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Specific wavelengths of laser energy appear to induce different responses in renal fibrotic tissue. These findings support further study in the development of a customized laser therapy program of combined wavelengths to optimize MSC effects in the treatment of renal fibrosis.

Abstract:Now a days, fire accidents are very common and sometimes it becomes very difficult for a fireman to save someone's life. It is not possible to appoint a person to continuously observe for accidental fire where robot can do that. Therefore in such cases fire fighting robot comes in picture . Robot will detect fire remotely. These robots are mostly useful in industries where probability of accidental fire is more. The proposed vehicle is able to detect presence of fire and extinguishing it automatically by using gas sensor and temperature sensor. It contains gear motors and motor driver to control the movement of robot . Relay circuit is used to control the pump and when it will detect fire then it will communicate with microcontroller (Arduino UNO R3) through Bluetooth module. The proposed robot has a water jet spray which is capable of sprinkling water. The sprinkler can be move towards the required direction .At the time of moving towards the source of fire it may happen that it will come across some obstacles ,then it has obstacle avoiding capability. It will provide GUI for arduino operation using android. It detects obstacles using ultrasonic sensors upto range of 80 m. Communication between the mobile phone and robot will take place through Bluetooth ,which will have GUI to control the movement of robot . When mobile gets connected to Bluetooth firstly it will set module name, baud rate . It is feasible to implement Bluetooth communication between smartphones and microcontroller. Android controlled robot can be used easily in everyday life such as in homes, market ,companies etc. The development of apps for Android in Android SDK is easy and free of cost.

Communicating with the person having hearing disability is always a major challenge. The work presented in paper is an exertion(extension) towards examining the difficulties in classification of characters in Indian Sign Language(ISL). Sign language is not enough for communication of people with hearing ability or people with speech disability. The gestures made by the people with disability gets mixed or disordered for someone who has never learnt this language. Communication should be in both ways. In this paper, we introduce a Sign Language recognition using Indian Sign Language.The user must be able to capture images of hand gestures using a web camera in this analysis, and the system must predict and show the name of the captured image. The captured image undergoes series of processing steps which include various Computer vision techniques such as the conversion to gray-scale, dilation and mask operation. Convolutional Neural Network (CNN) is used to train our model and identify the pictures. Our model has achieved accuracy about 95%

Segmental recanalization of chronically occluded arteries was observed in patients with chronic limb-threatening ischemia (CLTI) treated with Filgrastim, a granulocyte colony stimulating factor, every 72 h for up to a month, and an infra-geniculate programmed compression pump (PCP) for 3 h daily. Molecular evidence for fibrinolysis and neovascularization was sought. CLTI patients were treated with PCP alone (N = 19), or with Filgrastim and PCP (N = 8 and N = 6, at two institutions).Enzyme-Linked Immunosorbent Assay was used to measure the plasma concentration of plasmin and of fibrin degradation products (FDP), and the serum concentration of proteins associated with neovascularization. In the PCP-alone group, blood was sampled on Day 1 (baseline) and after 30 days of daily PCP. In the Filgrastim and PCP group, blood was drawn on Day 1, and 1 day after the 5th and the 10th Filgrastim doses. Each blood draw occurred before and after 2 h of supervised PCP. Significant (p < 0.01) PCP independent increases in the plasma concentration of plasmin (>10-fold) and FDP (>5-fold) were observed 1 day after both the 5th and the 10th Filgrastim doses, compared to Day 1. Significant (p < 0.05) increases in the concentration of pro-angiogenic proteins (e.g., HGF, MMP-9, VEGF A) were also observed. Filgrastim at this novel dosimetry induced fibrinolysis without causing acute hemorrhage, in addition to inducing a pro-angiogenic milieu conducive to NV. Further clinical testing is warranted at this novel dosimetry in CLTI, as well as in other chronically ischemic tissue beds.Trial registration. https://clinicaltrials.gov/ct2/show/NCT02802852.

Objective: The aim of our study was to quantify the effect of doses delivered by a He:Ne laser on individual macrophage kinetics, tissue oxidative stress, and wound closure using real-time in vivo imaging. Background: Photobiomodulation has been reported to reduce tissue inflammation and accelerate wound closure; however, precise parameters of laser settings to optimize macrophage behavior have not been established. We hypothesized that quantitative and real-time in vivo imaging could identify optimal fluence for macrophage migration, reduction of reactive oxygen species, and acceleration of wound closure. Methods: Larval zebrafish Tg(mpeg-dendra2) were loaded with dihydroethidium for oxidative stress detection. Fish were caudal fin injured, treated with 635 nm continuous 5 mW He:Ne laser irradiation at 3, 9, or 18 J/cm 2 and time-lapsed imaged within the first 120 min postinjury. Images taken 1 and 24-h postinjury were compared for percentage wound closure. Results: A fluence of 3 J/cm 2 demonstrated significant increases in macrophage migration speed, fewer stops along the way, and greatest directed migration toward the wound. These findings were associated with a significant reduction in wound content reactive oxygen species when compared with control wounded fins. Both 3 and 9 J/cm 2 significantly accelerated wound closure when compared with nonirradiated control fish. Conclusions: Wound macrophage activity could be manipulated by applied fluence, leading to reduced levels of wound reactive oxygen species and accelerated wound closure. The zebrafish model provides a means to quantitatively compare wound macrophage behavior in response to a variety of laser treatment parameters in real time.

In today’s world it is necessary to protect one’s authenticity in order to ensure the protection of personal information that only the authenticate credentials of a person can have access to. Nowadays there is an increase in number of malpractices like signature forgery to access the important information of a person. To encounter signature verification problem, there have been a number of advances in verifying the authenticity of signature using various techniques including Machine Learning and Deep Learning. This paper introduces a novel approach to verify the signatures using difference of gaussian filtering technique, gray level co-occurrence matrix feature extraction technique, principle component analysis and kernel principal component analysis associated with various machine learning algorithms. The publicly available Kaggle offline handwritten signature dataset is used for training. This article compares the accuracy of the dataset on various machine learning algorithms. After training datasets the lowest accuracy achieved is 56.66% for Naive Bayes algorithm. The highest accuracy achieved is 82% for K-Nearest Neighbour (KNN) and 81.66% for Random Forest using principle components and kernel principle components of the dataset.

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