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Objective: To assess sleep quality in patients of Chronic Kidney Disease using Pittsburgh Sleep Quality Index score and to compare the effects of Alprazolam and Pregabalin in patients having poor sleep quality. Study Design: Quasi-experimental study. Place and Duration of Study: Nephrology Department of Combined Military Hospital, Karachi Pakistan, from Oct 2021 to Mar 2022. Methodology: A total of 127 individuals coming to Nephrology Department diagnosed with chronic kidney disease were included. Sleep quality was assessed using Pittsburgh Sleep Quality Index score. Age, gender, duration of Chronic Kidney Disease and history of Diabetes, Hypertension and Cardiovascular disease were recorded. Those individuals having poor sleep quality were started randomly on either Alprazolam 0.5 mg and Pregabalin 75 mg daily. Effects of these drugs were assessed by determining Pittsburgh Sleep Quality Index two months after administration of these drugs. Results: Out of 127 individuals, 82(64.5%) had poor quality sleep characterized by Pittsburgh Sleep Quality Index ≥5 at the time of presentation. Among them, 40(48.7%) were male and 42(51.3%) were female, 46(56.1%) had history of Diabetes Mellitus, 48(58.5%) had history of Hypertension and 31(37.8%) had history of Cardiovascular disease. Forty-one were started on Alprazolam and 41 on Pregabalin. No statistically significant difference was found in the sleep quality between groups at the end of two months of regular treatment (p-value =0.088). Conclusion: Sleep disturbances are present in majority of the patients of Chronic Kidney Disease. Both Alprazolam and Pregabalin can be used to treat sleep related disorders in these patients.

Objective: To investigate and document the clinical course of typhoid fever and the sensitivity pattern of Salmonella typhi to antibiotics among patients admitted to Pakistan Naval Ship Shifa Hospital. Study Design: Cross-sectional study. Place and Duration of Study: Pakistan Naval Ship Shifa Hospital, from Jul to Dec 2021. Methodology: The patients admitted with typhoid fever to the hospital during the study period were included using consecutive sampling. After getting informed consent, the patients’ demographic characteristics, course of the disease, blood culture sensitivity, the treatment administered, the complications that emerged, and the length of their hospital stay were noted. Results: There were 77 patients with culture-proven typhoid fever admitted during the study period. The mean age was 18.6±11.84 years (range 1-55 years). The most frequent presenting complaints were fever, abdominal pain, and vomiting. Additional symptoms included a rash, bodily aches, and weariness. Out of the 77 patients, 76(99%) were extensively drugresistant (sensitive to Meropenem and Azithromycin only). The complications noted were hepatitis, myocarditis, ascites, pleural effusion, and shock. The mean length of stay in the hospital was 16.56+3.87 days. The typical time gap between commencing culture-specific antibiotics and fever defervescence was 4.03±2.84 days. Conclusion: Almost all (99%) patients admitted with typhoid fever in PNS Shifa are extensively drug-resistant and require a relatively longer hospital stay for management.

Objective: To evaluate the impact of haemodialysis on plasma carnitine levels. Method: The cross-sectional study was conducted from April 20, 2020 to May 10, 2022, at the dialysis unit of the nephrology ward of Jinnah Postgraduate Medical Centre, Karachi, and the Pakistan Navy Ship Shifa Hospital, Karachi, in collaboration with the Department of Biochemistry, University of Karachi, and comprised patients of either gender aged >18 years. They were divided into chronic kidney disease group A and end-stage renal disease group B. Control group C included subjects from the general population. Free carnitine and total carnitine values were detected using enzyme-linked immunosorbent assay. Acyl carnitine was estimated by applying the standard formula, and the ratio between acyl carnitine and free carnitine was calculated for accurate assessment of the carnitine status. Data was analysed using SPSS 23. Results: Of the 203 subjects, 143(70.44%) were cases and 60(29.55%) were controls. Among the cases, 120(84%) were recruited from Jinnah Postgraduate Medical Centre and 23(16%) from Pakistan Navy Ship Shifa Hospital. There were 60(29.55%) patients in group A, 83(40.88%) in group B and 60(29.55%) in group C. The mean age in group A was 47.90/5,65 years, it was 44.10/8.92 years in group B and 40.90/6.73 years in group C. There was a significant difference related to free carnitine, total carnitine, acyl carnitine values and the ratio between acyl carnitine and free carnitine values in groups A and B compared to control group C (p

Speech enhancement (SE) aims to improve the intelligibility and perceptual quality of speech contaminated by noise signals through spectral or temporal changes. Deep learning models achieve speech enhancement and estimate the magnitude spectrum. This paper proposes a novel and computationally efficient deep learning model to enhance noisy speech. The model pre-processes the noisy speech magnitude by redistributing energy from high-energy voiced segments to low-energy unvoiced segments using an adaptive power law transformation while maintaining the total energy of the speech signals constant. A U-shaped fuzzy long short-term memory (UFLSTM) estimates the magnitude of a time-frequency (T-F) mask by using the pre-processed data. Residual connections to the similar-shaped layers are added to avoid gradient decay. Attention process is adopted by modifying the forget gate of UFLSTM. To make a causal speech enhancement system, the processing does not include any future audio frames. We compare the proposed speech enhancement to other deep learning models in different noisy environments with signal-to-noise ratios of 0 dB, 5 dB, and 10 dB. The experiments show that the proposed SE system outscores the competing deep learning models and considerably improves speech intelligibility and quality. In terms of STOI and PESQ, the LibriSpeech database improves results by (0.211) 21.1% and (0.95) 36.39%, respectively, over noisy speech in seen noisy conditions, and by (0.199) 19.9% and (0.94) 35.69% over noisy speech in unseen noisy conditions. Further, the cross-corpus analysis shows that proposed SE system performs better when trained with the DNS dataset as compared to the LibriSpeech, VoiceBank, and TIMIT datasets.

Machine learning-based supervised single-channel speech enhancement has achieved considerable research interest over conventional approaches. In this paper, an extended Restricted Boltzmann Machine (RBM) is proposed for the spectral masking-based noisy speech enhancement. In conventional RBM, the acoustic features for the speech enhancement task are layerwise extracted and the feature compression may result in loss of vital information during the network training. In order to exploit the important information in the raw data, an extended RBM is proposed for the acoustic feature representation and speech enhancement. In the proposed RBM, the acoustic features are progressively extracted by multiple-stacked RBMs during the pre-training phase. The hidden acoustic features from the previous RBM are combined with the raw input data that serve as the new inputs to the present RBM. By adding the raw data to RBMs, the layer-wise features related to the raw data are progressively extracted, that is helpful to mine valuable information in the raw data. The results using the TIMIT database showed that the proposed method successfully attenuated the noise and gained improvements in the speech quality and intelligibility. The STOI, PESQ and SDR are improved by 16.86%, 25.01% and 3.84dB over the unprocessed noisy speech.

Objective: To determine if a goal-directed ECG workshop improves ECG interpretation competency and confidence among the house officers in PNS Shifa Hospital. Study Design: Prospective comparative study. Place and Duration of Study: Pakistan Naval Ship Shifa Hospital, Karachi Pakistan, from Jan to Dec 2021. Methodology: ECG workshops were conducted for House Officers in batches. The participants were asked to complete a questionnaire testing their ECG interpretation competency before and after the workshop and self-report their confidence level in ECG interpretation. Results: Sixty-eight house officers participated in the workshops and completed the test. There were 41(60.29%) female and 27(39.7%) male participants. The statistics showed significant improvement in ECG competency (p

Brain tumours are quickly increasing in prevalence all over the world. It causes the deaths of thousands of individuals annually. Misdiagnosis of brain tumours often results in unnecessary treatment, further lowering the survival rate of the affected individuals. Prompt medical diagnosis is crucial to improve the prognosis for patients with brain tumours. Positive advancements in deep and machine learning domains have been made due to repeated achievements in supporting medical practitioners in making correct diagnoses utilizing computer-aided diagnostic tools. Deep convolutional layers are superior to conventional methods at extracting unique characteristics from target regions. In this research, initially, Gabor filter and ResNet50 were applied to accurately extract the important features of brain tumours from the MRI images dataset. Firstly, the extracted features of Gabor and ResNet50 were classified individually through SVM, and secondly, the features from both these techniques were combined and then classified through SVM. The Kaggle MRI dataset for a brain tumour was utilized in this research. It includes 7,023 Images and four classes Glioma, Meningioma, No-Tumor, and Pituitary. The results from every system were outstanding, but the best results were shown by the combined features of Gabor and ResNet50, an advanced hybrid approach with 95.73% accuracy, 95.90% precision, and 95.72% f1 score.

This study presents an ultracompact dual-band bandpass filter with controllable transmission zeros based on quarter-wave dual-mode resonator for GSM (global system for mobile communications) and GPS (global positioning system) wireless applications. The filter is made up of two quarter-wave resonators, which help to independently control the passbands. A direct feed resonator creates the first operating band, which serves as a feeding source for the interior resonator and operates at a higher frequency band. Therefore, a pair of transmission zeros can be energized between the two passbands, and high roll-off skirts are obtained. To reduce the size of the entire filter, the two resonators are bent and connected together through a hole in a metal base. The structure is symmetrical in nature, so both frequency bands can be obtained using the even-odd mode analysis method. For GSM applications, the center frequency of the first working band is 850 MHz, while for GPS wireless applications, the center frequency of the second working band is 1.57 GHz. Although there is a feed line (λg is based on a waveguide length of 850 MHz), the filter has been simulated and fabricated for verification, with an ultra-compact size of 0.10 λg × 0.09 λg (0.0095 λg2). The simulation results and measured results match well, and the theory of the design concept is recognized.

In this paper, a model based on constraint convex optimization is proposed for the radiation pattern synthesis in cylindrical and spherical microstrip conformal array antennas. The optimization algorithm is modeled to decrease the Euclidean distance between the obtained radiation pattern of the deformed array and the desired radiation pattern of the planar array by calculating the suitable amplitude and phase values for the individual array patches. Four prototypes of 2×2, 3×3, 4×4, and 5×5 microstrip patch array antenna are used as the radiating elements which are deformed from planar arrangement and placed on the faces of prescribed spherical and cylindrical shapes with various radii of curvatures. The results reveal that the performance of optimization algorithm performs better in 5×5 array, followed by 4×4 array, 3×3 array, and 2×2 array. However, 5×5 array provides more degrees of freedom for tuning the radiation pattern in desired form. The 5×5 array computes suitable amplitude and phase values for the radiating elements of the array, which restore the radiation pattern in terms of mainlobe reconstruction, null locations, sidelobe levels, up to the deformation of 20 cm in both spherical and cylindrical configurations of conformal array. The proposed optimization technique when applied to conformal antenna array offers fast computational speed and good convergence accuracy for radiation pattern synthesis, which can be useful for various engineering applications.

Speech enhancement (SE) reduces background noise signals in target speech and is applied at the front end in various real-world applications, including robust ASRs and real-time processing in mobile phone communications. SE systems are commonly integrated into mobile phones to increase quality and intelligibility. As a result, a low-latency system is required to operate in real-world applications. On the other hand, these systems need efficient optimization. This research focuses on the single-microphone SE operating in real-time systems with better optimization. We propose a causal data-driven model that uses attention encoder-decoder long short-term memory (LSTM) to estimate the time-frequency mask from a noisy speech in order to make a clean speech for real-time applications that need low-latency causal processing. The encoder-decoder LSTM and a causal attention mechanism are used in the proposed model. Furthermore, a dynamical-weighted (DW) loss function is proposed to improve model learning by varying the weight loss values. Experiments demonstrated that the proposed model consistently improves voice quality, intelligibility, and noise suppression. In the causal processing mode, the LSTM-based estimated suppression time-frequency mask outperforms the baseline model for unseen noise types. The proposed SE improved the STOI by 2.64% (baseline LSTM-IRM), 6.6% (LSTM-KF), 4.18% (DeepXi-KF), and 3.58% (DeepResGRU-KF). In addition, we examine word error rates (WERs) using Google's Automatic Speech Recognition (ASR). The ASR results show that error rates decreased from 46.33% (noisy signals) to 13.11% (proposed) 15.73% (LSTM), and 14.97% (LSTM-KF).

Objective: To compare the efficacy of Amlodipine with Captopril in the management of patients presenting to the emergency department with uncontrolled blood pressure. Study Design: Comparative prospective study. Place and Duration of Study: Emergency Department, Combined Military Hospital, Malir Pakistan, from Jul to Dec 2021. Methodology: A total of 127 individuals presenting to the Emergency Department with two readings of uncontrolled blood pressure (Systolic blood pressure ≥ 160mmHg and Diastolic blood pressure ≥90mmHg) were included. They were administered a tablet of Captopril 12.5mg per oral and a tablet of Amlodipine 10mg per oral on the turn by turn basis. Patients were observed for 3 hours and monitored for the reduction in blood. The efficacy of medication was judged based on the ability to achieve target blood pressure reduction, which was at least a 20-30% reduction in systolic blood pressure. Results: Out of 127 individuals, 65(51.2%) patients were given a tablet of Captopril 12.5mg orally, and 62(48.8%) were given a tablet of Amlodipine 10mg orally. The mean reduction in systolic blood pressure was 20.73±5.17 in all patients. In addition,target blood pressure reduction was achieved in 35(53.8%) individuals of the Captopril-Group and 33(53.2%) of the Amlodipine-Group, with a total of 68(53.5%) individuals achieving target blood pressure within 3 hours after medication. Conclusion: Both medications were efficient in achieving target blood pressure levels. However, no drug was superior to another in reducing blood pressure in an emergency.

Objective: To determine the frequency of Pregnancy-related acute kidney injury in the Pakistani population and its effect on maternal health. Study Design: Cross-sectional study. Place and Duration of the Study: Department of Nephrology and Obstetrics and Gynecology, Combined Military Hospital Kharian, from Jan 2018 to Dec 2020. Methodology: All pregnant women with normal renal functions at the time of enrolment in the study and no previous history of any kidney disease or renal procedure in the recent past (at least 3 months) before conception were included in our study at Combined Military Hospital Kharian. All participants had serum creatinine tested at enrolment and were inquired specifically about any history of renal disease or any renal procedure in the recent past (at least 3 months old). Results: Mean maternal age in the study was 29 ± 7.67 years however it ranged from 16-41 years. Around a quarter of acute kidney injury cases occurred in the first and second trimesters combined, with 26 (12%) and 24 (11%) cases in the first and second trimesters, respectively. Thirty percent of acute kidney injury cases were diagnosed in the third trimester. A substantial number 58 (27%) of cases developed azotemia which persisted beyond three months and developed chronic kidney disease of various stages. Regarding maternal outcomes, 166 (77%) mothers recovered completely. However, 43 (20%) patients had some degree pf azotemia, a few cases required permanent renal replacement therapy. Conclusion: Acute kidney injury is a common problem in our community leading to suboptimal maternal outcomes..............

Objective: To assess the frequency of the various medical conditions in patients presenting with altered mental status (AMS) in the Emergency Department of Pakistan Naval Ship (PNS) Shifa Hospital. Study Design: Prospective longitudinal study. Place and Duration of Study: Emergency Department, Pak Naval Ship Shifa Hospital, Karachi Pakistan from Feb-Jul 2021. Methodology: Adult patients who have presented with altered mental status (Glasgow coma scale score less than 15) or who have the diagnosis "AMS" written in their notes were included in the study. Patients were observed in the wards until a definitive diagnosis could be made. Results: Sixty patients presented with AMS at the Emergency Department of PNS Shifa, during the study period. The causes of AMS were sepsis (20, 33.33%), CVA (12, 20%), metabolic (hepatic/uremic) encephalopathy (8, 13.33%), diabetic complications (7, 11.66%), seizures (5, 8.33%), drug intoxication (4, 6.66%) and respiratory failure due to lung pathology (4,6.66%). The overall mortality rate was 20%. Conclusion: Sepsis is the most frequently encountered cause of altered mental state in emergency department patients,followed by CVA, metabolic encephalopathy, and diabetic complications.

In this article, a simple method is developed to design a highly miniaturized tri-band bandpass filter (BPF) utilizing two asymmetric coupled resonators with one step discontinuity and one uniform impedance resonator (UIR) for worldwide interoperability for microwave access (WiMAX) and radio frequency identification (RFID) applications. The first and second passbands located at 3.7 GHz and 6.6 GHz are achieved through two asymmetric coupled step impedance resonators (SIRs), while the third passband, centered at 9 GHz, is achieved using a half-wavelength UIR, respectively. The fundamental frequencies of this BPF are implemented by tuning the physical length ratio (α) and impedance ratio (R) of the asymmetric SIRs. The proposed filter is designed and fabricated with a circuit dimension of 13.69 mm × 25 mm (0.02 λg × 0.03 λg), where λg represents the guided wavelength at the first passband. The experimental and measured results are provided with good matching.

In this article, compact a multiple-input and multiple-output (MIMO) system with flag-shaped radiators and a mountain-shaped ground plane is presented. Isolation is enhanced with the help of a decoupling stub placed between radiators, where two bands are stopped with the help of slits etched into the radiators. The overall size of the proposed antenna is 15 mm × 25 mm × 1.6 mm. The reflection coefficients are less than −10 dB between 3–10.9 GHz, except the bands WiMAX (3.2–3.7 GHz) and WLAN (5–6 GHz); similarly, measured and simulated transmission coefficients are less than −20 dB across the entire band of UWB. The envelope correlation coefficient (ECC) is less than 0.02 and the diversity gain is greater than 9.9 dB. The gain, ECC, radiation pattern, multiplexing efficiency, diversity gain and various other parameters are discussed and evaluated in detail.

The novel coronavirus-2019 (Covid-19), a contagious disease became a pandemic and has caused overwhelming effects on the human lives and world economy. The detection of the contagious disease is vital to avert further spread and to promptly treat the infected people. The need of automated scientific assisting diagnostic methods to identify Covid-19 in the infected people has increased since less accurate automated diagnostic methods are available. Recent studies based on the radiology imaging suggested that the imaging patterns on X-ray images and Computed Tomography (CT) scans contain leading information about Covid-19 and is considered as a potential automated diagnosis method. Machine learning and deep learning techniques combined with radiology imaging can be helpful for accurate detection of the disease. A deep learning approach based on the multilayer-Spatial Convolutional Neural Network for automatic detection of Covid-19 using chest X-ray images and CT scans is proposed in this paper. The proposed model, named as the Multilayer Spatial Covid Convolutional Neural Network (MSCovCNN), provides an automated accurate diagnostics for Covid-19 detection. The proposed model showed 93.63% detection accuracy and 97.88% AUC (Area Under Curve) for chest x-ray images and 91.44% detection accuracy and 95.92% AUC for chest CT scans, respectively. We have used 5-tiered 2D-CNN frameworks followed by the Artificial Neural Network (ANN) and softmax classifier. In the CNN each convolution layer is followed by an activation function and a Maxpooling layer. The proposed model can be used to assist the radiologists in detecting the Covid-19 and confirming their initial screening.

In this paper, we considered the problem of the speech enhancement similar to the real-world environments where several complex noise sources simultaneously degrade the quality and intelligibility of a target speech. The existing literature on the speech enhancement principally focuses on the presence of one noise source in mixture signals. However, in real-world situations, we generally face and attempt to improve the quality and intelligibility of speech where various complex stationary and nonstationary noise sources are simultaneously mixed with the target speech. Here, we have used deep learning for speech enhancement in complex-noisy environments and used ideal binary mask (IBM) as a binary classification function by using deep neural networks (DNNs). IBM is used as a target function during training and the trained DNNs are used to estimate IBM during enhancement stage. The estimated target function is then applied to the complex-noisy mixtures to obtain the target speech. The mean square error (MSE) is used as an objective cost function at various epochs. The experimental results at different input signal-to-noise ratio (SNR) showed that DNN-based complex-noisy speech enhancement outperformed the competing methods in terms of speech quality by using perceptual evaluation of speech quality (PESQ), segmental signal-to-noise ratio (SNRSeg), log-likelihood ratio (LLR), weighted spectral slope (WSS). Moreover, short-time objective intelligibility (STOI) reinforced the better speech intelligibility.

Human speech in real-world environments is typically degraded by the background noise. They have a negative impact on perceptual speech quality and intelligibility which causes performance degradation in various speech-related technological applications, such as hearing aids and automatic speech recognition systems. It also degrades the original phase of the clean speech and introduces perceptual disturbance which leads to the negative impacts on the quality of speech. Therefore, speech enhancement must vigilantly be dealt with in everyday listening environments. In this article, speech enhancement is performed using supervised learning of spectral masking. Deep neural networks (DNN) and recurrent neural networks (RNN) are trained to learn the spectral masking from the magnitude spectrograms of the degraded speech. An iterative procedure is adopted as a post-processing step to deal with the noisy phase. Additionally, an intelligibility improvement filter is also used to incorporate the critical band importance function weights where higher weights contribute more towards intelligibility. Systematic experiments demonstrated that the proposed approaches greatly attenuated the background noise. Also, they led to large improvements of the perceived speech quality and intelligibility, as well as automatic speech recognition. In experiments, TIMIT database is used. The STOI is improved by 17.6% over the noisy speech. Also, SDR and PESQ are improved by 5.22dB and 19% over the noisy speech utterances. These comparisons showed that the proposed speech enhancement approaches outperformed the related speech enhancement methods.

Reconfigurable antennas have received much attention in RF energy harvesting models owing to their selectivity for operating frequency and polarization. The characteristic of having frequency selectivity and polarization selectivity can be termed as frequency diversity and polarization diversity, respectively. This paper investigates a rectenna device with a new proposed topology in order to eliminate coupling between input and output lines and increase the rectification efficiency with the use of single feed hybrid reconfigurable antenna, switch between 28GHz and 38GHz frequency. Moreover, it is designed to charge a rechargeable battery of 1watt(W). The Reconfiguration mechanism is realized by electronically controlling different states of Switches. PIN Diode (as RLC Equivalent circuit) is used as a switch for ON/OFF states. This antenna mainly comprises rectangular shaped patches (28GHz and 38GHz) with Triango-Truncated edge at the corners. Eighteen PIN Diodes are placed symmetrically throughout the antenna presenting as, S1 & S2 for frequency reconfiguration, S3 to S6 & S7 to S10 connects Triango Truncated edge at the corners for polarization reconfiguration, and for radiation pattern reconfiguration at S11 to S14 & S15 to S18 has been used. The proposed antenna model is capable of simultaneously changing, the radiation patterns as clock and anti-clockwise directions at ±90-degree shift in E and H planes, circularly polarized (CP) states among, Linear Polarization (LP), Right Hand Circularly Polarization (RHCP), and Left Hand Circularly Polarization (LHCP). The current design describes using single antenna for energy harvesting and 5G mobile communication application. This would lead to higher output currents, leading to the ability to efficiently charge a wide variety of batteries. A fully functional prototype has been designed, fabricated and its compound reconfiguration characteristics have been validated for simulated and measured results. For validation of results, the experimental results and the simulation results from the proposed mathematical model were made into comparison, and excellent correlation between the measured and simulated results was obtained.

A novel three-mode step impedance resonator (TSIR) is developed to design a miniaturized multi-pole microstrip planar ultra-wideband (UWB) filter with independently controlled notched bands at different frequencies is presented in this work. The basic UWB filter consists of four L-shaped λ/4 short-circuited stubs operating in the range of i.e. 2.7 to 12.1 GHz with fractional bandwidth (FBW) 127%, and the TSIR is constructed using two T-shaped λ/2 open ended step impedance resonator (SIR) and one λ/4 short-circuited uniform impedance resonator (UIR) is coupled to the basic UWB design in order to achieve the stopbands performance at 5.1 GHz, 6 GHz, and 8 GHz, to supress the unwanted bands of WLAN, Wi-Fi 6E, and X-band satellite communication system, respectively. Commercial full-wave electromagnetic (EM) software HFSS-13 was used to design an ultra-compact structure having size 0.07 λg×0.02 λg on Rogers RT/Duroid 5880 substrate to justify good agreement between simulated and measured S-parameters.

Objective: To determine various factors associated with poor dialysis compliance as evident by early signoff and no shows. Study Design: Descriptive study. Place and Duration of Study: Nephrology department at Pak Emirates Military Hospital Rawalpindi, from Feb 2012 to Jan 2013. Material and Methods: A standardized proforma was formulated which was to be filled by dialysis staff each time a patient refused dialysis, absented “No show” or had premature termination of dialysis session against the medical advice, “early sign off” due to any cause. This data was compiled centrally on monthly basis and patients were counseled by doctors to evaluate the cause and various factors for early sign off and no shows. Using Non probability convenience sampling 364 dialysis sessions were included in our study. Data was analysed using SPSS version 20 and frequencies were calculated for various factors associated with early termination or absence altogether from dialysis. Results: A total of 11232 dialysis sessions were followed during study period. Amongst total of 364, 320 (88%) dialysis were terminated prematurely (Early sign off) while 44 (12%) dialysis sessions were missed out completely (no shows). Febrile reaction was most frequent factor causing early sign off n=97 (27%). Cramps were second most common factor for early sign offs n=70 (19%). Other factors like Symptomatic arrhythmias, nonspecific body aches, AV access site pain and socio economic issues also had contributions but less than 10% each. Conclusion: Poor hemodialysis compliance indicated by early sign offs and no show is fairly common problem in our community. Febrile reactions, cramps, poor education and hemodynamic instability are major contributory factors. These issues need to be addressed urgently to save a large population from life threatening complications and poor dialysis compliance. Identifying these complications and addressing them can ensure better compliance and likely will contribute to long term survival benefit.

Inherently UWB (Ultra Wideband) communication systems comes with interference problem with some if the existing narrowband communication systems. These bands are stopped with the help of band-stop filter in order to reduce electromagnetic interference However, the complexity and limitations are increased due to these filters, hence this solution is turned down in those applications where design complications and complexity is of concern. Introducing various slots of specific shapes and exact dimensions however, have solved this issue for the researchers around the world. This paper presents a hexagonal PMA (Printed Monopole Antenna) with triple stop bands. The antenna is used for UWB application. The antenna is stopped the WiMAX (Worldwide Interoperability for Microwave Access), WLAN (Wireless Local Area Network) and ITU (International Telecommunication Union) bands. The antenna dimensions are 30x28x16 mm3. FR4 is used between ground and radiating patch with relative permittivity of 4.4. The VSWR (Voltage Standing Wave Ratio) is less than 2 between 3-11 GHz except WiMAX (3.1-3.7 GHz), WLAN (5.1-5.8 GHz) and the ITU frequency band (7.95-8.4 GHz). The antenna is design in CST software.

In this article, a new method is developed to design a three-band miniaturized bandpass filter (BPF) that uses two asymmetrically coupled resonators with one step discontinuity and open-circuited uniform impedance resonator (UIR) to achieve Global Interoperability with Microwave Access (WiMAX) and Radio Frequency Identification (RFID) applications. First, a pair of asymmetrical step impedance resonators (ASIR) is used to implement a dual band filter, then a half wavelength uniform impedance resonator is added below to the transmission line to achieve a triple band response. The proposed filter resonates at frequencies of 3.7 GHz, 6.6 GHz, and 9 GHz with the fractional bandwidth of 7.52%, 5.1%, and 4.44%, respectively. By adjusting the physical length ratio (α) and the impedance ratio (R) of the asymmetric SIR, the proposed fundamental frequencies of the triple BPF are obtained. Moreover, the coupling coefficient (Ke) and external quality factor (Qe) are investigated between the resonators and the input/output ports of the transmission line and are calculated using full-wave EM simulator HFSS. In addition, five transmission zeros are introduced near the passbands to increase the filter selectivity. Finally, the proposed filter is designed and fabricated with a size of 13.69 × 25 mm (0.02 λg × 0.03 λg), where λg represents the guiding wavelength in the first passband. The simulated and measured results have a good correspondence, thus confirming the design concept.

This work focuses on the fabrication and evaluation of triboelectric nanogenerator (TENG) based self-powered tilt sensor. The proposed fabricated structure is composed of polydimethylsiloxane (PDMS), steel ball, gold (Au) as electrode and circular ring housing. A specific configuration of electrodes was used to measure the tilt at different angles. FEM simulations were used to verify the electric potential at the electrodes at different angles. The outputs of the fabricated sensor were measured at different angles from 0 to 360°. A sensitivity of 254 mV/rad is obtained in single axis. The TENG based tilt sensor generates an open circuit voltage of 450 mV at 10 MΩ.

Economic Load Dispatch problem has been previously solved successfully with swarm techniques. However, power systems with complex behaviours still await a robust algorithm to be developed for their optimization more precisely. Economic Dispatch problem with constraints such as generator limits, total power demand, ramp rate limits and prohibited operating zones, makes the problem more complicated to solve even for global techniques. To overcome these complications, a new algorithm is proposed called Hybrid Particle Multi-Swarm Optimization (HPMSO). The proposed algorithm has a property of deep search with quite fast response. Convex and Non-convex cost functions along with equality and inequality constraints have been used to evaluate performance of proposed approach. Moreover, Dynamic Economic Dispatch cases have also been included in statistical studies to test the proposed approach even in real time. Different case studies have been accomplished using standard test systems of Static and Dynamic Economic Dispatch. Comparison of proposed approach and previous techniques show that the proposed algorithm has a better performance.

The Federal Communication Commission (FCC) has authorized the use of unlicensed ultra-wide band (UWB) spectrum in the frequency range from 3.1 to 10.6 GHz for a variety of short-range applications, including wireless monitors and printers, camcorders, radar imaging, and personal area networks (PANS). However, the interference between coexisting narrowband channels and UWB signals that share the same spectrum should be avoided by designing UWB antennas with band notch characteristics. This work presents a printed monopole antenna (PMA) with slots of different shapes etched in the radiating element to obtain band rejection in the three coexisting communication bands, i.e., Worldwide Interoperability for Microwave Access (WiMAX), Wireless Local Area Network (WLAN), and International Telecommunication Union (ITU). A rectangular slot is etched to reject the WiMAX band (3.01-3.68 GHz), an upturned C slot stops the WLAN band (5.18-5.73 GHz) while an inverted-U slot halts the ITU frequency band (7.7-8.5 GHz). The proposed antenna occupies a volume of 32 x 30 x 1.6 mm3 and it radiates efficiently (>90%) with a satisfactory gain (>1.95 dBi) in the unnotched UWB frequency range. The simulations are performed in High Frequency System Simulator (HFSS), while the measurements are conducted in antenna measurement facility and found in close agreement with the former.

This paper addresses UI (User Interface) designing based on multi-touch collaborative gesture recognition meant for ASD (Autism Spectrum Disorder) - affected children. The present user interfaces (in the context of behavioral interventions for Autism Spectrum disorder) are investigated in detail. Thorough comparison has been made among various groups of these UIs. Advantages and limitations of these interfaces are discussed and future directions for the design of such interfaces are suggested.

Many forms of human communication exist; for instance, text and nonverbal based. Speech is, however, the most powerful and dexterous form for the humans. Speech signals enable humans to communicate and this usefulness of the speech signals has led to a variety of speech processing applications. Successful use of these applications is, however, significantly aggravated in presence of the background noise distortions. These noise signals overlap and mask the target speech signals. To deal with these overlapping background noise distortions, a speech enhancement algorithm at front end is crucial in order to make noisy speech intelligible and pleasant. Speech enhancement has become a very important research and engineering problem for the last couple of decades. In this paper, we present an all-inclusive survey on unsupervised single-channel speech enhancement (U-SCSE) algorithms. A taxonomy based review of the U-SCSE algorithms is presented and the associated studies regarding improving the intelligibility and quality are outlined. The studies on the speech enhancement algorithms in unsupervised perspective are presented. Objective experiments have been performed to evaluate the potential of the U-SCSE algorithms in terms of improving the speech intelligibility and quality. It is found that unsupervised speech enhancement improves the speech quality but the speech intelligibility improvement is deprived. To finish, several research problems are identified that require further research.

Plasmonic antennas are attractive optical components of the optoelectronic devices, operating in the far-infrared regime for sensing and imaging applications. However, low optical absorption hinders its potential applications, and their performance is limited due to fixed resonance frequency. In this article, a novel gate tunable graphene-metal hybrid plasmonic antenna with stacking configuration is proposed and investigated to achieve tunable performance over a broad range of frequencies with enhanced absorption characteristics. The hybrid graphene-metal antenna geometry is built up with a hexagon radiator that is supported by the Al2O3 insulator layer and graphene reflector. This stacked structure is deposited in the high resistive Si wafer substrate, and the hexagon radiator itself is a sandwich structure, which is composed of gold hexagon structure and two multilayer graphene stacks. The proposed antenna characteristics i.e., tunability of frequency, the efficiency corresponding to characteristics modes, and the tuning of absorption spectra, are evaluated by full-wave numerical simulations. Besides, the unity absorption peak that was realized through the proposed geometry is sensitive to the incident angle of TM-polarized incidence waves, which can flexibly shift the maxima of the absorption peak from 30 THz to 34 THz. Finally, an equivalent resonant circuit model for the investigated antenna based on the simulations results is designed to validate the antenna performance. Parametric analysis of the proposed antenna is carried out through altering the geometric parameters and graphene parameters in the Computer Simulation Technology (CST) studio. This clearly shows that the proposed antenna has a resonance frequency at 33 THz when the graphene sheet Fermi energy is increased to 0.3 eV by applying electrostatic gate voltage. The good agreement of the simulation and equivalent circuit model results makes the graphene-metal antenna suitable for the realization of far-infrared sensing and imaging device containing graphene antenna with enhanced performance.

This paper proposes a compact, semi-circular shaped multiple input multiple output (MIMO) antenna design with high isolation and enhanced bandwidth for ultrawide band (UWB) applications. A decoupling stub is used for high isolation reaching up to −55 dB over the entire bandwidth. The proposed antenna is used for UWB as well as super wide band (SWB) applications. The overall size of the proposed antenna is 18 × 36 × 1.6 mm3. The | S 11 | and voltage standing wave ratio (VSWR) of the proposed antenna are less than −10 dB and 2, respectively, in the range of 3–40 GHz. The total impedance bandwidth of the proposed design is 37 GHz. The VSWR, | S 11 | , | S 22 | , | S 21 | , | S 12 | , gain, envelope correlation coefficient (ECC), radiation pattern, and various other characteristic parameters are discussed in detail. The proposed antenna is optimized and simulated in a computer simulation technology (CST) studio, and printed on a FR4 substrate.

Exceptional advancement has been made in the development of graphene optical nanoantennas. They are incorporated with optoelectronic devices for plasmonics application and have been an active research area across the globe. The interest in graphene plasmonic devices is driven by the different applications they have empowered, such as ultrafast nanodevices, photodetection, energy harvesting, biosensing, biomedical imaging and high-speed terahertz communications. In this article, the aim is to provide a detailed review of the essential explanation behind graphene nanoantennas experimental proofs for the developments of graphene-based plasmonics antennas, achieving enhanced light−matter interaction by exploiting graphene material conductivity and optical properties. First, the fundamental graphene nanoantennas and their tunable resonant behavior over THz frequencies are summarized. Furthermore, incorporating graphene−metal hybrid antennas with optoelectronic devices can prompt the acknowledgment of multi-platforms for photonics. More interestingly, various technical methods are critically studied for frequency tuning and active modulation of optical characteristics, through in situ modulations by applying an external electric field. Second, the various methods for radiation beam scanning and beam reconfigurability are discussed through reflectarray and leaky-wave graphene antennas. In particular, numerous graphene antenna photodetectors and graphene rectennas for energy harvesting are studied by giving a critical evaluation of antenna performances, enhanced photodetection, energy conversion efficiency and the significant problems that remain to be addressed. Finally, the potential developments in the synthesis of graphene material and technological methods involved in the fabrication of graphene−metal nanoantennas are discussed.

Symmetrical precoding and algorithms play a vital role in the field of wireless communications and cellular networks. This paper proposed a low-complexity hybrid precoding algorithm for mmWave massive multiple-input multiple-output (MIMO) systems. The traditional orthogonal matching pursuit (OMP) has a large complexity, as it requires matrix inversion and known candidate matrices. Therefore, we propose a bird swarm algorithm (BSA) based matrix-inversion bypass (MIB) OMP (BSAMIBOMP) algorithm which has the feature to quickly search the BSA global optimum value. It only directly finds the array response vector multiplied by the residual inner product, so it does not require the candidate’s matrices. Moreover, it deploys the Banachiewicz−Schur generalized inverse of the partitioned matrix to decompose the high-dimensional matrix into low-dimensional in order to avoid the need for a matrix inversion operation. The simulation results show that the proposed algorithm effectively improves the bit error rate (BER), spectral efficiency (SE), complexity, and energy efficiency of the mmWave massive MIMO system as compared with the existing OMP hybrid and SDRAltMin algorithm without any matrix inversion and known candidate matrix information requirement.