Miracle-dz/UniFAR-FTUs huggingface dataset:
RISE-based robust formation control for multi-UAV system

This paper deals with a robust formation control methodology for the Multi-UAV system with uncertain exogenous disturbance. The fourth-order UAV model with disturbance and the disturbance estimate system is introduced. In order to achieve the rigid formation fight, graph theory and consensus algorithm are utilized and the state of the UAVs converges to desired value by using Leader-Follower structure. The proposed control law includes the Robust Integral of the Sign of error (RISE) for estimation of the disturbance and also involves collision avoidance property based on potential method. The stability and convergent properties are proven based on Lyapunov theory. Finally, several simulation results show the effectiveness of the proposed method compared with a conventional sliding mode control.
Normal photoresponses and altered b-wave responses to APB in the mdxCv3 mouse isolated retina ERG supports role for dystrophin in synaptic transmission

The mdxCv3 mouse is a model for Duchenne muscular dystrophy (DMD). DMD is an X-linked disorder with defective expression of the protein dystrophin, and which is associated with a reduced b-wave and has other electro- retinogram (ERG) abnormalities. To assess potential causes for the abnormalities, we recorded ERGs from pieces of isolated C57BL/6J and mdxCv3 mouse retinas, including measurements of transretinal and intraretinal potentials. The ERGs from the isolated mdxCv3 retina differ from those of control retinas in that they show reduced b-wave amplitudes and increased b-wave implicit times. Photovoltages obtained by recording across the photoreceptor outer segments of the retinas did not differ from normal, suggesting that the likely causes of the reduced b-wave are localized to the photoreceptor to ON-bipolar synapse. At a concentration of 50 μM, the glutamate analog DL-2-amino-4-phosphonobutyric acid (APB) blocks the b-wave component of the ERG, by binding to sites on the postsynaptic membrane. The On-bipolar cell contribution to the ERG was inferred by extracting the component that was blocked by APB. We found that this component was smaller in amplitude and had longer response latencies in the mdxCv3 mice, but was of similar overall time course. To assess the sensitivity of sites on the postsynaptic membrane to glutamate, the concentration of APB in the media was systematically varied, and the magnitude of blockage of the light response was quantified. We found that the mdxCv3 retina was 5-fold more sensitive to APB than control retinas. The ability of lower concentrations of APB to block the b-wave in mdxCv3 suggests that the ERG abnormalities may reflect alterations in either glutamate release, the glutamate postsynaptic binding sites, or in other proteins that modulate glutamate function in ON-bipolar cells.
Segmentation-free printed character recognition by relaxed nearest neighbor learning of windowed operator

Segmentation is considered by many researchers as the key technology for a reliable optical character recognition (OCR) system. To accomplish sound segmentation, many alternative techniques have been recently proposed. This paper presents a new technique to recognize characters without explicit segmentation. It is based on the automatic construction of a windowed operator by relaxed nearest neighbor learning. It has been implemented, tested and yielded excellent recognition accuracy and computational performance.
Myxoid liposarcoma FUS‐DDIT3 fusion oncogene induces C/EBP β‐mediated interleukin 6 expression

The myxoid/round cell liposarcoma oncogene FUS‐DDIT3 is the result of a translocation derived gene fusion between the splicing factor FUS and DDIT3. In order to investigate the downstream targets of DDIT3, and the transforming effects of the FUS‐DDIT3 fusion protein, we have introduced DDIT3‐GFP and FUS‐DDIT3‐GFP constructs into a human fibrosarcoma cell line. The gene expression profiles of stable transfectants were compared to the original fibrosarcoma cell line by microarray analysis. We here report that the NFκB and C/EBP β controlled gene IL6 is upregulated in DDIT3‐ and FUS‐DDIT3‐expressing fibrosarcoma cell lines and in myxoid liposarcoma cell lines. Strong expression of the tumor associated multifunctional cytokine interleukin 6 was confirmed both at mRNA and protein level. Knockdown experiments using siRNA against CEBPB transcripts showed that the effect of FUS‐DDIT3 on IL6 expression is C/EBP β dependent. Chromatin immunoprecipitation revealed direct interaction between the IL6 promoter and the C/EBP β protein. In addition, the effect of DDIT3 and FUS‐DDIT3 on the expression of other acute phase genes was examined using real‐time PCR. We demonstrate for the first time that DDIT3 and FUS‐DDIT3 show opposite transcriptional regulation of IL8 and suggest that FUS‐DDIT3 may affect the synergistic activation of promoters regulated by C/EBP βκB. © 2005 Wiley‐Liss, Inc.
An analytical approach to the design of wireless broadcast disks systems

The Broadcast Disks method is commonly used to schedule the data transmission in wireless push based networks. The performance of a system that utilizes this method depends upon several parameters. This paper presents the Optimization- Based Procedure (OBP), an analytical approach for estimating the optimal values of these parameters. The validity of the analysis is verified through simulation and comparison with other popular and traditional approaches. The new approach was found to be accurate and dominant in the vast majority of a wide set of test cases. It also provided a thorough insight of the system's stability and behavior in general.
Development and characterization of folic acid-conjugated chitosan nanoparticles for targeted and controlled delivery of gemcitabinein lung cancer therapeutics

Abstract The present study was designed to investigate the tumor-targeting potential of gemcitabine (GEM)-loaded surface-tailored chitosan (CS)/poly (ethylene glycol) nanoparticles (FA-PEG-GEM-NPs). The nanoparticles encapsulated with GEM were prepared, characterized, and tethered with folic acid. The developed formulations were characterized with respect to particle size/poly-dispersity index, shape, and zeta potential analysis. The in vitro study shows the sustained drug-release kinetics during 48 h. The present result shows remarkable cytotoxicity rendered by GEM when delivered through FA-PEG-GEM-NPs formulation. The microscopic assessment is suggestive of significant uptake of FA-PEG-GEM-NPs in comparison with the unmodified PEG-GEM-NPs and free drug. Finally, our results advocate for the sizeable compatibility, comparatively less organ toxicity, and higher anti-tumor activity of ligand-anchored and PEGylated CS nanoparticles in vitro and corroborated by in vivo investigations. In conclusion, it is interpreted that surface-tailored nanoparticles are capable to ferry bioactives selectively and specifically to tumor sites with the interception of minimal side effects, thereby suggesting their potential application in cancer therapeutics.
Generalized linear response method: Application to hydration free energy calculations

A generalized linear response (GLR) method was developed and applied to hydration free energy calculations. According to this method, the atomic hydration can be described as a two‐step process. In the first step a point particle is introduced into water, which, according to the scaled particle theory, creates a cavity with the size of a water molecule. The free energy change of this step for the simple point charge (SPC) water model can be calculated as 1.49kBT. In the second step the introduced point particle is transformed into a solute atom. The free energy change of this step can be calculated by the linear response approximation, which is applied to van der Waals and electrostatic interactions, as 〈V Ha 〉0.5. Here V Ha is the solute–water interaction function, and 〈⋅⋅⋅〉0.5 denotes the ensemble average at the midpoint of the thermodynamic path between the point particle state and the hydration state. The GLR method was tested by the calculation of hydration free energies of several neutral organic compounds. The results of the calculation were in close agreement with the experiment and were also comparable with those obtained by the conventional free energy simulation method; the computational cost was decreased by about one order of magnitude. The GLR approach is more general than the existing linear response methods for free energy calculations because it applies the linear response approximation to electrostatic and van der Waals interactions and does not incorporate any empirically determined parameters. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 749–759, 1999
Paricalcitol reduces proteinuria but does not modify peritoneal protein loss in patients on peritoneal dialysis.

INTRODUCTION Paricalcitol, a selective activator of Vitamin D receptors, is successfully used as a treatment of hyperparathyroidism secondary to chronic kidney disease (CKD). In addition, it has been proposed for reducing proteinuria in patients with CKD. Nonetheless, little is known about its effect on peritoneal protein loss in patients on peritoneal dialysis (PD). OBJECTIVES To analyse the efficiency of oral paricalcitol in secondary hyperparathyroidism control in PD patients and to verify its effect on urinary and peritoneal effluent protein loss. MATERIAL AND METHOD Prospective study with a 12-month follow-up on a cohort of PD patients. Invention consisted of the introduction of paricalcitol for the treatment of secondary hyperparathyroidism. Paricalcitol was dosed according to parathyroid hormone (PTH): 1mg/day for patients with PTH < 500 pg/ml, and 2mg/day for those with higher PTH levels. Epidemiological, clinical and analytical data were analysed. RESULTS 38 patients (56 ± 19 years, 55% women, 16% diabetics, technique time (14 ± 10 months) were included in the study. Thirty-three of them received 1mg/day of paricalcitol; the rest received 2mg/day. The use of paricalcitol was associated with a PTH decrease of 30.7 ± 6.8% (P<.001) after 12 months of treatment with no changes in calcium (8.82 ± 0.96 vs. 9.02 ± 0.91; P = .153) and phosphate levels (4.78 ± 0.63 vs. 4.93 ± 0.77; P = .693). Patients did not modify treatment concurrent with phosphate binders over the study period, nor did they change the cinacalcet dosage. However, fewer patients needed it by the end of the study. The PTH baseline levels were independent indicators of its decrease (b = 0.689, P = .018), and the rest of the analysed parameters were not affected. Over the study period there was a proteinuria decrease (0.79 ± 0.41 vs. 0.64 ± 0.36 g/day, P = .034) with no changes in renal function (7.2 ± 1.1 vs. 6.3 ± 0.9 ml/min, P =.104). Similarly, no differences were found in in the percentages of patients taking renin-angiotensin system inhibitors (71 vs. 68 %, P = .472) or the doses needed. There was no significant change in peritoneal protein loss (5.8 ± 1.9 vs. 6.0 ± 2.2g/24h, P = .731) nor in serum albumin levels (3.7 ± 1.1 vs. 3.7 ± 1.2g/dl, P = .697). CONCLUSIONS The use of oral paricalcitol reduces PTH levels safely and substantially in patients on PD. Their use is associated with a proteinuria decrease and is not linked to a decrease of glomerular filtration rate or changes in the medication that could modify it. We have found no modification in the amount of peritoneal protein loss.
Dynamic Median Consensus for Marine Multi-Robot Systems Using Acoustic Communication

In this letter, we present a dynamic median consensus protocol for multi-agent systems using acoustic communication. The motivating target scenario is a multi-agent system consisting of underwater robots acting as intelligent sensors, applied to continuous monitoring of the state of a marine environment. The proposed protocol allows each agent to track the median value of individual measurements of all agents through local communication with neighbouring agents. Median is chosen as a measure robust to outliers, as opposed to average value, which is usually used. In contrast to the existing consensus protocols, the proposed protocol is dynamic, uses a switching communication topology and converges to median of measured signals. Stability and correctness of the protocol are theoretically proven. The protocol is tested in simulation, and accuracy and influence of protocol parameters on the system output are analyzed. The protocol is implemented and validated by a set of experiments on an underwater group of robots comprising of aMussel units. This experimental setup is one of the first deployments of any type of consensus protocol for an underwater setting. Both simulation and experimental results confirm the correctness of the presented approach.
Model predictive control for the quantum series-parallel LCC-type resonant converter with capacitive output filter

This paper presents a model predictive control for the quantum series-parallel LCC-type resonant converter. A hybrid model for the converter including the autonomous change of the systems structure by the output rectifier of the converter is derived. By solving the piecewise linear state equations for the possible input voltages, generated by an H-bridge, the change of the output voltage can be calculated. The maximum resonant current and the voltage across the series-resonant capacitor at the next zero crossing of the resonant current can be estimated, too. Simulation results and measurements show the effectiveness of the control algorithm with constrained resonant current and multistep prediction.
Election Prediction with Automated Speech Emotion Recognition

Even though artificial intelligence has made meticulous outcomes, there is a gap and large thirst for speech emotion recognition in affective computing. Since machines don't understand human emotions, natural human-computer interaction is struggling a lot to strive and compete with today's market. The survey of past election results and prediction has become crucial and out-dated since the surveys could never clearly depicts the real mental state of an individual. Since the wealth and familiarity of the political people have a big title role in many surveys, it is not trustworthy. No surveys can understand the truth in the heart of the common people. So a novel approach is developed for day to day physical and psychological behavior of humans which is influenced by emotions. Other than behavioral expressions, emotion recognition from speech signals is a challenging modality. For the implementation, at least 100 audio signals of different areas, village, town, district, community, religion, and privileged people are considered and a nice questionnaire section (20 questions) is used to record the real emotion of the people. MFCC (mel-frequency cepstral coefficient) feature is extracted and classified with a decision tree, random forest, and CNN (convolutional neural network) to give the eight classes of emotions namely neutral, disgust, calm, angry, happy, sad, fearful and surprise. Any traditional algorithm can be compared to determine the performance of speech emotion recognition.
Anisotropic Smoothing for Illumination Invariant Face Anti-spoofing

Presently, in various biometric-based access systems face recognition has been used. But few of the systems have the facility to discriminate real and spoof faces. Moreover, plenty of researchers on face live detection primarily concentrated on intrusive approaches, which are non-user approachable in nature. An innovative non-intrusive face spoofing detection technique based on HOG and ELTP descriptors is proposed in this paper. More precisely, this approach adopts anisotropic smoothing for normalizing the illumination of a given image. The effectiveness of the proposed method has been evaluated by different types of experiments on the NUAA dataset.
Malware Analysis Platform Based on Software Gene for Cyberspace Security Practice Teaching

In recent years, a large number of malware has spread indiscriminately, which causes various significant cyberspace security incidents all over the world. Therefore, malware detection has become one of the important research topics in cyberspace security. At present, however, the practical teaching for malware detection mainly focuses on delivering the theory and skills, and actual combat training is relatively weak. As a novel method for malware recognition and analysis, software gene technology can quickly explore potential functional and behavioral information of malware, and detect unknown malware. Hence, building an experimental platform for malware gene analysis can effectively reduce the time required for students to quickly carry out the actual analysis process, support student needs for comprehensive data analysis, and provide a unified public service infrastructure for classroom teaching, practical training and scientific research.
Research on stability performance of speed estimation for induction motors based on adaptive full-order observer

To assure the stability performance of the speed estimation in the speed sensorless induction motor drives, the design strategy of feedback gain matrix for an adaptive full-order observer is a necessary issue. In this paper, the major cause of instability phenomenon based on adaptive full-order observer is analyzed, and a novel design of observer's feedback gain matrix is proposed to achieve the stability over the whole operating range especially in the low speed region, including the regenerating mode. Besides, the Popov hyper-stability theory is used to prove the stability improvement based on the proposed method. Some simulation results are given to demonstrate the effectiveness of the proposed solution.
Recognizing Human Emotion Based on Applied Force

In this paper, we studied if human emotions (anger, disgust, fear, happiness, and sadness) can be recognized using the force applied to a 6-axis force sensor. We asked human subjects to apply force to the force sensor to convey their emotions. We used the obtained data to extract 11 feature parameters such as the contact duration, the max magnitude of resultant force, and the mean magnitude of resultant force. Using these feature parameters, we trained a random forest classifier and obtained a classification accuracy of 55.5%. We also investigated how well human subjects could recognize the five emotions by the force applied to their shoulders. The human subject's overall accuracy was 55.9%, which was similar to the classifier's accuracy.
Myeloid‐derived suppressor cells are essential for maintaining feto‐maternal immunotolerance via STAT3 signaling in mice

Maternal immune system tolerance to the semiallogeneic fetus is essential for a successful pregnancy; however, the mechanisms underlying this immunotolerance have not been fully elucidated. Here, we demonstrate that myeloid‐derived suppressor cells play an important role in maintaining feto‐maternal tolerance. A significant expansion of granulocytic myeloid‐derived suppressor cells was observed in multiple immune organs and decidual tissues from pregnant mice. Pregnancy‐derived granulocytic myeloid‐derived suppressor cells suppressed T cell responses in a reactive oxygen species‐dependent manner and required direct cell–cell contact. Mechanistic studies showed that progesterone facilitated differentiation and activation of granulocytic myeloid‐derived suppressor cells, mediated through STAT3 signaling. The STAT3 inhibitor JSI‐124 and a specific short hairpin RNA completely abrogated the effects of progesterone on granulocytic myeloid‐derived suppressor cells. More importantly, granulocytic myeloid‐derived suppressor cell depletion dramatically enhanced the abortion rate in normal pregnant mice, whereas adoptive transfer of granulocytic myeloid‐derived suppressor cells clearly reduced the abortion rate in the CBA/J X DBA/2J mouse model of spontaneous abortion. These observations collectively demonstrate that granulocytic myeloid‐derived suppressor cells play an essential role in the maintenance of fetal immunotolerance in mice. Furthermore, our study supports the notion that in addition to their well‐recognized roles under pathologic conditions, myeloid‐derived suppressor cells perform important functions under certain physiologic circumstances.
Characterization of Radiation Damage in Carbon Nanotube Field-Effect Transistors

Carbon nanotube field-effect transistors with Al2O3 gate dielectrics have been characterized before and after 1 MeV electron irradiation. Pre-irradiation interface trap densities determined by charge pumping measurements were on the order of 1011 cm-2eV-1. Following irradiation to fluences of 1016 e/cm2 and 1017 e/cm2, the measured interface trap densities decreased significantly for all devices. This result is largely attributed to the removal of molecular adsorbates that act as trap sites on the nanotubes (de-doping) while the devices are irradiated under vacuum. Negative shifts in the transistor I-V curves with irradiation indicate radiation-induced hole trapping in the gate dielectric, with some recovery after room temperature annealing. No significant changes were observed in the Raman spectra following irradiation, indicating the intrinsic structure of the carbon nanotubes remained unchanged. These results suggest that the radiation response of these devices is dominated by charge trapping in the oxide layers and at the carbon nanotube surfaces. Furthermore, the charge pumping technique can be used as a tool for probing surface adsorbates in carbon nanotube devices, and elucidating their role in the device radiation response.
On the Strategic Accumulation of Intangible Assets

The resource-based view holds that firms can earn supranormal returns if and only if they have superior resources and those resources are protected by some form of isolating mechanism preventing their diffusion throughout industry. One isolating mechanism that has been proposed for intangible assets is their accumulation process. The hypothesis is that intangible assets are inherently inimitable because would-be imitators need to replicate the entire accumulation path to achieve the same resource position. Thus, entrants can never catch up to incumbents.An interesting challenge to this hypothesis is counterfactual evidence that entrants sometimes outperform incumbents. Such counterfactual evidence should not exist if the theory is strictly correct. This paper attempts to reconcile resource accumulation theory with the counterfactual evidence. We do so by building an intermediate good-production function for a firm's intangible asset stocks. We test the contribution of the intangible asset stock to the firm's final good-production function and examine the extent to which that asset stock deters rival mobility in the pharmaceutical industry.We find that the asset accumulation process itself cannot deter rivals, because asset stocks reach steady state rather quickly. Entrants can achieve an incumbent's intangible asset stock merely by matching its investment until steady state. Thus, we conclude that the accumulation process per se is not an isolating mechanism. While this is perhaps the most important contribution, another contribution is an empirical methodology for characterizing the accumulation function.