Anomalous origin of left coronary artery : an unusual case

Anomalies of the coronary arteries are rare but are an important cause of sudden cardiac arrest in young athletes. Sudden cardiac arrest has been reported in patients with congenital anomalies of the coronary arteries. We present a rare case of sudden cardiac arrest caused by anomalous left main coronary artery originating high from the posterior aspect of left sinus of Valsalva with intramural retroaortic segment, associated with bicuspid aortic valve.peer-reviewe

Identification of different personality traits among teenagers and their effect on behavioural conduct

To identify different personality traits among teenagers To give recommendations to help teenagers create a balance in personality development. METHODS: This research is based on a cross sectional study conducted at Services Institute of Medical Sciences, catering to the freshmen of MBBS. The tenure for the research lasted 8 months starting March 2017- October 2017.The estimated target population accounted to 100 teenage students who were incorporated for the research through convenient sampling. Selection criteria for the chosen sample was based on their age, institute and mental well-being. Any student over and above 19 years, not enrolled in SIMS or suffering through any diagnosed psychiatric illness was excluded from the research sample. To evaluate results from the sample population a questionnaire was generated based on the Big 5 personality assessment scale. All data was registered on the computer after screening for any errors. Data analysis was done by Statistical package for social science version 17. RESULTS: In order to incorporate all factors effecting one\u27s personality we collaborated 10 variables to be tested on a sample of 100 students.Each student from the sample was eligible to answer questions which helped us analyse that 70% of the students from the selected sample claimed to be talkative, where as 30 % were categorised as reserved, 25% of the lot said to bedepressed,32% affirmed to be helpful, 28% were said to be energetic, 31% said they were determined, 37% came out as moody, 34% were said to be ingenious whereas 31% were identified to beeasily distracted and 33%were stratified as politically liberal. CONCLUSION: In order to cater to the major personality traits in psychology we designed a questionnaire based on the BIG 5 personality assessment scale. We tested our target audience to analyse the factors that affect their general behaviour and attitude. The results we gathered from the selected sample were used to categorize the student\u27s personality based on the OCEAN theory

Architecture of Wireless LAN

Wireless communication is the fast growing industry and will continue to evolve. A wireless local area network (WLAN) is a flexible data communications system that use radio frequency to transmit and receive information over the air instead of physical wires. Wireless connectivity allows free movement hence world has become in-creasingly mobile

A Technique for Better Energy Management of Single-Stage Topology of Stand-Alone Photovoltaic System

This paper proposes a technique for energy managing of a stand-alone photovoltaic system. The proposed system employs a power processing inverter, which contains high PV voltage at the input to mitigate the magnitude of AC signal at the output, eliminating use of DC-DC converter and reduces the input capacitor size of PV array. To meet the power requirement of load and to maintain the maximum power point operation of PV array, battery bank is utilized with a bi-directional converter. An impedance model of the complete system is executed. Based on the model, the control architecture is designed which works in four modes: 1)  if load demands >  MPP of PV, additional current is extracted from the battery; 2) if load demands <  MPP of PV array, extra current is given to the battery; 3) only load management is utilized since the battery bank is not available because of over-charging or under-charging; 4) if irradiation varies then first mode is used for load requirement. The technique is designed which guarantees the maximum power point tracking of PV system even without using any intermediate stage of DC-DC converter, hence making it single-stage, MPPT is achieved by effectively controlling bi-directional converter used for battery charging and discharging purpose. To ensure better utilization of dc voltage enhanced efficiency and low less harmonic distortion, sinusoidal PWM technique is used to drive the inverter. Simulation results are carried out for ensuring better energy management along with MPPT operation demonstrated under uniform operating conditions

A Formal Model for Smart Living Room

we are living in an era full of technology and the most powerful feature behind this technology is the communication between two or more things. We achieved globalization with the power of digital computers and their ability to communicate. The next shape of computers for interactive remote processing is internet of things or wireless sensors network and for data storage it is cloud. These tiny computers with heterogeneous characteristics are very helpful in making environment smart and interactive in different ways.  In this paper, we are proposing an Ambient Intelligence architecture for safety and energy efficiency using sensors, further we are formalizing the architecture for its accuracy and reliability. The three major sensors are smoke sensor for safety, glass break detector sensor for security, motion sensor for energy efficiency. In addition, the working of all sensors is also formalized for its correctness

Synthesis and characterization of some new Schiff base derivatives of gabapentin, and assessment of their antibacterial, antioxidant and anticonvulsant activities

Purpose: To synthesize and characterize some new gabapentin Schiff base derivatives, and to assess their antibacterial, antioxidant and antiepileptic activities.Methods: Four Schiff base derivatives of gabapentin, termed G1, G2, G3 and G4, were synthesized by condensation with benzoin, vanillin, acetophenone, and benzophenone, respectively. Their chemical identities were established by FTIR, 1 H NMR and 13C NMR techniques. The new compounds were screened for antibacterial activity using agar well method, antioxidant activity by DPPH assay, and anticonvulsant activity against pentylenetetrazole (PTZ) induced seizures in mice.Results: All the compounds showed antibacterial activity against the test strains to variable degrees, while the parent drug did not exhibit antibacterial activity. The zones of inhibition of compound G2 against Micrococcus luteus (36.2 ± 1.0 mm) and Serratia marcescens (28.2 ± 1.0 mm), and of compound G4 against Stenotrophomonas maltophilia (36.8 ± 1.0 mm) were larger compared to thestandard drug, doxycycline, exhibiting zones of inhibition 28.2 ± 1.3, 28.2 ± 0.9 and 20.0 ± 0.9 mm, respectively. In addition, compounds G1 and G2 possessed significantly greater (p < 0.05) radical scavenging activity (82.3 ± 1.8 and 92.3 ± 2.2 %, respectively) than the precursor drug, gabapentin (63.2± 2.6 %). The seizure scores for compounds G1 (0.7 ± 0.06) and G2 (0.9 ± 0.07) were comparable(p ˃ 0.05) with gabapentin (0.8 ± 0.06), while compounds G3 and G4 were less active (p < 0.05) than gabapentin.Conclusion: Compounds G1 and G2 exhibit good antibacterial and antioxidant activities while retaining the anticonvulsant activity of the parent drug, gabapentin, thus making them suitable candidates for further development for the treatment of neurodegenerative pathologies associated with bacterial infections. Keywords: Gabapentin, Antibacterial, Seizures, Antioxidant, Anticonvulsan

Seismotectonic analyses of Karachi Arc, Southern Kirthar Fold Belt, Pakistan

In this study geomorphological and seismotectonic analyses were carried out in Karachi arc area, southernPakistan to locate relatively safe areas from earthquakes disasters. Karachi arc is the southern extremity of the Kirtharmountain chain that occupies a major part of southern Pakistan and is comprised of a number of narrow, elongatedmountain ranges, i.e. Laki, Kirthar, Khud, Pab and Mor ranges. Based on geomorphological and seismotectonicanalyses Karachi arc area has been divided into three parts. These parts are northern, frontal and southern part. Thenorthern part of Karachi arc is seismically active where minor to moderate (3-5.9Mb) earthquakes occurred. Somebasement structures in Sehwan area seem to be still active and affected by the present-day transpressional stress field.The frontal part of Karachi arc is also active as manifested by the existence of active faults in Jhimpir, Surjan andMeting areas. These embryonic structures in the eastern part of the Arc are indicators of active deformation of Karachiarc. Presently the active deformation is taking place in frontal and northern parts of the arc, while the southern part thathas experienced deformation prior to Quaternary time is inactive and is relatively stable geoblock. The instrumental andhistoric seismicity record of the adjoining areas of Karachi arc show that the area has experienced light to moderateseismic events (4-5.9) with occasional occurrence of strong and major earthquakes. Any major or strong event in Katchrift zone, Makran subduction zone and Ornach-Nal fault zone may cause intensity of VII to VIII in Karachi arc area aswell as Karachi city of environmental seismic intensity scale 2007

A review of NLIDB with deep learning: findings, challenges and open issues

Relational databases are storage for a massive amount of data. Knowledge of structured query language is a prior requirement to access that data. That is not possible for all non-technical personals, leading to the need for a system that translates text to SQL query itself rather than the user. Text to SQL task is also crucial because of its economic and industrial value. Natural Language Interface to Database (NLIDB) is the system that supports the text-to-SQL task. Developing the NLIDB system is a long-standing problem. Previously they were built based on domain-specific ontologies via pipelining methods. Recently a rising variety of Deep learning ideas and techniques brought this area to the attention again. Now end to end Deep learning models is being proposed for the task. Some publicly available datasets are being used for experimentation of the contributions, making the comparison process convenient. In this paper, we review the current work, summarize the research trends, and highlight challenging issues of NLIDB with Deep learning models. We discussed the importance of datasets, prediction model approaches and open challenges. In addition, methods and techniques are also summarized, along with their influence on the overall structure and performance of NLIDB systems. This paper can help future researchers start having prior knowledge of findings and challenges in NLIDB with Deep learning approaches

Detecting wake lock leaks in Android apps using machine learning

The popularity of Android devices has increased exponentially with an increase in the number of mobile devices. Millions of online apps are used in these devices. Energy consumption of a device is a major concern for end-users, who want a long usage time on a single battery charge. The energy consumed by the app must be optimized by developers, and the available APIs must be used carefully. A wake-lock is used in apps to control the power state of the Android device and often leads to energy leakage. In this study, we detected wake-lock leaks in Android apps using machine learning. We pre-processed apps by extracting wake-lock related APIs to obtain the structural information of wake-lock usage and oversampled the data using the synthetic minority oversampling technique (SMOTE) to balance the dataset. The machine learning algorithms used to detect wake-lock leaks were first optimized using grid search to determine the best parameters. These parameters were then used in training to detect wake-lock leaks in these apps. We employed various machine learning algorithms and divided them into simple and ensemble algorithms to evaluate their efficacy. The support vector machine (SVM) and stochastic gradient boosting (SGB) were the most effective, producing 97 % and 98 % accuracy, respectively