MALLAMPATTI SCORE AS A PREDICTOR FOR RISK OF OBSTRUCTIVE SLEEP APNEA

Objective: To observe the association of high Mallampatti score with obstructive sleep apnea and to see its predictive value for high risk individuals. Study Design: A Prospective Cross Sectional Study. Place and Duration of Study: Department of Anaesthesia Indus Hospital Muzaffargarh Bahawal Victoria Hospital Bahawalpur and Nishtar Hospital Multan, from July 6, 2017 to January 20, 2018. Methodology: Body mass index was calculated from weight and height. Mallampatti score was evaluated besides Berlin questionnaire, snoring, Epworth sleeping scale. Patients were divided into four groups on the basis of Mallampatti score. Mallampatti score was cross tabulated against snoring grades, Berlin score risk, Epworth score classes and body mass index categories and was compared by applying Chi-square test. SPSS v.23 was used, considering p≤0.05 statistically significant. Results: In group III and IV of Mallampatti score, there was significantly more snoring of grade III and grade IV (p=0.043). Mallampatti score difference was not statistically significant among normal, overweight and obese persons (p=0.962). On the basis of Berlin Score risk, the difference was not found to be of any statistical significance (p=0.366). There was a statistically significant increase in Mallampatti score when we moves from class I to class IV of Epworth Sleep Score (p=0.031). Conclusion: We concluded that high Mallampatti score is greatly interrelated with snoring and high Epworth sleep score. This shows a strong relationship between high Mallampatti score and obstructive sleep apnea. Therefore, Mallampatti score can be used to predict the risk of obstructive sleep apnea. Keywords: Obstructive Sleep Apnea, Mallampatti Score, Epworth Sleep Score, Berlin Score. DOI: 10.7176/JMPB/55-17 Publication date:May 31st 201

A multi-channel soft biometrics framework for seamless border crossings

As the number of passengers at border entry points such as airports and rail stations increases, so does the demand for seamless, secure, and fast biometric technologies for verification purposes. Although fingerprints are currently useful biometric technologies, they are intrusive and slow down the end-to-end verification process, increasing the chances of tampering. Emerging as an alternative technology, soft biometrics have proven successful for non-intrusive and rapid verification. Soft biometrics consists of a large set of features from three different modalities of the human body, including the face, body, and essential & auxiliary attachments. This paper proposes a multi-channel soft biometrics framework that leverages soft biometrics technology over traditional biometrics. The framework encapsulates four distinct components: ApparelNet, which verifies essential and auxiliary attachments; A-Net, which measures anthropometric soft biometrics; OneDetect, which predicts global soft biometrics; and RSFS, which develops a set of highly relevant and supportive soft biometrics for verification. The proposed framework addresses several critical limitations of existing biometrics technologies during the verification process at border entry points, such as intrusive behavior, response time, biometric tampering, and privacy issues. The proposed multi-channel soft biometrics framework has been evaluated using several benchmark datasets in the field, such as Front-view Gait (FVG), Pedestrian Attribute Recognition At Far Distance (PETA), and Multimedia and Vision (MMV) Pedestrian. Using heterogeneous datasets enables the testing of each framework component or channel against numerous constrained and unconstrained scenarios. The outcome of the envisioned multi-channel soft biometrics framework is presented based on distinct outcomes from each channel, but it remains focused on determining a single cumulative verification score for verification at border control. In addition, this multi-channel soft biometrics framework has extended applications in several fields, including crowd surveillance, the fashion industry, and e-learning

Development of affordable hot box calorimeter to determine the U-value of inhomogeneous building material

open access articleIn recent years, the use of three-dimensional printing to create construction components has advanced quickly; it is possible now to simplify construction, increase speed, and lower cost while using natural resources responsibly. It also allows us to use recycled material to produce building envelopes while increasing design flexibility. However, the thermal performance of building materials must be characterized to achieve the necessary energy efficiency of the building envelopes. This study aims to develop, produce, and calibrate a hot box calorimeter at a reasonable price for thermal testing components building envelope. The heat loss through these components using a hot box can be measured in a lab to get an idea of the thermal performance of the building envelopes. In order to evaluate and analyze the thermal performance of various 3D-printed building brick samples made in the labs, this study explains the design and creation of an inexpensive hot box. The hot box can conduct a conventional thermal experiment, which involves monitoring heat flux, surface temperatures, and air temperatures. The testing process, instrumentation, test conditions, and validation of the new metering box are all covered in the article. The U-value of the brand-new lattice-based 3D printed building blocks was afterward determined using the validated new hot box. It was observed that the U-values values of 1.04 W/m2.K and 0.99 W/m2.K, respectively, for small components utilizing developed hot box and larger lattice panels using commercial equipment, with a maximum variance of 5%. It highlights the dependability of the hot box apparatus, which is also made affordable to operate by using less material for specimen preparation and less energy to maintain the temperature in the hot and cold chambers. Its small size also makes setup and thermal testing of construction materials simple

Effect of Condensate Flow Rate on Retention Angle on Horizontal Low-Finned Tubes

This article is in an Open Access journalThe paper reports experimental results using simulated condensation on eight horizontal integral finned tubes with different fin spacing but same root diameter. Condensation was simulated with low approaching zero vapor velocity of condensate using three liquids (water, ethylene glycol and R141b) supplied to the tube via small holes between the fins along the top of the tubes. Controlling parameters of the investigation were fin spacing of condensation tubes, flow rate of condensate and surface tension to density ratio of the condensate. The results indicate that the retention angle (measured from the top of the tube to the position where the inter-fin space is completely filled with liquid) increases with the increase in fin spacing. Also, retention angle increases as the density of the condensate increases but retention angle decreases with increase in surface tension. Interesting finding is seen as retention angle remains constant with increase in condensate flow rate, starting from very low (nearly zero) flow rate to the flow rate at which the tube gets fully flooded. The critical flow rate for eight tubes of defined fin density against three working fluids is measured. Results obtained from simulated condensation for almost zero condensate velocity are in good agreement with earlier data and theoretical model for retention angle on such tubes

The prevalence of bipolar spectrum disorder in medical students of Pakistan

Background: Bipolar affective disorder is cyclic swinging of mood between mania or hypo-mania and depression. Bipolar disorder is the sixth leading cause of disability worldwide and has a lifetime prevalence of about 1 to 3% in the general population. Despite a growing body of knowledge on bipolar spectrum disorder (BSD), relatively little is known about the clinical characteristics of BSD in medical students. This study evaluates the prevalence and severity of BSD in medical students in relation to certain socio-demographic factors like age, sex and class of education.Methods: A questionnaire based study was done on 298 medical students of Nishtar Medical University, Multan and Shaikh Zayed Medical College, Rahim Yar Khan chosen on basis of random sampling to test the prevalence of bipolar spectrum disorders using Mood Disorder questionnaire (MDQ). Out of these students 161 were males and 137 were females. Students were interviewed to obtain information about age, sex and academic year of education.Results: According to mood disorder questionnaire scoring, of the total 298 students 80 (26.84%) screened positive for bipolar spectrum disorder (BSD). Among 80 students who screened positive for BSD 43 (53.75%) are males while 37 (46.25%) are females. Class-wise distribution of BSD is as follows: Out of 80 students screened positive 15 (18.75%) are from 2nd year, 22 (27.5%) from 3rd year and 43 (53.75) from 4th year. Age-wise distribution of BSD is as following: Students of age 19, 20, 21, 22 and 23 years suffering from BSD were 5 (6.25%), 17 (21.25%), 23(28.75),22 (27.5%) and 13 (16.25%) respectively.Conclusions: In our study, the estimated rate of prevalence for bipolar spectrum disorder among medical students of Pakistan is 26.84%. There was no significant difference in prevalence on the basis of gender. Prevalence was increasing with both age and class wise distribution

Gaussian mixture model based probabilistic modeling of images for medical image segmentation

In this paper, we propose a novel image segmentation algorithm that is based on the probability distributions of the object and background. It uses the variational level sets formulation with a novel region based term in addition to the edge-based term giving a complementary functional, that can potentially result in a robust segmentation of the images. The main theme of the method is that in most of the medical imaging scenarios, the objects are characterized by some typical characteristics such a color, texture, etc. Consequently, an image can be modeled as a Gaussian mixture of distributions corresponding to the object and background. During the procedure of curve evolution, a novel term is incorporated in the segmentation framework which is based on the maximization of the distance between the GMM corresponding to the object and background. The maximization of this distance using differential calculus potentially leads to the desired segmentation results. The proposed method has been used for segmenting images from three distinct imaging modalities i.e. magnetic resonance imaging (MRI), dermoscopy and chromoendoscopy. Experiments show the effectiveness of the proposed method giving better qualitative and quantitative results when compared with the current state-of-the-art. INDEX TERMS Gaussian Mixture Model, Level Sets, Active Contours, Biomedical Engineerin

Passive cooling analysis of an electronic chipset using nanoparticles and metal-foam composite PCM: An experimental study

Thermal management of electronic components is critical for long-term reliability and continuous operation, as the over-heating of electronic equipment leads to decrement in performance. The novelty of the current experimental study is to investigate the passive cooling of electronic equipment, by using nano-enriched phase change material (NEPCM) with copper foam having porosity of 97 %. The phase change material of PT-58 was used with graphene nanoplatelets (GNPs) and magnesium oxide (MgO) nanoparticles (NPs), having concentrations of 0.01 wt. % and 0.02 wt. %. Three power levels of 8 W, 16 W, and 24 W, with corresponding heating inputs of 0.77 kW/ m2, 1.54 kW/ m2 and 2.3 kW/ m2, respectively, were used to simulate the heating input to heat sink for thermal characterization. According to results, at 0.77 kW/ m2 heating input the maximum base temperature declined by 13.03 % in 0.02 wt. % GNPs-NEPCM/copper foam case. At heating input of 1.54 kW/ m2, the maximum base temperature reduction of 16 % was observed in case of 0.02 wt. % GNPs-NEPCM/copper foam and 13.1 % in case of 0.02 wt. % MgO-NEPCM/copper foam. Similarly, at heating input of 2.3 kW/ m2, the maximum temperature of base lessened by 12.58 % in case of 0.02 wt. % GNPs-NEPCM/copper foam. The highest time to reach the set point temperature of 50 ⁰ C, 60 ⁰ C, and 70 ⁰ C was in case of GNPs-NEPCM/copper foam composites, while at all power levels MgO-NEPCM/copper foam gave comparable performance to GNPs based composite. Similar trend was observed in the study of enhancement ratio in operation time. From the results, it is concluded that the copper foam incorporation in NEPCM is an effective measure to mitigate the heat sink base temperature and can provide best cooling efficiency at low and higher heating loads

Prevalence of anxiety and depression among Medical Students in MMCH, Sindh, Pakistan

Introduction: Medical education is stressful. High levels of stress have been seen in medical students in various studies. The academic stressors include the volume of material to be learned, academic performance and evaluation, examination and continuous assessment, mental tension and too much work load. All this can result in decreased life satisfaction among students.  Stress during medical school can lead to problems later in professional life compromising patient care. Objectives: To know the prevalence of anxiety and depression among medical students of Muhammad Medical College, Mirpurkhas, Sindh, Pakistan  Methodology: A Cross-sectional study was done on the students of Muhammad Medical College, Mirpurkhas, Sindh, who had spent more than six months in the medical college. Self-administered questionnaire was given to the students, present in the class and willing to participate in the study. The instrument used to assess the anxiety and depression levels was the, Aga Khan University Anxiety and Depression Scale (AKUADS). Additional quotations regarding socioeconomic variables were also included in them survey instrument, such as student’s age order, family monthly income, and gender, marital status. Results: Using anxiety and depression scale it was found out that 318 (96.36%) students had anxiety and depression. Among them 215 (67.61%) were females and 103 (32.38%) males. Prevalence of anxiety and depression in students of Final, 4th year and 3rd year 2nd and 1st years was 13%, 15%, 20% and 21%, 28% respectively. It was significantly higher in 1st year and 2nd year students, as compared to final and 4th year and students. Conclusions: Most of medical students have anxiety and depression due to study burden and a busy schedule. It is also seen that anxiety and depression is more among female medical students, and more among in 1st year and 2nd year MBBS students, as compared to the final and forth year students.   Keywords: Anxiety, depression, Medical students, prevalenc