (generalized tonic-clonic (GTCS), psychogenic nonepileptic, and complex partial seizures) from 20 patients with a total of 270 false alarms (<inline-formula><tex-math notation="LaTeX">$\text{1.16/24}\;\text{h}$</tex-math></inline-formula>). Furthermore, the algorithm showed a comparable performance (sensitivity <inline-formula><tex-math notation="LaTeX">$\text{95.23}\%$</tex-math></inline-formula> and false alarm rate <inline-formula><tex-math notation="LaTeX">$\text{0.64/24}\;\text{h}$</tex-math></inline-formula>) with respect to existing unimodal and multimodal methods for GTCS detection. The promising results shows the potential to build an ambulatory monitoring convulsive seizure detection system. A wearable accelerometer based seizure detection system would aid in continuous assessment of convulsive seizures in a timely and non-invasive manner.
A Multiobjective Evolutionary Algorithm Based on Coordinate Transformation

In this paper, a novel multiobjective evolutionary algorithm (MOEA/CT) is proposed to better manage convergence and distribution of solutions when MOEAs are used for solving multiobjective optimization problems. The coordinate transformation strategy, an external archive update strategy, and a diversity maintenance strategy are proposed in MOEA/CT. The coordinate transformation strategy in the objective space is designed to find more efficient solutions that can accelerate the convergence process. Based on the coordinate transformation strategy, a novel update strategy and diversity maintenance approach for selecting nondominated solutions from the external archive set are integrated in MOEA/CT for getting better distribution of the solutions. The proposed MOEA/CT is compared with eight state-of-art algorithms on six biobjective and seven tri-objective test problems. In terms of four performance metrics, the comparative experimental results demonstrate that MOEA/CT outperforms the other eight competitors and it can achieve solutions with better distribution and better convergence to the Pareto front. In addition, parameter sensitivity analysis is provided to investigate the effect of a key parameter in MOEA/CT; the proposed three strategies are also studied individually to investigate their contribution to MOEA/CT; the performance analysis along with the capacity of external archive is given to clearly make the influence in MOEA/CT; finally, the scalability performance of MOEA/CT is investigated and compared with five notable many-objective evolutionary algorithms on the DTLZ and WFG test suites with 5, 8, 10, and 15 objectives.
An RJMCMC-Based Method for Tracking and Resolving Collisions of Drosophila Larvae

Drosophila melanogaster is an important model organism for ongoing research in neuro- and behavioral biology. Especially the locomotion analysis has become an integral part of such studies and thus elaborated automated tracking systems have been proposed in the past. However, most of these approaches share the inability to precisely segment the contours of colliding animals leading to the absence of model and motion-related features during collisions. Here, we translate the task of tracking and resolving colliding animals into a filtering problem solvable by Markov Chain Monte Carlo methods and elaborate an adequate larva model. By comparing our method with state-of-the-art approaches, we demonstrate that our algorithm produces significantly better results in a fraction of time and facilitates the analysis of animal behavior during interaction in more detail.
New HPLC instrument performance evaluation in HbA1c determination and comparison with capillary electrophoresis

Abstract Glycated hemoglobin (HbA1c) measurement provides the most important medium to long-term marker of time-averaged glycemic status. Its relationship to clinical outcome in diabetes has been convincingly demonstrated for both type 1 and type 2 diabetes. The main HbA1c measurement methods for clinical routine are as follows: ion-exchange chromatography; affinity chromatography, capillary electrophoresis, immunoassay and enzymatic methods. In this study, we evaluated the analytical performances of a new HPLC instrument (Tosoh HLC-723 G11 in the VAR mode) in HbA1c analysis and compared it with a capillary electrophoresis instrument (Sebia Capillarys 2 Flex Piercing). HbA1c analysis was performed in parallel by both methods for 250 samples randomly chosen from healthy and diabetic subjects at ‘Tor Vergata’ University Hospital of Rome. Tosoh HLC-723 G11 showed good reproducibility for 10 days both in quality controls and in samples analyzed (%CV < 2%). We found good linearity for HbA1c values ranging from 15 mmol/mol (3.5%) to 178 mmol/mol (18.5%), with a correlation coefficient R2 = 1. In a comparison between Tosoh HLC-723 G11 and Capillarys 2FP a good correlation (r = 0.99) was found; however, Tosoh HLC-723 G11 showed higher values in the low range of HbA1c and lower in the high range (Tosoh HLC-723 G11 = 4.3043 + 0.913 Capillarys 2FP; p < 0.001). Tosoh HLC-723 G11 showed good repeatability, reproducibility, accuracy and automated simplicity, and it seemed suitable for routine use in clinical chemistry laboratories.
Overnight continuous saline irrigation after transurethral resection for non-muscle-invasive bladder cancer is helpful in prevention of early recurrence.

INTRODUCTION It has been reported that many methods prevent recurrence after transurethral resection of bladder tumour (TURBT) for non-muscle-invasive bladder cancer (NMIBC), but it has rarely been reported that overnight continuous saline irrigation is effective in preventing recurrence. The purpose of this study was to evaluate the efficacy of overnight continuous saline irrigation in preventing recurrence after TURBT. METHODS We retrospectively studied patients with NMIBC who underwent TURBT from January 2010 to May 2015 at our institution. Patients who underwent cystoscopy every 12 weeks during the first year after surgery were included. Patients with cancer stage ≥pT2, lymph node metastasis, or distant metastasis were excluded. The overnight continuous saline irrigation (OCSI) group and the no irrigation group were compared and analyzed. RESULTS A total of 332 patients were included in the study. There were no differences in the basic characteristics of the patients between the two groups. In the OCSI group, the recurrence-free survival rate was higher than that in the no irrigation group, indicating that there was a significant difference between the two groups (p=0.032). CONCLUSIONS After TURBT surgery, OCSI may help prevent early recurrence of NMIBC.
Distributed Event-Triggered Cooperative Control for Frequency and Voltage Stability and Power Sharing in Isolated Inverter-Based Microgrid

The distributed cooperative control for frequency and voltage stability and power sharing in microgrid considering the limitation of communication network is concerned in this paper. Two types of novel event-triggered mechanism with distributed architecture are first proposed, which can greatly reduce the communication burdens among power source inverters. Based on the event-triggered schemes, distributed restoration mechanism is constructed, which can restore the frequency and voltage magnitude of microgrid and realize the fair utilization of all power sources with comparative less requirements for the transmission data. Simulation is carried out to verify the effectiveness of the proposed method.