Search

Purpose This study evaluated whether the rate of retinal nerve fiber layer (RNFL) thinning is faster in eyes receiving intravitreal injections than in fellow uninjected eyes among patients suspected of having or confirmed to have glaucoma and exudative age-related macular degeneration (AMD). Design Retrospective comparative cohort study. Methods Patients with a diagnosis of unilateral exudative AMD and confirmed to have or suspected of having glaucoma in both eyes receiving unilateral intravitreal injections were identified. Those with ≥3 RNFL optical coherence tomography scans and ≥6 injections were included in the study. Rates of RNFL thinning in the injected eye versus the uninjected eye were estimated using linear mixed models. The main outcome measurement was the differences in rates of RNFL thinning in the injected versus the fellow uninjected eye. The effects of postinjection elevation of intraocular pressure (IOP), injection frequency, and number of injections were also evaluated. Results A total of 53 patients met the inclusion criteria, receiving 26.4 ± 15.9 intravitreal injections. The average rate of RNFL thinning in uninjected eyes was −0.620 μm/year (P = .029). Injected eyes had an additional incremental loss of −0.385 μm/year, but this value was not statistically significant (95% confidence interval [CI]: −1.147 to 0.379 μm/year; P = .324). Subgroup analysis with only glaucoma patients (n = 33) also demonstrated a nonsignificant effect of injections (−0.568 μm/year; 95% CI: −1.454 to 0.319 μm/year; P = .212). Postinjection IOP elevation, injection frequency, and total number of injections were not associated with faster RNFL loss. Conclusions Among exudative AMD patients with glaucoma or suspected of having glaucoma, the rate of RNFL thinning in eyes receiving intravitreal injections did not significantly differ from that of fellow uninjected eyes.

In this experimentation tried to optimize spark gap in wire electric discharge machining on AISI 4140. The parameters considered for this study is Pulse on time (Ton), Pulse off time (Toff), Servo Voltage (SV), and Wire Feed (WF). AISI 4140 majorly used in defense because it is high hardness and strength and literature review available on wire electric discharge machining of AISI 4140 is scanty. Due to this reason, AISI 4140 is chosen for this study. Analysis of variance and regression analysis is carried out by using Minitab-18 software. Analysis of variance (ANOVA) gives percentage contribution of each factor for spark gap and regression analysis gives the mathematical relationship between process parameters and spark gap. For optimization purpose, Taguchi L9 orthogonal array is used. From ANOVA it is clear that servo voltage is the major influencing parameter than other parameters for spark gap. After optimization i.e. (machine parameters set at the optimum level) percentage decrement in spark gap is 72.52%

Nowadays, the demand of micro-components is steadily on the rise so that it is becoming increasingly necessary to develop a process, which can manufacture the micro-component with less cost and time. In terms of cost and time Hot Embossing is the best replication technique for the manufacturing of micro-component on a mass scale. In the Hot Embossing, mostly polymers like PMMA, PC, etc. are mainly used as the work material. These replicated structures have a wide range of applications in MEMS. In single-stage hot embossing the parameters which are considered are: applied pressure, heating temperature, embossing time, and demolding temperature. The major important process parameters studied in case of Roller Hot Embossing are roller speed, roller temperature, and applied pressure. Most of the researchers tried to achieve good replication accuracy of embossed parts by varying the process parameters. The present paper aims at reviewing the work carried out in hot embossing process, different modified setups of the hot embossing process, hot embossing of different thermoplastic polymers, and simulation of hot embossing process. The papers discussed in the present review covers research work published in the past 20 years. This review papers aims at providing as consolidated source for all the research work carried out in Hot Embossing and is expected to be a help for any researcher who is new to the field. Through this paper the wiling researcher will be able to get an overview of the type of research work that has already been carried out in the field of Hot Embossing.

PURPOSE: To determine the risk factors for development of neovascular glaucoma (NVG) in patients after an acute central retinal vein occlusion (CRVO). DESIGN: Retrospective cohort study METHODS: Review of medical records of 646 patients with a diagnosis of CRVO between 2013 to 2017 at the Bascom Palmer Eye Institute. Inclusion criteria: 1) CRVO onset to presentation

Purpose: To describe the rare entity of concurrent herpetic acute retinal necrosis (ARN) and orbital inflammation. Observations: Two cases of ARN with simultaneous orbital inflammation are described. A 40-year old male presented with a painful left eye and hand motion visual acuity (VA). Both panuveitis and orbital inflammation with involvement of the sclera and optic nerve were observed. He was initially treated with oral steroid therapy, after which the orbital inflammation improved but the panuveitis remained. A diagnostic anterior chamber paracentesis was positive for HSV-2 by PCR. He was started on systemic antivirals, but ultimately developed a retinal detachment. The second patient was an 18-year old female with hand motion VA in the left eye. Panuveitis and severe conjunctival chemosis were observed. MRI demonstrated dacryoadenitis with preseptal inflammation. The patient was initially started on oral steroid therapy, which alleviated the orbital inflammation but not the intraocular inflammation. An anterior chamber diagnostic paracentesis was positive for HSV-1, after which the patient underwent vitrectomy for a retinal detachment. The patient was started on systemic antiviral therapy. Conclusions and Importance: Herpetic disease should remain on the differential for cases of concurrent intraocular and orbital inflammation. Early recognition of this process may help prevent severe vision loss. It is important to recognize that orbital inflammation secondary to herpetic disease may be diverse in its presentation. Keywords: Acute retinal necrosis (ARN), Orbital inflammation

In this study main focus is on the minimized value of the response variables such as surface roughness and kerf width by setting process parameters of wire electric discharge machining at the optimum level. Single objective optimization is done by using Taguchi L9 orthogonal array and for multi-objective optimization grey relational analysis is used. For experimentation pulse on time (Ton), pulse off time (Toff), servo voltage (SV), wire feed (WF) those process parameters are to be varied while other parameters such as input current (Ip), gap voltage (V), water pressure (WP), wire tension (WT) and servo feed (SF) those parameters are taken as fixed parameters. The major application of AISI 4140 material is in the defense due to its high hardness and high strength. Literature review available on wire electric discharge machining of AISI 4140 is very scanty because of that reason AISI 4140 material is taken for this study. Regression analysis and analysis of variance (ANOVA) find out with help of Minitab software. ANOVA helps to identify the major influencing process parameter for surface roughness and kerf width. From ANOVA major influencing factors for surface roughness, kerf width is the pulse on time and servo voltage respectively. Result analysis shows that for single objective optimization using Taguchi method gives decrement in surface roughness, kerf width individually are 15.65% and 19.35% respectively. In the case of grey relational analysis decrement of surface roughness, kerf width simultaneously at the optimal condition as compared to the initial condition is 9.39% and7.62%.

In recent years use of the nonconventional type of machines is increasing due to some limitations of the conventional type of machines. Electric discharge machine is one of the nonconventional types of the machine generally used for cutting an intricate shape from the hard work piece. Variation in process parameters of electric discharge machining affects its response variable like material removal rate, surface finish, recast layer, wear ratio etc. Because, of that for getting good results of response variables its necessary that proper selection of response of variable. Many researchers tried to optimize process parameters of electric discharge machining with the help of Taguchi method and Grey relational analysis for getting acceptable results of the response variable. Researchers use the Taguchi method for single objective optimization and grey relational analysis for multi-objective optimization. The main focus is on optimization of process parameters of EDM and its modified versions like WEDM, Micro-EDM and PMEDM using Taguchi method and Grey relational analysis and hence, only such research works are included in this review. Where the Taguchi method and Grey relational analysis method is used to optimizing process parameters of EDM; that were published in the last 15 years since 2003. The review work on such large extent was not tried earlier by considering this optimization process for EDM and its modified versions and hence this review work may become ready information at on a place and help researchers to decide their direction of research.

The kinship between man and machines has become a new trend of technology such that machines now have to respond by considering the human emotional levels. The signal processing and machine learning technologies have boosted the machine intelligence that it gained the capability to understand human emotions. Incorporating the aspects of speech processing and pattern recognition algorithms an intelligent and emotions specific man-machine interaction can be achieved which can be harnessed to design a smart and secure automated home as well as commercial application. This paper emphasizes on implementation of speech emotion recognition system by utilizing the spectral components of Mel Frequency Cepstrum Coefficients (MFCC), wavelet features of speech and the pitch of vocal traces. The different machine learning algorithms used for the classification are Gaussian Mixture Model (GMM) and K- Nearest Neighbour (K-NN) models for the recognition of six emotional categories namely happy, angry, neutral, surprised, fearful and sad from the standard speech database Berlin emotion database (BES) followed by the comparison of the two algorithms for performance analysis which is supported by the confusion matrix.